Advanced Diagnostics in Combustion Science [1st ed. 2023] 9819905451, 9789819905454

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Zhen-Yu Tian Editor

Advanced Diagnostics in Combustion Science

Advanced Diagnostics in Combustion Science

Zhen-Yu Tian Editor

Advanced Diagnostics in Combustion Science

Editor Zhen-Yu Tian Institute of Engineering Thermophysics Chinese Academy of Sciences Beijing, China University of Chinese Academy of Sciences Beijing, China

ISBN 978-981-99-0545-4 ISBN 978-981-99-0546-1 (eBook) https://doi.org/10.1007/978-981-99-0546-1 Jointly published with Science Press The print edition is not for sale in China (Mainland). Customers from China (Mainland) please order the print book from: Science Press. © Science Press 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publishers, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publishers nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publishers remain neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Contents

1 Introduction to Advanced Diagnostic Techniques in Combustion Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhen-Yu Tian, Vestince Balidi Mbayachi, Maria Khalil, and Daniel A. Ayejoto

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2 Gas Chromatography/Mass Spectrometry . . . . . . . . . . . . . . . . . . . . . . . . Zhen-Yu Tian, Vestince Balidi Mbayachi, Wei-Kang Dai, Maria Khalil, and Daniel A. Ayejoto

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3 Thermal Analysis Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Zhen-Yu Tian, Vestince Balidi Mbayachi, Wei-Kang Dai, Maria Khalil, and Daniel A. Ayejoto

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4 Gas Potentiometry Diagnostics in High-Temperature Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Vestince Balidi Mbayachi, Zhen-Yu Tian, Zhi-Min Wang, Maria Khalil, and Daniel A. Ayejoto 5 Raman Scattering Diagnostics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Vestince Balidi Mbayachi, Zhen-Yu Tian, Zhi-Min Wang, Maria Khalil, and Daniel A. Ayejoto 6 Coherent Anti-Stokes Raman Scattering . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Zhen-Yu Tian, Vestince Balidi Mbayachi, Xu Zhang, Maria Khalil, and Daniel A. Ayejoto 7 Laser-Induced Fluorescence in Combustion Research . . . . . . . . . . . . . . 223 Vestince Balidi Mbayachi, Zhen-Yu Tian, Xu Zhang, Maria Khalil, and Daniel A. Ayejoto 8 Nuclear Magnetic Resonance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Vestince Balidi Mbayachi, Zhen-Yu Tian, Wei-Kang Dai, Daniel A. Ayejoto, Zhi-Min Wang, Xu Zhang, and Maria Khalil

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Contributors

Daniel A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou, China; University of Chinese Academy of Sciences, Beijing, China Wei-Kang Dai Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, China Maria Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, China; University of Chinese Academy of Sciences, Beijing, China Vestince Balidi Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China; University of Chinese Academy of Sciences, Beijing, China Zhen-Yu Tian Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China Zhi-Min Wang Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing, China Xu Zhang School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing, China

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Abbreviations

ASA CAD CaO CARS CCD CFD Cp CPIV CRDS CS CSRS CW DB-CARS DC DFWM DHI DI DM DMC DSC DTA EC ECDL EDM EGA FAR-LIF FID FLBMR FMS FQY fs

Active surface area Crank-angle degree Calcium oxide Coherent anti-stokes Raman spectroscopy Charged coupled devices Computational fluid dynamics Specific heat capacity Conditioned particle image velocimetry Cavity ring-down spectroscopy Ceriporiopsis subvermispora Coherent stokes Raman scattering Continuous-wave Dual-broadband rotational CARS Direct current Degenerate four-wave mixing Digital holographic interferometry Direct injection Dichroic mirror Demineralized bituminous coal Differential scanning calorimetry Differential thermal analysis Elemental carbon External-cavity diode laser Exchanged gas measurement Exchanged gas analysis Fuel/air ratio-laser-induced fluorescence Flame ionization detector Fluidized-bed membrane reactor Frequency modulation spectroscopy Fluorescence quantum yield Broadband ix

x

FTIR GC GC/MS GOPs GPCA GPFA GPGA GTL HCCI HG HPIV HPLC HSQC HTA HTO Hz ICTAC ID ISPD JM KD KHz LC/MS LDA LDV LE LIF LLOQ LOD LRS LTHR LTO M&C m/z MAC MAS MCA MCP MS MSD MTV N.A ND NDIR NMR

Abbreviations

Fourier transform infrared spectrometry Gas chromatography Gas chromatography/mass spectrometry Gas potentiometric oxygen probes Gas potentiometric combustion analysis Gas potentiometric flame analysis Gas potentiometric gasification analysis Gas-to-liquid Homogeneous-charge compression ignition Harmonic generation Holographic particle image velocimetry High performance liquid chromatography Heteronuclear single-quantum correlation spectroscopy High temperature High temperature oxidation Hertz International Confederation for Thermal Analysis and Calorimetry Internal diameter Intensifier silicon photodiode Pyroelectric joulemeter Distribution constant Kilohertz Liquid chromatography/mass spectrometry Laser Doppler anemometry Laser Doppler velocimetry Lentinula edodes Laser-induced fluorescence Lower limit of quantification Limit of detection Linear Raman scattering Low-temperature heat release Low-temperature oxidation Monitor and commander Mass-to-charge Mass-specific absorption cross-section Mobility aerosol spectrometer Multichannel analyzer Multichannel plate Mass spectrometry Mass-selective detector Molecular tagging velocimetry Numerical aperture Neutral density Non-dispersive infrared gas analyzers Nuclear magnetic resonance

Abbreviations

NO-LIF NOM OC ONERA OPOs PAHs PbTiO3 PD PDA PDPA PDV PE PID PIV PLC PLIF PM PMTs ps PSTs PT Pt Py-GCMS Q-branch R R&D RAM RS RSA Rt RTD SDT SE SEM SIDMS SIMS SNR SRS TA Tc TDLAS TE TEA TEM Tf

xi

Nitric oxide-laser induced fluorescence Natural organic matter Organic carbon Office National d’Etudes et de Recherches Aerospatiales (in French) Optical parametric oscillators Polycyclic aromatic hydrocarbons Lead titanate Photo diode Planar Doppler anemometry Phase Doppler particle analyzer Point Doppler velocimetry Pleurotus eryngii Proportional integral derivative Particle image velocimetry Programmable logic controller Planar laser-induced fluorescence Particulate matters Photomultiplier tubes Narrowband Pressure-sensitive adhesive tapes Piezoelectric Platinum Pyrolysis gas chromatography mass spectrometry Quantum number J Rayleigh signal Research and development Random Access Memory Raman scattering Reactive surface area Retention time Resistance temperature detectors Simultaneous differential techniques Solid electrolyte Scanning electron microscope Speciated isotope dilution mass spectrometry Speciated isotope mass spectrometry Signal-to-noise ratio Spontaneous Raman Scattering Thermal analysis Crystallization temperature Tunable diode laser as a light source Thermoelectrometry Thermoelectrical analysis Transmission electron microscopy Final temperature

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TG Tg TG TGA Ti TK Tm TM TMA TNF TOA TPB TPD TZ Ueq UV VOCs VOP VUV WMS YSZ ZrO2 ω1 ω2 ω3 % wt.

Abbreviations

Gas temperature Glass transition temperature Thermogravimetry Thermogravimetry analysis Initial temperature Transient kinetics Melting temperature Thermomechanometry Thermomechanical analysis Turbulent non-premixed flames Thermoptometric analysis Triple phase boundary Temperature-programmed desorption Sensor temperature Nernst equation Ultraviolet Volatile organic compounds High temperature Vacuum ultraviolet Wavelength modulation spectroscopy Stabilized zirconia Zirconium oxide Pump beam Stoke beam CARS Signals Weight per cent

Chapter 1

Introduction to Advanced Diagnostic Techniques in Combustion Science Zhen-Yu Tian, Vestince Balidi Mbayachi, Maria Khalil, and Daniel A. Ayejoto

1.1 Introduction During the past few decades, immense progress and development have been made to combustion research. These diagnostic techniques significantly impact combustion understanding, such as fewer environmental hazards and more device improvement capable of further development of processes. Nowadays, this field has proliferated such that numerous purposes include fundamental research academics, pollutant control, reliable operation process, and production on a commercial level. This chapter will consist of the details of resolute techniques, uses, and applications that can be scientific and technical. As a result, essential properties of these techniques with examples and general discussions will be discussed. Hence, a generalized form of information about diagnostic techniques within combustion science is provided. According to the relative quantitative phenomenon of the diagnostic approaches outlined, it is mentioned that suitable measuring techniques depend on the properties of the combustion process to investigate. Under the general aspect, several commonly used diagnostic techniques are Z.-Y. Tian (B) Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China e-mail: [email protected] Z.-Y. Tian · V. B. Mbayachi · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_1

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described. These techniques are divided into two subclasses based on mechanical probing and optical diagnostics. The discussion of each technique possesses a short detail of physics, method application on a laboratory and technical scales. In the other portion, imaging and multidimensional diagnostics, the history of working of laser diagnostics in combustion diagnostics research is made prominent. Eventually, the probability of laser diagnostics corroborating those perspectives in numerical simulations is discussed. The outline is dressed with the accessible quantity equipment with the detailed information of other applications of diagnostic techniques. With the substantial development of spectroscopic methods for combustion diagnostics, the laser is regarded as starting point of research. Before the onset of laser technology, emission and absorption spectroscopy served well in combustion diagnostics. Some important intermediate species are listed in flames as OH, CH, HCO, NH, or C2 . Their presence is proven by using spectroscopic methods. Besides, laserbased spectroscopy offers innovative, widely refined ways to observe combustion. When we employ the spectral bandwidth of laser light, it becomes easy to discern various spectral properties of atoms and molecules at a higher resolution. The Prior method is carried out without the coherent light source contrary ability to produce laser pulses made possible the analysis of transient processes. Depending upon the unique properties of prominently well-defined laser beam formation, point-like sharp geometric shapes, and planes like conventional light sources propagation direction of laser light can be controlled with precision. As a result, the accuracy of irradiated volumes can be acquired. Altogether, the above-mentioned unique properties can make laser diagnostics the most widely used technique in applied combustion research and investigation control combustion systems.

1.2 Main Works of Advanced Diagnostics Main works of advanced diagnostics revolve around pressure, temperature, velocity, concentration and their distribution with space and time, flame peak position and propagation speed, flame structure, and reaction flow field display, particle size distribution, solid fuel combustion surface, and subsurface status, their chemical structure, the temperature distribution of emissions, component concentration, and signal characteristics, etc. It is not easy to understand the tasks and needs of combustion diagnostics without any prior knowledge of combustion properties. A brief description of such properties should help to explain how specific requirements are imposed on diagnostic techniques. The desired temporal and spatial resolution of a measurement depends on the system’s governing time and length scales to be characterized. An estimate of these scales for a small collection of different combustion applications is shown in Table 1.1. Combustion often occurs in thin, sheet-like regions (flames) as a spatially extremely inhomogeneous process. Since, in most natural combustion systems, the thickness of these layers is on the order of some ten to a hundred micrometeres,

1 Introduction to Advanced Diagnostic Techniques in Combustion Science Table 1.1 Estimated combustion application time scale and length scale [1]

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Application

Time scale (ms)

Length scale (m)

Flame measurement—laminar

105 –106

10–4 –10–2

Flame measurement—turbulent

10–2 –102

10–5 –10–2

Fire research

102 –103

10–5 –10–2

Jet engine; compressor inlet

103 –104

10–4 –10–1

Gas turbine burner

10–1 –101

10–5 –10–4

After burner

10–1 –100

10–5 –10–4

in terms that govern the dynamics of a combustion system, those species that exist in tiny amounts [down to mass fractions in the parts-per-million (ppm) scale] may exert a more significant influence on the systems the behavior than those which are abundantly present, in the per cent range. The ability to detect and measure these key species (e.g., OH, CH in Fig. 1.1) without interference from the much more abundant bath of hundreds or thousands of other species represents a significant requirement for the successful experimental combustion analysis. The potentially high sensitivity of combustion conmtcerning the variations in physical boundary conditions can render prohibitive use of measurement techniques that significantly alter the physical conditions during an experiment. A diagnostic approach should not change the system that it is attempting to measure; indeed, a significant indicator for the quality of a diagnostic technique in this respect would be its level of non-intrusiveness. Recognized diagnostic techniques can be quite sharply separated, based on their level of intrusion, with most optical techniques considered non-intrusive and those involving mechanical probes highly intrusive.

Fig. 1.1 a Structure of a premixed methane/air flame at 20 bars (simulation). The spatial extent of the scene shown is 0.1 mm; b Sketch of the temporal and spatial scales relevant to combustion [1]

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Fig. 1.2 The temperature structure of a turbulent flame is taken by 2D Rayleigh scattering (false-color representation, top right), which is hidden in flame photography (bottom left) [3]

Finally, significant constraints exist when a diagnostic technique is used within a technical combustion environment [2]. Unlike laboratory systems, most realistic environments are not explicitly designed to allow or alleviate diagnostic procedures to be carried out. Hence, diagnostic techniques must often be applied under conditions that are not optimally suited to the underlying measuring principles. An essential property of a diagnostic technique is, therefore, its robustness—that is, its ability to function reasonably well under conditions that may deviate strongly from those for Fig. 1.2. The temperature structure of a turbulent flame is taken by 2D Rayleigh scattering (false-color representation, top right), which is hidden in flame photography (bottom left) [3]. Robustness also implies that the instruments used for diagnostics can operate under the adverse conditions (e.g., high temperatures and pressures, presence of highly reactive substances) encountered in combustions. The ideal diagnostic technique must be sufficiently robust enough to survive hostile environments and provide a large amount of combustion-related information.

1.3 Classification Classification of the diagnostic techniques is majorly based on sampling methods, spectroscopic procedures, velocity, concentration, and particle size. Various instruments are included; for example, thermocouples are used to measure temperature, and LIF is applied to study flame structure. Table 1.2 summarizes the classification of diagnostic techniques according to their test principles, experiments, methods, information collection, and detection means.

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Table 1.2 A summary of the classification of diagnostic techniques Classification

Names of methods or instruments

Sampling

Thermocouple temperature probe

Examples Non-shielded

Temperature

Suction type Pneumatic dual sonic hole temperature probe Pneumatic speed probe

Pitot tube with two holes Five-hole Pitot trust

Gas sampling probe

Metal or quartz probe Molecular beam probe

Two-phase sampling probe Spectroscopic method

Optical emission and adsorption

Radiometer

Sample collection Spectral line inversion

Temperature

Radiation absorption Color temperature Spectroradiometer

Absolute strength Relative intensity

Atomic resonance absorption spectrometry

Concentration

Infrared absorption Near-infrared

T/C

Mid-infrared MS

Mass spectrometry

Concentration

Electron energy spectrometry

Auger electron spectroscopy

Surface composition

X-ray photoelectron spectroscopy

Particle size

Microscope

Optical Ion/electron

SEM/ TEM/ HIM

Particle damping and nozzle two-phase flow loss

Malvine ion analyzer Single particle counter Velocity

Single point

LDV

3D

PDPA

Particle size

Imaging

PIV

½D

PDV MTV (continued)

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Table 1.2 (continued) Classification

Names of methods or instruments Stable

Examples

HPIV

3D

Pressurized burning rate meter

Solid rocket propellant

Closed bomb or burner Acoustic emission Unstable

Microwave Ultrasonic Absorption Real-time screen

Concentration

Spectroscopic

LIF

Flame structure

CRDS Sampling

Capillary Molecular beam

1.4 Invasive Techniques These techniques are based on traditional combustion diagnostic approaches where a mechanical examination is performed in research. This area can be either a measurement system, a device to measure the system, or a sample analysis system. These approaches are used to measure the system under experimental conditions. Firstly, the unwanted and unavoidable property of the invasive probe is the local interaction with the system, which is further analyzed. Secondly, systematic errors must be handled carefully if the measured quantity is rated. These errors are relatively caused by the mechanical probes depending upon the size of the probe and the combustion field under study.

1.4.1 Temperature Combustion can often lead to flame, so the temperature is the most critical variable for technical application to be measured in combustion chambers. It accounts for downscaled flame temperature measurements. This combustion temperature needs to be carefully controlled. In this regard, immense development is made to analyze temperature distributions. There are several other advanced devices used to measure the temperature.

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1.4.1.1

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Thermocouples

The most widely used device for temperature measurement is a thermocouple. Thermocouples consist of two dissimilar metals joined together at one end, which produces a small unique voltage for a given temperature, and this voltage is measured and interpreted by a thermocouple thermometer. Here, the Seebeck effect is an intrinsic principle, which describes the material-dependent electrical voltage when a temperature difference forms a closed loop. Two materials provide standardized voltage-temperature rather than applicable temperature ranges [4]. Some details of the material used as the pair of thermocouples and their application ranges can be used in the combustion system, as illustrated in Table 1.3. The main drawback of the device is related to the probe, which should be placed into the measuring volume, and it can affect the flame with various mechanisms. These drawbacks are accepted mostly for applications based on sapid evaluation and assessment. Based on the dimensions of the probe and flow condition, the local flow field in the probe can be influenced, and fuel mixing and oxidizer can also be affected [5]. Moreover, heat conduction and radiation from surrounding walls can affect the heat balance of flame. These specific materials on sensors act as chemical catalysts. This must be differentiated in contrast to the thermocouple reaction material by using Table 1.3 Pairs of thermocouple materials and their application ranges [4] Type

Positive material

Negative material

Sensibility at 20 °C (μV/ °C)

Range of temperature (°C)

E

Chromel (nickel 10% chromium)

Constantan (nickel 45% copper)

58.7

−270 to 1,000

G

Tungsten

Tungsten 26% Rhenium

19.7 (600 °C)

0 to 2,320

C

Tungsten 5% rhenium

Tungsten 26% rhenium 19.7 (600 °C)

0 to 2,320

D

Tungsten 3% rhenium

Tungsten 26% rhenium 19.7 (600 °C)

0 to 2,320

J

Iron

Constantan (nickel 45% copper)

50.4

−210 to 760

K

Chromel (nickel 10% chromium)

Alumel (nickel 5% aluminum and silicon)

39.4

−270 to 1,372

N(AWG 14)

Nicrosil (84.3% Ni, 14% Cr, 1.4% Si, 0.1% Mg)

Nisil (95.5% Ni, 4.4% Si, 0.1% Mg)

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−270 to 400

N(AWG 28)

Nicrosil (84.3% Ni, 14% Cr, 1.4% Si, 0.1% Mg)

Nisil (95.5% Ni, 4.4% Si, 0.1% Mg)

26.2

0 to 1,300

B

Platinum 6% Rhodium

Platinum 30% Rhodium

1.2

0 to 1,820

R

Platinum 13% Rhodium

Platinum

5.8

−50 to 1,768

S

Platinum 10% Rhodium

Platinum

5.9

−50 to 1,768

T

Copper

Constantan

38.7

−270 to 400

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chemically active material to increase the decomposition of stable contrary ceramic, which primarily acts as an insulator in flames at high-temperature material. Heitor and Moreira [6] have provided a brief overview of the limitations and successful applications of these sensors in the field of combustion diagnostics.

1.4.1.2

Resistance Thermometry

Resistance thermometry is another invasive technique that is used to measure temperature. Devices are also called resistance temperature detectors (RTD), shortly named sensors to measure temperature. RTD mainly consists of a wire wrapped around a ceramic. Along with this, another construction is also used. The fine wire wrapped around should be a pure material, e.g., copper, nickel, and platinum [7]. Even though the perfect linearity of resistance-based thermometers and the availability of standardized types of Pt100 have, a major drawback is its limited application range of up to about 1300 K and the long response times required, compared to the thermocouples. Their accuracy is far more than thermocouples [8].

1.4.1.3

Thermochromic Painting

In the past years and recent years, thermochromic painting has been famous in temperature estimation upon heat change. The fundamental principle behind this color formation phenomenon is the change in the heat, which directly changes the color of components. This change is the molecular structure and crystalline property of the material. There is a recent development in this field. This temperaturesensitive phenomenon is further developed in temperature-sensitive paints, which are based on the sensitivity of luminescent molecule’s thermal environment following (ultraviolet) excitation [9]. An increase in temperature of the luminescent molecule increases the probability of the molecule to return to the ground state via no excitation process [10], rather than emitting a photon. This thermally induced phosphorescence quenching forms the basis of the temperature measurement via a quantitative detection of emission attenuation.

1.4.2 Species Concentrations Before, after, and during the combustion system, concentration measurement is essential for investigation basics and process control applications. Under the measurement principle, there are probing strategies applied in general, due in part as well to regulate and normalize the historical methods for sampling, for example, constant volume sampling has been used for many decades to support the testing of vehicle emissions, whereby a constant total flow rate of a vehicle exhaust plus dilution air is maintained.

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For this to occur, as the exhaust flow increases, the dilution air must be automatically decreased [11]. In this case, a bag measurement of emissions represents the key method for legislative purposes, as it provides a single value for the major exhaust species of a complete test cycle, including the different phases of acceleration and constant speed. Although the sampling may be conducted continuously using a suitable ejector or probing device (e.g., Pitot tube or low-pressure sampling), followed by additional dilution stages, the quantitative analysis of the species concentration can be performed batch-wise in the case of some diagnostic techniques. An example is the gas-chromatographic measurement of species in engine exhaust gases. However, this is also often applied to analyze basic properties such as heating value and the composition of gaseous hydrocarbon fuels for combustion in stationary gas turbines.

1.4.2.1

Flame Ionization Detector

Flame ionization detector (FID) is an invasive technique commonly used for gas analysis of hydrocarbons at different detection ranges [12]. This technique is mass sensitive, and the concentration of gases downstream in a coiled column is less affected by the flow of carrier gas. The working principle of FIDs, as shown in Fig. 1.3, involves the production of ions when hydrocarbon gas is heated in hydrogen flames inside the column. Two electrodes with different potentials are used to detect these ions. The negative electrode is located above the flame, and its plate attracts the ions, which induces a current proportional to the ionization rate of the hydrocarbon concentration in the sample. FIDs are applied in portable gas chromatographs, and their advantages include a comprehensive measurement of hydrocarbon gases and positive results in the presence of moisture. The limitations of FIDs involve a poor response to hydrocarbons with high numbers of halogens, destruction of the sample, and flame failure to ignite the gas in high humidity. Fig. 1.3 Schematic of flame ionization detector [13]

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Gas Chromatography/Mass Spectrometry

Gas chromatography (GC) combined with mass spectrometry (MS) is an analytical, diagnostic technique that is applied in the identification and quantification of small molecules of less than 650 Daltons [14]. GC-MS possesses superior separation capability, reproductivity, and sensitivity, thus achieving a higher chromatographic resolution than LC-MS [15]. GC-MS unit consists of sample preparation, data acquisition, data processing, and quality control (Fig. 1.4). GC-MS has advantages such as fast analysis, higher accuracy, inexpensiveness, and efficiency, even though it can only detect volatile materials with lower molecular weight. Gustavsson et al. [16] analyzed flame retardants using GC-MS. Axford et al. [17] studied the effects of applied electric fields and electric potential variation in a flame using MS to sample electrically charged species from flames at atmospheric pressure.

1.4.3 Pressure Sensor The pressure sensor in a combustion chamber plays a vital role in security and stability, thus providing essential information on thermal stability. In-cylinder pressure sensors (Fig. 1.5) are installed into automotive engines to increase power energy, knock control and check for leak status [18]. These sensors consist of a piezoelectric element built of lead titanate (PT, PbTiO3 ). The properties of the in-cylinder pressure sensors majorly depend on the type of piezoelectric element incorporated. Lead titanate is a crystal structure of perovskite, which provides the advantage of a high piezoelectric constant, high ferroelectric Curie temperature of 490 °C and a higher signal-to-noise ratio. Besides the application of in-cylinder pressure sensors in automotive, they are also applied in the

Fig. 1.4 Gas chromatography/mass spectrometry

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Fig. 1.5 A spark plug integrated with an in-cylinder pressure sensor [18]

detection and measurement of pressure dynamics in the harsh combustion environment of premixed gas turbines where the fluctuation of the heat release in the burning chamber results in extreme combustion noise with a pressure range of hundreds of millibars (Fig. 1.6). Currently, low-cost in-cylinder pressure sensors such as fiber-optic combustion pressure sensors with 500 million pressure lifecycles have been introduced and applied in engine diagnostics [19]. They are incorporated with a spark plug, glow plug, or fuel injector at a low cost in engines to control combustion, improve efficiency, and minimize pollution. Fig. 1.6 Glow plug integrated with in-cylinder pressure sensor for diesel engine [18]

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1.4.4 Particulates Soot particles are formed due to incomplete combustion of hydrocarbons such as methane (CH4 ) and methane-nitrogen (CH4 –N2 ) mixture within an inverted laminar diffusion flame [20]. Mass-specific absorption cross-section (MAC) of soot is assumed to be dependent on its mass and size particle. Transmission electron microscopy (TEM) is employed to characterize soot particle diameter and morphology. Raman spectroscopy is used to investigate the graphitization level of soot particles. Combustion of hydrocarbons with a diffusion flame under atmospheric pressure leads to thermophoretic deposition inside the cold walls of the flow field [21]. In Fig. 1.7, a probe is introduced into a diffusion flame for enough exposure time to capture a remarkable sample but short enough to avail a cold surface to the flame borne particle. The cold surface freezes the already captured particle’s heterogeneous reaction, which prevents the change in morphology of the particle after contact with a cold surface. Fig. 1.7 Diffusion flame of the thermophoretic probe sampling [21]

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1.5 Noninvasive Techniques The development and introduction of noninvasive methods in combustion diagnostic were influenced by the urge to overcome the disadvantages of invasive diagnostic tools. The problem can be illustrated by comparing point-wise photographic images that show concentration measurements using either laser or mechanical probes in a laminar premixed flame [21]. In the mechanical probe, there is a disturbance of the flame shape, as seen in Fig. 1.8, resulting in dislocation of the flame front. The flame shape is unaffected in the laser probe since it shows the exact symmetry as if no probe was applied. Another comparison was conducted using a continuous-wave (cw) laser, Raman probe, and Qswitched ruby laser to measure temperature and concentration of a laminar premixed methane/air flame [23]. The deviation in oxygen concentration was taken by a quartz suction probe and plotted in two downstream positions in the reaction zone (as shown in Fig. 1.9). It was confirmed that the difference between noninvasive and invasive techniques was due to a worse local resolution of the mechanical probe, which tends to change the reaction zone, impacting both less deep gradient and squeezed reaction at the outer part of the flame [23]. Several studies recently focused on the non-intrusive laser as a diagnostic technique in combustion. Figure 1.10 illustrates the principle of optical measurement technique where various processes are compared in terms of signal intensity by the magnitude of the cross-sectional interaction. When a laser beam with frequency v0 is irradiated into a gas sample, irradiated photon interacts with matter present in the probe, giving rise to physical processes that can be distinguished by laser beam attenuation by extinction processes such as absorption and scattering or by the emission of radiation with a different frequency to that of various approaches. Emission of

Fig. 1.8 The Concentration measurement in a laminar flame. a The mechanical probe causes disturbances of the reaction zone; b No influence of the noninvasive laser probe can be observed [22]

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Fig. 1.9 Radial O2 concentration profiles at a downstream position: a within the reaction zone and b in the post-reaction zone. Comparison between the mechanical probe and laser Raman measurements at a downstream position of 1d (a) and 6.5 d (b) [23]

intensities of various processes depends on the magnitude of the interaction crosssection, thus providing direct information on the strength of the signal achieved. The unique qualities of the weakest Raman and Rayleigh processes have become the best measurement tools in different combustion diagnostics CO2 (%).

Fig. 1.10 Schematic illustration of different interaction processes between the matter present in the sample volume and the irradiated laser beam [22]

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1.5.1 Visualization Techniques Flow visualization is a modern diagnostic technique that has significantly contributed to the combustion application. Long [24] introduced the study of refractive index fields in aerodynamics and suggested a Schlieren technique in combustion application. Holographic interferometry allows the investigation of non-intrusive temperature measurements in optical flame with temporal resolution and high spatial (Fig. 1.11). These new measurement and imaging techniques use Digital holographic interferometry (DHI) to record a hologram on CCD electronically and reconstruct it by numerical methods [25].

1.5.1.1

Schlieren Techniques

Schlieren imaging systems are the oldest diagnostic technique used since the nineteenth century to visualize fluctuations in optical density leading to refractive index variation [26]. Schlieren optics provide non-intrusive information in 2D transparent and optical media. The benefit of this technique in fluid dynamics studies is that it does not interfere with the flow despite being sensitive to changes. Schlieren imaging works under the principle of Snell’s Law, which states that light slows with the interaction of matter (Fig. 1.12). Light travels steadily and at a constant velocity in homogenous media such as space and vacuum. Light also refracts and deflects when it encounters inhomogeneous media in terms of temperature, density, pressure, and chemical composition resulting in Schliere. Recently, the invention of a more powerful computing system and digital cameras has led to the development of Schlieren optics in the study of refractive media. Schlieren techniques have been reported in many combustion applications with laser-induced fluorescence to study the structure of premixed flame of propane and air as a function of flame stabilization processes and the difference in the fuel–air ratio [27]. In addition, these techniques have been applied to observe how pressure influences the structural turbulent of premixed Bunsen flames [28]. Figure 1.13 illustrates the observation of premixed flame at different atmospheric pressure. It can be Fig. 1.11 A simple digital holography system in combustion study [25]

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Fig. 1.12 Experimental setup of Schlieren system [26]

Fig. 1.13 Instantaneous Schlieren photographs of the turbulent flames: a 0.1 MPa; b 0.25 MPa; c 0.5 MPa; d 1.0 MPa [22]

seen that at 0.1MPa, the flame is wrinkled with low intensity and large-scale turbulence, but with the increase in pressure, the bluntly wrinkle flame becomes fine spikes making it difficult to differentiate each wrinkle to see its depth.

1.5.2 Emission Spectroscopy The analysis of spectra radiation emitted by the flame is one of the most optical diagnostic techniques in combustion. Most emission spectroscopy in the gas phase relies on the chemiluminescence of molecules rather than the excitation of atoms from one energy band to the other. Many kinetic reactions are temperature dependent in

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Fig. 1.14 Emission spectra of an ammonia-doped, fuel-rich premixed butane–air flame [22]

hydrocarbon combustion resulting in detectable intermediate radicals such as OH, CH, NH, and CN (Fig. 1.14) [29]. In chemical and thermal excitation, molecules such as CO2 and H2 O are the products of hydrocarbon flames. Emission spectroscopy for years has been used for the detection of flame radicals. Previously, emission spectroscopy was used to measure radical concentration in low-pressure flames, but currently, it is advanced in the industrial application as an active feedback control parameter for equivalent ratio disturbance of high-pressure premixed flames [30]. Combustion reaction in the solid phase leads to components such as soot particles that emit black body (Planck) radiation that can be used in industrial applications for temperature measurement. According to Planck’s radiation law, temperatures can be calculated effectively by directly measuring radiation intensity within a band of the emitted black body emission spectrum. Distribution pyrometry is always applied in two almost adjacent bands where radiation intensity is measured. Recently, coherent anti-Stokes Raman spectroscopy (CARS) has been used as 1D emission spectroscopy in temperature measurement of sooting premixed flame [31].

1.5.3 Absorption Spectroscopy Absorption spectroscopy is an advanced diagnostic technique used to quantitatively measure transparent media species in the industrial analytical system. It operates under the principle of a molecule’s partial absorption of light radiation. If the emission spectrum overlaps the absorption spectrum of the probed molecule, the transmitted intensity can be calculated by the Lambert–Beer law. Quantum mechanics calculate the absorption spectra by describing the molecule’s vibrational, rotational, and electronic energy levels. The introduction of laser radiation has facilitated a new

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application in temperature measurements based on two-line absorption techniques and sensitivity and a strong increased signal-to-noise ratio (SNR) [32]. NDIR analyzer is a broadband excitation used for noninvasive measurement of exhaust gas analysis such as CO2 and CO. The limitation of the broadband technique is that other species can be absorbed in the IR region. Due to the low cost of tunable diode laser as a light source (TDLAS), it has recently been used in online monitoring and combustion diagnostics [33]. Mokhov et al. (2005) used TDLAS to measure acetylene in atmospheric pressure premixed methane/air fuel-rich flames. Tunable diode laser and frequency modulation spectroscopy (FMS) or wavelength modulation spectroscopy (WMS) lead to a significant increase of signal-to-noise in the species under investigation. The Diode laser system can probe most combustion species such as O2 , CH4 , CO, NO, H2 O, CO2, and NO2 . Kranendonk et al. [34], in their experiment, used a tunable external-cavity diode laser (ECDL) as an absorption technique to scan from 1374 to 1472 nm for crank angle resolved gas temperature and H2 O mole fraction in an engine operating on heptane/air in the ratio of 0.16 in homogeneouscharge compression ignition (HCCI) mode. This approach offers a strategy for quasisimultaneous multispecies analysis as a new diagnostic technique for a wide range of applications in combustion. Figure 1.15 shows the pressure change per crank angle degree (CAD). The pressure change curve reveals a two-stage combustion process occurring before TDC. H2 O absorption data recorded in the region between the vertical dotted lines was reduced to gas temperature and water mole fraction.

Fig. 1.15 Pressure in the combustion chamber as a function of crank-angle degree after top dead center [34]

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1.5.4 Laser-Induced Fluorescence (LIF) Spectroscopy Laser-induced fluorescence (LIF) is a two-step process of absorption-emission in which a laser photon is absorbed with the emission of a fluorescence photon from the excited state [35]. Because of the resonant character of the excitation, with its typically large cross-section, minor species at very low concentration levels such as parts per million (ppm) can also be evaluated. It is possible to detect flame radicals and pollutant species with LIF in the in-situ detection. This is done by using singlephoton absorption processes (for example, CH, OH, NO, or formaldehyde) or by tuning the exciting laser to a wavelength where the species absorb two photons at the same time (two-photon LIF) (e.g., OH, N, O, CO). During the LIF process, a laser is usually used to excite a fluorescent species within the flow. Specifically, the tracer is an organic fluorescent dye such as fluorescein or rhodamine. Some portion of the excitation energy is absorbed by the dye and simultaneously re-emits some of the absorbed energy as fluorescence. The emitted fluorescence is then evaluated and used to determine the local concentration of the dye. In addition to this, LIF can also be used in measuring scalar concentrations at a point along a line in 2D planes [36], and in 3D volumes [37], although LIF is widely used in fluid flows for 2D planar laser-induced fluorescence (PLIF). There are many different strategies for studying combustion phenomena by employing LIF. When fundamental chemistry mechanisms are investigated, laminar systems are used, and quantitative concentration or temperature measurements are executed. This is commonly achieved by a point-wise scanning of the object of investigation step wisely. When complex flow phenomena are studied, PLIF is usually employed using a light sheet technique to obtain two-dimensional (2D) information about the mixture or flame structure simultaneously and instantaneously. The fundamentals, potential applications, and working principles of LIF for combustion research will be discussed later in this book.

1.5.5 Scattering Techniques Generally, laser scattering techniques consist of frequency-unshifted scattering, namely, Mie and Rayleigh scattering and frequency-shifted Raman scattering. It is worthy to note that the achievable signal intensities of these scattering processes vary widely in magnitude so that the instantaneous application of these techniques may be complicated or even unfeasible. This is particularly correct for Mie and Rayleigh scattering, which have the same emission frequency.

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Mie Scattering

Mie scattering is the elastic scattering of light from atomic and molecular particles whose diameter is greater than the wavelength of the incident light. When the dipole size is greater, the quasi-static evaluation will be inadequate to estimate the solution. Therefore, there is a need to work out the boundary value problem, i.e., the full-wave theory or Mie theory [38, 39]. With the help of this theory, the scattering crosssection does not grow continually with frequency. Considering a sphere of radius, the scattering cross-section has a high-frequency boundary of πa2. Mie scattering being the most robust scattering process, results from an interaction between phase boundaries and irradiated light. It can be utilized to know the location at which different phases occur, such as liquid-phase droplets or gas-phase bubbles in liquids or solid-phase particles in a gaseous state, which could still be a combustion environment. For example, Fig. 1.16 shows the typical mushroom-like complex of a diesel jet in the primary break-up region a few microseconds after leaving the injection nozzle (start of injection). It presents the liquid intact core being surrounded by a two-phase flow, and the gas phase is achieved by cavitation inside the nozzle [40]. It can be concluded that a laser sheet has been aimed into the center with the diesel jet of a mini sac-hole nozzle, using a long-distance microscope for signal detection. The jet velocity can then be calculated by recording two frames with a defined temporal delay. Mie scattering is commonly employed for a more macroscopic characterization of the direct injection of gasoline and diesel fuel, either directly or indirectly in the injection chambers [41]. In the case of particle Mie scattering, the scattering object size should equal the magnitude of the incident light wavelength. The intensity is a function of the particle diameter (dp), N is the number of particle density which is related to the direction of the incident laser beam. Considering the experimental study of an appropriately particle seeded flow, where the mean particle diameter and Fig. 1.16 Diesel jet primary spray break-up a few microseconds after the start of the injection [41]

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the observation angle are in good approximation constant, the intensity is relative to the number of particles, and to the seeded gas component concentration that can be utilized for imaging the flow of the gas concentration. To obtain Mie scattering, scattering particles are needed in the flow to be measured. In case no natural scattering particle is involved, artificial particles are used in the flow, which is referred to as seeding. Chen and Roquemore [42] developed a potential seeding technique for investigating flames, in which propane–air-jet diffusion flames were analyzed with respect to the zone of reaction and the flame structure. Another similar approach is directly seeding reactant gases with TiO2 or oil droplets as a flame-front marker. This is majorly applicable in the flamelet regime of premixed flames, where the thickness of the reaction zone is only 100 mm. For seeded oil, the flame front is shown by Mie scattering disappearance at the entrance of the reaction zone as the oil disappears. A direct seeding of TiO2 , which also occurs downstream of the reaction zone, helps to measure velocities flow in both the burned and unburned regions of the flame. In this case, the transition from the reactant to the product zone can be attained from the different seeding densities that result from the temperature-related gas density difference, and this can be used for a conditioned evaluation of the turbulence characteristics [43]. Mie scattering has also been considered to create the physical basis of laser Doppler anemometry (LDA). The Doppler principles are majorly based on the optical Doppler Effect that results from the light scattering of a moving object. The particle diameter can be calculated from the observable phase shift of the Doppler signals detected by the various sensors; this technique is known as phase Doppler anemometry (PDA) [44]. Recently, PDA has been used in spray flames to measure the mean droplet diameter in a gas-supported, swirl stabilized kerosene flame to determine the location of the high burning fraction of the droplets and the temperature measurements. In another example, the influence of different electrical field strengths and geometries on the atomization process of electrostatically charged hydrocarbon fuel sprays has been investigated [45]. It is worth noting that it is possible to employ both 2D material Raman and Mie scattering to determine the droplet diameter. For example, as a 2D measurement technique, Malarski et al. [46] have recommended imaging metrology to measure droplet diameters by simultaneously applying Mie scattering and 2D Raman. In this method, the ratio between the volume-dependent Raman signal and the surface area-proportional Mie signal is utilized to generate frozen images of the droplet diameter.

1.5.5.2

Rayleigh Scattering

The radiation scattered with no change of wavenumber is known as Rayleigh scattering when the scattering centers are very much smaller than the wavelength of the incident radiation. A simple solution for this scattering can explain the physical phenomena in nature. For example, what makes the sky have the color blue? The

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sunset is so excellently beautiful how birds and insects can move without the help of a compass. In Rayleigh scattering, the molecule is excited to a higher virtual energetic state, immediately falling back to a fundamental molecular energy level. This is because the incident photon’s energy is not adequate enough to excite higher quantum levels of the probed molecule. If the final level is indistinguishable from the initial level, then no energy exchange has occurred between the molecule and photon. It is crucial to conduct an independent scattering of the molecules in order to obtain a similar frequency for the emitted photon and the incident laser. It is usually impossible to detect selectively one individual species in a combustion system by Rayleigh scattering, as the signal will have followed all species in the gaseous mixture. Moreover, differences between the Rayleigh signal from scattered laser light (e.g., Mie scattering from particles or droplets) and the stray light of the environment are not possible unless additional measures are employed to block any undesired light, maybe by using a molecular filter to absorb the stray laser light and the narrow-band Mie scattering (filtered Rayleigh scattering) [47]. The strength I of the scattered light from one individual species is proportional to its number density c, multiplied by a species-specific, approximately temperatureindependent Rayleigh scattering cross-section [48]: I ∞c × σ where the index i runs over all n components in the mixture. For an ideal gas mixture, the number density ci can be expressed by the molar fraction  (xi) of  the species, ci.σ i. By pressure (p), and temperature (T) as ci = xi p/RT such that I ∞ P RT . applying this formula, temperatures can be obtained from Rayleigh signals, provided that information about the pressure and the mixture-averaged Rayleigh cross-section  ci.σ i is available. Although, this requires that the mixture-averaged Rayleigh cross-section does not vary significantly with the chemical composition, nor can it explicitly be estimated or determined [49]. Another approach for measuring temperature using Rayleigh scattering is to study the effect of the temperature-dependent Doppler broadening of Rayleigh light [50]. Recent planar Rayleigh scattering has been using a light sheet technique to obtain information on the temperature inside a 2D and 3D plane crossing the combustion field. In a 2D approach, two different wavelengths are irradiated simultaneously to form two adjacent parallel planes, with the signals being collected on two separate CCD cameras. Rayleigh experiments in crossed-plane configurations have also been performed, usually in combination with additional diagnostic approaches for obtaining 3D information along a line [51]. Rayleigh scattering has also been used on sooting flames by employing the filtered Rayleigh technique in practical systems like combustors or to investigate fuel vapor distribution in a heavy-duty direct injection (DI) diesel engine [52]. It has been applied to detect polarized and depolarized components of the Rayleigh signal in turbulent non-premixed flames, hence allowing measurement of the 2D distribution of fuel concentrations [53]. This method was coupled with LIF of OH and CO to

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obtain information on four different quantities (mixture fraction, temperature, scalar dissipation rate, and the rate of the reaction CO + OH → CO2 + H) in turbulent partially premixed flames. It is worthy to note that Rayleigh scattering can also be used together with other techniques to get broad information on the combustion process and validation of numerical simulations. This has been accomplished for instants by the simultaneous use of OH-LIF and planar Rayleigh, or planar Rayleigh with PIV, collecting at the same temperature, time, and flow velocity field information and allowing the direct determination of the turbulent flux [54].

1.5.5.3

Raman Scattering (RS)

Linear Raman Scattering (LRS) Raman scattering is an inelastic scattering in which the incident photons interact with molecules so that energy is either gained or lost, and the scattered photons are shifted in frequency. Raman scattering depends on the polarizability of the molecules. For polarized molecules, the incident photon energy can excite vibrational modes of the molecules, resulting in scattered photons with lower energy associated with the number of vibrational transition energies. Spectral analysis of the scattered light under this condition will reveal spectral lines under the peak of the Rayleigh scattering at the incident frequency. These lines are referred to as “Stokes lines.” When the vibrational state of the scattering molecules is excited, then it is also feasible to notice scattering at frequencies exceeding the incident frequency as the vibrational energy is attached to the incident photon energy. These weaker lines are known as anti-Stokes lines. Simultaneous excitation of all molecules in the sample volume without any restriction of the excitation frequency is one of the critical advantages of Raman scattering. Molecules in combustion have at least one Raman-active molecular energy transition. It is possible to measure a direct relative concentration by simultaneously collecting the Raman signals of all species in the probe volume if the relative Raman cross-sections of all species are known. Thus, high-frequency radiation is essential for Raman excitation, and Raman experiments with laser excitation at short wavelengths. In most combustion systems, the existence of species that fluoresce when exposed to UV radiation put a limit to the shortest practically feasible excitation wavelength in Raman experiments. Current knowledge suggests that the KrF-excimer excitation at 248nm is the shortest wavelength yet used for Raman experiments in combustion [55]. Figure 1.17 shows several approaches at which temperature can be determined from Raman scattering using temperature-dependent intensity distributions in the pure vibrational or rotational bands [57]. Information regarding the concentration can be obtained from the vibrational branches’ integrated line intensities or single rotational lines. Since absolute measurements are challenging to carry out, calibration at room temperature will simplify the procedure.

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Fig. 1.17 Schematic of the temperature dependence of the Raman spectrum in the pure rotational and rotational–vibrational bands. This example shows oxygen excited by a ruby laser [56]

Generally, the Raman technique has been used in the early stage for concentration and temperature measurement in combustion [58]. However, since then, linear Raman scattering has been applied widely to flame studies [59], with both 1D [60] and 2D [61] spatial resolution having been achieved. Despite the difficulties associated with the extremely weak signals, Raman measurements have also been performed in practical systems, such as in engines [62].

Polarization-Resolved Linear Raman Scattering It is almost impossible to apply linear Raman scattering in sooting flames and combustion systems because of the hindrances caused by chemiluminescence emissions, hydrocarbon fuel fluorescence interferences, particle Mie scattering, laser light reflection, or stray light. Therefore, the Raman effect’s polarization property is used to obtain unhindered Raman signals under these conditions [63]. The polarization method of Raman scattering involves suppressing the depolarized emissions from the highly polarized Raman signals by collecting separately the horizontally and vertically polarized signal components, followed by subtraction of the horizontal from the vertical polarization. Using this technique, Raman measurements have successfully been employed in combustion systems, which is difficult to achieve in traditional Raman techniques. The 2D distributions of several different combustion species and the gas temperature are displayed in Fig. 1.18. These have been determined via 1D Raman measurements in a highly sooting, non-premixed flame (which is also shown in Fig. 1.18).

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Fig. 1.18 2D distribution of combustion species concentration and flame temperature within the indicated field of view (left) in a sooting, non-premixed methane flame with bluff body taken by 1D polarization-resolved linear Raman scattering (the distributions of C2 H2 , CO2 , CO, and H2 are not shown here) [64]

Coherent Anti-Stokes–Raman Scattering Coherent Anti-Stokes–Raman Scattering (CARS), being one of the most widely used nonlinear Raman techniques, is a four-wave mixing process used to enhance the weak (spontaneous) Raman signal. In the CARS process, four different beams are employed. During the interaction of three irradiated laser beams in the interaction area, a fourth beam is generated that is emitted laser-like in one direction. The frequency of the CARS beam can be further explained from the knowledge of energy conservation which depends on the frequencies of the three irradiated beams and the energy difference between both molecular states of the studied species probed by the CARS process [65]. If these are vibrational states, then it will result in a vibrational CARS spectrum. On the other hand, if only rotational states within one vibrational molecular state are involved, then a pure rotational CARS spectrum is obtained.

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1.5.6 Simultaneous Multidimensional and Multiparameter Laser Diagnostics It is feasible to combine two or more advanced techniques to enhance the performance of these techniques, for example, to form an advanced sensor system. This may be either by applying different sensor types for process control in a parallel manner or by simultaneous application of non-intrusive tools in fundamental research. In general, there are two problems associated with combustion, which has called for more advanced diagnostic tools in combination. First, fundamental questions regarding the nature of turbulent combustion must be answered, including investigations of turbulence–chemistry interactions for non-premixed and premixed flames. Information regarding the structure of turbulent flames needs to be provided under the influence of different parameters such as turbulence ratios and varied mixture compositions. From the results of these studies, technically relevant conditions such as flame flashback, local extinction phenomena, flame instability, and pollutant formation would be better understood. Second, researchers have aimed to facilitate the numerical modeling of combustion phenomena and support computational fluid dynamics (CFD) studies. The experimental effort has provided pertinent data to validate and improve the current numerical approaches. However, the experimental strategies employed for investigating non-premixed and premixed flames differ widely due to their inherent nature. The mixture fraction expresses the most crucial quantity when describing the local state of non-premixed flames. Simultaneous imaging techniques have been introduced to understand the fundamental processes in non-premixed combustion better. For example, Carter et al. [66] demonstrated the applicability of a combined diagnostics approach to locate the flame front via single-shot-based CH-LIF and to characterize the flow field simultaneously by PIV. The study results showed the CH-layer to be typically 1mm smaller than the investigated jet flame, while simultaneous PIV measurements allowed an evaluation of the instantaneous flame front strain rates for which the flame was uninfluenced by flow-induced extinction. A flamelet assumption is applied for the numerical modeling for premixed flames, which allows a decoupled treatment of the turbulence and the locally laminar-like chemistry field [67]. Knowing the scalar field and the provision of flow field characteristics is essential if premixed flames are investigated to obtain a deeper fundamental understanding of numerical modeling. Because of this, Ferrao and Heitor [68] developed a combined LDA/Rayleigh system based on a single continuous-wave light source for the instantaneous time-resolved measurement of velocity and temperature. Their approach enabled a direct evaluation along with the radial profiles of two components of the turbulent heat flux in baffle-stabilized premixed flames to characterize better the turbulent heat flux of the reaction progress variable in a natural gas–air flame. Figure 1.19 shows typical instantaneous images of the V-shaped methane–air flame to investigate the local flame structure and heat release effects in various lean

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Fig. 1.19 Single-shot image of the simultaneous flow and heat release field measurement in a turbulent premixed V-shaped methane–air flame [69]

premixed flames. Simultaneous imaging has been used to examine changes in the flame structure and turbulent premixed methane–air flames approaching the blowoff condition. Breaks appearing in the heat release region at conditions far from blow-off revealed localized disappearance along with the shear layer, which showed not to be evident from the signal of the OH-PLIF. The heat-released region was shown to follow the main steps of the mean flame shape approaching blow-off: crossing the shear layer and entering the recirculation zone. This could be due to the local quenching of the flame, CH2 O was seen inside the recirculation zone, i.e., in regions filled with OH at conditions further from blow-off. The heat-released region is observed to be disconnected more toward the end than near the starting point, implying more extinctions there.

1.5.7 Interaction of Combustion Diagnostics, Theory, and Modeling Interaction between fields such as theory and modeling is essential for effective combustion diagnostics. For example, the Rayleigh technique has been employed to measure temperature in combustion processes. Although, this method is not applicable for all types of systems, as the mixture-averaged Rayleigh scattering crosssection of a reacting gas sample may be significantly altered during the reaction, thus disturbing the simple reciprocal dependence between the temperature and the Rayleigh signal. For example, Fig. 1.20 gives a diagrammatic illustration of the computed correlation between the Rayleigh signal (R) and temperature many of thermochemical states. The chemical composition (molar fractions) and temperatures of these states were

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Fig. 1.20 Computed correlation between the Rayleigh signal strength and temperature in a reacting methane–air system. a Random, but physically allowed initial states; b After the initial states have undergone combustion reactions for 100 ms [22]

generated randomly with the restrictions of meeting the conservation laws of energy and element composition. Therefore, the conditions are physically meaningful and could, in principle, appear in a combustion system. Figure 1.20a illustrates the dataset resulting from Rayleigh signal/temperature space, where each scatter point represents the corresponding computed (temperature and composition-dependent) Rayleigh signal and the temperature of a random state. The thick point cloud indicated that the signal–temperature relationship was very blurred, and it is worthy to note that if the gas composition were random, it would not be possible to determine the temperature from a Rayleigh signal with reasonable accuracy. To assess temperature with high precision and accuracy, the random states in Fig. 1.20a were allowed to undergo the combustion process for 100 ms, thus changing their chemical composition and temperature. When the Rayleigh signals were re-computed for the resulting new states and plotted against the new temperatures, there was a much sharper correlation between temperature and signal (Fig. 1.20b), and the temperature determination from the Rayleigh signal was now possible with reasonable accuracy [70]. Significant interactions between diagnostics, modeling, and theory in the combustion process are illustrated schematically in Fig. 1.21. One essential example of the interaction between diagnostics and modeling is the workshop series on turbulent non-premixed flames (TNF) [71]. This workshop sustains and encourages interaction of modeling and diagnostics, for example, by giving databases of detailed diagnostic results obtained in a set of flames that can be used to check the predictions of combustion models.

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Fig. 1.21 Some interaction mechanisms between diagnostics theory and modeling in combustion [22]

1.6 Exercises (1) Individual task: Find a scientific article on the classification of advanced diagnostic techniques from a relevant journal and discuss the experimental instrument used, its working principle, and the parameter analyzed by this diagnostic tool. (2) Individual task: Find a literature paper on one invasive method and present it. (3) Group task: In small groups, find a research article on one non-invasive technique, for instance, CARS or LIF, and do a PowerPoint presentation while highlighting its working procedure and the area of research. (4) Group task: In small groups, find a scientific article on different types of thermocouples and describe the material used and their applications across different research fields.

1.7 Questions (1) What is the difference between invasive and non-invasive diagnostic techniques? (2) Which methods can be applied in comparing invasive and non-invasive diagnostic techniques? (3) Can you describe the principle under which non-invasive diagnostic techniques operate? Use an illustrative diagram. (4) Explain pressure detection methods for in-cylinder pressure sensors. (5) Describe the detection principle of an In-cylinder Pressure Sensor.

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(6) (7) (8) (9) (10) (11)

Explain the working principle of piezoelectric pressure sensors. Describe the soot formation mechanism. Describe the Shadowgraphy visualization technique. Explain the principle of resistance thermometry. Describe how Schlieren imaging systems work. Describe under which condition the excited molecule in Rayleigh scattering immediately falls back to a fundamental molecular energy level. (12) Explain the importance of Polarization- Resolved Linear Raman Scattering over traditional Raman methods. (13) Briefly explain Coherent Anti-Stokes–Raman Scattering’s working principle and state its importance over other Raman Scattering approaches. (14) Describe the advantages of combining two or more advanced diagnostic techniques.

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18. Shimasaki, Y., et al. (2004). Study on engine management system using in-cylinder pressure sensor integrated with spark plug. SAE Technical Paper. 19. Poorman, T. J., et al. (1997). Ignition system-embedded fiber-optic combustion pressure sensor for engine control and monitoring. 1375–1380. 20. Dastanpour, R., et al. (2017). Variation of the optical properties of soot as a function of particle mass. 124, 201–211. 21. Bejan, A. (2016). Advanced engineering thermodynamics. Wiley. 22. Leipertz, A., et al. (2010). An overview of combustion diagnostics. 1–50. 23. Haumann, J., & Leipertz, A. (1985). Giant-pulsed laser Raman oxygen measurements in a premixed laminar methane–air flame. 24(24), 4509–4515. 24. Long, R. (1963). Optics of flames Including methods for the study of refractive index fields in combustion and aerodynamics. Butterworths, 1963. x+ 251 pp.(illus.). 55s. Elsevier. 25. Xiao, X. (2002). Digital recording and numerical reconstruction of holograms: An optical diagnostic for combustion. \41(19), 3890–3899. 26. Settles, G. S. (2001). Schlieren and shadowgraph techniques: Visualizing phenomena in transparent media. Springer Science & Business Media. 27. Gutmark, E., et al. (1989). Planar imaging of vortex dynamics in flames. 28. Kobayashi, H., et al. (1997). Turbulence measurements and observations of turbulent premixed flames at elevated pressures up to 3.0 MPa. 108(1–2), 104–117. 29. Leipertz, A., et al. (1996). Industrial combustion control using UV emission tomography. Paper presented at the Symposium (International) on Combustion. 30. Paschereit, C. O., et al. (1998). Structure and control of thermoacoustic instabilities in a gasturbine combustor. 138(1–6), 213–232. 31. Weikl, M., et al. (2009). Validation experiments for spatially resolved one-dimensional emission spectroscopy temperature measurements by dual-pump CARS in a sooting flame. 32(1), 745– 752. 32. Furlong, E., et al. (1996). Combustion control using a multiplexed diode-laser sensor system. Paper presented at the Symposium (International) on Combustion. 33. Gersen, S., et al. (2005). Extractive probe/TDLAS measurements of acetylene in atmosphericpressure fuel-rich premixed methane/air flames. 143(3). 34. Kranendonk, L. A., et al. (2005). Wavelength-agile sensor applied for HCCI engine measurements. 30(1), 1619–1627. 35. Eckbreth, A. C. (1996). Laser diagnostics for combustion temperature and species (vol. 3). CRC press. 36. Dahm, W., & Dimotakis, P. (1987). Measurements of entrainment and mixing in turbulent jets. 25(9), 1216–1223. 37. Van Vliet, E., et al. (2004). Time-resolved, 3D, laser-induced fluorescence measurements of fine-structure passive scalar mixing in a tubular reactor. 37(1), 1–21. 38. Mie, G. (1908). Beiträge zur Optik trüber Medien, speziell kolloidaler Metallösungen. 330(3), 377–445. 39. Wikipedia. (2020). “Mie scattering,” https://en.wikipedia.org/wiki/Miescattering 40. Heimgärtner, C., & Leipertz, A. (2000). Investigation of the primary spray breakup close to the nozzle of a common-rail high pressure diesel injection system. SAE Technical Paper. 41. Münch, K. U., & Leipertz. A. (1992). Investigation of Spray Penetration and Fuel Distribution Inside the Piston Bowl of a 1.9 l DI Diesel Engine Using Two-Dimensional Mie Scattering. SAE Technical Paper. 42. Chen, L. D., et al. (1986). Visualization of jet flames. 66(1), 81–86. 43. Armstrong, N. W., & Bray, K. N. (1992). Premixed turbulent combustion flowfield measurements using PIV and LST and their application to flamelet modelling of engine combustion. 2000–2011. 44. Bachalo, W., & Houser, M. (1984). Phase/doppler spray analyzer for simultaneous measurements of drop size and velocity distributions. 23(5), 235583. 45. Shrimpton, J., & Yule, J. (1999) Characterisation of charged hydrocarbon sprays for application in combustion systems. 26(5), 460–469.

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46. Malarski, A., et al. (2007). Laser sheet drop sizing using Raman and Mie scattering. Paper presented at the Journal of Physics: Conference Series. 47. Hoffman, D., et al. (1996). Two-dimensional temperature determination in sooting flames by filtered Rayleigh scattering. 21(7), 525–527. 48. Zhao, F. Q., et al. (1993). The applications of laser Rayleigh scattering to combustion diagnostics. 19(6), 447–485. 49. Namer, I., & Schefer, R. (1985). Error estimates for Rayleigh scattering density and temperature measurements in premixed flames. 3(1), 1–9. 50. Pitz, R., et al. (1976). Temperature and density in a hydrogen-air flame from Rayleigh scattering. 27, 313–320. 51. Chen, Y. C., et al. (2002). Experimental investigation of three-dimensional flame-front structure in premixed turbulent combustion—I: Hydrocarbon/air bunsen flames. 131(4), 400–435. 52. Espey, C., et al. (1994). Quantitative 2-D fuel vapor concentration imaging in a firing DI diesel engine using planar laser-induced Rayleigh scattering. 1145–1160. 53. Fielding, J., et al. (2002). Polarized/depolarized Rayleigh scattering for determining fuel concentrations in flames. 29(2), 2703–2709. 54. Most, D., & Leipertz, A. (2001). Simultaneous two-dimensional flow velocity and gas temperature measurements by use of a combined particle image velocimetry and filtered Rayleigh scattering technique. 40(30), 5379–5387. 55. Linow, S., et al. (2002). Measurement of temperature and concentration in oxy-fuel flames by Raman/Rayleigh spectroscopy. 13(12), 1952. 56. Leipertz, A. (1989). Raman processes and their application. Instrumentation for combustion and flow in engines (pp. 107–122). Springer, Netherlands. 57. Lapp, M., & Penney, C. M. (1974). Laser Raman gas diagnostics. Springer. 58. Boiarski, A., et al. (1978). Flame measurements utilizing Raman scattering. 32, 111–114. 59. Hassel, E. P. (1993). Ultraviolet Raman-scattering measurements in flames by the use of a narrow-band XeCI excimer laser. 32(21), 4058–4065. 60. Nandula, S. P., et al. (1994). Single-pulse, simultaneous multipoint multispecies Raman measurements in turbulent nonpremixed jet flames. 19(6), 414–416. 61. Long, M. B., et al. (1983). Instantaneous Ramanography of a turbulent diffusion flame. 8(5), 244–246. 62. Miles, P. C., & Dilligan, M. (1996). Quantitative in-cylinder fluid composition measurements using broadband spontaneous Raman scattering. SAE Technical Paper. 63. Leipertz, A., & Fiebig, M. (1980). Using Raman intensity dependence on laser polarization for low gas concentration measurements with giant pulse lasers. 19(14), 2272_1–2274. 64. Egermann, J., et al. (2004). Application of 266-nm and 355-nm Nd: YAG laser radiation for the investigation of fuel-rich sooting hydrocarbon flames by Raman scattering. 43(29), 5564–5574. 65. Maker, P., & Terhune, R. (1965). Study of optical effects due to an induced polarization third order in the electric field strength. 137(3A), A801. 66. Carter, C. D., et al. (1998). Simultaneous CH planar laser-induced fluorescence and particle imaging velocimetry in turbulent nonpremixed flames. 66(1), 129–132. 67. Peters, N. (2000). Turbulent combustion. Cambridge University Press. 68. Ferrão, P., & Heitor, M. (1995). Turbulent mixing and non-gradient diffusion in baffle-stabilized flames. In Turbulent Shear Flows 9 (pp. 427–437): Springer. 69. Pfadler, S., et al. (2007). Flame front detection and characterization using conditioned particle image velocimetry (CPIV). 15(23), 15444–15456. 70. Abrukov, S., et al. (1975). Application of interference and holographic methods to the study of combustion processes in coaxial burners. 29(2), 1043–1045. 71. Barlow, R. S. (2003). International workshop on measurement and computation of turbulent nonpremixed flames.

Chapter 2

Gas Chromatography/Mass Spectrometry Zhen-Yu Tian, Vestince Balidi Mbayachi, Wei-Kang Dai, Maria Khalil, and Daniel A. Ayejoto

2.1 Introduction Gas chromatography/mass spectrometry (GC/MS) is an analytical technique that is used to analyze complex organic mixtures [1]. Gas chromatography (GC) separates semivolatile and volatile components with a great resolution, while mass spectrometry (MS) identifies these components and provides detailed structural information at a molecular level. The combination of these two analytical techniques has been used in the study of chemical components such as organic molecules or gases (Fig. 2.1). Combustion (exothermal sequence reaction between a fuel and oxygen) and pyrolysis (thermal decomposition of matter in the absence of oxygen) yields volatile components that are studied by GC/MS. In Pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS), sufficient heat is applied to a high molecular weight sample and this causes the cleavage of bonds in the presence of inert atmosphere (vacuum) resulting in volatile molecules of low molecular weight (pyrograms). Using mass spectrometry (MS), the chromatogram (pyrograms) provides quantitative and qualitative information of the sample. Kong et al. [2] investigated the Z.-Y. Tian (B) · W.-K. Dai Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China e-mail: [email protected] Z.-Y. Tian · V. B. Mbayachi · W.-K. Dai · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_2

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Fig. 2.1 Gas chromatography/mass spectrometry

different concentrations of phenol species in coal pyrolysis using GC/MS [2]. In their experiment, seven species of phenol were obtained from the pyrolysis of four different coals which was characterized by flash pyrolysis (Py)-GC/MS in situ. Combustion research using GC/MS differs from that of pyrolysis since it is performed offline and the combustion products are collected, injected followed by extraction into a suitable solvent and then analyzed by GC/MS. Solid products from combustion may also be captured and analyzed using Py-GC/MS (Fig. 2.2). Cheng et al. [3] used TD-GC/MS in the measurement of volatile organic compounds (VOCs) during coal combustion at various heating rates [3]. In this chapter, both combustion and pyrolysis research approaches have been included.

2.2 Theory In 1952, the modern gas chromatography was invented by James and Martin [4]. Since then, there has been an advancement in terms of columns, sample introduction, and detection methods, making GC an ideal analytical tool in modern scientific society. Gas chromatography (GC) works under the principle where the sample components are partitioned between stationary and mobile phase, as shown in Fig. 2.3. Compounds with high affinity for mobile phase have shorter retention time (Rt), thus spending less time in the capillary columns compared to those samples with high affinity for the stationary phase which spend more time in columns due to polarity and intermolecular interactions. The separation is achieved by distribution of the sample between the carrier gas and stationary phase (columns). Figure 2.4 illustrates how the sample is injected into a heat block and how it vaporizes and then gets swept by carrier gas into the column inlet. Inside the column, the solutes are absorbed by the stationary phase and desorbed

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Fig. 2.2 Schematic of pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) [5]

Fig. 2.3 A schematic diagram of a gas chromatograph [6]

by the carrier inert gas (helium). Each solute in the column travels at its own rate resulting in distinct band zones based on the partition coefficient. The solutes elude and enter the detector in an increasing order of their distribution constant (KD). A series of signals results from elution rate and concentration change and are recorded

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Fig. 2.4 Schematic of GC working principle [7]

in form of peaks. The quantitative data is then yielded by measuring the width, area, time, and height of these peaks. GC/MS columns are usually a long and coiled capillary tube of silica with an internal coating of a viscous liquid such as Carbowax [6]. There are two main GC column types that include packed and capillary columns (Fig. 2.5). Packed columns consist of stainless steel that is filled with absorbent materials and they are characterized by their high capacity and robustness. Capillary columns are mostly used nowadays in most applications because of their high separation efficiency. Capillary columns (open tubular columns) are thin and usually fused with silica (quartz, SiO2 ) capillaries coated with polyamide layer that improves its stability and flexibility. Mass spectrometry (MS) measures precisely the mass (weight) of compounds in a substance, then identifies each compound and its quality from the weight. MS works under the basic principle of utilizing the nature of ions and the different intensities of the magnetic field. The ions are accelerated to a certain speed and then passed through a magnetic field. The path of the ion is deflected by the magnetic field and the mass number of ions is determined by the amount of deflection, as presented in Fig. 2.6. The coupling of gas chromatography with mass spectrometry (GC/MS) provides a powerful tool for the analysis of complex organic mixtures. In GC/MS, ionized molecules through chemical ionization or electron bombardment exit from gas chromatography to mass analyzer and get separated based on the mass-to-charge (m/z) ratio, as displayed in Fig. 2.7. Quadrupole mass analyzers are commonly used because of their low cost, ruggedness, and fast scanning capability. Ion-trap analyzers and Time of flight are also

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Fig. 2.5 Packed column (left) and capillary column (right) diagrams [8]

Fig. 2.6 Schematic illustration of the working principle of MS. Excerpted from OpenStax under CC-BY 4.0

common. Electron multiplier detectors convert ion beams to electrical signals, which are then amplified and processed by the data analysis system. The data is recorded as a single ion chromatogram, monitoring a single m/z ratio during the analysis or as a total ion chromatogram, which sums the ion abundances in the mass scans and plots this as a function of time. The limitation of GC/MS in sample analysis is timeconsuming and limited to thermal stable and volatile compounds. The advantages include high efficiency, accuracy, ability to quantify analytes, separation of complex mixtures, and determination of trace elements of organic contamination.

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Fig. 2.7 Schematic representation of a GC/MS system [6]

2.3 Literature Review According to the search, conducted by SciFinder on the research topic, combustionGC/MS on December 8, 2008, the data shows a growth trend and maturation of this research technique from the mid-1990s (histogram in Fig. 2.8) [9]. Py-GC/MS technique with similar search showed a wider application with a number of publications (1881 in total; data not shown). Focusing the search using the same information from a period of 2006 to 2008 gave a total of 94 references for Py-GC/MS and 36 references for combustion-GC/MS.

Fig. 2.8 A histogram conducted on (8th December 2008) by SciFinder showing a total of 226 number of publications on research topic, combustion-GC/MS [9]

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Table 2.1 demonstrates a breakdown of the reports on different applications of PyGC/MS and combustion-GC/MS research by articles from the past three years. The report was classified based on the type of sample being analyzed to show the diversity in the application of GC/MS in pyrolysis and combustion research. Around one-third of the Py-GC/MS papers are related to natural organic matter (NOM) in soil, sludge, wood, and sediments. Moreover, Py-GC/MS is applied in the characterization of microorganisms and microbial agents, and in the thermal degradation of biomass with the recent emphasis on coal, fuels, and energy. Earlier, pyrolysis and combustion reviews include coal pyrolysis [10], which is the landmark to this subject; wood and coalified logs [11]; brominated flame retardants in on-line operation [12]; fossil fuel research [13] and chemical characterization of organic matter in soil [14]. Table 2.1 Scientific literature survey (2006–2008) on Py-GCM/S and Combustion-GC/MS analysis

Subject area

No. of reports

Combustion-GC/MS or Py-GC/MS analysis Soil, sediment, sludge

12

Lignin, wood, peat

12

Microbial, fungal

11

Natural organic matter

8

Rubber

7

Energy, fuels

7

Flame retardants

5

Nanoparticles, nanotubes

5

Black carbon

4

Forensics, fingerprinting

4

Ink, art

4

Resins

3

Carbohydrates, sugars

3

Miscellaneous

9

Combustion-GC/MS analysis Biomass, microbes

7

Food, glucose

5

Coal

4

Fuels

4

Emission, exhaust

3

PAHs

2

Miscellaneous

11

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2.4 Recent Applications of GC/MS Recently, combustion-GC/MS and Py-GC/MS have been applied across various fields ranging from the study of furfural oxidation in a jet-stirred reactor (JSR) [15] to the fingerprinting of environmental samples [16]; Py-GC in forensic science [17] and the study of microplastics identification [18]. In this chapter, the following application methods have been discussed in detail.

2.4.1 Motored Engine Study Synthetic diesel and biodiesel fuels have been investigated as possible alternatives to diesel fuel. Szybist et al. [19] experimented on the autoignition process of gasto-liquid (GTL) diesel, methyl decanoate, convectional diesel fuel, biodiesel, and n-heptane in the motored engine by studying their premixed condition behavior. The experiment was done using different fuels, fuel-to-air mixtures, and cylinder compression ratios while monitoring the exhaust compositions by Fourier transform infrared (FTIR) spectrometry and analyzing them using gas chromatography/mass spectrometry (GC/MS). Two ignition processes were demonstrated for each fuel where a low-temperature heat release (LTHR) was followed by the main combustion (High-temperature heat release). Figure 2.9a, exhibits n-heptane LTHR as a percentage of the total heat release at 110 °C. From Fig. 2.9a, it’s evident that the highest LTHR percentage of total heat takes place at the lowest equivalent ratio (ϕ), and an increase in ϕ decreases the % LTHR initially but remains constant at ϕ > 0.75. Figure 2.9b indicates the % LTHR for (GTL diesel at 260 °C, diesel light at 260 °C, and methyl decanoate at 230 °C) and it’s evident that the fuel composition determines the LTHR magnitude.

Fig. 2.9 LTHR as percent of the total heat release for (▲) n-heptane, (⟁) GTL diesel, (◯) diesel light and (∎) methyl decanoate [19]

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FTIR analysis of these fuels also showed that LTHR produced high amounts of carbon monoxide (CO) and aldehyde but low concentration of carbon dioxide (CO2 ). GC/MS analysis of GTL and convectional diesel fuel at LTHR showed high molecular weight of ketones and aldehydes. For methyl decanoate, the GC/MS analysis of the condensed exhausted showed that aliphatic chain acted similar to n- paraffin during LTHR, while the ester group remained intact. GC/MS in this experiment played a crucial role in determining the occurrence of a series of reactions under combustion experimental conditions.

2.4.2 Alteration of Organic Matter Ionizing radiation refers to the energy source that can generate and alter complex organic matter. In this application, the effects of ionizing radiation were studied using pyrolysis–gas chromatography/mass spectrometry (Py-GC/MS) on a set of ten naturally occurring extraterrestrial organic matter (Bitumen) [20]. In the experiment, Court et al. [20] used a CDS pyroprobe1000 fitted with a 1500 valve interface and coupled to an Agilent Technology 6890 gas chromatograph and a 5973 mass-selective detector (MSD). During pyrolysis, the samples were heated under a flow of helium to a temperature 20 °C to 600 °C ms−1 for 15 s. Gas chromatography oven temperatures were held at 50 °C for 1 min, then increased at 5 °C min−1 to 300 °C and held at that temperature for 9 min. Helium carrier gas flowing at 1.1 ml min−1 with a SGE BPX5 column was used in separation and the compounds were identified using 5973 mass spectrometry. Pyrolysis products data (Chromatograms) showed that alkene-alkane couplets (Fig. 2.10) are dominated by the nonirradiated group 1 (complex hydrocarbon mixtures A-B) while group 2 mixtures (Fig. 2.11) are dominated by the polycyclic hydrocarbon (F-J). Group 3 (in Fig. 2.10) is the presumed methane-derived mixtures (C-E) and is dominated by bitumen. From Figs. 2.10 and 2.11, it is observed that the heterogeneity of products, the average size of the mixtures, and the polycyclic hydrocarbon (PAH) alkylation degree decrease with the increase in radioelement concentration (% wt.). Presumed methanederived mixture group 3 (C-E) is also dominated by PAH, but their heterogeneity, average size, and alkylation degree of PAH increase with the increasing radioelement concentration. Moonta and Laxey (Fig. 2.11) contain oxygen compounds such as benzaldehyde and benzoic acid. In conclusion, it was suggested that radiolytic alteration may increase the mean combustion temperature of organic matter due to the gradual loss of hydrogen (H) that causes a decrease in H/C ratio.

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a

b

c

d

e

Fig. 2.10 Chromatogram of pyrolysis products of the nonirradiated group 1 mixtures (a–b) and presumed methane-derived mixture group 3 (c–e). The radioelement concentration is represented in percentages (%wt.) [20]

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f

g

h

i

j

Fig. 2.11 Chromatogram of pyrolysis products of the irradiated group 2 mixtures (f–j). The radioelement concentration is represented in percentages (%wt.) [20]

2.4.3 Identification of Historical Ink Ingredients Inks have been prepared in the past centuries by using several recipes. It consists of a wide variety of ingredients such as galls, vitriol in iron gall inks, and charcoal in carbon-based ores which were believed to be a major cause of paper degradation. Thus, there is a need to know how inks were prepared and which substrates were employed during their production process. This can be done by providing a simple chemical characterization of these ingredients using pyrolysis–gas chromatography/

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Fig. 2.12 Schematic diagram of Py-GC/MS. The evolved gas was led into the separation column while the valve of the selective sampler was closed [21]

mass spectrometry (Py-GC/MS) (see Fig. 2.12). The pyrolysis profile is known as pyrogram [21]. Programs were collected for a series of substances that were commonly used in past centuries during the course of ink preparation [22]. The study was aimed at providing a basic chemical characterization of ingredients, such as the seeds and peels of pomegranate, gum Arabic, apricot gum, saffron, henna, and mustard. Pyrolysis was carried out at 500 °C using an SGE Projector II microfurnace, which was connected directly to a CLARUS 500 GC/MS system (Perkin-Elmer). Helium carried the pyrolysis products to a 30 m × 0.25 mm internal diameter (i.d.) fused-silica column coated with a 0.25 mm film of RTX® 5 (cross-bonded 5% diphenyl, 95% dimethyl poly-siloxane). The oven temperature was set to 45 °C for the first 3 min, and then increased at 10 °C min−1 to 250 °C, which was held for 20 min. The electron impact mass spectrometer was scanned from m/z 25 to m/z 1200 in 0.2 s. The structural assignment of compounds was based on spectral matching with the NIST 2002 library. A variety of compounds were identified in the programs, some of which were characteristics of the particular ingredient. For example, the program was found for white mustard (Sinapis alba L.), a perennial plant the seeds of which are yellow to light brown in color (despite the name) and consist mostly of proteins and fatty oils. The seeds were also rich in oleic acid, and contained a variety of aromatic compounds, as well as phenol and 4-methyl-phenol. However, it was noted that further investigations would be required to identify the best analytical approach for these aged ingredients, and how other constituents of the inks might influence the pyrolysis process, before examining any original artworks. Py-GC/MS has been shown to be a useful technique to detect between ingredients of inks of organic origin, such as gums, extracts of seeds and peel of pomegranate, henna, mustard, etc., which were used in medieval to 19th-century ink recipes. A variety of compounds have been identified in the pyrograms, some of which are characteristics of the particular ingredient. An example is the pomegranate seeds which contain lignin, cellulose and other polysaccharides, tannins (in lesser amounts

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Fig. 2.13 Total ion chromatogram obtained from pyrolysis of pomegranate seeds at 500 °C [22]

than the peel), amino acids (bound to lignin and phenolic acids) [23]. The pyrogram obtained from analysis of pomegranate seeds at 500 °C is shown in Fig. 2.13. From Fig. 2.13 above, it can be seen that the composition of pomegranate seeds is reflected by the high amounts of phenolic derivatives among the fragmentation products. The compounds 2-methoxy-phenol (8), 2-methoxy-4-methyl-phenol (9), 2-methoxy-4-(1-propenyl)-phenol (14) are decomposition products of lignin. 2-Methoxy-4-vinylphenol (12) is probably a degradation compound of ferulic acid, which is itself formed as a decomposition product of lignin. Sinapyl alcohol, also a moiety of lignin, is probably the precursor of 2,6-dimethoxy-phenol (13). Pyrrole (1), toluene (2), and 1-hydroxy-2–2-butanone (3) are extracted at early retention times. Derrick and Stulik [24] also employed Py-GC technique to characterize natural gums used in works of art. Gum arabic, tragacanth, guar, ghatti, and karaya all gave distinguishable and reproducible pyrograms, enabling their identification. Figure 2.14 shows the pyrogram of gum arabic. It is characterized by the formation of cyclopentene and furan derivatives, as 2-furaldehyde (19), 2-cyclopenten-1one (30), 2-hydroxy-cyclopenten-1-one (23), 3-methyl-1,2-cyclopentanedione (5), 2-methyl-2-cyclopenten-1-one (33), and 2,3-dimethyl-2-cyclopenten-1-one (36).

2.4.4 Analysis of Deteriorated Rubber-Based, Pressure-Sensitive Adhesives In a study done by Kumooka [21], with implications for forensic investigations, packing tapes were exposed to sunlight for six months in order to accelerate oxidation of the adhesives. Programs were collected on the exposed and unexposed adhesives, using a PY2020D pryolyzer equipped with a SS-1010E selective sampler (Frontier Laboratories, Koriyama, Japan). The pyrolysis was conducted at 500 °C with the pyrolysis–gas chromatograph interface set at 320 °C. The gas chromatograph was a model 6890 and the MSD was a 5973N (both from Agilent). The pyrolysis products

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Fig. 2.14 Total ion chromatogram obtained from the pyrolysis of gum arabic at 500 °C [22]

were separated on a 30 m Ultra alloy-5þ metal capillary column (0.25 mm i.d., film thickness 0.25 mm). The temperature programming consisted of 40 °C for 2 min, followed by a heating rate of 10 °C min–1 to 200 °C, then 20 °C min–1 to 300 °C, and finally held constant at this temperature for 5 min. The MSD was operated in scan mode with a range of 29–450 (m/z). Approximately 0.2 g of the unexposed RBPSA of the other samples was analyzed. Both, isoprene and limonene—the main pryolyzates of natural rubbers—disappeared from the programs of the adhesives following the exposure period, and the elastomer of each adhesive was oxidized. Other differences were observed between packing tapes and between exposed and unexposed adhesives, including a pyrolyzate peak of b-pinene resin (used as a tackifier) found in the exposed product but not in the unexposed product, although this may have been due to masking by the limonene peak. Because forensic chemists use both Py-GC/MS and FTIR spectroscopy to discriminate adhesives, the research group also collected IR absorption spectra. Such spectra for the adhesives were changed so drastically after exposure that it was difficult to identify the constituents. In comparison to FTIR, these authors concluded that Py-GC/MS would be more suitable for the examination of RBPSAs. They also found that natural rubbers and aliphatic petroleum resins decomposed completely during the course of deterioration. However, the tackifiers, which were mostly coumarone resins, aromatic petroleum resins, and b-pinene resins, could be identified by Py-GC/ MS, even after deterioration. An aliphatic petroleum resin was used as a tackifier in adhesive 204 (Fig. 2.15a). The pyrolyzate of an aliphatic petroleum resin disappeared from the pyrogram of adhesive 204 after the exposure (Fig. 2.15b). Pyrograms of Quintone A100 (an aliphatic petroleum resin) and the exposed resin are also shown in Fig. 2.15c and d. Aliphatic petroleum resins oxidized severely. A coumarone resin was used as a tackifier in adhesive 244. Styrene, amethylstyrene, coumarone, and indene were identified in the programs of the exposed

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Fig. 2.15 Total ion pyrograms of a adhesive 204, b the exposed adhesive 204, c Quintone A100, and d the exposed Quintone A100 [21]

Fig. 2.16 Total ion pyrograms of a adhesive 244, b the exposed adhesive 244, c Escuron G-90, and d the exposed Escuron G-90 [21]

adhesive 244 and the unexposed adhesive (Fig. 2.16a, and b). Programs of Escuron G-90 (a coumarone resin) and the exposed resin are also shown in Fig. 2.16c and d.

2.4.5 Determination of Ergosterol as an Indicator of Fungal Biomass The detection and analysis of fungi is important in a number of fields, including biology, nutrition, and medicine. Substances that have been used as markers of fungal

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contamination include chitin (a component of the fungal cell wall) and ergosterol (a major sterol constituent of most fungi). Efforts have been made to develop techniques for the rapid screening of fungal samples; classical methods may require incubation periods and rely on morphology and biochemical reactivity studies [25]. Gijs van Erven and his coworkers [26] performed a study on ergesterol detection. In their research, the combination of quantitative 13 C-IS py-GC–MS and whole cell wall HSQC NMR was applied to fungal-treated wheat straw after growth of two strains of C. subvermispora, P. eryngii, and L. edodes to give a better understanding of their delignification mechanisms. Ceriporiopsis subvermispora (Cs) and Lentinula edodes (Le) were found to be more effective and selective wheat straw lignin degrading fungi than Pleurotus eryngii (Pe). They degraded more than 60% (w/w) of lignin without extensive carbohydrate degradation within 7 weeks of treatment. Although Cs and Le followed a similar pattern of lignin degradation in time, the structural features of residual lignin as determined by quantitative 13C-IS py-GC–MS and in situ HSQC NMR were greatly different. Both techniques revealed that Cs-treated lignin was remarkably high in Cα-oxidized substructures (up to 24% of aromatic units) and a factor is two times higher than Le-treated lignin. Le and Pe, on the other hand, more specifically targeted ferulic acid substructures, while Pe preferentially removed tricin up to 40% more than other substructures. Furthermore, carbons’ delignification mainly proceeded via Cβ –O–aryl and Cα –Cβ cleavage of the lignin inter-unit linkages, while inter-unit degradation by Le and Pe seemed dominated by Cα –Cβ cleavage with Cβ –O–aryl cleavage occurring to lesser extents. We, therefore, suggest that the underlying delignification mechanisms of these fungi are fundamentally different. Besides assisting the further optimization of fungal pretreatment of plant biomass, it was also found that the choice of fungus has an effect on the structure of residual lignin which leads to lignin with remarkable structure. Thus, fungal pretreatment not only enhances the degradability of plant cell wall polysaccharides, but also results in an interesting lignin fraction that can be exploited to further increase the sustainability of the process. Parsi and Gorecki [27] also reported a new rapid and robust method for ergosterol detection based on the combination of non-discriminating flash pyrolysis (see Fig. 2.17) with GC/MS detection. This method, which is further described by Parsi et al. [28], minimizes loss of the less-volatile pyrolyzates by modifying the pyrolyzers (essentially eliminating the pyrolysis–gas chromatograph injector interface). By reducing the dead volume and forcing the flow of the carrier gas through the pyrolyzed sample, it was possible to provide a more efficient transfer of highmolecular-weight compounds (e.g., ergosterol) to the GC/MS system. By using this set-up, the authors determined the presence of ergosterol—and thus the presence of fungi in the pyrolyzed sample—in a variety of matrices, including baker’s yeast, moldy bread, indoor dust, and a leaf infected with powdery mildew. Ergosterol was detected in all samples, ranging from approximately 6 mgg−1 for the indoor dust to 4000 mgg−1 for the baker’s yeast. The major advantages of the method over conventional extraction schemes were that only a very small sample was required, and this needed no preparation prior to the analysis.

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Fig. 2.17 Schematic diagram of the non-discriminating flash pyrolysis system [27]

The method of non-discriminating flash pyrolysis proved to be a useful tool in the analysis of biomarkers. The method reduces sample preparation time and disposal costs compared to many alternative procedures. It has been successfully applied to the analysis of a wide variety of samples in combination with GC/MS and 2D gas chromatography–time-of-flight mass spectrometry (GC × GC/TOFMS) [29–32]. Figure 2.18 illustrates the pyrogram obtained for the same sample in selected ion monitoring mode (SIM) mode (m/z 337, 363, and 396 u). The relative abundances of the ions were in good agreement with those obtained for the ergosterol standard. Using the ergosterol calibration curve and the internal standard, the average amount of ergosterol in the baker’s yeast sample (S. cerevisiae) was estimated to be ∼4 mg/ g (0.4%), which was comparable to the amounts reported in the literature [33]. The feasibility of the non-discriminating flash pyrolysis-GC/MS method for the detection of the ergosterol content of fungi was thus confirmed using S. cerevisiae. Fig. 2.18 Ergosterol peak from non-discriminating flash pyrolysis of S. cerevisiae at 650 °C (SIM mode; m/z 337, 363, and 396 u) [27]

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2.4.6 Characterization and Evaluation of Smoke Tracers in PM During the 2003 wildfire season, western Montana was heavily impacted by forest fire smoke (see Fig. 2.19). Ward. Ward et al. [29] collected 24 h samples of 2.5 mmdiameter particulate matter (PM2.5) during significant smoke events, and analyzed the filter samples using high-performance liquid chromatography (HPLC) and GC/ MS. The reason behind the analysis was to evaluate the concentrations of several chemical markers of wood smoke generated under natural combustion conditions. The filter samples were extracted and analyzed for levoglucosan, following a derivatization procedure, and for methoxyphenols by using a recovery standard with the label in methoxy group (CD3 ). A HP5890 gas chromatograph and a HP5970 mass spectrometer were used, and several characteristic ions were monitored in selected ion monitoring mode for quantification. It was concluded that, of all the potential markers for wood smoke derived from PM, levoglucosan remain the most valuable as it was found in all samples when using GC/MS, and it had the strongest correlation with PM. The anhydrosugars, galactosan, and mannosan were also detected, but at lower levels than levoglucosan; HPLC was unable to detect the former biomarkers. Interestingly, the ratios of the markers (levoglucosan to mannosan, and guaiacol derivatives to syringol derivatives) were indicative of softwood (major tree) combustion. It was reported that the source profiles might be used to apportion forest fire smoke PM2.5 in northern Rocky Mountain airsheds during forest fire events such as the one studied. Cordell et al. [34] also reported the development of an improved gas chromatography–mass spectrometry method to quantify atmospheric levels of monosaccharide anhydrides (MA) which was fully validated. The method employed an optimized, low-volume methanol extraction, derivatization by trimethylsilylation, and analysis with high-output gas chromatography–mass spectrometry (GC–MS). Recovery of levoglucosan was approximated to be 90%, and 70% for the isomers galactosan and mannosan, was obtained using spiked blank filters estimates. The method was extensively validated to ensure that the precision of the method over five experimental replicates on five repeat experimental occasions was within 15% for low, mid, and Fig. 2.19 Smoke tracers in particulate matter from wildfires

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high concentrations and accuracy between 85 and 115%. The lower limit of quantification (LLOQ) was 0.21 and 1.05 ng m−3 for levoglucosan and galactosan/mannosan, respectively, where the assay satisfied precisions of ≤20% and accuracies 80–120%. The limit of detection (LOD) for all analytes was found to be 0.105 ng m−3 . The stability of the MAs, once deposited on aerosol filters, was high over the short term (4 weeks) at room temperature and over longer periods (3 months) when stored at − 20 °C. The method was applied to determine atmospheric levels of MAs at an urban background site in Leicester (UK) for a month.

2.4.7 Trace Organic Species Emitted from Biomass Combustion and Meat Charbroiling Relative to Particle Size Emissions resulting from burning of biomass remain a significant, global source of trace gas and aerosol species in the atmosphere and affect climate, visibility, and human health. Kleeman et al. [35] conducted research on analysis of size-resolved particulate matter emissions from pine, California oak, east coast oak, eucalyptus, rice straw, cigarette smoke, and meat cooking for trace organic species using solventextraction followed by GC–MS analysis. Six particle size fractions were studied between 0.056, 0.1, 0.18, 0.32, 0.56, 1.0, and 1.8 μm particle diameter. The smallest particle size fraction analyzed was in the ultrafine (Dp < 0.1 μm) range that has been implicated as a potential health concern (see Fig. 2.20). Fourteen PAHs were also detected in the ultrafine size fraction of wood smoke with the most abundant species (benzo[ghi]fluoranthene) emitted at a rate of 0.2–0.4 (mg kg−1 wood burned). Nine PAHs were detected in the ultrafine size fraction of rice straw smoke with the most abundant compound (benzo[a]pyrene) emitted at 0.01 (mg kg−1 rice straw burned). The most abundant PAH measured in the ultrafine size fraction of cigarette smoke was benzo[ghi]fluoranthene (0.07 mg cigarette−1 ) followed closely by chrysene/ triphenylene (0.06 mg cigarette−1 ). Fig. 2.20 Particle-sized emissions from biomass combustion

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Apart from the PAHs, the most abundant compounds identified in the wood included levoglucosan ( 0.9) with the size distribution of particle-phase organic carbon (OC) and/or elemental carbon (EC). The only organic compounds besides PAHs detected in the ultrafine size fraction of rice straw and cigarette smoke were benz[de]anthracen-7-one (0.19 mg kg−1 rice straw burned) and 4-methylphenylacetone (2.64 mg cigarette−1 ), respectively. Caffeine was measured in cigarette smoke size fractions >0.1 μm with a total PM1.8 emissions rate of 1 (mg cigarette−1 ). The most abundant organic species measured in meat cooking smoke was cholesterol with a size distribution that was highly correlated with both OC and EC. The concentration of each compound normalized by the concentration of total OC was relatively uniform for all particle sizes. Cholesterol and levoglucosan should prove to be useful tracers for meat cooking and wood smoke emissions in the ultrafine size range.

2.4.8 Conversion of Rice Husks and Sawdust to Liquid Fuel via Pyrolysis In recent years, the application of agricultural and wood residues such as rice husk and saw dust has gained much more attention than other agricultural wastes, as they are cheaper in cost. Both the abundant availability of agricultural residues and the technological development of biomass conversion techniques have allowed the biomasses generated from rice industry to be converted into an essential source of renewable power. Fig. 2.21 shows the potential application of rice husk for power generation. Rice husk and saw dust have accounted for over 900 million tons of dry mass in China. However, the traditional methods for processing these organic wastes such as composting and incineration are not reliable as they consist of little nitrogen for composting and lot of solid grains and smoke will be released to pollute environment during incineration. Therefore, there is a need to develop a new method to deal with rice husk and saw dust. In view of this, Zheng et al [36] have presented a systematic approach for converting organic solid wastes such as rice husk and saw dust into liquid fuel using pyrolysis method. When the rice husks and sawdust were pyrolyzed at between 420 and 540 °C in the absence of oxygen, a volatile gas (which could be partially condensed into liquid fuel) and charcoal were produced. A portion of the uncondensable gas could be used as fuel gas, while the crude oil could be refined into a vehicle fuel. This research employed GC/MS to reveal that the liquid fuel contained a complex mixture of organic compounds that had a low caloric value but could be used directly as a fuel oil for combustion in a boiler or a furnace, without any upgrading. Other conclusions from the study were that there was an optimal temperature for

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Fig. 2.21 The potential application of rice husk for fuel and power generation

the thermal conversion of rice husks and sawdust into liquid fuel (the yield first increased but then decreased as a function of temperature). Yields attained ranged from 56 to 61%. Notably, the cost of the conversion could be reduced by replacing electric heating and the carrier gas nitrogen with charcoal combustion and its hot flue gas, respectively. Fig. 2.22 shows a schematic representation of converting rice straw into fuels.

2.4.9 Coal Pyrolysis and Hydropyrolysis GC/MS is a necessary analytical tool to analyze and characterize fossil fuels, their reaction mechanisms, and reaction products. After thermal decomposition of coal or carbonization takes place initially in many coal consumption processes, GC/MS analysis offers wide-ranging analysis conditions for the pyrolysis process to occur under different reactions and environmental conditions [37]. In coal pyrolysis, lots of fundamental reaction parameters are included such as temperature [38], heating rate [39], pyrolysis atmosphere [40], reaction pressure [41], and coal particle [42]. The conditions of pyrolysis gas flow can signify the final quality[43] and yield of product inside the reactor [44]. As shown in Fig. 2.23, Fixed bed reactor was used for experimental procedure. The heating took prominently different times in different reactors for reaching 500°C at their central points monitored. It means essentially different heating rates for the coal bed under such different

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Fig. 2.22 Routes for pyrolysis of rice straw [36]

Fig. 2.23 Heating curves for coal near the wall of the central gas collection channel when varying a reactor, b coal particle size, c furnace temperature, and d coal moisture content [37]

conditions. Major products from coal pyrolysis according to major analysis products comprise H2 , H2 O, CO, CO2 , N2 , H2 S, CH4 , C2 H4 , C2 H6 , C3 H8 , C6 H6 , C6 H5 CH3 , C6 H4 (CH3 )2 , tar [45–47], and char [48]. The analysis of product distribution has led

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Fig. 2.24 Gas chromatograms of the volatile fraction of the tars generated from Shendong coal pyrolysis under different atmospheres [44]

to species-based kinetic models [49] which, in turn, have offered understandings of the features of the macromolecular structure of coal. As shown in Fig. 2.24, there are the chromatograms of Shendong coal tars generated under different atmospheres, figures show that the tars generated from different atmospheres and CRMP process have alike chromatograms under the identical GC conditions. Phenol and its alkyl-substituted homologs from C1 to C3 are the major products in the volatile fractions of the tars, here C1, C2, or C3 represent the total numbers of carbon substituted to the aromatic ring. Naphthalene and C1 to C3 alkyl-substituted homologs are also shown in Fig. 2.24. All the tars obtained have a little difference in different atmospheres but compound proportion is different.

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For instance, the naphthalene peak in the tar resultant from coal pyrolysis under H2 atmosphere is much higher than those in other atmospheres. Chen et al. [50] identified pyrolysis products with molecular weight up to 200 atomic mass units (amu). Hydropyrolysis refers to the thermal decomposition of coal in the presence of hydrogen at high pressure. As shown in Fig. 2.25, there is result of a raw coal. The series of reactions can be viewed from the overall kinetics of pyrolysis reactions as shown in Table 2.2 based on a thermal balance at a constant heating rate, hydropyrolysis caught more attention in the 1970s during an energy crisis. Also, this technology was used to separate the pollutants in the gas phase which were more reachable than those used for solid phase. Both Graffet al. [51, 52] and Dobneret al. [52] explored the product distribution of coal hydropyrolysis, their analysis of volatile species established the connection between the yields of coal pyrolysis and hydropyrolysis and the properties of various coals [53]. The organic oxygen and aliphatic hydrogen contents in coal were found to govern the volatile yields. Additionally, the reactivity was better correlated with the petrographic composition than with the rank of coal. Exinite is a minor maceral constituent in coal that seems to offer a synergetic impact on the acuteness of other macerals in coal.

Fig. 2.25 Chromatograms of two raw coals [50]

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Table 2.2 Basic pyrolysis reactions [54] Temperature range 300–500 °C

At 550 °C

(1) Cleavage of weaker chemical bonds of coal structure

(1) Cleavage of stronger chemical bonds of coal structure

(2) Distillation of volatiles (so-called tar)

(2) Formation of methane from aliphatic side chains or hydroaromatic rings

(3) Formation of aliphatic hydrocarbons, mainly CH4 from aliphatic bridges

(3) Formation of hydrogen and char or coke by linkage of aromatic rings to graphitic clusters

(4) Formation of H2 O/CO/CO2 from oxygen-containing groups

(4) Formation of CO from heterocyclic O

2.4.10 Soot Formation Soot is formed when hydrocarbons are burnt such as natural gas, oil, and wood. Soot comprises carbon particles formed in the gas-phase combustion system as well as soot is very important for industrial processes. Soot is formed within a short period in hydrocarbon flames, in 1 to 10 ms soot particles of 500Å are formed. The molecular precursors of soot particles are thought to be heavy PAHs of molecular weight 500– 1000 amu. Previously, PAHs are considered a crucial intermediate in particle growth. These kinds of species are found in all sorts of soots, hydrocarbon flames, they have the same structure to soot graphic morphology and contain C: H ratios in most starting fuels. Particle growth follows the reaction network that involves the small molecules such as benzene to larger and larger PAH appears to involve the addition of C2 , C3 , or acetylene, C3 H3 radicals, free radicals, and monatomic and diatomic hydrogen. Aromatic hydrocarbons in soot are mutagens that are carcinogenic to humans. Scientists have discovered a mechanism for soot formation. In Fig. 2.26. of a candle flame, the colors are from hot soot luminescence. The mass spectrum at the bottom shows the peaks for the radicals that drive the reaction. The incipient particle (lower drawing) is the cluster that marks a transition to the condensed phase. Fast reactions grow the particle (upper drawing). 1 nm =1 nanometer=10−9 m [55]. Mass spectrometry has been used broadly by measuring the reaction intermediates and their prodmucts for analyzing soot formation mechanisms and kinetics in flames. Such as, it was investigated [56] that the benzene formation mechanisms in a C2 H2 / O2 /Ar are analyzed flat flame by using molecular-beam mass spectrometry as a result benzene was formed via a chemically activated addition and isomerization. It was also examined that PAH is formed during ethyl acetylene [57] and allene (C3 H4 ) pyrolysis [58], by using vacuum ultraviolet (VUV) photoionization time-of-flight mass spectrometry. Single-photon VUV ionization with vitalities just directly above the ionization likely consents to the nondestructive analysis of free radicals in the reacting system, as shown in Fig. 2.27. Molecular-beam mass spectrometry has been extensively used for the analysis of stable species and free radicals have been widely adopted in the analysis of stable

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Fig. 2.26 Soot formation [55]

species and free radicals at the initial stages of soot formation. This method gathered remarkable soot growth-related. In Fig. 2.28, it was [44] identified that the constant and transitional species up to 202 amu in flat, low-pressure flames of benzene/Ar discovered CO, C6 H6 O, and C5 H6 seem to be the major species in the flame [59]. Common hydrocarbon species have been detected that exhibit concentration maxima indicative of a transition in the general reaction scheme. To discern whether this type of progression or sequential growth might lead to soot in sooting flames, Howard and Bittner [59] analyzed species larger than 200 amu. This was achieved by shutting off the DC voltage on the quadrupole, thus transmitting all and only ions with an m/ z ratio greater than a specified value, as a result, the maxima concentrations were observed for species up to 750 amu. The growth rates of these species were also inspected. These studies lead to a more detailed review [60].

2.4.11 Desorption of Surface Oxides up to 1100 °C Desorption is a phenomenon where a substance is released from a surface which occurs in a system being in a state of sorption equilibrium between bulk phase and an adsorbing surface. Similarly, the desorption of surface oxide from a char is defined to be the rate-controlling step of carbon gasification thus the surface oxides at different fortes have been a topic of inquiry. In the past, there were several characterization techniques used for abundance and fortes GC/MS for combustion and

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a

b

c

Fig. 2.27 Schematic view of the clusters of hydrocarbons and radical-chain reactions (CHRCR) mechanism [55]

pyrolysis of surface oxides along with this mass spectrometry is immensely used for the desorption products analysis. These techniques collectively with isotope labeling techniques and mass spectrometry represent a method for illumination the oxygen transportation on char surface. When desorption was conducted at 1100 °C, it was discovered that the surface oxides of two different strengths were there [61, 62]. Firstly, the surface area of char covered by the labile [C(O)] and stable complexes [C–O] was termed as active surface area (ASA). Secondly, transient kinetics (TK) and temperature-programmed desorption (TPD) was established for the measurement of surface area covered by labile and stable oxides. TK was intended to measure the labile oxides as well as RSA. In the partial gasification of char at 1153 K, there was a switch in reactive gases to an inert gas, as a result, desorption of CO as surface oxide was monitored. By assuming the value of 0.08 nm2 for every oxygen atom, the unified area under CO absorption and time curve calculates the RSA.

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Fig. 2.28 Number densities and average particle sizes in a premixed benzene/oxygen/argon flame [60]

Interestingly, it was found that the RSA determined by TK was in remarkably good accord with the difference of ASA and stable C–O determined with the two TPD procedures [63]. It was also shown experimentally that the surface area occupied by the labile oxides, or ASA, was a good normalization parameter of the oxidation rates of chars resultant from lignite and bituminous coal during CO gasification [63] as shown in Fig. 2.29. It was also reported that lignite char has a higher RSA than bituminous coal. It is an observation for higher reactivity of lignite char in oxidation-reduction of NO.

2.4.12 Temperature-Programmed Desorption of Young Chars up to 1650 °C The acuteness of coal-derived chars in flame conditions such as those from high temperatures and short residence times were characterized by temperatureprogrammed desorption (TPD) up to 1650 °C. The research on the chars up to now is related to the reactivity and reacts properties of traditional old chars. The clean chars that have been pyrolyzed with an extensive typical 1 to 3 hour settling time demonstrated recently the reactivity of char from coal decreased to a certain level in flame. To obtain the more representative reactivity of young chars in the flames, it was [64, 65] lately applied TPD/MS to the chars produced from pyrolysis and combustion with a residence time in an order of seconds. For this, the TPD was directed up to 1650 °C. Previously mentioned chars can oxidize at 1000°C with the 0.3s settling time which is quite less than before. Fig. 2.30 shows CO desorption

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Fig. 2.29 Specific gasification rate in 1 atm CO* a bituminous coal char at 1093 K; b Saran char at 1133 K; c lignite char at 953 K [63]

peaks during TPD at three various and notable temperatures; 730 °C, 1280 °C, and 1560 °C. There is a comparison between TPD profiles of oxidized chars with those from pyrolyzed chars and ashes. It is recommended that the young char oxidation has a strong influence on organic oxygen, mineral matters, and gas-phase oxygen [66]. Three peaks were elaborated along with the representation in Fig. 2.31, the peak at 730 °C was caused by incomplete devolatilization because of small oxidation time, while at 1280 °C peak was caused by desorption stable surface oxides third one the broader peaks between 1400° and 1650 °C were caused by the reaction of oxidants and carbon in char. CO widespread emission from wood coal char during TPD suggested that O2 or minerals could promote oxygen transfer on the surface of char and carbon oxidation. Concentrations were normalized to 1 mg carbon at the beginning of the TPD experiment. CO productions from DMC derivatives during

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Fig. 2.30 TPD profiles of pyrolyzed and partially oxidized chars derived from demineralized lignite (DMC). a CO productions from DMC derivatives during TPD are low and flat. b CO2 productions from DMC derivatives during TPD are also low [66] Fig. 2.31 TPD profiles of pyrolyzed and partially oxidized chars from (DMC) [66]

TPD were low and flat. Reports regarding the existence of stable surface oxide on coal-derived chars that desorb at 1000 °C were made. TPD profiles reported [65], proved, and supported the existence of stable surface oxide on young coal-derived chars in flames. The stability and activation energy of these oxides are much higher therefore it is possibly a rate-controlling step of char oxidation. Moreover, several known mechanistic conclusions that have been reported, such as CO scavenging of surface oxides, have been based on the assumption that all surface oxides desorb below 900 °C, even though in their TPD/MS experiments, in Fig. 2.32, Pan and Yang [67] reported the existence of stable oxides on graphite that desorbed at 1500 °C.

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Fig. 2.32 XPS O(1 s) spectra of nuclear graphite oxidized in 0.2 atm of O2 at 600 °C to 20% burn off. a Before TPD. b After TPD to 1050 °C. c After TPD to 1500 °C and held at 1500 °C for 2 h [67]

2.4.13 Isotope-Labeling Techniques Isotope labeling is a technique used to trail the passage of an isotope through a reaction. The reactant is labeled by replacing specific atoms with their isotopes. Both, Miura and Nakagawa [68] and Cricket et al. [69] have investigated the carbon oxidation mechanisms by using alternatives 18 O2 and 16 O2 . This method consents to the measurement of both the adsorption rate and the carbon gasification rate. The results demonstrated that the part of oxygen can adsorb below 500 °C but in inert gas, it desorbs around 900 °C that the part of the oxygen adsorbed below 500 °C does not desorb below 900 °C in inert gas. The oxides at the surface react with gas-phase oxygen to form CO2 . The thermal stability of a gas containing oxide is much higher than the surface oxides in inert. Besides, it led to a reaction mechanism of carbon oxidation that involved interactions between the surface oxides and gaseous oxygen. Zhuang et al. [70] showed char oxidation by switching 18 O2 to 16 O2 and 16 O2 to He that is tailed by TK and TPD. The results also display oxygen in the gas phase accelerated the gasification of surface oxides moreover, gas-phase oxygen activated stable oxides on the surface. There is a general expression based on previous information. ( ) ( ) C 18 O + 16O2 C 16 O + C18 O, CO16 O18 These results were also proved experimentally. Their model suggested that the contribution of the above reaction to the overall rate of gasification of carbon ranged from 45% at 873 K to 4% at 1073 K. There is no actual contribution in flames and also stable surface oxides only desorb above 1000 °C as observed by Chen et al. [64, 65] and shown in Fig. 2.33. The combined use of isotope-labeled thus, its contribution would be diminished in the actual flame. During carbon oxidation collective use of isotope-labeled compounds and MS has been applied for the catalytic mechanism

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Fig. 2.33 Schematic representation of the experimental set-up of gasification

studies. Calcium catalyzed graphite oxidation by 18 O2 was also investigated. There are three steps regarding their experimental procedures; oxidation with MS analysis; TPD/MS; and SIMS for the surface analysis. Sample transported from TPD reactor to vacuum chamber bombardment by Ar that is primary ion gun. This experiment was carried out using a moving rod so that sample should not come in contact with air [71]. The results showed that CaO served as an oxygen shuttling agent also a carbon atom was gasified after it attained two oxygen atoms consecutively [72] the calcium catalyzed oxidation of a carbon sample by 13 CO2 was also elaborated. The sample phenolformaldehyde (PF) resin oxidized by HNO3 after that 13 CO2 oxidized sample was also characterized using TPD/MS. There were two types of results that demonstrated CO production after the Ca—C was attacked by CO2 the detachment of CO2 from the decomposition of CaCO3 and desorption of the surface oxide on carbon. Transient kinetic studies of peat char labelled by CO2 have conducted the results suggested that there are two types of surface oxides first to decay in a second and the second decayed in a minute [73]. There are different sources of elements in nature, and those various sources of carbon have a different abundance for carbon. In MS spectroscopy section C12 /C13 determined in combustion system were investigated in different carbon origins. In the NO reduction bay carbon 15 NO and 15 N18 O were used. Oxidized low-rank coals by 15 NO/Ar, O2 /Ar, and 15 NO/O2 /Ar in a temperature-programmed reaction with online mass spectrometry measurement of the subsequent TPD/MS analysis of char. Moreover, in Fig. 2.34, the N2 formation rate was correlated with NO concentration and the number of surface nitrogen species [6].

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Fig. 2.34 Measured species isotope ratios (NI5/N14) for NO, N2 , NH3 and HCN. The ordinate is normalized by the NIS/N TM ratio for the total gas-phase nitrogen. Note that NH data is for lignite only and HCN data are for bituminous coal only [74]

2.5 Outlook Nowadays, the world is facing extraordinary challenges to fulfill energy production and their usage. Crude oil supply has many uncertainties which caused energy cost ups and downs along with this main issue it also affected the economy. Because of climate change, there is a need for renewed energy resources, as a result, alternative approaches are made for the utilization of fossil fuels to lessen carbon emission. In the development of these technologies, the use of GC/MS in combustion research, concerning energy and nanotechnological applications will grow within time. (SIDMS) via GC/MS may in the future play a greater role in determining combustion pathways and associated molecular transitions contempt its use is limited because of the great expense associated with the preparation of stable isotope molecular tracers. It has been identified that various recent innovations and future trends in GC/ MS as follows: (i) the use of microfluidic control valves for miniaturization and the rapid changing of columns and separation conditions; (ii) resistance column heating to reduce the overall size of the system, with the ultimate goal of field portability; (iii) new monolith columns in which the internal porous media, unlike packed columns, is prepared in situ; and (iv) ultra-small-diameter micro-wall-coated open tubular (WCOT) columns providing high separation efficiencies. Recent commercial instrumental developments have included: • Single Quadrupole GC–MS the selectivity and confidence provided by mass spectral data with a Thermo Scientific ISQ 7000 single quadrupole GC–MS system. • Triple Quadrupole GC–MS/MS Combine superb sensitivity and selectivity with outstanding reliable productivity with a Thermo Scientific TSQ 9000 triple quadrupole GC–MS/MS system. This system is the go-to instrument for sensitive and specific quantitation of target compounds.

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• The DFS is a high-resolution double-focusing magnetic sector GC/MS introduced by the Thermo Electron Corporation. • The QP2010 Plus, a GC/MS system with expanded mass range and increased sensitivity, was manufactured by the Shimadzu Corporation. • A GC/MS system using a Fourier transform mass spectrometer developed by Varian Inc.

2.6 Exercises (1) Individual task: Find a research paper on combustion fuel and explain how GC/MS was used as an analytical technique in that study. (2) Group task: In groups of 3–5, find the recent scientific paper on GC/MS and make a presentation on their application across different fields such as Smoke Tracers in PM, Soot formation, etc.

2.7 Questions (1) Describe how GC/MS is applied in studying both combustion and pyrolysis substances, cite examples. (2) Explain the working mechanism of GC/MS. (3) Explain the types of capillary columns. (4) Differentiate between packed and capillary columns. (5) Explain the effect of internal diameter and column length in capillaries. (6) Why is the coupling of gas chromatography with mass spectrometry √ important? (7) Define TOFMS and derive the equation of t is proportional to m. (8) Advantages of quadrupole MS over time of flight. (9) What is Ionizing radiation, and explain how radiolytic alteration may increase the mean combustion temperature of organic matter? (10) Briefly, describe how GC/MS is used in the study of the motored engine. (11) State substances that are used as markers of fungal contamination, and describe how flash pyrolysis coupled with GC/MS detection technique is utilized in studying these markers. (12) Define Coal Pyrolysis and Hydropyrolysis and state their major products.

References 1. Hussain, S. Z., & Maqbool, K. (2014). GC-MS: Principle, technique and its application in Food. Science, 13, 116–126. 2. Kong, J., et al. (2014). Study on the formation of phenols during coal flash pyrolysis using pyrolysis-GC/MS. 127, 41–46.

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3. Cheng, J., et al. (2018). Emission of volatile organic compounds (VOCs) during coal combustion at different heating rates. 225, 554–562. 4. James, A. T., & Martin, A. J. (1952). Gas-liquid partition chromatography: the separation and micro-estimation of volatile fatty acids from formic acid to dodecanoic acid. 50(5), 679. 5. Crawford, C. B., et al. (2017). Microplastic identification techniques. 219–267. 6. McMaster, M. C. (1998). HPLC: A practical user’s guide. Wiley Online Library. 7. Turner (2020). Gas chromatography—How a gas chromatography machine works, how to read a chromatograph and GC x GC. Retrieved from https://www.technologynetworks.com/ analysis/articles/gas-chromatography-how-a-gas-chromatography-machine-works-how-toread-a-chromatograph-and-gcxgc-335168 8. Balzer, M. (2021). Columns for gas chromatography. Retrieved from www.chemeurope.com/ en/whitepapers/126475/columns-for-gas-chromatography.html 9. Cizdziel, J., & Chen, W. Y. (2010). GC/MS for combustion and pyrolysis research. 51–74. 10. Howard, J. B. (1981). Fundamentals of coal pyrolysis and hydrophrolysis. 2, Chap. 12. 11. Hatcher, P. G., et al. (1988). Pyrolysis GC—MS of a series of degraded woods and coalified logs that increase in rank from peat to subbituminous coal. 67(8), 1069–1075. 12. Thoma, H., & Hutzinger, O. (1987). Pyrolysis and GC/MS-analysis of brominated flame retardants in on-line operation. 16(6), 1353–1360. 13. Philp, R. P. (1982). Application of pyrolysis-GC and pyrolysis-GC-MS to fossil fuel research. 1(10), 237–241. 14. Hempfling, R., & Schulten, H.-R. (1990). Chemical characterization of the organic matter in forest soils by Curie point pyrolysis-GC/MS and pyrolysis-field ionization mass spectrometry. 15(2), 131–145. 15. Jin, Z. -H., et al. (2021). An experimental investigation of furfural oxidation and the development of a comprehensive combustion model. 226, 200–210. 16. White, D. M., et al. (2004). Pyrolysis-GC/MS fingerprinting of environmental samples. 71(1), 107–118. 17. Blackledge, R. D. (2006). Theory & Instrumentation: Pyrolysis gas chromatography in forensic science. 18. Hermabessiere, L., et al. (2018). Optimization, performance, and application of a pyrolysis-GC/ MS method for the identification of microplastics. 410(25), 6663–6676. 19. Szybist, J. P., et al. (2007). Premixed ignition behavior of alternative diesel fuel-relevant compounds in a motored engine experiment. 149(1–2), 112–128. 20. Court, R. W., et al. (2006). The alteration of organic matter in response to ionising irradiation: Chemical trends and implications for extraterrestrial sample analysis. 70(4), 1020–1039. 21. Kumooka, Y. (2006). Analysis of deteriorated rubber-based pressure sensitive adhesive by pyrolysis-gas chromatography/mass spectrometry and attenuated total reflectance Fourier transform infrared spectrometry. 163(1–2), 132–137. 22. Keheyan, Y., & Giulianelli, L. (2006). Identification of historic ink ingredients using pyrolysisGC-MC: A model study. (3), 5–10. 23. Dalimov, D., et al. (2003). Chemical composition and lignins of tomato and pomegranate seeds. 39(1), 37–40. 24. Derrick, M. R., & Stulik, D. C. (1990). Identification of natural gums in works of art using pyrolysis-gas chromatography. Paper presented at the ICOM Committee for Conservation, 9th triennial meeting, Dresden, German Democratic Republic, 26–31 August 1990: preprints. 25. Fischer, G., et al. (2002). Quality assurance and good laboratory practice in the mycological laboratory–compilation of basic techniques for the identification of fungi. 205(6), 433–442. 26. Van Erven, G., et al. (2018). Mechanistic insight in the selective delignification of wheat straw by three white-rot fungal species through quantitative 13 C-IS py-GC–MS and whole cell wall HSQC NMR. 11(1), 1–16. 27. Parsi, Z., & Górecki, T. J. (2006). Determination of ergosterol as an indicator of fungal biomass in various samples using non-discriminating flash pyrolysis. 1130(1), 145–150. 28. Parsi, Z., et al. (2005). Advances in non-discriminating pyrolysis. 74(1–2), 11–18.

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29. Ward, T. J., et al. (2006). Characterization and evaluation of smoke tracers in PM: Results from the 2003 Montana wildfire season. 40(36), 7005–7017. 30. Poerschmann, J., et al. (2005). Analytical non-discriminating pyrolysis in soil analysis. 19, 8–14. 31. Poerschmann, J., et al., (2005). Characterization of non-discriminating tetramethylammonium hydroxide-induced thermochemolysis–capillary gas chromatography–mass spectrometry as a method for profiling fatty acids in bacterial biomasses. 1071(1–2), 99–109. 32. Arnezeder, C., et al. (1989). Rapid determination of ergosterol in yeast cells. 225, 129–136. 33. Parsi, Z., et al. (2005). Non-discriminating analytical pyrolysis-A novel tool for studying environmental samples. 18(11), 582-+. 34. Cordell, R. L., et al. (2014). Validation of an assay for the determination of levoglucosan and associated monosaccharide anhydrides for the quantification of wood smoke in atmospheric aerosol. 406(22), 5283–5292. 35. Kleeman, M. J., et al. (2008). Size distribution of trace organic species emitted from biomass combustion and meat charbroiling. 42(13), 3059–3075. 36. Zheng, J. -l., et al. (2006). Thermal conversion of rice husks and sawdust to liquid fuel. 26(12), 1430–1435. 37. Zhang, C., et al. (2014). Coal pyrolysis for high-quality tar and gas in 100 kg fixed bed enhanced with internals. 28(11), 7294–7302. 38. Roy, C., et al. (1985). Vacuum pyrolysis of Prince Mine coal, Nova Scotia, Canada. 64(12), 1662–1666. 39. Hirajima, T., et al. (1986). Vacuum and atmospheric pressure TGA on an eastern Canadian coal. 65(6), 844–848. 40. Anthony, D. B., et al. (1976). Rapid devolatilization and hydrogasification of bituminous coal. 55(2), 121–128. 41. Li, C. Z., et al. (1993). Characterization of tars from variable heating rate pyrolysis of maceral concentrates. 72(1), 3–11. 42. Zhang, X., et al. (2011). Coal pyrolysis in a fluidized bed reactor simulating the process conditions of coal topping in CFB boiler. 91(1), 241–250. 43. Zhong, M., et al. (2012). Continuous high-temperature fluidized bed pyrolysis of coal in complex atmospheres: Product distribution and pyrolysis gas. 97, 123–129. 44. Wang, P., et al. (2013). Analysis of coal tar derived from pyrolysis at different atmospheres. 104, 14–21. 45. Domenech-Carbo, M. T. (2008). Novel analytical methods for characterising binding media and protective coatings in artworks. 621(2), 109–139. 46. Pant, P., & Harrison, R. M. (2013). Estimation of the contribution of road traffic emissions to particulate matter concentrations from field measurements: A review. 77, 78–97. 47. Platt, S. M., et al. (2013). Secondary organic aerosol formation from gasoline vehicle emissions in a new mobile environmental reaction chamber. 13(18), 9141–9158. 48. Duan, L., et al. (2009). Investigation on coal pyrolysis in CO2 atmosphere. 23(7), 3826–3830. 49. Wu, Z., et al. (2008). Particle number size distribution in the urban atmosphere of Beijing, China. 42(34), 7967–7980. 50. Chen, W. -Y., et al. (1982). Pyrolysis of solvent-refined coals. 27, 3–4. 51. Graff, R. A., et al. (1976). Flash hydrogenation of coal. 1. Experimental methods and preliminary results. 55(2), 109–112. 52. Dobner, S., et al. (1976). Flash hydrogenation of coal 2. Yield structure for Illinois No. 6 coal at 100 atm. 55(2), 113–115. 53. Chen, W.-Y., et al. (1983). Flash hydrogenation of coal. 3. A sample of US coals. 62(1), 56–61. 54. Balat, M. (2009). Economics, planning, & policy. Coal in the global energy scene. 5(1), 50–62. 55. Johansson, K., et al. (2018). Resonance-stabilized hydrocarbon-radical chain reactions may explain soot inception and growth. 361(6406), 997–1000. 56. Westmoreland, P. R., et al. (1989). Forming benzene in flames by chemically activated isomerization. 93(25), 8171–8180.

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57. Pfefferle, L. D., et al. (1994). Benzene and higher hydrocarbon formation during allene pyrolysis. In Soot formation in combustion (pp. 25–49). Springer. 58. Warnatz, J., et al. (2006). Combustion. Springer. 59. Richter, H., et al. (2000). Formation of polycyclic aromatic hydrocarbons and their growth to soot—a review of chemical reaction pathways. 26(4–6), 565–608. 60. Richter, H., et al. (2005). Detailed modeling of PAH and soot formation in a laminar premixed benzene/oxygen/argon low-pressure flame. 30(1), 1397–1405. 61. Lizzio, A. A. (1992). The concept of reactive surface area applied to uncatalyzed and catalyzed carbon (char) gasification in carbon dioxide and oxygen. 62. Radovic, L. R., et al. (1991). A transient kinetics study of char gasification in carbon dioxide and oxygen. 5(1), 68–74. 63. Lizzio, A. A., et al. (1990). On the kinetics of carbon (char) gasification: Reconciling models with experiments. 28(1), 7–19. 64. Chen, W. Y., et al. (2007). Stable oxides on chars and impact of reactor materials at high temperatures. 21(2), 778–792. 65. Chen, W. Y., et al. (2008). Characterization of early-stage coal oxidation by temperatureprogrammed desorption. 22(6), 3724–3735. 66. Wan, S., et al. (2009). Roles of mineral matter in the early stages of coal combustion. 23(2), 710–718. 67. Pan, Z., et al. (1992). Strongly bonded oxygen in graphite: detection by high-temperature TPD and characterization. 31(12), 2675–2680. 68. Miura, K., & Nakagawa, H. (1996). Analysis of carbon-oxygen reactions by use of a squareinput response technique and {sup 18} O isotope. 41(CONF-960376). 69. Crick, T. M., et al. (1993). Analysis of coal char gasification by use of the pulse method and oxygen-18 isotope. 7(6), 1054–1061. 70. Zhuang, Q., et al. (1996). Desorption behavior of surface oxygen complexes on carbon in an inert gas and in O2-gasification atmosphere. 10(1), 169–172. 71. Sobeih, K. L., et al. (2008). Recent trends and developments in pyrolysis–gas chromatography. 1186(1–2), 51–66. 72. Cazorla-Amoros, D., et al. (1991). Further evidence on the mechanism of the carbon dioxide carbon gasification catalyzed by calcium: TPD after carbon-13 dioxide chemisorption. 36, 975–981. 73. Kapteijn, F., et al. (1991). Active sites in carbon gasification with CO2 transient kinetic experiments. in fundamental issues in control of carbon gasification reactivity (pp. 221–233). Springer. 74. Burch, T. E., et al. (1994). Interaction of fuel nitrogen with nitric oxide during reburning with coal. 98(4), 391–401.

Chapter 3

Thermal Analysis Methods Zhen-Yu Tian, Vestince Balidi Mbayachi, Wei-Kang Dai, Maria Khalil, and Daniel A. Ayejoto

3.1 Introduction According to the International Confederation for Thermal Analysis and Calorimetry (ICTAC), thermal analysis (TA) has been considered as one of the techniques which measures the physical properties of a sample as a function of time or temperature while the temperature of this sample is programmed in a specific atmosphere to achieve a constant rate of reaction [1]. During the long history, different techniques of thermal analysis have been invented and applied in several fields [2]. In 1826, Becquerel developed thermocouples. Austen-Roberts invented differential thermal analysis in 1899 and Honda in 1915 invented a thermobalance (Fig. 3.1). TA methods determine the properties and enable the interpretation of the thermal processes of the sample [3]. The origin of the present TA techniques is clay minerals. Lavoisier (1743–1794) investigated the mass change upon oxidation of clay minerals during heating. The aspect of heat led to the introduction of thermocouples which later enabled LeChatelier to publish his work on clay in 1887 [4]. In modern science, TA has been strongly emphasized on the fundamental chemical investigations and finding solutions in engineering and material science [5]. Z.-Y. Tian (B) · W.-K. Dai Chinese Academy of Sciences, Institute of Engineering Thermophysics, Beijing, 100190, China e-mail: [email protected] Z.-Y. Tian · V. B. Mbayachi · W.-K. Dai · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing, 100049, China V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou, 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_3

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Fig. 3.1 Schematic diagram of Honda’s original thermobalance in 1915 where he obtained the first TG curves for MnSO4 · H2 0, CaCO3 , and CrCO3 . (AB) and (CD) are the two arms of a balance beam; (M) is a vertical mirror; (F) is a thin porcelain tube; (G) is a cylindrical sample container; (H) is a Dewar vessel and (E) is a spiral spring [6]

3.2 Classification of Thermal Analysis Parameters such as mass, dimension, heat flux, or temperature have allowed the classification of thermal analysis techniques (Fig. 3.2) [3]. These TA techniques include thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), differential thermal analysis (DTA), thermomechanical analysis (TMA), thermoelectrical analysis (TEA), exchanged gas analysis (EGA), and thermoptometric analysis (TOA). Table 3.1 summarizes the physical properties, thermal analysis techniques, and analysis methods of the sample under study. Thermal analysis has been used to characterize the inorganic and organic substances, minerals, metals, electronics materials, ceramics, pharmaceuticals, polymers, and biological organisms. In this chapter, thermogravimetry, differential scanning calorimetry, and differential thermal analysis have been discussed in detail.

3.3 TA Instrumentation Different techniques of TA have common instrumentation features [7]. Figure 3.3 illustrates how the sample in the furnace is subjected to a temperature control program. During this experimental procedure, properties of the sample are monitored by a suitable transducer which is then converted into current or voltage. Measurements are normally continuous and the heating rate of the sample is usually linear with time. Measurements of the thermal events of the sample result in TA curves which are presented in the form of peaks, changes of slope, and discontinuities.

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Fig. 3.2 A flowchart of thermal analysis parameters and methods [3] Table 3.1 A summary of thermal analysis techniques, analysis methods, and properties of the sample [7] Properties

TA Techniques

Analysis methods

Mass

Thermogravimetry

Thermogravimetric analysis (TGA)

Temperature

Thermometry

Heating or cooling curve analysis

Temperature difference

Differential thermometry (DT)

Differential thermal analysis (DTA)

Heat flow difference

Differential scanning calorimetry

Differential scanning calorimetry (DSC)

Pressure

Thermomanometry

Thermomanometric analysis

Dimensional/mechanical properties

Thermomechanometry (TM)

Thermomechanical analysis (TMA) (continued)

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Table 3.1 (continued) Properties

TA Techniques

Analysis methods

Electric properties

Thermoelectrometry (TE)

Thermoelectrical analysis (TEA)

Optical properties

Thermoptometry (TO)

Thermoptometric analysis (TOA)

Magnetic properties

Thermomagnetometry

Thermomagnetic analysis

Gas exchange

Thermally stimulated

Thermally stimulated analysis

Exchanged gas measurement (EGM)

Exchanged gas analysis (EGA)

Fig. 3.3 A schematic of a generalized TA and its resulting curve [7]

3.4 Important Terminologies Used in Thermal Analysis Thermobalance: It is an instrument used for constantly weighing a sample when it is being heated or cooled. Heating Rate: This is an increase in the temperature rate recorded in degrees per minute. A constant in heating or cooling rate occurs when the curve of the time/ temperature is linear.

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Initial Temperature (Ti ): It is the temperature (on the Kelvin or Celsius scale) at which the sample cumulative mass change reaches the magnitude that can be detected by the thermobalance. Final Temperature (Tf ): It is the temperature (on the Kelvin or Celsius scale) at which the sample cumulative mass change is at the maximum. Reaction Interval: It is the difference in temperature between the final temperature (Tf ) and initial temperature (Ti ). Sample: It is the material under investigation, whether it is diluted or undiluted. Sample Holder: It is the container that supports the sample. Reference Material: It is the material of a known substance. Normally, it is thermal inactive at the temperature interest range. Specimens: These are the reference and sample materials. Reference Holder: It is the container that supports the reference material. Isobaric Mass-change Determination: It is a technique in which the sample mass equilibrium is measured at a constant partial pressure of the volatile product as a function of temperature while the sample is subjected to a temperature control program. Heating-curve Determination: It is a technique in which the sample temperature is measured as a function of the programmed temperature while the sample is subjected to a temperature control program in the heating mode. Base Line: It is the portion of the DTA curve in which ΔT is approximately zero. Peak: It is a portion of the DTA curve which departs from and subsequently returns to the base line. Simultaneous Techniques: It is the application of more than two techniques at the same time to the same sample. For an instant, simultaneously TG and DTA. Coupled Simultaneous Techniques: This is the application of two techniques that are connected by an interface to the same sample. For example, simultaneous TG and DTA are connected with mass spectrometry.

3.5 Thermogravimetry (TG) TG is a technique in which the sample mass is measured as a function of temperature while the sample is subjected to a controlled temperature program [8]. The sample is analyzed in an increasing or decreasing temperature at a constant rate (isothermal temperature). TG is one of the most powerful thermal analysis techniques and it consists of a furnace, a temperature programmer, a microbalance, and a data acquisition system (Fig. 3.4). The sample mass is simultaneously weighed and heated or cooled in a predetermined condition, and the mass, temperature, and time data are captured and recorded. Thermal curve is then plotted as the mass or mass percentage against temperature or time [9].

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Fig. 3.4 Interaction mechanisms between the component, furnace, thermobalance, programmed temperature, and data acquisition system

3.5.1 TGA Instrumentation A classical TGA equipment has a microbalance which is composed of a balance and a furnace for continuous measurement of sample weight, a purge gas system to supply reactive or inert atmosphere, a thermocouple for temperature measurement, and a computer system to control the furnace programming and to record and process the results (Fig. 3.5) [10]. Thermogravimetric analysis (TGA) is a low-cost technique, requires a small quantity of sample, and allows qualitative or quantitative analysis. However, if the samples contain volatile matter, then TGA analysis may not be accurate. Microbalance of TGA instruments has several designs that include but are not limited to spring balance, torsion balance, and electrobalance. The sample of TGA is normally very small and is placed in a small inert crucible which is attached to a microbalance and has a furnace positioned around the sample. The balance is normally thermally isolated from the furnace. TGA balances are available for sample masses from 1 mg to 1 g but there is a specialized high capacity TGA system which can hold up to 100 g of the sample. The furnace surrounds the sample and sample holder and has a heating rate of up to 1000 °C per minute.

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Fig. 3.5 Schematic diagram of the classical thermobalance system [10]

3.5.2 The Design and Measuring Principle of TGA The top loading, hang down, and horizontal thermobalances are the three commercially available thermobalances designs (Fig. 3.6) [11]. In these types of balances, the sample position in the furnace remains the same even if the mass changes. Protective measures have been employed between the furnace and the balance to protect the balance against the effect of the heat radiation and corrosion caused by decomposition of products. In most cases, a protective gas is purged in the balance chamber and in other thermobalances, an external furnace is used. Thermobalance works under the measuring principle of the change in the sample weight with respect to time and temperature in a reactive or inert atmosphere [12]. Change in the sample weight at the balance generates electrical signals which are transformed into weight gain or loss by the data acquisition system (Fig. 3.7). The modern microbalances have a galvanometer (a rotating pivot) which is controlled electronically by a zero-detection device, normally a photocell, a light, a magnet, and a moving coil system for system restoration [13]. The balance operates on a zero or null-balance principle in which the zero position is equivalent to the amount of light shone on the two photodiodes (Fig. 3.8). If the balance deflects out of the zero position, unequal amount of light is shone on the two photodiodes. Then the current is applied to the galvanometer movement to return the balance to the zero position. The amount of current is equal to the weight gain or loss [14].

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Fig. 3.6 Schematic diagram of top loading, hang down, and horizontal thermobalance design [11] Fig. 3.7 Measuring principle of TGA [15]

Fig. 3.8 Schematic illustration of a zero position/ null point balance [14]

3.5.3 Mechanism of Weight Change in TGA Kinetic processes of a sample inside a microbalance lead to either weight loss or gain [16]. Weight loss is caused by decomposition of the sample where due to combustion the chemical bonds break apart. Evaporation also causes weight loss due to loss of volatile materials at an increased temperature. Other phenomena which cause weight loss are desorption and reduction, in reduction the sample interacts with the reducing

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atmosphere usually ammonia or hydrogen gas. Weight gain is caused by oxidation and adsorption.

3.5.4 Temperature Measurement Thermocouples are often used in the measurement of temperature (Fig. 3.9) [17]. They consist of two different metals fused into a bead or junction. The junction is where temperature is measured. The change in temperature at the junction creates a signal, which can be interpreted by the data acquisition system. The reference junction of the thermocouple must be held at defined and fixed temperature. Factors such as sensitivity, stability, and cost determine the choice of thermocouple [18].

3.5.5 Temperature Control The most critical aspect of thermogravimetry is to control the sample temperature [18]. The main fundamental aspects are (i) heat transfer to (and from) the sample; (ii) the actual sample temperature determination, and (iii) feedback and control of the furnace temperature [7]. The main means of controlling the temperature is to adjust the surrounding temperature of the sample. Furnace temperature control is based on the thermocouples and the set time–temperature program. Linear heating or cooling ramps are the most common temperature programs. Isothermal programs are used in kinetic studies to measure the change in mass as a function of time. Proportional

Fig. 3.9 Schematic illustration of thermocouple [19]

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integral derivative (PID) control is used for the measurement of heating/cooling rates for the processes under investigation [18].

3.5.6 Atmosphere Control Thermobalances are usually housed in metal or glass systems [20], to allow the operation ranging from the pressure at a high vacuum (10–4 Pa) to a high pressure of about 70 bar [21]. At atmospheric pressure, the atmosphere can be flowing or static. A flowing atmosphere has several advantages: (i) decreases the condensation of reaction products on cooler parts of the microbalance, (ii) decreases secondary reactions, (iii) flushes out corrosive products, and (iv) acts as a coolant for the microbalance [7]. The furnace must be purged with inert gas, usually argon or nitrogen, to provide a desirable atmosphere for the experiment to take place [11]. Air is often used for combustion and oxidation studies. Hydrogen gas is normally used to provide reducing atmosphere following an appropriate precaution to prevent explosion. Modern instruments allow automatic switch of the purge gas so that the sample can start heating in an inert atmosphere and be switched to air or other reactive gas at high temperatures (Fig. 3.10) [22].

3.5.7 Presentation of TGA Data TG experimental results are represented in a graphical way [14]. The TGA plot is referred to as the thermal curve. The mass or mass percentage is normally plotted on (Y-axis) and the time or temperature is plotted on (X-axis). Mass percentage Fig. 3.10 Schematic diagram showing the purge gas inlet and outlet of the thermobalance [22]

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Fig. 3.11 Schematic diagram of TG curve [14]

has the advantage that various results can be compared on normalized set of axes. The derived plot in Fig. 3.11 shows the change of mass as a function of time or temperature.

3.5.8 Interpretation of TG and DTG Curve The TG and DTG curves are classified into several types [23]. Figure 3.12 illustrates a possible interpretation of these curves. Type (i): The sample undergoes no decomposition over the entire range of temperature. No mass loss. Type (ii): Desorption or drying occurs where there is an initial mass loss then followed by a mass plateau. Type (iii): The sample undergoes single-stage decomposition. Type (iv): The sample undergoes multistage decomposition. Type (v): The sample undergoes multistage decomposition but at a faster heating rate due to lack of intermediaries. Type (vi): This curve shows a mass gain due to the sample reaction with the surrounding atmosphere. An example is the oxidation of a metal substance. (C + O2 → CO2 ). Type (vii): Oxidation products decompose at higher temperature. (CO2 → C + O2 ). The resolution of the more complex individual stage TG curves can be improved by examining the derivative DTG curves (Fig. 3.13).

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Fig. 3.12 Classification of TG/DTG curves [23]

Fig. 3.13 Comparison of TG and DTG curves [23]

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3.5.9 Factors Affecting TG Curve The factors affecting the TG curves are classified into two main groups that include instrumental and sample characteristic factors [24]. Heating rate, furnace atmosphere, gas flow rate, and sample holder are some of the instrumental or thermobalance factors, whereas weight and the particle size are the sample characteristic factors. An increase in the heating rate of a sample causes a faster decomposition at a higher temperature. If the substance is heated at a slow rate, it decomposes at a lower temperature. The furnace atmosphere, the gas flow rate, the size, and shape of the sample holder affect the thermal reaction and the nature of the TG curve. Small weight is recommended in a thermobalance since it eliminates the temperature gradient existence in the sample. The particle size of the sample under experiment should be uniform and small since the use of a large particle can result in rapid weight loss during heating.

3.5.10 Sources of Error in TG Thermogravimetry errors can lead to inaccuracies in weight and temperature data [22]. Fluctuation in balance mechanism is due to the improper placement of TGA apparatus close to vibration and heat source. This phenomenon is known as buoyancy effect, but it has been eliminated in modern TGA instruments by running a blank (empty sample container) under the same condition of gas flow and heating used for the sample. Errors can also arise due to turbulence caused by heating rate and gas flow rate, to correct this error, the heating rate and gas flow rate should be kept as low as possible. There are errors associated with placement of thermocouples into the sample where they sometimes react with the sample and affect the weight of the sample, this error is corrected in modern instruments where the thermocouple is placed close to the sample or is in contact with the sample pan. The heat of the reaction may also cause errors in that the endothermic reaction may cause self-cooling of the sample, thus causing a greater lag in the sample temperature, while exothermic may decrease the lag in the sample [25].

3.6 Differential Analysis (DTA) 3.6.1 Introduction According to the International Confederation for Thermal Analysis and Calorimetry (ICTAC), Differential thermal analysis is the most widely used technique in which the temperature of a sample is programmed in a specific environment as a result temperature difference between a sample and reference material is recorded in counter to

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Fig. 3.14 The Saladin recording system as modified by Le Chatelier (1904); G, G, galvanometers; L, lens; P. prism; S. light source; V, photographic plate [26]

the time or temperature. It appears to have been first employed by Le Chatlier in 1887 (Fig. 3.14). His work was rapidly followed by Osmond and his investigation revolved around the heating and cooling behavior of iron and steel with an elaboration of the effects of carbon as an additive and another additive. In 1990, this initiative was extended by Dr. (later Sir) William Anderson and then transferred to Prof. William Chandler RobertsAusten, FRS (1843–1902). After this work, scientists moved toward investigation for the committee and found out the effect of small admixture of certain elements on the iron copper and lead. After the funding for this work was approved, Robert Austen managed to construct a device for record output of platinum-rhodium thermocouples. He named this device or instrument as thermoelectric pyrometer. As shown in Fig. 3.15, it consists of a lightbox with a photographic plate at one end termed as C which was moved vertically by clockwork machinery D past a horizontal slit AB, and the reflected vertical line of light from mirror M of galvanometer was situated at the far end of the box. There was an argand gas burner to provide light, a vertical slit, and a mirror H. After the part of the light was reflected from the fixed mirror and interrupted by pendulum E, there was also a huge success to provide Timebase by Robert Austen as in Fig. 3.15b, there are interpreted cooling curves which were automatically recorded (Fig. 3.16) [27, 28] This work was further developed into the semiquantitative method and thermal decomposition of kaolin minerals was also studied. The most essential step in this process is to determine the temperature at which the reaction is taking place, sample study, and magnitude of thermal effect. The determination is carried out utilizing heating two specimens at the same time at a constant rate, one may be a clay material and the other is a thermally inert material without a temperature difference. The reference material should have some specific characteristics, for instance, It should not endure thermal events concluding operating temperature range, It may not react with the sample holder, and both thermal conductivity as well as the heat capacity of reference should be similar to the sample. As reference substances of an inorganic

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Fig. 3.15 a Thermoelectric pyrometer b time base [27] Fig. 3.16 Automatically recorded cooling curves [28]

substance, Alumina and carborundum, SiC, have been utilized. While for organic compounds, polymers have been used [28].

3.6.2 DTA Instrumentation In Fig. 3.17, there is a block diagram in which the sample, as well as reference, are placed symmetrically in the furnace, which is under a controlled temperature program, and the temperature of both sample and reference are changed. Through this process, a differential thermocouple is set to notice the temperature difference between them. Also, the sample temperature is detected.

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(a)

(b)

Fig. 3.17 a DTA instrumentation b Sample size: 1 ~ 20 mg Reference: inert materials (e.g., Al2 O3 , SiC, glass, etc.) the apparatus 1. Cell holder 2. Cell 3. Metal block 4. Heater 5. Quartz support 6. Thermocouple [29]

Sample The sample introduced into the furnace is a material that is being investigated. Reference Material The reference material is a substance that is known as type material that is not active thermally over the temperature range of interest. Specimens The specimens are the sample and reference materials. Sample Holder The sample holder is the place or container for or backing for the sample. Reference Holder The reference holder is the container for the reference material. Specimen-holder Assembly The specimen-holder muster is the complete assemblage in which the specimens are retained. Where the heating or cooling fount is merged in one unit with the ampoules or supports for the sample as well as reference material.

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Block This is a type of specimen-holder assembly in which a relatively large number of materials are in close contact with the specimens or specimen holders.

3.6.3 Working Principle of DTA As mentioned previously, DTA consists of a sample holder with thermocouples, sample holders, a furnace made of ceramic or metallic, a temperature programmer, and a recording system. In a basic arrangement of two thermocouples, they are connected to a high gain noise variance amplifier. Thermocouples are placed in such a way that it is placed in inert material Al2 O3 and the second one is placed in a sample of material which is under study. There will be a voltage deflection if there is phase transition as the temperature is elevated, this happens because of heat input while raising the temperature of inert substance as the material heat is in a phase transition [30]. In Fig. 3.18, there is a DTA output for melting and freezing of pure metal under specific conditions. When the material is heated, melting entails an input of heat, and the downward peak is endothermic. On the contrary, when cooling, freezing releases heat because that upward heat is exothermic. The fundamental exposure of melting and freezing is designated by the fundamental linear portion up to the maximum rebounding. The area of peak is used for heat flow calibration while fundamental recognition of phase change is indicated by the linear peak portion for temperature calibration [32]. Fig. 3.18 DTA responds to the melting and freezing of a pure material under ideal conditions. a-onset temperatures (taken here as equal to the melting point, TM), b-peak signals, c-peak temperatures [31]

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3.6.4 Interpretation of DSC and DTA Curves At the updraft of thermal analysis experiments, there are limitations of associating the features verified with the thermal events happening in the sample. DTA can provide information and the parallel experiment results are not possible, using various techniques such as TG, DSC, or DTA, underneath the conditions as closely harmonized as possible are more appreciated. As the DTA features curve is established, and baseline gaps examined, attention can be absorbed in the correlation of peaks that are endothermic as well as exothermic with thermal events in the sample. Usually, endothermic processes are readily reversible on cooling and reheating, or not. Exothermic processes are not usually reversible, whatsoever, in contrast to melting and solid–solid transitions. The melting endotherms for pure substances are very sharp which occur at narrow temperature pauses and melting point is found out as shown in Fig. 3.19, by extrapolation of rising steep, closely linear, endotherm region back to baseline. Endotherms of impure substances are broader and impure content is also estimated up to a maximum of about 3 mol% from the elaborated shape of the melting endotherm. The DSC or DTA record should ideally be the endothermic mirror image of that shown. The utilization of the heating compared to that of the cooling curve avoids Fig. 3.19 Measurement of heat capacity using DSC, DTA, displacement of baseline, a scan of the sample compared to the standard shift in baseline after a transition [7]

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Fig. 3.20 a DSC and DTA slow cooling of molten mixtures b schematic diagram comparison of DSC and DTA phase transition [33] Fig. 3.21 Relationship between melting and enthalpy comparison [33]

problems of supercooling. Preferably, the DSC or DTA traces should be eagerly relatable to the segment diagram, as illustrated schematically in Fig. 3.20. The area under the peak for the eutectic melting is a simple function of concentration and such a curve may be used to determine the composition of an unknown mixture, e.g., an alloy (Fig. 3.21).

3.6.5 DTA Calibration The measurement accuracy of quantity relies on the instrumentation. The consistency of the sample as well as experimental procedures and techniques are used in procedures. High accuracy is the essential factor for true value determination. Some

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methodical errors can cause counter errors in experimental findings, and calibration is required to detect these errors.

3.6.5.1

Mass Calibration

Calibration masses in an extensive range of sizes and various classes of correctness may be obtained from national standards organizations or commercial suppliers. A 100 mg Class S mass can tolerate mg or 250 ppm, while a Class S-1 mass has a twice tolerance than that. Gallagher [34] warns not to keep very high temperatures (above about 1300 °C for platinum) as the vaporization of metal from the sample suspension system can give a surprising mass loss (Fig. 3.22). A DTA was made for the particles of various sizes until the transition temperature was attained. This was then followed by cooling to produce recrystallization. A new DTA was made later.

3.6.5.2

Temperature Calibrations

The sharp exotherms in DTA curves can determine the temperature onset of decompositions. The calibration of DTA may be calibrated in the way using melting points of suitable pure metal standards. As an example, there are differential scanning calorimetry DSC and TG curves of complex glycerin (gly) are shown in Fig. 3.23.

Fig. 3.22 A vertical and horizontal view of the specimen-holder assembly showing the temperature in the different parts. The thermal interchanges are regulated by the K, KM, and K, coefficients [34]

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Fig. 3.23 Temperature calibration using explosive decomposition a DSC curves b TG curves of glycerin complex [35]

Instantaneous TG-DTG instruments are calibrated by direct temperature measurement in the DTA system. Herein measured melting point is utilized to interpret correction curve to construct the correction curve for curie temperatures as in the figure there is a plot of suggested values for Ni-Co system which is a plot of the recommended values of TC vs. composition for the Ni-Co system (Fig. 3.24). The smooth line is a key fit to the five points. Fig. 3.24 Curie temperature as a function of composition in the Ni–Co system [36]

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3.7 Differential Scanning Calorimetric (DSC) 3.7.1 Introduction This is an analytical technique, specifically, it is a thermoanalytical technique that measures the difference in the amount of heat essential to increase the sample temperature and reference as a function of temperature. Over the whole experiment, the sample and reference temperature are maintained at the same temperature. More precisely, calorimetry is a process to measure the heat released or absorbed while performing the chemical reaction. In 1960 and then in 1963, Watson ad O’Neil established this analysis commercially at the Pittsburg conference [37]. The fundamental principle in DSC involved technique which is used to study the heating effect on polymers or samples. This technique is also used to further study the heating effect on the crystalline polymer, glass transition, and crystallization. In this process, sample and reference materials are heated through the experimental at the same temperature in separate heaters. The energy is measured which is essential to obtain zero difference in temperature of sample and reference [38].

3.7.2 Instrumentation and Working The foremost components of DSC are illustrated in Fig. 3.25. There are two pans used in this technique, one for the same and the other for the reference. In the first sample pan, the sample is placed while the reference pan is reserved empty. Each one of the pans is having a heater to heat the two specific pans at a specific rate specifically the rate is usually 10 °C per minute. Then the computer is used to normalize a persistent heating rate during the entire experiment. Nevertheless, heaters do not provide heat at a constant rate. This is due to the difference in pans, one can contain polymer and the other does not have. Consequently, extra heat is obligatory Fig. 3.25 DSC apparatus [39]

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Fig. 3.26 The DSC curve of reactive epoxy is mentioned [40]

for the sample pan to keep the temperature to zero between the sample and reference [38]. The heater under-sample pan has more to do than the heater. DSC experiment can measure this extra heat of heater under-sample pan by plotting a graph where Xaxis resembles temperature and Y-axis resembles temperature difference of heaters (Fig. 3.26). Moreover, DSC is used to detect the rate of flow of heat between two crucibles with accuracy, as shown in Fig. 3.27 of the containers have material to investigate and the other empty as described earlier. For polymers, characteristic physical phase transition [40] such as melting, crystallization, evaporation, and glass conversion leads to heat flow between two containers. This crosslinking reaction is exothermic and can be detected with DSC. The DSC curve of reactive epoxy is mentioned in Fig. 3.13. The exothermic peak is provided at a maximum of 140 °C. It’s also a popular method to determine curie degree. / α DSC = 1 − ΔHr ΔHt

3.7.3 Types of DSC 3.7.3.1

Heat Flux DSC

This is a type of DSC that makes use of single heat source (furnace) to generate temperature difference between the sample and reference materials. The resulting temperature differences recorded are varied and converted to heat flow as shown in Eq. 3.1. / Overall heat flow d H dt. in heat flux DSC is given as

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Fig. 3.27 Schematic diagram of a heat flux DSC system. The sample and reference are heated at the same rate and the temperature difference is measured [41]

/ / d H dt = C p d H dt + f (T , t)

(3.1)

where H represents the enthalpy in J/mol, f (T,t) is the kinetic response of the material in J/mol as a function of temperature and time, Cp represents the specific heat capacity in J/K/mol. In summary, the overall heat flux is the sum of the kinetic response and specific heat capacity. Since the sample and reference materials are in a good thermal contact as shown in Fig. 3.28, the resulting heat flow is expected to be small. A thermocouple is usually employed during heat flux DSC process to measure the temperature difference between the sample and the reference materials [41].

3.7.3.2

Power Compensated DSC

Unlike heat flux DSC, both reference and sample materials in power compensated DSC are heated individually under separate heating source (furnace). The temperature difference generated between the reference and sample materials is maintained constant. Power compensated DSC as shown in Fig. 3.29 makes use of platinum sensor for controlling the temperature of the reference and sample materials. The resulting power is recorded as a function of temperature. Power compensated DSC benefits from fast and high resolutions and suffers from low sensitivity [42]. ( / ) ( / ) Δ dq dt = dT dt (Cs − Cr )

(3.2)

where Cs and Cr represent the heat capacity of the sample and reference materials, respectively.

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Fig. 3.28 Schematic of a DSC system with power compensation. The sample and reference materials are heated individually. In order to keep their temperature difference near zero, the heat flow to each material is modified. There is a record of the difference in heat flow [42]

Fig. 3.29 Working principle of DSC [43]

3.7.4 Working Principle of DSC The heat required to maintain a constant temperature difference between the sample and reference materials is measured as a function of temperature. Depending on the phase transition process, the reaction may either be exothermic (heat emitted) or endothermic (heat absorbed). For example, when a solid sample transitions to a liquid at a constant heating rate, more heat is needed to be added to the sample in order to increase its temperature. This occurs because the sample absorbs heat as it changes from solid phase to liquid phase. This process is known as endothermic

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Fig. 3.30 Generation of DSC signal [44]

reaction process. Examples include; melting, boiling, sublimation, vaporization, and di-solvation. However, in exothermic process, less heat is required to increase the temperature of the sample since the sample emits heat during the phase transition, examples include crystallization, degradation, and polymerization (Fig. 3.30) [43].

3.7.5 Generation of DSC Signals The differential signals ΔT generated during DSC analysis are majorly used to calculate the heat differences between the sample and reference materials (ΔT = TS − TR ). . Irrespective of the types f DSC, the differential signal (heat flow) generated is measured as a function of temperature. For example, considering the DSC signal of two temperature curves as shown in Fig. 3.31. The differential signals (ΔT ) which represent the difference in temperature between sample and reference material are shown at the adjacent end of the figure while the blue peak in the Area A represents an endothermic process (melting). The curve of the generated peaks may either moves up or down depending on whether the reference temperature was subtracted from the sample temperature (T S − TR ) or vice-versa (T R − TS ). The peak area is associated with the transitions heat content (enthalpy in J/g) [44].

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a

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Fig. 3.31 Schematics of a transition in glass. Due to the change in heat power, the glass transition results in a kink in the heat versus temperature plot (a). It is a steady progression that takes place over a range of temperatures in a heat flow plot versus temperature (b). The temperature of glass transition is taken to be the core of the sloped region [42]

3.7.6 Interpretation of DSC Curve The result of DSC curve can be used to obtain qualitative and quantitative interactions about the physical and chemical changes which include; glass transition, melting, and crystallization.

3.7.6.1

Glass Transition Temperature

When the polymer is cooled in its molten state, its physical properties transition from elastic materials to a hard material. This transition does not take place abruptly at a single temperature but rather over a wide temperature range as shown in Fig. 3.32. The temperature at which the process occurs at the middle of the curve is taken as the Tg. Fig. 3.32 Example of a crystallization ‘peak’ in a plot of heat flow against temperature. Crystallization is an exothermic process, which means that the heat passing to the sample must be lowered to maintain a constant heating rate [42]

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Crystallization

After glass transition, the polymers have high mobility which makes them to move freely for a long time until they get to the right temperature region where they will emit energy to form ordered arrangements and thus undergo crystallization. When the polymers form the ordered arrangement, they emit heat resulting into a drop in the heat flow, which signifies a sharp peak in the curve of the heat flow versus temperature (Fig. 3.33). Crystallization is an exothermic process at which heat is emitted to the surroundings and it is the lowest point of the dip.

3.7.6.3

Melting

If the polymer is heated beyond its crystallization temperature (Tc), another thermal transition will be reached, which is known as the melting temperature. The polymer crystals begin to drop at this temperature (melting takes place). The polymer moves out their well-arranged position to start moving freely, which is spotted on the DSC curve. It is important to note that when the polymer crystal melt, they will absorb heat. Since melting is a first-order transition, the temperature of the polymer will not increase until all crystals have been melted. Any additional heat added to the system during the melting process is the latent heat of melting (Fig. 3.34). The temperature will increase with increase in heating after the melting process has finished.

3.7.6.4

Combining Tg, Tc, and Tm

Figure 3.35 shows a DSC curve consisting of glass transition (Tg), crystallization tempeture (Tc), and melting point (Tm). It is worthy to note that not all polymers that

a

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Fig. 3.33 Melting is an endothermic process which means the heat flowing through the sample must be increased to keep the heating rate constant, resulting in a break in the plot of heat versus temperature (a). This appears as a peak if the heat flow is plotted against temperature (b). The area under the curve can be used to measure the latent heat of melting [42]

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Fig. 3.34 Example plot of a heat flow versus temperature plot for a polymer that undergoes a glass transition, crystallization, and melting [42]

Fig. 3.35 Schematic representation of modulated temperature versus time plot for MDSC. A sinusoidal temperature variation is overlaid on a linear heating [42]

can create crystals, the crystallization, and melting peaks are only detected. Polymers having both the crystalline and amorphous arrangements can only undergo the three transitions.

3.7.7 Modulated-Temperature DSC (MT-DSC) Modulated temperature scanning calorimetry (MT-DSC) is a revised version or an extension of the conventional DSC [45]. In modulated DSC, a sinusoidal modulation is typically overlapped on the linear heating ramp to create a signal which is analyzed by a Fourier transformation (Fig. 3.36). The Fourier transformation can be used to separate the DSC signals into two different categories, namely, reversing and non-reversing thermal events; / T =T0 = bt + B sin(wt)dq dt = c[b + Bw cos(wt) + f (t, T ) + k sin(wt)]

(3.3)

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Fig. 3.36 Typical DSC scan for a polymeric material. Note the step transition at about 63°C (Tg) [46]

where T represents the temperature, t is the time, C represents specific heat capacity. F (t,T) is the average kinetic function gotten by subtracting the effect of sine wave modulation, and w represents frequency. [b + Bwcos(wt)] is the calculated quantity dT/dt or curve reversing, k = kinetic response amplitude of the sine wave modulation. An example of MT-DSC is the curve showing the separation of DSC signals into reversing and non-reversing thermal events as shown in Fig. 3.37. The temperature at which transitions take place appears around 60 °C in the reversing thermal event connected with the heat capacity portion of the overall heat flow. The endothermic process occurs in the reversing thermal event at a temperature near 250 °C while the exothermic process takes place in the non-reversing thermal event at a temperature near 150 °C [46].

3.8 Simultaneous Techniques As a way of enhancing the result performance of thermal analysis, two or more techniques have been simultaneously combined. This method benefits from high thermal stability, precise temperature measurement, and determination of unsuspected transition. An example of the simultaneous technique is the DSC-TGA (Fig. 3.38) which is mainly employed to determine the changes in heat flow and mass in a sample as a function of time and temperature in a constrained environment. In addition to increasing efficiency, simultaneous measurement also gives more explanation on the information of the results. The supplementary data collected makes it possible to

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Fig. 3.37 DSC-TGA (SDT): Instrument design [47] Fig. 3.38 DSC curve for a polymer a Glass transition; b Crystallization; c Melting. The subsequent reactions may be endothermic or exothermic [45]

differentiate between endothermic and exothermic reactions with no related mass loss such as melting which signifies endothermic reaction and a degradation (exothermic reaction) having mass loss [47].

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3.9 Applications DSC is used in polymer science to measure the transition temperatures such as glass transition (Tg), melting point, and crystallization temperature (Tc). This provides information such as thermal events, degree of cure, and polymer’s plastic composition. Figure 3.39 shows a DSC curve for a polymer where the first peak marked “a” represents the glass transition (a point at which the polymer in its molten state is cooled) corresponding to a downward shift, b represents crystallization temperature (a point above the glass transition in which the polymer has high mobility. The crystallization is an exothermic reaction process, i.e., heat is emitted to the surroundings. The area marked “c” represents the melting temperature (a point at which the polymer having high mobility moves around the chains without any crystalline arrangements). The melting process is an endothermic reaction which requires the absorption of heat thus resulting in an upward shift of the DSC curve [45]. Another application of DSC can be seen in isothermal experiments to determine the degradation or oxidation rate of polymers as shown in Fig. 3.40. A stabilizer was added during the experiment to enhance the stability of polyethylene to oxidative degradation. The process follows an exothermic reaction which means that the polymer is degraded by emission of heat resulting in a downward shift [33]. Fig. 3.39 Isothermal oxidation of polyethylene at a temperature of 200 °C [33]

Fig. 3.40 DSC used for identification of the components of plastic waste. LDPE = low density polyethylene; HDPE = high density polyethylene; PP = polypropylene; PTFE = poly (tetrafluoroethylene), “teflon” [33]

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Fig. 3.41 Thermogravimetry/differential thermogravimetry curves of a coal sample [48]

DSC has also been employed to determine the purity of compounds such as identification of valuable components in plastic waste (Fig. 3.41). It is important to recover valuable minerals in waste by identifying, sorting, and collecting the components of the valuable minerals in waste. The process follows an endothermic reaction indicating that heat was absorbed resulting in an upward shift [33].

3.9.1 DSC, TG/DTG, and DTA Studies on Coal Samples DTA is one of the earliest thermoanalytical methods used in studying coal samples. It has majorly been employed to study the behavior of coal by means of characterization. Since coal consists of valuable components that exist in different amount, there is a need to investigate these components in order to understand their thermal effects. A few major factors influence the behavior of coals during its combustion which include; chemical structure, the original distribution of materials within the fuel components, the level of sorting the materials within the fuel components, and the level of mixing of the different components that may arise as the reaction progresses [48]. In principle, the burning of coal starts once it interacts with oxygen, with the essence of the reaction being regulated by the combination of fuel, oxygen supply, and temperature. Three reaction zones were found at different temperature intervals in the thermogravimetry (TG)/differential thermogravimetry (DTG) analysis of the coal sample: the first zone was attributed to evaporation of water in the sample; the second zone was as a result of the volatile matter release and carbon combustion (known as the major reaction region); while the third zone was related to degradation. The major mass loss takes place in the second zone, which involves burning of the carbon-based materials of the sample (Fig. 3.42).

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Fig. 3.42 Thermogravimetry/differential thermogravimetry curves of a crude oil sample [48]

Two sequential stages were detected during the study of different ranges of coal samples. The first phase involves an initial stage that is mainly regulated by coal depolymerization while the second stage involves the restriction of the actual rate which is regulated by the surface characteristics of the coal [49]. Using power compensating form differential scanning calorimeter (DSC) and thermogravimetry (TG–DTG) at different temperatures ranging (5, 10, and 15 °C/min), the combustion characteristics of two separate coal samples were analyzed. At each reaction temperature studied, differential scanning calorimeter (DSC) and thermogravimetry (TG–DTG) curves revealed mainly two reaction regions. The regions of reaction, peak and incinerate temperatures, weight loss and heat of the sample reactions were evaluated. Different methods also determined the reaction kinetics of the coal samples and it was observed that the activation energy values of the coal samples ranged from 27.2 to 76.2 kJ/mol for different reactions [49]. Hao Zhang and his co-workers [50] studied the non-isothermal characteristics and pyrolysis kinetics of bituminous coal at different heating rates of 10, 20, and 30 °C/ min by combining TG-MS/DSC techniques. They also investigated the concentration, pyrolysis phase, the maximum weight loss rate, the characteristic peak temperature, and the release of the main volatile gases. They reported that with the addition of CaO and the rise in the rate of water feeding, the concentrations of H2 , CO, and CO2 in gas products also increased. In addition, with the rise in water feeding volume, the concentration of CH4 also increases but decreases due to the addition of CaO. It is also important to note that, in relation to in-situ CO2 captured and catalytic cracking reactions at the initial stage of the pyrolysis process, the pyrolysis process was improved by CaO.

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3.9.2 DSC, TG/DTG, and DTA Studies on Crude Oil Samples The first thermoanalytical method to be used in the study of crude oil was differential thermal analysis, with most of the crude oil analysis aimed at finding a link between the samples’ thermal behavior and kinetic studies. The influence on the combustion properties of crude oils of various metallic substances has also been studied through this method. During the oxidation of crude oil in porous media by air injection, a number of reactions were observed in combustion with air, namely, low-temperature oxidation (LTO), fuel deposition (FD), and high-temperature oxidation (HTO). In thermogravimetric experiments (TG/DTG), the first reaction is the LTO which occurs at a temperature up to 380 °C, with the reaction rate being equal to the area of the sample substrate. The crude oil is heated and deposited as fuel on the sample substrate in the second reaction area, named FD, which occurs at a temperature range of 380 to 500 °C. HTO is the final reaction region which takes place at a temperature range of 500– 600 °C as shown in Fig. 3.43. In this region, the oil products under study are exposed to heat in an acidic medium, resulting in higher impact of the exothermic reaction heat. While the different reaction mechanisms can be traced to the specific activation energies for each reaction region, they don’t provide evidence of the contribution of each region to the overall crude oil reactivity [48]. Kok and his co-workers [51] studied the effect of several clay minerals such as bentonite, illite, and kaolinite on the combustion behavior and kinetics of crude oils from Kazan region (Russia) using thermogravimetry (TGA) and differential scanning calorimeter (DSC). They performed ramped temperature tests in the presence of air at constant heating rates (10, 20, and 30 °C/min). Two reaction regions known as low temperature oxidation (LTO) and high temperature oxidation (HTO) were detected in both TGA and DSC studies. They reported that the peak temperatures and reaction

Fig. 3.43 Thermogravimetry/differential thermogravimetry curves of an oil shale sample [48]

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intervals were affected by the presence of the clay minerals. Also due to the surface area effect, the addition of various clay minerals lowered the weight loss percentages of the crude oil samples. In addition, through a significant reduction in the energy gap, all clay samples were reported to have a strong catalytic effect.

3.9.3 DSC, TG/DTG, and DTA Studies on Oil Shale Samples Oil shales are commonly known as petroleum rocks containing a reasonable amount of organic matter compositions needed to make their practical use possible. Oil shales have recently been discovered to be an alternative source of energy due to their large resources which are much more than that of crude oils. In view of this, much attention have been drawn to the use of oil shale as feed stock and energy sources [48]. Thermal analysis has been popularly used to study the decomposition kinetics of oil shake, kerogen (organic matters in rock). A dynamic, multistage thermal method has been demonstrated to investigate the burning of natural organic matter as shown in Fig. 3.44. It is worthy to note that the thermal activity of oil shale in volatile air atmospheres can exhibit properties of both inorganic (mineral) and organic (kerogen · bitumen) components. Although the low-temperature section of the thermal curves may reflect a thermal decomposition similar to that found in an inert environment, the oxidative properties of the organic component typically prevail at elevated temperatures (Fig. 3.44). Many researches have been conducted on the kinetic studies of the combustion and pyrolysis of oil shales.

Fig. 3.44 TG/DTG and DTA curves of Ulukila oil shale [52]

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Kok and his co-workers [52] conducted the kinetic and thermal studies of ten lignites and two oil shale samples of different sources using TA 2960 thermal analysis tool with thermogravimetry (TG/DTG) and differential analysis (DTA) modules. In most of the samples analyzed, three distinct reaction areas were primarily observed. The first area detected was due to the evaporation of water in the sample. The second region, known as the main reaction area, was attributed to the release of volatile matter and carbon combustion. The third area was as a result of the mineral matter decomposition in the analyzed samples. Oxidation of lignite and oil shale is defined by first-order kinetics in kinetic calculations. The activation energy values differ and the effects are examined, based on the features of the samples (Fig. 3.44).

3.10 Conclusion Several literature reviews have shown that thermal methods are not only gaining growing applications in fossil fuel analysis, but also have been used very effectively to research the interactions of fossil fuels with nitrogen and other gases, including air and oxygen. In terms of evaluating changes in properties such as structure, decomposition features, calorific impacts, kinetics, and proximate analysis, the use of thermal methods has shown great significance. The data obtained simply demonstrated that thermal analysis is a well-established tool used in the field of fossil fuel research. A review of the available reports also showed that, from both scientific and analytical points of view, thermal methods are significant.

3.11 Exercises (1) Individual task: Find a research paper on fossil fuel and explain how thermal analysis (TA) was used in that study. (2) Group task: In small groups, find a literature article on thermal analysis techniques and make a presentation on their applications.

3.12 Questions (1) Illustrate the instrumental of the thermobalance system and describe its working mechanism. (2) Make a chart to explain the types and characteristics of thermal analysis (TA). (3) Explain how temperature and atmospheric pressure affect thermobalance. (4) Using a sketch, analyze the TG and DTG curves. (5) What are the most causes of errors in TG? (6) Explain the advantages of thermocouples.

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Describe the working principle of DTA instrumentation. Illustrate on mass and temperature calibration of DTA. Explain the working principle of DSC. How are DSC signals generated and results interpreted? Impact factors of accuracy in TG.

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29. Ozawa, T. (1966). A new method of quantitative differential thermal analysis, 39(10), 2071– 2085. 30. Boettinger, W. J. et al. (2007). DTA and heat-flux DSC measurements of alloy melting and freezing. In Methods for phase diagram determination (pp. 151–221): Elsevier. 31. Boettinger, W., et al. (2006). DTA and Heat-flux DSC Measurements of Alloy Melting and Freezing: NIST Recommended Practice Guide, 960, 15. 32. Presoly, P., et al. (2013). Identification of defect prone peritectic steel grades by analyzing high-temperature phase transformations, 44(12), 5377–5388. 33. Riga, A., & Collins, R. (2006). Differential Scanning Calorimetry and Differential Thermal Analysis. In Encyclopedia of Analytical Chemistry. 34. Gundlach, E., & Gallagher, P. (1997). Synthesis of nickel base alloys for use as magnetic standards, 49(2), 1013–1016. 35. Brown, M. E., et al. (1994). Temperature calibration in thermogravimetry using energetic materials, 242, 141–152. 36. Gallagher, P., et al. (2003). Magnetic temperature standards for TG, 72(3), 1109–1116. 37. Brickwood, K. J., et al. (2019). Consumer-based wearable activity trackers increase physical activity participation: Systematic review and meta-analysis, 7(4), e11819. 38. Akash, M. S. H., & Rehman, K. (2020). Essentials of pharmaceutical analysis. Springer. 39. Yi, F., & LaVan, D. A. (2019). Nanocalorimetry: Exploring materials faster and smaller, 6(3), 031302. 40. Ehrenstein, G. W. et al. (2003). Praxis der thermischen Analyse von Kunststoffen: Hanser Verlag. 41. Chatwal, G. R., & Anand, S. K. (2002). Instrumental Methods of Chemical Analysis: (for Hons. and Post-graduate Students of Indian and Foreign Universities): Himalaya publishing house. 42. Berlin, H. U. A. Z. (2009). Investigation of polymers with differential scanning calorimetry, 1–17. 43. Global, H. H. T. (2021). Principle of differential thermal analysis (DTA) https://www.hitachihightech.com/global/products/science/tech/ana/thermal/descriptions/dta.html. 44. Schoff, C. K. (2008). Differential scanning calorimetry. In Am Coatings Assoc-Aca 1500 Rhode Island Ave Nw, Washington, DC 20005 USA. 45. Warrington, S. B., & Höhne, G. W. (2000). Thermal analysis and calorimetry. 46. Skoog, D. A. et al. (2007). Principles of instrumental analysis. In Thomson Brooks/Cole. 47. Banerjee, D. (1993). Experimental techniques in thermal analysis thermogravimetry (TG) & differential scanning calorimetry (DSC). Paper presented at the Analytical Proceedings. 48. Kok, M. V. (2010). Combustion characteristics of Fossil Fuels by thermal analysis methods, 75–87. 49. Kok, M. V. (2012). Simultaneous thermogravimetry–calorimetry study on the combustion of coal samples: effect of heating rate, 53(1), 40–44. 50. Zhang, H., et al. (2020). Study on non-isothermal kinetics and the influence of calcium oxide on hydrogen production during bituminous coal pyrolysis, 150, 104888. 51. Kök, M. V., et al. (2021). TGA and DSC investigation of different clay mineral effects on the combustion behavior and kinetics of crude oil from Kazan region. Russia, 200, 108364. 52. Kök, M., et al. (2004). Combustion characteristics of lignite and oil shale samples by thermal analysis techniques, 76(1), 247–254.

Chapter 4

Gas Potentiometry Diagnostics in High-Temperature Environments Vestince Balidi Mbayachi, Zhen-Yu Tian, Zhi-Min Wang, Maria Khalil, and Daniel A. Ayejoto

4.1 Introduction Gas potentiometry is a method of study for the calculation of partial gas oxygen pressure [1, 2]. A strong electrolyte is mostly employed in this method to separate a reference compartment and a test compartment. It is worth noting that gas potentiometry reaction mechanisms are very complex and it is therefore important to determine the various parameters of the test system such as velocity, strain, temperature, density, and chemical composition in order to be able to understand this complex process [2, 3]. In view of this, a broad variety of studies on theoretical modeling and ways of enhancing measurement have been carried out as a means of understanding the dynamics of reaction processes [4, 5]. In recent times, laser spectroscopy techniques such as CARS spectroscopy, laser doppler anemometry, among others, have been developed to detect highly sensitive single atoms and molecules in the reaction zone and to determine parameters such as reaction species concentrations, temperature, and velocity [6]. This form of technology, however, is very expensive and therefore

V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China e-mail: [email protected]; [email protected] V. B. Mbayachi · Z.-Y. Tian (B) · Z.-M. Wang · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China e-mail: [email protected] Z.-Y. Tian · Z.-M. Wang Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_4

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only applies specifically to gas targets and, in particular, to gas flames. Therefore, other options need to be searched with a low-cost benefit. While less familiar, stabilized zirconia (ZrO2 ) has recently been documented as a solid electrolyte for direct analysis of reaction processes. This includes the use in the reaction process of oxygen as a major reaction component. It is used to measure oxygen concentration, which in turn provides data on the reaction process itself. The ability to make in situ measurements directly in the reaction zone of a combustion chamber is one of the advantages associated with this process. In order to carry out an accurate and precise quantitative study of the reaction processes, attention was drawn to the development of a gas potentiometric analysis system (see Fig. 4.1), which describes the progress of thermochemical conversion processes for fuel gases (combustion, reforming), solids (combustion, gasification) and facilitates the characterization of solid fuels [7, 8]. The goal of this chapter is to provide a general overview of the various potential applications of gas potentiometry in combustion processes as an advanced diagnostic tool. Different gas potentiometry applications in several fields will also be discussed, a broad overview of the current and new applications will be given, and emerging developments in the use of gas potentiometry for in situ diagnostics will be discussed.

Fig. 4.1 Schematic illustration of type I potentiometric gas sensor with oxygen conductor a and protonic conductor b used as solid electrolytes [7, 8]

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4.2 Theoretical Foundations of Gas Potentiometry In comparison to calculation methods such as amperometry and similar methods, gas potentiometric oxygen probes (GOPs) measure the potential of an electrochemical cell at a constant current. As there is no or little current passing through the cell, the component still remains static.

4.2.1 Physico-Chemical Measuring Principle During the calculation of GOPs, metal such as platinum is usually employed due to its chemical and thermal stability. The measuring theory behind these methods includes applying an oxide ion-conducting solid electrolyte to create a galvanic oxygen concentration chain. The formed galvanic oxygen concentration chain is then linked with a porous valuable metal in contact with oxygen-containing gas phases along with the opposing surface of the solid electrolyte (Fig. 4.2a). The two electrodes (reference and measurement) cover the three phases in the solution, namely gas, precious metals, and solid electrolytes, as shown in Fig. 4.2a. The galvanic oxygen concentration chain can be explained in various ways depending on the contents of the measuring and reference gas. For example, consider a gas phase having a reference gas having a constant O2 content, and the other of a measuring gas with an unknown O2 concentration. The following cell symbol can be used to describe the galvanic oxygen concentration chain [10]: 

p (O2 )/Pt/Zr0,85 Ca0,15 O1,85 /Pt/r e f er ence gas p  (O2 ).

Fig. 4.2 a Functional principle and b a schematic representation of a gas potentiometric oxygen probe three-phase reaction, in an oxidizing atmosphere [9]

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CaO-stabilized ZrO2 (15 mol% Ca) is used as a solid electrolyte in the above equation. The overall reaction is given as follows (Eq. 4.1) (see also the schematic representation in Fig. 4.2b): O2 (gas phase) + 4e− (Pt)  2O2 (solid electr olyte)

(4.1)

The level of electrochemical potentials in the specific electrode is adjusted as a function of O2 concentration. The difference between the oxygen concentration chains of various electrochemical potentials, designated as the equilibrium cell voltage Ueq, yields the O2 concentration in the measuring gas over a temperature range of approximately 600 to 1600 ◦ C [11]. This equation is known as the Nernst equation: 

Ueq =

R.T p (O2 ) ln . 4.F p  (O2 )

(4.2)

where, respectively, Universal gas and Faraday constants are R and F. The equation  substitutes the intrinsically efficient oxygen concentrations by partial pressures p O2 and p  O2 since gases with a high temperature act as an ideal gas [12]. Given the logarithmic relationship between the equilibrium cell voltage and concentration (Eq. 4.2), the sensor’s sensitivity and accuracy of measurement is the greatest for small O2 concentrations, and relatively low for larger concentrations. At an assumed accuracy of 0.1 mV and 1 K, an error of approximately 1 percent is specified for cell voltage, whereas it is approximately 10 percent for accuracies of 2 mV and 5 K [11]. The Nernst equation is translated into Eq. 4.3 by replacing R and F with the necessary numbers, and with a known air pressure p and known operating temperature T:     Ueq p O2 T = a 0.0336 + 0.0496 log . . mV p K

(4.3)

The oxygen content in the measuring gas can be determined using a measured cell voltage using Eq. 4.4: 

Ueq [mV ]/T [K ]−0.0336 p O2 0.0496 = 10 p

(4.4)

There will be an appropriate high forward and reverse reaction rate if an equilibrium is realized in the electrode, with a mechanism different from that in Eq. 4.1, resulting in sufficient oxygen ions for electrochemical conversion [13]. The partial pressure of oxygen is therefore directly linked to the pressure of dissociation between the complementary gas components. In the surrounding gas, this helps assess their redox ratio [14, 15]. For instance, the electrode reactions in the atmosphere

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Fig. 4.3 Schematic representation of a gas potentiometric oxygen probe three-phase reaction in a reducing atmosphere with a CO/CO2 and b H2 /H2 O mixtures [9]

of CO/CO2 can be explained by the overall balance shown in Eq. 4.5: C O2 (gas phase) + 2e− (Pt)  C O(gas phase) + O 2− (solid electr olyte) (4.5) Examples of CO2 /CO and H2 O/H2 mixtures display the phase reactions in the decreasing atmosphere in Fig. 4.3. As there is no free oxygen present, the equilibrium cell voltage produced by the GOP cannot be explained by Eq. 4.2. However, it can be used to derive other cell voltage equations that explain the quantitative association between the cell voltage and the concentration of the respective fuel and exhaust gases [10].

4.2.2 Solid Electrolytes Solid ionic conductors, which can be used as electrolytes in electrochemical cells, are known as solid electrolytes. They can also be used to assess the pure oxygen ion conduction of O2 concentrations in GOPs. A significant research on the use of solid electrolyte (ZrO2 ) to determine oxygen concentration was conducted. Zirconium oxide (ZrO2 ) was used in a concrete shape that naturally occurs as the monoclinic mineral baddeleyite, resulting in a phase change above 1000 ◦ C with the tetragonal modification and 2300 ◦ C with the cubic fluorite structure. It has been stated that through the addition of calcium oxide (CaO) and heating to 1600 °C, the cubic lattice structure can be transformed into a new stage that is stable in ceramic at room temperature. With a CaO content of between 15 and 28 percent mol, the only form that appears is CaO-stabilized zirconium oxide

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Fig. 4.4 Zirconia probe for oxygen measurement [16]

[16]. If heated at 700 ◦ C, zirconium oxide (due to the oxygen vacancy in the ceramic lattice) is selectively conductive to oxygen ions (Refer to Fig. 4.4). A DC voltage is generated on opposite sides of the zirconium oxide membrane if two gases differ in O2 concentration, as per Nernst, who established this relationship. There are other criteria for determining O2 concentrations using solid electrolytes, including minimum gas solubility and permeability under measurement conditions [17]. In order to produce gas-tight ceramic bodies formed as plates and tubes, ceramic processes and sintering at 1800 ◦ C were applied [16]. Figure 4.5 shows a schematic diagram of an oxygen sensor centered on the YSZ thimble type. The output of this potentiometric sensor is due to chemical and electrical processes having a combined effect. The oxygen molecules are adsorbed onto the porous electrode, commonly made of platinum, and dissociate into atomic oxygen when the sensor is exposed to a test gas environment [18]. The oxygen atoms then diffuse through the electrode (Pt), electrolyte (YSZ), and gas boundaries called the “triple phase boundary” (TPB), where electron transfer takes place from the electrode to the O2− ion atomic oxygen (reduction).

4.2.3 Resume In determining oxygen concentrations during reaction processes, this section provides a description of the aforementioned gas potentiometric oxygen probes (GOPs). It should be remembered that the high GOP sensitivity not only makes it possible to measure free molecular oxygen under oxidizing conditions, but also to measure so-called equilibrium oxygen in gas atmospheres. For in situ measurement applications, the rapid establishment of equilibrium in a GOP is a fundamental prerequisite [19].

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Fig. 4.5 Schematic diagram of a potentiometric oxygen sensor employing a thimble YSZ electrolyte and platinum electrodes (a) and the chemical potential profile in the sensor cell (b) [18]

4.3 GOP Application in Research and Industry Gas potentiometric oxygen solid electrolyte sensor applications have gained a great deal of attention in industry in recent decades, becoming the standard part of many systems such as lambda oxygen sensors and exhaust gas probes. In particular, they are used in motor vehicle emission control systems or in power plant monitoring systems, primarily to characterize gases, also to assess the absolute oxygen content in a significant way. The GOPs, however, perform much more than basic oxygen concentration determinations in many in situ applications. They also strengthen the study of conversion processes, as the basis for future regulation and also in the characterization of fuels applied. There is also a need for a closer study of the architecture and systems of the GOPs [20].

4.3.1 Materials, Design, and Systems The material chosen and the specifics of its design play important roles in the assembly of an optimally designed measurement device for gas potentiometric oxygen probes (GOPs). When used directly in a reaction chamber as in situ measurement instruments, GOPs are perpetually subject to thermal and mechanical stresses.

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Sensor Materials

Three parameters usually describe a working sensor: sensitivity, selectivity, and time of response. Sensitivity is the sensor’s ability to assess the test gas under given conditions quantitatively. The intrinsic physical and chemical properties of the materials used are regulated by them. A sensor’s selectivity is its capacity to detect a specific gas free from interference. Response time is a calculation of how soon the maximum signal shift is done with changes in gas concentration. In addition, reversibility, long-term reliability, size, and power consumption are other factors that influence the overall performance of the sensor. The GOP measurement device consists of a true potentiometric oxygen concentration measuring chain (gaseous electrode, solid electrolyte, and reference gas electrode measuring device) and a thermocouple for sensor temperature determination [21].

Potentiometric Oxygen Concentration Measuring Chain Due to its ionic nature and greater stability in harsh conditions, stabilized zirconia (YSZ) is typically used since the ceramic solid electrolyte content remains the material of choice [22]. Although a wide variety of material choices have been tested and optimized in order to expand the range of applications with regard to the lower temperature range and conductivity of oxygen ions, it has been demonstrated that YSZ is ideally suited for use in combustion plants [23]. The three-phase boundary where the electrode reaction occurs is formed by a measuring gas electrode consisting of a measuring gas, the electrode metal, and a solid electrolyte. As electrode materials, precious metals such as Pt, Pd, Au, Ag, or even mixed oxides, perovskites, and alloys are typically used. These materials need to be redox-stable, thermostable in the unique atmosphere of the sample gas, and also have the catalytic activity required to achieve chemical equilibrium. The size of the electrode is also important during the measurement of oxygen using GOPs. A small electrode surface area enables a particularly short response time and can reflect the quality of gas with precise precision. It is worth noting that the greater the surface area of the electrode, the more integral the signals produced are. The metals on the measuring and reference side of the electrode create thermoelectromotive forces that contribute to asymmetric voltages. By adding similar gases to the measurement and reference side, this voltage can in turn be calculated as a function of temperature [24]. On the other side, for the measuring chain, the reference gas electrode produces a recognized and static oxygen potential. Purging the reference chamber with gases is a convenient way to produce a static O2 partial pressure, and for this reason the technical gases are used with proven oxygen concentrations (e.g., pure oxygen or nitrogen blends as an inert gas fraction). The use of (ambient) air as the reference medium is another easy option; however, the water vapor content of ambient air must be permitted in the calculation, since any additional impurities must have been

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extracted for accurate measurements. It is necessary to adjust the appropriate material combination of the gas atmosphere and the planned operating temperature in order to ensure that the service life of the sensors meets the operating requirements [25].

Thermocouple As a way of maximizing precision, it is necessary to link thermocouples to instrumentation and at the same time to ensure that unwanted noise does not occur in the measurement process. The temperature calculation resulting from this is only as precise as the sensor and its interface. To evaluate gas concentrations from measured cell voltage, electrode temperature is measured on the measuring or reference gas side [26]. A solid precious metal thermocouple (R, S, B) may be mounted by touching a platinum/rhodium wire if Platinum (Pt) is used as an electrode material. Depending on the manufacturer’s requirements, where an oxygen carrier (air) is used to extract the reference gas side, marketable extremely fine precious metal-free thermocouples (e.g., K, N) can be added up to approximately 1300 ◦ C. Their protective metal sheathing must be capable of withstanding extreme operating conditions in a situation in which the thermocouples are applied on the measuring gas side (Fig. 4.6). Thus, when working at an exceptionally high temperature (>1000 ◦ C) or in a decreasing atmosphere, precious metal thermocouples are normally reversed. If there are no ideal isothermal properties in the potentiometric measuring chain, then precision measurements would require the use of a second thermocouple to calculate and correct the thermoelectromotive forces between the electrodes of the sensor. A way to enforce this has been found by Mobius. The extension wires remain the chosen wires for reducing any errors in temperature calculation when connecting the thermocouples to the measuring unit.

4.3.1.2

GOP Design

In GOP designs, there are two main sensors used, namely, Tubular GOPs and Planar sensors. These sensors are mostly used to miniaturize probes to a few centimeters in size, or, depending on the method of use, they can be several meters long. Miniaturized potentiometric oxygen sensors possess better advantages over their macroscopic equivalents. The classical design in which the potentiometric measuring chain is mounted on the end of a semi-closed solid electrolyte tube is represented by tubular GOPs as the sensor. Figure 4.8 demonstrates a standard setup, with air purging of the reference gas chamber [9]. Many electrodes can be applied to solid electrolytes, which consequently expand the way captured signals can be analyzed. Variants with several electrodes can be used with electrodes having the same or different materials and hence different catalytic activity. For locally resolved signal evaluation, several electrodes with the same

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Fig. 4.6 Scheme of a classical gas potentiometric oxygen probe (GOP) (a), the sensor element in magnification (b), and a protected GOP (c) [9]

material configuration are optimal, while a mixture of different materials enables the qualitative evaluation of gas equilibrium at the measuring electrode. Figure 4.7 provides several examples of sensors with electrodes of various configurations and materials. Alternative approaches for developing the GOP with a low-cost advantage are planar sensors in which thick or thin film technology can be used to apply the probe

Fig. 4.7 Water-cooled GOP (a); a turbulence GOP with a point electrode (b); a gradient GOP (c); and GOPs with combinations of gold and perovskite electrodes (d) [9]

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Fig. 4.8 A fully closed GOP (a), and GOP protected by baffle plates (b, c) [9] Fig. 4.9 ZR202G Oxygen probe used in the harsh industrial environment [28]

surfaces to a ceramic carrier. While the reference and sample gas electrode can be coated onto the oxygen-ion conductor (usually YSZ) either next to or atop each other, heat can be applied either on the back of the carrier or in interlayers. To produce the reference, a Me/MeO mixture or pump electrode can be used. In reaction chambers, this design can also be used directly [27].

Mechanical Barriers (Plates, Tubes, Meshes) and Sensor Mounting Gas potentiometric oxygen probes (GOPs) have various designed baffle plates that protect the sensors from mechanical stresses such as fluidized beds. Figure 4.8 shows how rustproof and thermostable stainless steel (Hastelloy, Inconel) tubes and plates shield the electrodes and ceramic tubes of the GOP. Shuk et al. (2007) described the zirconia oxygen probe as an example of the commercial GOP probe applied in the industrial environment for the measurement of hazardous chemicals and extreme temperatures (Fig. 4.9) [28]. The measuring electrodes of these GOPs may also be shielded by porous or mesh ceramic coats.

Heating GOP’s sensors must be heated to achieve the optimum working temperature when the measured gas temperatures are low. The heat source can be installed either outside as radiant heating or inside the sensor.

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Fig. 4.10 Schematic diagram of a modified solid electrolyte cell (measuring electrode covered with a catalyst) for the potentiometric gas analysis [29]

Facilitating the Establishment of Equilibrium A chemical equilibrium establishment in the measuring electrode is complicated when taking measurements in reactive gas mixtures. The solution to this problem is achieved when the electrode is surrounded by a catalyst, which facilitates the chemical equilibrium of the gas before it reaches the electrode. Hartung demonstrated an example of the design and selection of the catalyst for the analysis of water–gas equilibrium (Fig. 4.10) [29]. High flow rate of the measuring gas may also disrupt the establishment of the equilibrium, in this case, the sheathing of the electrode may considerably reduce the velocity of the gas thus improving the relationship between the flow rate and flow rate.

Protection Against Carburization Carbon may be deposited on the catalytic active electrode when analyzing the reducing atmosphere that contains hydrocarbon fractions. The formation of carbon– metal alloys may lead to the destruction of the measuring electrode. The incorporation of perovskite as an electrode material and the use of carbon traps such as porous ceramic coats and mineral wool can protect the electrode from carbon inclusions.

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Fig. 4.11 A mesh wire is stretched around the sensor to protect against explosion

Explosion Protection GOPs are at the risk of explosion since they constitute an ignition source in the atmosphere. Such conditions are prevented by equipping the sensors with the explosion protection (see Fig. 4.11). Wire mesh usually is stretched around the sensor to prevent flame propagation.

4.3.1.3

Electrical Metrology

GOP sensors produce a voltage of around −1600 mV in the reducing atmosphere and between −350 and 0 mV in the oxidizing atmosphere. These voltages are picked at zero current, hence the signals are first converted in order to be conducted for a long period at the measuring device. The thermal voltage of the converter and its cables that transmit the cell voltage must be shielded to prevent any misinterpretations caused by electric fields. For dynamic measurements, a higher sampling rate in Kilohertz (KHz) is required, whereas a low sampling rate in hertz (Hz) is required for general application. Bonde illustrated the analysis of the hydrodynamic fluctuations in the flame using potentiometric solid electrolyte oxygen gas sensors [30]. In Fig. 4.12, the GOP sensor was set up in the flame to stimulate rare application conditions. The sensor was moved in the three regions of the flame (oxidation and reduction). In the oxidizing region of the flame, the sensor was heated to a temperature of around 650 ◦ C. Then in the reducing region, the sensor was cooled down to a temperature of 400 ◦ C. Finally, the temperature was brought to the ambient temperature.

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Fig. 4.12 Experimental set-up for the long-term investigation of gas flame using GOP sensor [30]

4.3.1.4

Response Time

The response time of the GOP depends majorly on the design (barriers and electrode size) and the gas characteristics (reducing/oxidizing atmosphere, intensity of variation, and basic voltage). Dynamics of GOP measurements and test findings of the response time taken in the oxidizing atmosphere is represented in Fig. 4.13 as a cell voltage curve at four different temperatures. Here, a classical GOP was used and the t90 -value (the time when 90% of the final cell voltage is given by the sensor after a change) is less than 15 ms for the temperature higher than 800 ◦ C that are characterized for combustion processes [31].

4.3.2 Analysis and Characterization of Gaseous and Liquid Fuel Combustion The combustion process of liquid fuels and gaseous fuels can be analyzed either inflame (in-situ) using GOP at a temperature between 600 and 1500 ◦ C or off-flame at a

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Fig. 4.13 Response times of a classical GOP taken in oxidizing atmosphere [31]

Table 4.1 An overview of gas potentiometric flame analysis (GPFA) methods In-flame analysis

Off-flame analysis

Performance Use of flame GOPs with bum-out arid tur bulence sensors

Use of flow measuring cells

Measurements without gas sampling (in situ measurement)

Measurement with sampling of flame gas (on line/off line measurement)

Measurement at particular flame temperature Measurement at optimal sensor operat ing (operating temperature, establishment of temperature (external sensor heating): Minimal equilibrium): Thermal and mechanical stress in stress of the solid electrolyte solid electrolyte Results Flame body geometry; Contour, length, degree of bum-out Degree of mixing Analysis of turbulent flame structure

Fud gas analyses: stoichiometric air re quirement, determination of heating value

New concepts to optimize and regulate combustion

temperature below 600 ◦ C or exceeding 1500 ◦ C. An overview of gas potentiometric flame analysis (GPFA) methods is given in Table 4.1.

4.3.2.1

In Situ Measurement

Cell voltage signals are always produced when the flame is scanned by GOP [32]. Figure 4.14 illustrates a schematic of a temporal signal curve of a free jet flame.

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Fig. 4.14 Schematic of cell voltage sensor signals in different positions of a free jet flame [32]

The structure of the flame in Fig. 4.14 is due to the cell voltage signal fluctuation because of the oxidizing and reducing atmosphere. The flame roof represents the oxidizing atmosphere, here the oxygen molecule (2.1 vol%) reacts with the gas fuel and is measured at the cell voltage of −40 Mv. The root of the flame is the reducing atmosphere, and it is responsible for the highly negative cell voltage value because of high fuel gas surplus. The function of the Nernst equation (Ueq ) is to describe the relationship between the cell voltage and the different concentration of flame gases such as CH4 , O2 , CO, CO2 , N2 , H2 O, and H2 . Ueq data enables the quantitative evaluation of the combustion conditions of the flame structure thus the high cell voltage values represent the fuel– gas region (bottom of the flame) followed by the water–gas region and finally the inflection region of exhaust gas–air (low cell voltage) at the roof of the flame. Figure 4.15 shows the cell voltage values in Ueq and the sensor temperature (TZ) in conjunction with the corresponding concentration of CH4 , O2 , CO, CO2 , N2 , H2 O, and H2 which are analyzed by gas chromatography as a main axis of the flame structure. These data measured from gas potentiometry enable the calculation of important flame parameters such as mixing and the degree of burn out. A turbulence GOP allows the detection of the frequency distribution of Ueq and the bales of gas–fuel and air for a specific position in the flame.

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Fig. 4.15 Cell voltage (Ueq ), sensor temperature (TZ), the concentration distribution of equilibrium gases, and the gas temperature (TG) in the X-axis of free jet gas flame [32]

These data measured from gas potentiometry enable the calculation of important flame parameters such as mixing and the degree of burn out. A turbulence GOP allows the detection of the frequency distribution of Ueq and the bales of gas–fuel and air for a specific position in the flame. Figure 4.16 demonstrates a possible flame eddy and the corresponding signal of the GOP. The temporary resolution of the cell voltage gives the flame eddy structure. The previously mentioned correlation between burnt-out of the gas fuel and the value of the cell voltage is applied here too. Any passages at the point of inflection between −300 and −400 mV correspond to the flame front that separates reductive and oxidative structure elements from one another. The quantity of such flame front is an expression of the intensity of the combustion. Figure 4.17 graphically demonstrates the theoretical cell voltage curve of a gradient sensor for the flame structure element shown in Fig. 4.16. Here, peaks instead of points of inflection indicate the flame fronts. Figure 4.18 relates the cell voltage–time curve of a regular and a gradient sensor recorded near the tip of a free-burnt jet flame. It can be easily derived that, the temporal correlation between the various peaks of both curves and the improved gradient sensor resolution was due to its minimized geometry. Identical investigations have been carried out on oil flames using an adapted GOP [33]. Figure 4.19 demonstrates the contour of the sharply twisted flame of a commercial oil burner. Even under complex circumstances of high boiling and cyclic hydrocarbon sprays, parameters like degree of mixing, burnt-out, and contour can be determined with the help of the GOP.

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Fig. 4.16 A Cell voltage–time curve and a possible flame eddy structure [32]

4.3.2.2

Online Measurement (Off-Flame) Gas Potentiometry Measurement

In an off-flame (on-line) gas potentiometry measurement set-up, the gas is sampled by silica glass suction probe positioned in the flame. The sampled gas is then quickly conveyed into the measuring chamber of a gas potentiometric flow measuring cell through a tempered gas duct. The silica glass tube is installed by a sensor of the solid electrolyte tube cell, while the external electrode is purged with air and the sample gas to be measured from the flame is purged into the internal electrode. Figure 4.20

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Fig. 4.17 Theoretical cell voltage curve of a gradient sensor for the structure in Fig. 4.16 [32]

Fig. 4.18 Cell voltage–time curves measured by a regular (a) and a gradient sensor (b) near the tip of the jet flame [32]

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Fig. 4.19 Outline of an oil flame studied with a GOP [32]

is an illustration of the special GOP with the solid tube closed on one side, used for gas potentiometric titrations of gas fuel with air. The precise determination of air required for the gas fuel enables the burner to be set appropriately. The experimental gas potentiometric flame analysis described here has proven the test of model flame in the combustion chamber and the influence of gravity on the formation of hydrogen diffusion flame under microgravity conditions [34].

Fig. 4.20 Schematic diagram of a gas potentiometric titration measuring cell [34]

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4.3.3 Analysis and Characterization of Solid Fuel Conversion Recent investigations involve the technical application of the GOP in combustion facilities for large-scale power generation [32]. The measurements are done with different solid fuels in a lab-scale fluidized bed reactor. Figure 4.21 shows a complete experimental setup of a lab-scale fluidized bed reactor for combined gas potentiometric combustion analysis and on-line gas analysis. Solid fuels such as coal fuel [35], biofuel are combusted and gasified to produce power and high calorific gases like fuel gas, reduction, and synthesis gas [36]. Combustion processes mainly operate with a defined oxygen/air excess (oxygen ratio λ > 1), while gasification processes are marked by the presence of reducing conditions (λ < 1). Optimum control process requires a detailed knowledge of the gasification and combustion characteristics of solid fuel, where they can be described by in-situ measurements of the redox ratio present in the reaction zone using GOP.

Fig. 4.21 A complete experimental setup of a lab-scale fluidized bed reactor for combined gas potentiometric combustion analysis and on-line gas analysis [32]

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Gas Potentiometric Measurements in Combustion and Gasification Chambers

The equilibrium cell voltage at a given reactor and sensor temperature, measured under combustion and gasification conditions will reflect the redox ratios inside the combustion chamber. Figure 4.22 demonstrates the gas potentiometric measured values of the equilibrium cell voltage and correlated gas concentrations as a function of air–fuel ratio [32]. A combustion curve is obtained as a function of fuel–air ratio that corresponds to the principle of a titration curve of coal with air. Flame gas analogous, the clearly distinguishable regions with high cell voltage values between 600 to 800 mV (λ < 1) can be assigned to the water–gas region (lUeq l > 350 mV), whereas the low cell voltage values below 50 mV (λ > 1) can be assigned to the exhaust gas–air region (lUeq l < 350 mV). The equilibrium point (λ = 1, lUeq = 350 mV) represents the stoichiometric conditions between fuel and air. Water–gas equilibrium occur at the water–gas region and the increase in hydrocarbons indicates the rise in the fuel gas fraction.

Fig. 4.22 GOP signals interpretation. A relationship between cell voltage and correlated gas composition as a function of the air ratio (l) at a mean temperature of 850 ◦ C for the laboratory-scale fluidized bed reactor [32]

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Burnout Characteristics of Solid Fuels, Biofuels, and Waste Materials Under Combustion and Gasification Conditions

The burnout characteristics are premediated with the help of experiments. For the study of this, a solid sample can be put into the gasification reactor while a GOP directly positioned in the reaction chamber through a specific oxygen conversion tracks the burnout. Examples of GOPs are demonstrated in Fig. 4.23. The experimental instrument here is fluidized and field bed reactors. The relation between equilibrium cell voltage and redox ratios in the combustion chamber facilitates a better understanding of the sensor signal curves. The burnout curves are obtained by specific cell voltage as well as oxygen concentration–time curves, which specifically reflect the solid burnout behavior. In the figure, there are burnout curves of various ranges of fuels and waste materials. The burnout method is indicated by a fall in oxygen level and initiated by the ignition of the sample, also it ends when oxygen in the fluidized bed is utilized. This time is called combustion time termed as tb it can also be measured from the burnout curves and called burnout rate. There are two peaks, gas peak of coal, biomass and, waste material describes the release, burning, and ignition of volatile matter. The char combustion is affected by the volatile matter in terms of the fraction and composition of the remaining char. In the case of brown coal, biofuel, and waste material, there are notable char combustion and volatile stages (of semi-anthracite and bituminous coal), and both processes occur at the same time. Redox rapid change can refer to oscillations measurement in the concentration of oxygen. High measurement dynamics make them measurable (Fig. 4.24). Fuels of the same kind can be compared and evaluated depending upon differences in the gas potentiometrically measured burn-out [7, 34, 38]. In situ measurements moreover help homogeneous and heterogeneous processes of solid materials thoroughly. The heating, drying, igniting, and burning of the matter specifically volatile matter can be distinguished with the quantitative analysis duration. The gas potentiometric analysis of gasification of solids under the combustion provides fuel-specific burn-out gasification curves as a function of the gasification

Fig. 4.23 The burn-out behavior of solid fuels in a a fluidized-bed reactor and b a fixed-bed reactor along with a gas potentiometric oxygen probe (positioned directly in the fluidized bed and just below the grate, respectively) [37]

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Fig. 4.24 Burn-out curves of various fossil fuels, biofuels, and waste materials on a lab-scale fluidized-bed reactor [7]

agent employed with the specific fuels having specific behaviors. The impact of solid fuel characteristics can be distinguished from curves [7]. Examples of measured cell voltage-time curves for the gasification of brown coal coke with air, CO2 /water vapor, and miscellaneous CO2 water vapor mixtures are demonstrated in Fig. 4.25. In the graphical demonstration, various samples were used to construct the ratios of fuel gasification. There is a clear conversion upon fuel charge. The steep is elevated in the cell voltage to the higher value, which indicates that the conversion begins. Afterward, diverse voltage levels are achieved that further aid in characterizing the oxygen partial pressure. When the amount of sample rises in the process of air gasification, combustion conditions and then subsequently, gasification conditions are detected. The stable cell sloping varies between 600 to 800 mV. The aforementioned information specifies steady-state conditions with consistent particular gas composition and quality. Hence GOP is monitored as a quality monitoring technical process [9]. Cell voltage and redox ratios in the reaction process seem to determine gasification time and to characterize the mean conversion rate. In contrast to the gasification medium working, the rate of adaptation falls from air to CO2 and water vapor as demonstrated in Fig. 4.25 a–c [39].

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Fig. 4.25 Voltage–time curves for the conversion of different sample quantities of brown coal coke with different gasification agents in a lab-scale fluidized-bed reactor [39]

4.3.3.3

Gas Potentiometric Combustion and Gasification Analysis: Burnout Characteristics and Fuel-Specific Makrokinetic Parameters

The burnout characteristics of solid fuel can be measured by alternative effective methods named gas potentiometric combustion analysis (GPCA) and gas potentiometric gasification analysis (GPGA) [40]. The behavior of solid fuel burns out is attained in the form of curves. As well as quantitative and qualitative measurement, burn-out course portrayal suitable models also consent makrokinetic parameters can be determined. These parameters appear to be effective reaction rate constant shortly Keff (a reactivity parameter) and the apparent activation energy abbreviated as AE. Keff values are mainly influenced by certain reaction conditions. Results and details of the performance of GPCA are summarized in Table 4.2. The burnout curves are attained for brown coal combustion, bituminous coal, and a 1:1 mixture of both are shown in Fig. 4.26. The combustion time and Keff values to evaluate reactivity are also indicated in Fig. 4.26. The burnout behavior can be improved by adding considerably more reactive brown coal. Mixed combustion helps to find the mixing ratios. Firing operations can be rapidly adjusted to modify fuel quality.

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Table 4.2 Results of the gas potentiometric combustion analysis (GPCA) [7] Potential information

Results

Burn-out curve Qualitative and quantitative information of the course of burn-out (devolatilization, char combustion, residual char burn-out = burn-out of the “remaining 5 wt%”) Combustion time

Residence time for complete burn-out of the fuel, mean combustion rate

Effective reaction rate constant

Mean combustion rate, information on heat release per time unit, input parameters in combustion models

Relative reactivity

Comparison of combustion rates of different fuels

Activation energy

Temperature dependence of the combustion rate, makro-kinetics of the overall process

Fig. 4.26 Co-combustion utilizing gas potentiometric combustion analysis (fluidized bed, 850 ◦ C, 0.1 g sample) [7, 39]

4.3.3.4

Modeling to Determine Fuel-Specific Makrokinetic Parameters

The models of applied gas were established following the measured burnout curve with a simple microkinetic tactic to measure an effective rate of reaction. They are based only on cell voltage time, their curves, and measured gas potentiometrically as for converted gas phase and different from particle-based combustion models. The actual rate of reaction constant is acquired elaborates the burnout process under the reaction specificities and also affects the mass transfer as well as the chemical kinetics. Technically, the combustion model’s gasification varies to determine the partial pressure of the reactant gas. Here the GOP signal specifies the converted quan-

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tity of oxygen for combustion. The redox ratios resulted under gasification conditions allow the gasification gradation agents partial pressure. This partial pressure is then applied by the cell voltage equation validates the present equilibria [8].

4.3.3.5

Resume

The flawless measurements of redox ratios in the reaction zone can be presented by using GOP, it is also applied to examine the complex homogeneous and heterogeneous method that happens in the combustion and gasification of solid matter. Regardless of the scale, appropriately the GOPs allow for diagnostics of reaction equipment typically used for the solid-gas conversion. Without any time lag and high degree chronological, the association between equilibrium cell voltage and redox ratios in the reaction zone enables the quantitative description of the combustion and gasification processes unceasingly. GPCA as well as GPGA have proven their values as another possibility that efficiently characterize the burnout behavior of any solid fuels under practical conditions.

4.3.4 Applications with Potential for Development The applications of GOP can be executed in many spheres of energy industries based on their wide range of oxygen concentrations from oxidizing to reducing atmosphere (100 vol% to 10–20 vol%). The classification of GOP application is provided by the synthesis process of gas production, on each step of use of GOP improvement, in situ monitoring is plausible which is named as fuel gas generation, cleaning conditioning, and utilization of gas. Likewise, GOPs denote a convenient measuring device for rapid adjustment and regulation of fuel and the oxidizing agent rations when the concentrations of gases are quickly transformed.

4.3.4.1

The Performance of a Velocity-Oxygen Probe

The combination of high temperature (HTA) and GOP is represented by the velocity oxygen probe (VOP) in Fig. 4.27. VOP is a cohesive probe for the measurement of gas velocity and oxygen content in a solid fuel kiln environment [41]. The demonstrations of the biomass-fired system have the level of reliability and receptiveness to enable the VOP to take part to further enhance the control of kiln or boiler operation in Fig. 4.28 [42]. An example of VOP displayed the aptitude for measurement at inset depth up to 5 m, which can cover the geometry of large industrial-scale kilns. The air of the aerostatic bearing in the figure acts as the reference gas of the oxygen sensor [43]. The attribute of the design is including the temperature up to 1400 ◦ C, the active system with loads of gas, possible measurements are carried in non-transparent flames [44].

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Fig. 4.27 Velocity-oxygen probe. a Schematic cross-section; b After application in a biomass fired boiler [41]

Fig. 4.28 Short-term variation for velocity, temperatures, and oxygen content obtained in a run of a 500 kWth pulsating combustor [42]

4.3.4.2

Measurement of Fluid Dynamics in a Fluidized Bed Reactor

GOP measurement systems are complementary for charting dynamic processes as in fluidized beds, which can relate to the short response time of sensors in irregular oxidizing and reducing atmospheres. Now electrodes can detect the oscillations in gas quality in real-time. This allows that a cross-association can be applied to find out the time difference (t ¼ t) e among electrode oscillating signals when two resembling electrodes are positioned lengthwise for flow direction as in Fig. 4.29. 1 1,2 (τ, T ) = T

+T  /2

U1 (t)U2 (t + τ )dt

(4.6)

t=2T /2

Once the structural spacing(s) is known, the velocity can be attained (v ¼ s t1). When multiple sensors are wrapped up in the fluidized bed longitudinally to flow direction, the bubble velocity can be determined [46]. The analysis is applied to the

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Fig. 4.29 Multiple-sensor GOP (a) and its placement in a fluidized-bed reactor [45]

single bubbles or means over a longer period have cross-correlation. In Fig. 4.30, there are examples of signal curves of electrodes with a left upper panel, left middle panel, and analysis is performed manually with a left lower panel with cross-association called right panel.

Fig. 4.30 Measurement of bubble velocity during coke combustion in a fluidized-bed reactor [9]

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Fig. 4.31 a Gas potentiometric oxygen probe (GOP) placement in a fluidized-bed reactor; b GOP signals from alternating combustion (step 1), gasification (step 2), and burn-off (step 3) [9]

4.3.4.3

Feed Control in Solid Fuel Gasification

GOP can be used as a source to measure and control the fuel-to-air ratio in a reactor chamber. To measure that, the GOP position is selected such that it is closer to the conversion section. By means of that, fuel gas after the gas–solid reaction contacts the GOP. The signals are demonstrated in Fig. 4.31. During step 1, biomass combustion is repeated to gasification which is step 2. As seen in Fig. 4.31, the first signal peak specifies a change to gasification from combustion and successive bed burn off (step 3). Complete burn-off is followed by a return to gasification (step 2). When the produced gas passes the GOP sensor, a cell voltage is generated according to the composition of the gas. The GOP signal is used to find the redox ratios by applying a valid cell voltage equation [47] as in Table 4.3. The attained ratio is then compared to a set value. If there is variance presence, there is a difference between both measured and set values. The input flux of solid fuel and gasification agent is settled in such a way that measured and set values of redox ratio to become equal to achieve the desired fuel gas atmosphere in the reactor as in Fig. 4.32.

4.3.4.4

O2 Concentration Distribution in a Fluidized Bed Membrane Reactor

The instrumental arrangement is known as the fluidized-bed membrane reactor (FLBMR) in Fig. 4.33. During partial oxidation of hydrocarbons, a persistent and equal oxidizing medium dosage is preconditioned [48]. Promising results are obtained when the secondary gas is applied to the primary gas through porous membrane tubes arrange orderly inside the reactor. The advantages of the equal gas sector are highest when optimal fluid dynamic in FLMBR is attained.

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Table 4.3 The redox ratios by applying a valid cell voltage equation [47] Measuring gas atmosphere

Reaction equilibrium

Cell voltage equation U eq [mV]

H2 O, H2

H2 O ↔ H2 + 1/ 2O2

eq = −1290 + mV p

0.326 + 0.0992. lg pHH2 O − 0.0496. lg p ·

U

2

CO2 , CO

H2 O, CO2 , H2 , CO

CO2 ↔ CO + 1/ 2O2

U

eq = −1458 + mV p

2 0.481 + 0.0992. lg pCO − 0.0496. lg p · CO

T K

CO + H2 O ↔ CO2 Ueq = −1374 + mV p p

+ H2 CO2 0.403 + 0.0496. lg HpH2 O PCO − 0.0496. lg p · 2

H2 O, CO2 , H2 , CO, C(s)

T K

C(s) + H2 O ↔ CO + H2

T K

U

eq = −911.4 + mV p p

−0.1626 + 0.0496. lg H2pOH CO − 0.0496. lg p · 2

H2 O, CO2 , H2 , CO, C(s) , CH4

CH4 + H2 O ↔ Co + 3H2

U

eq = −1080.5 + mV 5

 p pCO 0.1937 + 0.0166. lg pH2 O p3 − 0.0496. lg p · CH4 H 2

Fig. 4.32 A gas potentiometric oxygen probe control loop

T K

T K

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Fig. 4.33 Schematic cross-sections of a fluidized-bed membrane reactor FLBMR (a, b), and a set of membranes (c) [47]

The measurements were performed with five folded sensor GOPs in such positions that were lined (p1–p5) at three different levels (L1–L3) in Fig. 4.34 along with the height of the reactor [49].

Fig. 4.34 a Five folded gas potentiometric oxygen probe (GOP) sensor; b Schematic of the GOP positioning [49]

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Fig. 4.35 O2 concentration profiles as a result of admixing O2 through membranes (air flow ¼ 80 l min−1 ) into an N2 flow (40 l min−1 ) of plug-flow mode (a) and fluidized-bed mode (b), measured with a gas potentiometric oxygen probe [8]

To measure the distribution of oxygen, nitrogen was streamed from sintered metal distribution plate, while other four sintered membrane tubes through which air could be introduced were arranged proportionally in the reactor. These experiments were to test the steadiness and mixing properties of membrane tubes in addition to sintered metal distribution plate in the fluidized bed and plug-flow mode. There was a homogeneous gas concentration in fluidized bed mode rather than plug flow mode, but asymmetric oxygen was detected in plant arrangements as shown in Fig. 4.35 [50].

4.4 Outlook Conventional applications of oxygen gas potentiometry, such as exhaust gas probe and lambda oxygen sensors in vehicles and furnaces will be widely functional on an industrial scale in the near future. Moreover, in situ monitoring technical components with fuel gas atmospheres, GOP grasps extensive potential as a measuring instrument. Further GOP developments include a reduction in the temperature of GOP operation and produce longterm stability. The continuous air purging would enhance freedom degree in designs. Such developments will surely lead the GOP applications approach to engineering research. These current research investigations further target the developing methods of gas potentiometric analysis to find the combustion and gasification characteristics of fuels with high volatile matter fraction such as biomass.

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4.5 Conclusion Gas potentiometry is a reputable diagnostic procedure in combustion engineering. A GPOs in-situ measurement can provide detailed information on the development of conversion and on the gas composition of oxidizing and reducing atmospheres as well. This piece of information makes GOP a practicable instrument to analyze the thermochemical conversion of fuel gas (combustion reforming) and solids (combustion gasification) in engineering research according to the extensive range of design and material to add control and monitor combustion plant systems and components in industrial applications. More predictions in the further developments will enhance the applications of GOPs as a fast, cost-friendly, and easy to use the instrument in combustion engineering.

4.6 Exercises (1) Individual task: Find a research paper illustrating the recent applications of gas potentiometry across different fields. (2) Group task: In small groups, find a literature article and make a presentation on various potential applications of gas potentiometry in combustion chemistry.

4.7 Questions (1) Draw and explain the Physico-chemical measuring principle of gas potentiometry. (2) State techniques that are used to detect highly sensitive single atoms and molecules in the reaction zone. (3) Which criteria are used for determining O2 concentrations using solid electrolytes? (4) Describe the factors that influence the overall performance of the GOP sensor. (5) What is the importance of thermocouples in gas potentiometry? (6) Why are gas potentiometric oxygen probes designed with baffle plates? (7) How is the equilibrium achieved in GOPs? (8) Describe the cell voltage sensor signals produced in different positions of a free jet flame, and explain the importance of the Nernst equation (Ueq ). (9) With the help of a schematic diagram, explain the measurement of off-flame using GOP. (10) Describe the importance of GOP in combustion engineering.

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27. Currie, J. et al. (1999). Micromachined thin film solid state electrochemical CO2 , NO2 and SO2 gas sensors, 59(2–3), 235–241. 28. Shuk, P., et al. (2008). Zirconia oxygen sensor for the process application: State-of-the-art., 90, 174–184. 29. Hartung, R. (1996). On the analysis of CO2 , H2 and CO, H2 -mixtures by water-gas potentiometry with solid electrolyte cells, 356(3), 228–232. 30. Bode, M., et al. (1992). On-line failure detection for potentiometric solid-electrolyte oxygen gas sensors, 7(1–3), 733–737. 31. Lorenz, H. et al. (1997). Characterisation of fuel burnout with the aid of sensor techniques; Charakterisierung des Abbrandverhaltens von Brennstoffen mit Hilfe von Sensormesstechniken. 32. Lorenz, H., et al. (1996). Gas-potentiometric method with solid electrolyte oxygen sensors for the investigation of combustion, 356(3), 215–220. 33. Schwartz, W., & Rau, H. (1980). Zur Messung des Ausbrandverlaufs in Ölflammen mit einer gaspotentiometrischen Meßsonde, 29, 83–84. 34. Tittmann, K., et al. (1996). Hydrogen diffusion flames under microgravity, 9(1), 40–45. 35. Prawisudha, P., et al. (2012). Coal alternative fuel production from municipal solid wastes employing hydrothermal treatment, 90(1), 298–304. 36. Gan, Y. Y., et al. (2019). Torrefaction of de-oiled Jatropha seed kernel biomass for solid fuel production, 170, 367–374. 37. Scallan, P. (2003). Process planning: the design/manufacture interface. Elsevier. 38. Knauth, P., & Tuller, H. L. J. (2002). Solid-state ionics: roots, status, and future prospects, 85(7), 1654–1680. 39. Schotte, E. (2003). Untersuchungen zur Vergasung und Verbrennung von Kohlen und Biomassen unter Anwendung der Gaspotentiometrie mit Sauerstoff-Festelektrolyt-Sonden. 40. Lorenz, H. et al. (1998). Investigation of combustion and characterization of solid fuels by means of the gas-potentiometric method. 41. Zimmel, M., et al. (2001). Simultaneous measurement of local gas velocity and oxygen concentration in combustion systems, 24(10), 1009–1012. 42. Rath, J., et al. (2002). Measurement of gas-velocity in a large coal burner test rig. Paper presented at the 6th European Conf. on Industrial Furnaces and Boilers. 43. Aravind, P., et al. (2012). Evaluation of high temperature gas cleaning options for biomass gasification product gas for solid oxide fuel cells, 38(6), 737–764. 44. Radhakrishnan, R. et al. (2005). Design, fabrication and characterization of a miniaturized series-connected potentiometric oxygen sensor, 105(2), 312–321. 45. Makkawi, Y., & Wright, P. (2002). Fluidization regimes in a conventional fluidized bed characterized by means of electrical capacitance tomography, 57(13), 2411–2437. 46. De Jong, W., & van Ommen, J. (2009). Scale-up in fluidized bed biomass combustion. 47. Andres, M.-B., et al. (2011). In-situ CO2 capture in a pilot-scale fluidized-bed membrane reformer for ultra-pure hydrogen production, 36(6), 4038–4055. 48. Leckner, B. (2013). Atmospheric (non-circulating) fluidized bed (FB) combustion. In Fluidized bed Technologies for near-zero Emission Combustion and Gasification (pp. 641–668): Elsevier. 49. Smart, S. et al. (2013). Porous ceramic membranes for membrane reactors. In Handbook of Membrane Reactors (pp. 298–336): Elsevier. 50. Nwogu, N. et al. (2015). Gas permeation behaviour of single and mixed gas components using an asymmetric ceramic membrane, 9(6).

Chapter 5

Raman Scattering Diagnostics Vestince Balidi Mbayachi, Zhen-Yu Tian, Zhi-Min Wang, Maria Khalil, and Daniel A. Ayejoto

5.1 Introduction The practical combustion system entails high power density to decrease the physical size as well as the mass of the system. Gas turbine engines in aircraft attained some of the chief power densities of the practical combustion system, concluding the settled utilization of fundamental principles firstly, vigorous or turbulent mixing to lower the effective fuel as well as airflow mixing time and secondly, an elevated temperature to decrease both the chemical reaction time and size of the combustion chamber. In Fig. 5.1, there are illustrations of the interaction of turbulent flow, radiation, and chemical reactions, creating turbulent combustion, and methods that give relevant information about these effects as well. To cross-examine the non-insensitive species with chemical concentrations and temperature. Some optical diagnostics techniques can operate appropriately at high pressure, these are necessary to use in the system while at the same time the high resolution in length and time. The claim for the numerous chemical species and information of temperature with tolerable sequential and longitudinal single laser resolution, more importantly, only V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China e-mail: [email protected]; [email protected] V. B. Mbayachi · Z.-Y. Tian (B) · Z.-M. Wang · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China e-mail: [email protected] Z.-Y. Tian · Z.-M. Wang Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_5

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Fig. 5.1 An interaction of turbulent flow, radiation, and chemical reactions creating turbulent combustion, and methods that give relevant information about these effects [1]

leaves a single methodical approach which is named an excited spontaneous Raman Scattering (SRS) spectroscopy [2]. SRS signals are not sensitive to the thermal beamsteering effect, and these are challenging for nonlinear optical-grating methods for instance Degenerate four-wave mixing or (DFWM) Coherent anti-strokes Raman scattering (CARS). It is also not sensitive to the collisional quenching effect as encountered using laser-induced fluorescence (LIF). Collisional quenching scales linearly with pressure when the gas composition is not changed; nevertheless, the gas composition and the quenching cross-sections are temperature-dependent in Fig. 5.2. For flame diagnostics, SRS can provide an important advantage to require a single port of optical access in the case of back-scattering collection mode. However, there

Fig. 5.2 Temperature-dependence of the NO-LIF quenching rates in equilibrium burnt gases at fuel/air ratios from 0.8 to 1.3 at 10 bar [4]

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is a beneficial approach when the number of optical windows is kept to a minimum level. As in opposition to CARS or LIF, SRS is the linear optical method, and the measurements are simple, versatile, and costly. SRS makes signal levels available that scale linearly with high pressure and higher signals for high-pressure combustion studies [3]. Therefore, there is transformed interest in basic studies on SRS in highpressure diagnostic combustion studies. The high-pressure burner is illustrated in Fig. 5.3. High-pressure flames were established by following the procedure (1) the flame was ignited at 1 bar by the igniter, (2) N2 shielding gas was attuned and the CH4 flow rate was matched air mixture exit velocity, (3) the flow rate of compressed gas can also be elevated, and the needle valve on its top was adjusted to change the pressure slowly [5]. Lately, there is quantitative data for validating the computational model of high-pressure turbulent combustion. The basic theory governs the signal intensity after that SRS apparatus following the development of state of the art in SRS system is concluded in this chapter.

5.2 Theory of SRS Signal Estimation The SRS is used as an analytical technique for time-resolved gas-phase measurement in solids as well as Raman scattering. Nevertheless, as a time-resolved diagnostic, their applications in SRS seem more reasonable. With the use of continuouswave (CW) lasers and optoelectronic detectors, for instance, photomultiplier tubes (PMTs) and charge coupled devices (CCD), hence the SRS time-resolved gas-phase diagnostic is more apparent as a practical option. It is shown in the figure that the cross-sectional Raman scattering for a gas molecule is weak [6] as in Fig. 5.4. Mainly, the idea drives the SRS design apparatus that can generate, collect, and detect lots of Raman-scattering signal photons. Designing an SRS system, it will allow to collection of an enormous number of photon signals for high-quality data. It is also important to approximate the signal level for design and component selection through the process called signal estimation. In Fig. 5.5, there is decomposition of the signal to components related to mean and random noise fluctuations. The most important consequence of the loss of detail is the difficulty that ascends in the precise determination of the circumstantial light level. From the authors’ experience, a state-of-the-art SRS system utilizing about 700 mJ of 532 nm laser energy per pulse, f/2 collection optics with a high optical in Fig. 5.6, there are single-cycled images obtained under low gas density.

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Fig. 5.3 High-pressure burner [5]

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Fig. 5.4 Raman scattering cross-section for gas molecules [6]

Fig. 5.5 Decomposition of the measured signal into components associated with the mean signal, signal, and random noise fluctuations [7]

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Fig. 5.6 Sample single-cycle image obtained under conditions of low gas density or fouled beam [7] entrance and exit windows

5.3 Current Status in Multiscale Diagnostics Several reviews have specified the ability to attain a widespread set of multiscale measurements on combustion systems that provide necessary information on turbulent flame modeling and new concepts. Applications in practical research combustors use characteristically more realistic burner configurations and operational conditions, prominently high pressure: 1. In new practical combustion systems, there is a highly turbulent atmosphere for faster mixing, for instance, swirl stabilization conformations that are found in aeronautics. 2. This requires spatial and temporal diagnostic resolution. 3. Along with this, a larger examination zone is required for the large-scale flame structure. Real-world systems function under higher pressures which also necessitates studies to be conducted at high pressures. Tactlessly, the pressurization requirement forces the diagnostic technique to have optical access, the reason is the inadequate aperture and/or the limited number of windows and optical access ports. For this very reason, the instantaneous multiple laser techniques application that requires multiple beams and multidirectional signal collection is not viable. By the same token, the use of Rayleigh scattering diagnostics in pressurized systems is difficult and less practical, because complete elimination of stray background light at the excitation wavelength is caused by scattering from the optical windows and the combustion rig walls, is almost impossible to achieve in practice. On the other hand, one strong advantage of these experiments is a linear increase of the SRS signals with pressure increase, as a result, this results in a higher signal-to-noise ratio (SNR). Enhanced SNRs can make improvements in both single-point scalar measurements, and may even enable 1D SRS line-imaging with an acceptable level of precision [9]. In Fig. 5.7, there is a traditional multi-tube burner nozzle providing a quasipremixed flame at high pressures. Mostly combustion systems utilizing complex hydrocarbon fuels including liquid fuel droplets, oxidizer air, and fuel vapor are

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Fig. 5.7 Schematic illustration of multi-tube burner nozzle providing a quasi-premixed flame at high pressures. (cross-sectional diagram), Units are in inches [8] under high pressure, the practical system requires study conduction at increased pressures

Fig. 5.8 Liner thermal images and paint stripe orientation [10]

involved. The multiphase fluid flow and integral chemical reactions make the combustion different from the gaseous-state combustion. This fact leaves the study of gaseous simple hydrocarbon-fueled (H2 , CH4 , and C3 H8 , etc.). Figure 5.8 shows representative liner temperature measurements and the paint stripe orientation. prominently, any laser diagnostic that includes SRS spectroscopy must face phase difference measurement discriminations providing enormous precision for gas-phase measurements [10]. Due to the limitations mentioned, it is meaningful to continue the advanced SRS- multiscale diagnostics in a simpler form.

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5.4 Designing and Building an SRS System 5.4.1 Excitation System 5.4.1.1

Laser Source

There are two choices for the excitation wavelength in laser Raman-based multiscale diagnostics known as ultraviolet (UV). Among a few choices, it is noted that the second harmonic of the Q-switched (QS) Nd: YAG pulsed laser at 532 nm (2*:Nd: YAG) is the most popular for an excitation source, mainly because it provides a consistent and appropriate source of high-energy pulsed excitation with typical pulse energies in the 1 J range. The Raman-shifted signals lie in the detector spectral regions with a high quantum efficiency; there is a comparatively low level of optical background emissions from PAHs in Fig. 5.9 and the data is listed in Table 5.1 [11] and its alignment in a visible wavelength is easy. A flashlamp dye laser used at 489 nm represents the choice of the visible laser that provides to some extent an elevated Raman cross-section. There is a need for positions of Stokes shifted Raman lines and anti-stokes shifted N2 comparative to C2 LIF interventions [12]. UV multiscalar measurements utilized an image-magnified CCD camera rather than high-speed mechanical shutter gating [13]. The experimental drawing is shown in Fig. 5.10.

5.4.1.2

Pulse Stretching

To avoid the laser-induced sparking along with the volume probe as well as to further avoid the damage in the excitation scheme, a means of laser pulse stretching must be applied. For this very purpose, external ring-cavity systems are regulated as costeffective and efficient pulse stretching sources are used [14, 15]. The arrangement of a pulse stretcher with three beam splitters that form three-ring cavities within the system is shown in Fig. 5.11. A stable pulse stretcher is decorated with the combination of fused silica substrate optics with the coating of multilayer dielectrics as illustrated in Fig. 5.11, for high power pulsed lasers, as well as fixed-height kinematic mechanical optic bases which provide a stable base for widespread pulse stretcher. Moreover, larger optics allowed for larger beam sizes resulted because of beam spread captured [17]. The effective alignment of the pulse stretcher depends upon the following tips to ensure (1) all beams in the pulse stretcher should propagate in coplanar fashion with the optical table, (2) the beam propagates into the ring cavity and exiting from it is as close to a 90° merging angle as possible. The constant beam height can be checked by using a fixed-height mount iris that can be moved around anywhere on the optical table as a height gage. In Fig. 5.12, misalignment of the beam splitters comparative to the external beams would show on a target placed at the exit of each cavity. Most significantly, all cavities

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Fig. 5.9 Schematic drawing of the experimental arrangement

Table 5.1 Equilibrium mole fractions of exhaust gas of C2H4/air flame [11] φ

N2

CO

CO2

H2

H2 O

1.58

0.641

0.133

0.047

0.064

0.114

1.92

0.595

0.174

0.029

0.118

0.085

2.00

0.585

0.182

0.026

0.130

0.077

2.07

0.577

0.188

0.024

0.140

0.071

formed in the cavity that are being examined should be impassable to segregate the misalignment limitation during this method. Double-pulse 2 × :Nd: YAG lasers are designed mainly for elementary image velocimetry (PIV) and with an internal pulse delay generator it’s also been shown to characterize a valued substitute [18] as pulse stretchers. A long-cavity 100 ns pulse Nd: YAG laser accommodating a

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Fig. 5.10 Experimental setup for line-imaged Raman scattering measurements in a laminar CH4 / air jet flame. The shutter assembly is mounted in place of the entrance slit of the spectrograph, the mechanical layout of the shutter [13]

Fig. 5.11 Schematic of a high-performance Raman scattering apparatus. RC = rotary chopper; LS = leaf shutter [16]

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Fig. 5.12 Sketch of a pulse stretcher alignment. The beam spot of each pulse on a target shows a degree of alignment of each cavity. Pulses traveling a longer distance due to repeated circulation round-trips within a cavity show more divergence (larger spots) [16]

multiple traverse mirror system within the laser oscillator is also called a white cell, has recently been proposed in practice as the excitation source of single-shot Raman measurements [19].

5.4.1.3

Probe Volume

A lens with a focal length of 700–1000 mm is preferred for forwarding beam focusing. And the shorter focal-length lenses provide a smaller probe volume but it has a higher hazard of producing spurs at the waist of the beam. The probe volume energy can also be creased by back-propagating the laser beam. There is a procedure for checking the alignment of the return beam through the probe volume with a pinhole, which is usually created from a thin metal plate in Fig. 5.13 where a beam-size hole is pierced by the focused laser pulse. On the other hand, a precise alignment jig can be laboring with the numbers of drilled holes at various heights above the burner surface. Configuration of the return beam is attained vertically by the vertical tilt pivotal movement of the right-angle prism, also by translating the prism horizontally to place the return beam directly on the forward beam at a pinhole location. For measurements in practical combustors, crossing the appearance or sector is not possible, and accordingly, the probe volume and collection optics must be traversed. Due to the limitations around a combustion rig, this is depending on the physical limitations around a combustion rig, this can be a stimulating task when the beam back-propagation optics is also involved in it. Several preparations can be used to contrivance this type of traversing. An example is to have all forwardand back-propagating laser optics, that include the beam dump, which is such a position fixed in relative to each other, either through mechanical means or by an electronically harmonized solid-body motion by the use of programmable digitally controlled precision traversing stages [16].

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Fig. 5.13 Sketch of a return beam alignment jig using a pin hole [16]

Figure 5.14 shows how it can be attained, where the laser-transmitting optics traverse in axial (vertical or Z) and radial (horizontal or X) directions as a whole, while the collection optics would be independently traversed horizontally (X direction), but synchronized vertically (Z direction) with the laser optics. For a comparatively short distance along the X-direction, the intensive beam deviation from the probe volume is not significant, and this allows the collecting optics to be traversed to a limited degree along the radial direction while keeping the laser beam dissemination optics stationary along the horizontal direction. Concerning the SRS-probe volume size, typically a size of 0.2–1 mm diameter and 0.5–2 mm length (along the beam-propagating direction) is estimated under the excitation laser beam diameter after the pulse stretcher and the focal length and position of the forward focusing lens. Of course, the SRS-probe control volume is elaborated by the intersection of the beam diameter and its perpendicular image as defined by the collection of optic aperture assembly, the scattering is observed at a right angle to the beam propagation direction. The laser probe volume alignment and the collection lens can be checked by a pinhole alignment jig (similar to that previously described) that is fixed in height and crosswise position above the burner and also free to rotate about the vertical axis to allow both the laser and collection optics to be checked successively. This can be achieved by projecting the backpropagated fiber-coupled diode laser beam onto the probe volume through the collection lens. This mechanical alignment step is a trick of the trade which is categorically critical to the rapid optimization of the SRS system. When provided with holes at various known heights, this alignment jig also allows the vertical traverse system to be confirmed for exactness [16].

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Fig. 5.14 Sketch of a 2D (X–Z) traverse system with three separated translating motions. The top periscope mirror, two lenses, prism, and beam dump are mounted on an optical rail [16]

5.4.2 Spectroscopy System 5.4.2.1

Scattering Collection

When light is scattered it can either be collected by achromatic lens or a reflective optic such as a Cassegrain mirror lens. To optimize the collection solid angle, the collection lens should have a large aperture. The efficient aperture may be constrained by the window size in many practical uses, so standard 35 mm format camera lenses, such as the famous 85 mm f/1.4 type, are commonly used due to their excellent image performance and increased optical output. Direct free-space pairing with a spectrometer entrance (slit) is widely used in systems where size is not a problem and the burner is small enough to pass through. An example of which the scattering problem has been solved is shown in Fig. 5.15. For spherical particles with diameters ranging from 20 to 900 nm and wavelengths ranging from 400 to 800 nm, a composite graph of the spectroscopic dependence of the differential scattering coefficient σs p(θ ) vs. inverse size parameter 1/x is shown in Fig. 5.1. The three lines indicate the following combinations of relative index of refraction m and scattering angle θ : m = 1.06 and θ =1800 (solid curve); m = 1.06 and θ =1550 (dashed curve); m = 1.04 and θ =1800 (dotted curve). The slope of the Rayleigh scattering is shown by the straight dotted line, which is relative to λ−4 [20].

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Fig. 5.15 A composite graph of the spectroscopic dependence of the differential scattering coefficient σs p(θ) versus inverse size parameter 1/x [20]

5.4.2.2

Spectrally Resolved Detection

Although specific measurements of each Raman band using a photodetector such as photomultiplier tubes (either with optical narrow bandpass filters or a spectrograph) are still in use at present, spectrally resolved detections using CCD image detectors are becoming more popularly used due to their advantages. With a spectral resolution mostly on scale of 1 nm around the excitation wavelength, spectrally resolved Raman spectroscopy detects a single spectrum that encompasses all Stokes bands (and anti-Stokes if required for thermometry) of the major species. Additionally, the ability to validate the spectral form and the reliability of pixel integration for each species at any given condition is another important advantage of specially resolved detection. It also offers extensive information on spectral interference (crosstalk) and the optical background induced by flame luminosity, all of which must be avoided for the diagnostics to be effective. Kazukata and his colleagues employed spectrally resolved detection (pumpprobe-type transient-reflection measurement, Fig. 5.16) to investigate the optimization of the detection sensitivity for coherent optical phonons and found a strong optimization of approximately 35 times in diamond [21].

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Fig. 5.16 Schematic representation of the experimental setup for spectrally resolved detection on the transient-reflectivity measurement. PD represents the photodiode measuring pulse intensity, BS denotes a beam splitter, CM is a chirp mirror, and BF is a bandpass filter for spectral cutting [21]

5.4.2.3

Gating

The temporal signal optical gating system is among the most important aspects of setting up a single-shot SRS diagnostic system. In the availability of a high amount of background optical emissions, a short optical gate is needed for weak SRS signals to be detected with a good SNR. Gating can be achieved in one of two ways: (i) using an ICCD for electronic gating, or (ii) using an electromechanical optical chopper (rotary chopper wheels/mechanical shutter combination). Because of their nanosecond gating capability and simplicity of application, several groups have selected ICCDs for Raman scattering detection. However, when using ICCDs for Raman diagnostics, problems such as image quality (or spectral resolution in spectroscopy), detector dynamic range, and noise must all be addressed. The spatial resolution of the CCD array is harmed by photon spread caused by proximity focusing on the internal fiber-optic coupling plate between the intensifier and the CCD array. Alternatively, when studying a combustion system with less optical history, a cooled and nonintensified back-illuminated CCD (BI-CCD) detector can provide superior detection, particularly when combined with a high-speed electromechanical shutter system to provide microsecond optical gating. Figure 5.17 portrays an example of one of these shutter systems. The shutter system allows the detection of single photons similar to CCD while still retaining the high spatial resolution, dynamic range, and robustness of the BICCD. When using a nonintensified CCD detection with a high-speed rotary shutter, the electronics’ timing regulation must be improved. Figure 5.18 illustrates an example of a timing regulation system. The first delay generator (master control) in this example activates the second delay generator, which launches the Nd:YAG laser flash lamp

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Fig. 5.17 A high-speed electromechanical rotary shutter system. a Perspective view of the assembly; b Timing diagram [16]

immediately preceded by the QS trigger for full-energy laser pulse emission after the usual QS delay (about 200 ms). Since the actual emission is regulated by the high-speed shutter, the laser flash lamp trigger often causes the CCD exposure gate to open and continue to operate for several milliseconds. In synchrony with the master delay generator, the master delay generator controls the mechanical shutter mechanism by sending various TTL (transistor-transistor logic) signals to control the optical chopper drivers in a phase-locked loop mode. As shown in Fig. 5.18b, the master delay generator regulates the electromechanical leaf shutter with enhanced delay parameters. Figure 5.19a depicts a clear method for checking and maximizing the timing difference between both the excitation laser pulse and the shutter gate, as well as improving shutter efficiency in terms of timing deviation and other variables. The laser timing is controlled in this example by measuring the laser scattering off the layer of any optics in the excitation optical train or a laser dump, while the gate signal (gate opening window) is regulated concurrently. The modification optimizes the gate timing, allowing for optimum scattering transmission through the shutter system. This is verified by using a quick oscilloscope to track all signals, as seen in Fig. 5.19b. To achieve optimum SRS signal temporal throughput, the aforementioned high-speed shutter timing set-up and validation process is important. The Raman spectrum which occurs in ambient air (532 nm excitation at 400 mJ per pulse) was recorded using three kinds of CCD detectors. While no optical context is

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Fig. 5.18 Timing control of an electromechanical shutter-based Raman system. a Hardware connection; b Typical delay generator parameter setting. Note The manufacturer names and model numbers are provided for accuracy, and are not an endorsement [16]

taken into account in this comparison, the physical shutter-based EMCCD detection has a great deal of potential for single-shot measurements. When EMCCDs for signal gain or ICCDs for image intensifier gain are used, the signal rises above the readings and the noise signal is noticeable. It is worth noting that these gain settings should be calibrated and set to the absolute lowest gain, since increasing the gain beyond

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Fig. 5.19 Schematic of the temporal detection system showing the timing overlap between the excitation laser pulse and electromechanical gating. a Timing overlap validation test set-up. PD denotes photodiode; PMT represents the photomultiplier tube; LD is the laser diode; DG represents digital delay generator; b An ideal timing overlap [16]

the ideal level will not increase the SNR but will only reduce the dynamic range. The laser-generated optical context (e.g., PAH-LIF) can remain a problem regardless of the gating method used if such phenomena are strong enough to interfere even within the nanosecond gating window. Interference-free Raman techniques have been suggested in this regard [22].

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Optical Calibration

For statistical multiscalar measurements, the optical device needs two calibrations: wavelength calibration and spectral response calibration: • Wavelength calibration of a spectrometer with a CCD array This is performed by combining the wavelength and intensity data from partial spectra acquired for a Kr lamp in overlap regions to achieve a continuous spectrum over a wider range of wavelengths. There are minor wavelength variations and large intensity differences in the overlapping area of the two partial spectra in Fig. 5.20. The partial spectrum with the central wavelength set to 560 nm is shown in solid form, while the partial spectrum with the central wavelength set to 630 nm is shown in dotted form. In the overlap zone, the peak maxima values vary by less than 0.1 nm. At a wavelength of 600 nm, the spliced spectrum was generated by joining the two spectra shown in Fig. 5.20 [23]. • Spectral response calibration It’s worth noting that the calculation of extended spectra, which necessitates the splicing of several partial spectra, requires spectral response correction to remove splicing objects. As a result, spectral response calibration is a necessary component of the measurement. An example of spectral response calibration is shown in Fig. 5.21. The dotted trace in Fig. 5.21a depicts the corrected spectrum, which accounts for variations in the CCD detector’s spectral efficiency as well as artifacts introduced by partial spectral splicing. The normalized corrected spectrum from Fig. 5.21a is shown as a solid trace in Fig. 5.21b. For wavelengths less than 650 nm, the correspondence between the two normalized spectra is excellent. The disparity in source geometry

Fig. 5.20 The overlap area of two partial Kr lamp spectra captured by a CCD spectrometer [23]

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Fig. 5.21 a The solid trace represents the measured extended spectrum from an SRM 2490, which is a cuvette-shaped piece of orange glass that fits easily into the spectrometer sample holder. b The solid trace displays the normalized approved values of the relative emission spectrum from SRM 2490, while the dotted trace shows the corrected spectrum of component [23]

relative to the sample is more likely the cause of the slight divergence at longer wavelengths [23].

5.4.3 Data Reduction 5.4.3.1

Raman Signal Calibration

The SRS signals basically provide species molecular number density information by calibrating the Raman scattering. The formulation of the calibration matrix is an important part of the SRS calibration procedure due to the presence of spectral crosstalk between neighboring species. Figure 5.22 depicts an illustration of the overall calibration method. This procedure starts with the collection of Raman spectra (from 450 to 700 nm for anti-Stokes/Stokes measurements with 532 nm excitation) in calibration-standard burners of various fuels (H2 , H2 /CO, CH4 , prevaporized liquid fuel, etc.) over a wide range of temperatures. According to Fig. 5.22, a plot of nonlinear relationship between a molecule’s number density, j, and the SRS signal strength of a superpixel for the molecule I (i.e., Nj/Si) over a temperature range of T

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Fig. 5.22 A flowchart for SRS signal calibration [16]

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yields a temperature-dependent function (via polynomial fitting), which provides one element of the calibration matrix. This nonlinear plotting will specify the molecular species’ diagonal (self, i14j) and off-diagonal (crosstalk, I, j) components completing the matrix calibration constant kij (T) [24]. 5.4.3.2

Calibration Burners

A schematic of the calibration burner is illustrated in Fig. 5.23. The described design produces very stable flames with 1D temperature and concentration profiles along the flow path, as well as atomic tracer species seeding. Because of these features, the burner can be used for both laser-based thermometry and laser-based concentration measurements (major species, radical concentration, and soot).

Fig. 5.23 Calibration burner was used to stabilize the flat premixed methane/air flames. a Crosssectional view, b top view [25]

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Data Processing

Raman spectroscopy can have a high accuracy but there might be spectral variation in data processing [26]. Post-processing of the measured single-shot SRS spectra normally begins with data smoothing to eliminate random shot noise before passing through the inverse matrix calibration [16]. Parameters such as averaging over window of algorithm smoothing should be chosen carefully. Rarely, the spark emission intensity due to laser-induced breakdown overloads the Raman signals which in turn disqualifies the further reduction processes of some single-shot events. Shot by shot noise can define the background baseline of the spectrum in a proper Raman free region. After this, clean-up process occurs with the inverse matrix calibration. Raman signals of the main species are converted into the molecular number density Ni via Eq. 5.1. The main species measured mole fraction may be used as a continuous approach to evaluate the estimated ideal law-based thermodynamic temperature for validation of the directly measured spectroscopic temperature [27].

5.4.3.4

Example of Multiscalar Data in Practical Combustion Systems

Figure 5.24 presents the SRS time average spectrum taken in a non-premixed methane–air turbulent flame at fuel-rich conditions at elevated pressure. It is observed that there is spectral interference between O2 and CO2 while CH4 , H2O, and N2 are spectrally separated thus, it is necessary to apply the calibration matrix formulation.

Fig. 5.24 A 200-shot averaged rotational–vibrational Raman spectrum at 532 nm excitation, observed in a swirl-stabilized methane–air flame at global equivalence ratio of 0.56 at moderate pressure (5 atm) [16]

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Figure 5.25 demonstrates an example of SRS point-wise single-shot measurements of swirl-stabilized methane–air flame at high pressure of about 5 bars. This burner platform is in accordance with a lean direct injection model which is fitted to a multiple-point fuel injector adapted into a combustor design with low emission [28]. As shown in Fig. 5.25, SRS measurements were made at different locations involving recirculation and postflame zone. Three scalar corrections of oxidizer (O2 ), fuel (CH4 ), and temperature are given in the scatterplot diagrams which are as a result of chemistry-turbulent interaction arising in these two regions. The top scatterplot represents a postflame zone which is comparatively homogenous and well-reacted condition due to very low concentration of methane and fewer variation in the distribution of temperature. Contrary, the bottom scatterplot measured in high turbulent shows a huge scatter in all dimensions. These variations in all three scalars are as a result of unsteadiness in the mixing and reactions in this region. Incomplete combustion around the edge of flame occurs due to low temperature points with high concentration of oxidizer. These results show the details of the nature of the turbulent

Fig. 5.25 Multiscalar scatterplot of oxidizer (O2 ), fuel (CH4 ), and temperature investigated from 400 single-shot data measured in swirl-stabilized methane–air flame at a high pressure of 5 bars [16]

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mixing and its impact at elevated pressure on chemical reactions in a realistic direct injection flame.

5.4.4 Flow Controller System Design 5.4.4.1

Flow Meters

Research and development (R&D) dictate and investigate the type of combustor, the burner model, and the design of a flow control system to be utilized in research quality high-pressure combustion systems [29]. Previously, many R&D high pressure combustion systems depended on the use of thermal conductivity-based mass flow controller to monitor and meter the flow of different gases (Fig. 5.26) [30]. Despite these systems functioning well, they were prone to calibration drifts which led to inaccuracies [31]. Also, they had a dynamic range of a typical 50:1 turndown ratio, which limited the ability of researchers to operate on a wide range of flow rate and equivalent ratios to administer informative data. Successful efforts have been achieved to shift from calibration-based flow measurement techniques to staged dynamic orifice plate-type flow meters, and have been used with Bunsen-type flame [27]. Nguyen and Dibble (1996) in Fig. 5.27 demonstrated a methane–air Bunsen burner with the long tube which assured the condition of fully developed laminar pipe flow at the exit. The pressure regulator Fig. 5.26 Schematic diagram of combustion, burner chamber, flame zone location, and major features of the flow field such as inner recirculation zone (irz), outer recirculation zone (orz), and the stream of injected gases [30]

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Fig. 5.27 Schematic diagram of Bunsen burner and coflow air homogenized by glass beads before entering the honeycomb flow straightener [27]

controlled the flow of fuel (CH4 ) and oxidizer through calibrated orifice plate meters which were fitted with digital manometers. A static mixer was used to homogenize the fuel and oxidizer, thus providing a steady premixed fuel-to-air ratio [27, 32]. Staged critical-flow orifice meters were successfully used on atmospheric turbulent jet flames by joining three different ranges of critical flow orifice meters together to achieve a wide dynamic range of up to 8000:1 using manually selectable manifold of valves [33]. This type of flow control system is not based on thermal conductivity calibration since it has a fixed orifice diameter. The orifices are highly accurate and have a precise pressure measurement. Additionally, the mass flow rate downstream is independent of the back pressure variation as long as the flow is maintained in a critical flow (sonic) condition. The flow rate is fully determined by temperature measurement using thermocouples. While developing a flow control system, three-stage electronically switched critical-flow venture design was used to enhance excellent precision, accuracy, a wide range of flow rates, a wide variety of gases,

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Fig. 5.28 Schematic of a high pressure gaseous burner rig and gas flow system for up to 30 atm combustion. T: thermocouple; P: pressure transducer; V: venturi; RB: remotely operated ball valve; SV: sonic venture; BD: burst disk; BPV: back-pressure valve; PID: process controller; PR: remotely operated regulator [34]

and free from the electronic calibration drift for high-pressure combustion systems of high pressure output of up to 60 bar (Fig. 5.28) [34]. The use of a critical flow venturi instead of an orifice plate allowed an additional advantage of excellent pressure recovery of up to 95% of the gas flow. The high operational efficiencies were achieved by maximizing bottled gas usage between cylinder refills. The other advantages of using critical flow elements such as venturis and orifices are: (i) that the elements do not go out of calibration (assuming that there is no mechanical wear); (ii) when changing gases, new calibrations are not needed; and (iii) scaling factors for different gases are readily available [34].

5.4.4.2

Flow Control Software

Automated software control system is important when designing the flow control system, it operates by switching the manifold, acquisition of data, electronically controlling the pressure regulators, and automatically shut down the system in case

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Fig. 5.29 Schematic of the monitor and commander (M&C) PLC system composed of a software and a hardware component [36]

of emergency [16]. The use of industrial-grade programmable logic controller (PLC) is the most effective software which permits the same level of operation for critical applications that include high pressure combustion rig and flow of combustible gases (Fig. 5.29) [35]. Industrial PLCs are designed to enhance safety and programmed for 24/7 operation. They are equipped with over 100 possible automatic shutdown combination sequences based on transducer triggers for rig overtemperature or burner, based on sensors, rig over-pressure, detection of fuel system leaks, and lack of test cell ventilation [34].

5.5 Outlook Simultaneous measurements and 1D or 2D imagining techniques are a growing trend in multiscalar diagnostics of flames at laboratory scale. As discussed in this chapter, point-wise single-shot multiscalar diagnostics is capable of providing precision and accurate data on high pressure combustion systems [5], which play a vital role in CFD code validation for practical combustion systems. Development of multiscalar diagnostic techniques such as SRS and LIF using minimum number of laser excitation technology and detection system while delivering maximum flexibility is entrancing. One example is the use of Nd:YAG laser which simultaneously provides both the excitation for SRS and pump UV optical

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parametric oscillators (OPOs). The use of wavelength conversion techniques, faster mechanical shutters, and electronic light gating with nanosecond-gated fast-frame transfer CCDs will take SRS diagnostics for combustion on another level. Since the combustion system is not affected by contamination, a combination of point-wise 2D or 3D nonseeded spectral-shift velocimetry methods coupled with point-wise single-shot SRS measurements may be used to characterize turbulent flow fields of chemical species [37]. Existence of liquid fuel droplets in the application of twophase reaction flow in aviation jet fuels poses a serious challenge to the quantitative SRS measurements since this affects the introduction of bias to the resulting data.

5.6 Summary Recent advancement of SRS laser diagnostics in the applications of practical combustion systems has been reviewed in this chapter. SRS constitute both theoretical and experimental mature diagnostic technology for multiscalar measurement in turbulent combustion at elevated pressure since increased SRS signals can be expected at high pressure. Point-wise SRS diagnostics provide precision and high accuracy on temperature and chemical species measurements and continue to play a vital role in the study of such harsh conditions [38]. The use of second harmonic Nd:YAG pulsed laser (532 nm) combined with pulse stretching optics or the introduction of the recent White Cell-based laser seems to be the most preferred source of excitation by the combustion research community. The detection techniques based on the design choice and the level of background flame emission maybe divided into a rotary chopper electromechanical shutter-based CCD array detection and ICCDbased nanosecond gate detection. Raman signal calibration process is based on the crosstalk matrix formalism, the construction, and the designs of the flow control system for high pressure burner were also presented in this chapter.

5.7 Exercises (1) Individual task: Find a scientific paper and explain the combustion system and the flow controller system design in SRS. (2) Group task: In small groups, find a literature paper and make a presentation on the applications of SRS in combustion research.

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5.8 Questions (1) Describe SRS’s importance in flame diagnostic. (2) State the advantages of SRS over other diagnostics techniques such as CARS and LIF. (3) Describe how a high-pressure flame can be established. (4) Explain the reason why Nd: YAG pulsed laser is preferred in the excitation source in the SRS system. (5) In the SRS system, why is pulse stretching necessary? (6) State the essence of using mirrors in SRS system. (7) With a supporting diagram, describe the working principle of the SRS system. (8) State the advantages of using CCD image detectors over convectional Photomultiplier tubes in the SRS system. (9) State ways in which gating can be achieved in SRS. (10) Which technique can be utilized to detect weak SRS signals with a good SNR? (11) Describe the two types of optical devices calibration in SRS.

References 1. Hassel, E. P., et al. (2000) Laser diagnostics for studies of turbulent combustion. 11(2), R37. 2. Masri, A., et al. (1996). The structure of turbulent nonpremixed flames revealed by RamanRayleigh-LIF measurements. 22(4), 307–362. 3. Gu, Y., et al. (2000). Pressure dependence of vibrational Raman scattering of narrow-band, 248-nm, laser light by H2 , N2 , O2 , CO2 , CH4 , C2 H6 , and C3 H8 as high as 97 bar. 71(6), 865–871. 4. Bessler, W., et al. (2002). Quantitative NO-LIF imaging in high-pressure flames. 75(1), 97–102. 5. Cheng, T. S., et al. (2002). The application of spontaneous vibrational Raman scattering for temperature measurements in high pressure laminar flames. 174(5–6), 111–128. 6. Eckbreth, A. C. (1996). Laser diagnostics for combustion temperature and species (vol. 3): CRC press. 7. Miles, P. C. (1999). Raman line imaging for spatially and temporally resolved mole fraction measurements in internal combustion engines. 38(9), 1714–1732. 8. Kojima, J., & Nguyen, Q. V. (2004). Measurement and simulation of spontaneous Raman scattering in high-pressure fuel-rich H2–air flames. 15(3), 565. 9. Kreibig, U., & Vollmer, M. (2013). Optical properties of metal clusters (vol. 25). Springer Science & Business Media. 10. Sidwell, T., et al. (2006). Optically accessible pressurized research combustor for computational fluid dynamics model validation. 44(3), 434 443. 11. Meier, W., Keck, O. (2002). Laser Raman scattering in fuel-rich flames: Background levels at different excitation wavelengths. 13(5), 741. 12. Meier, W., et al. (2000). Investigations in the TECFLAM swirling diffusion flame: Laser Raman measurements and CFD calculations. 71(5), 725–731. 13. Barlow, R., Miles, P. (2000). A shutter-based line-imaging system for single-shot Raman scattering measurements of gradients in mixture fraction. 28(1), 269–277. 14. Nguyen, Q. V. (2005). High-speed electromechanical shutter for imaging spectrographs. In: Google Patents. 15. Nguyen, Q. V. (2005). High-speed electromechanical shutter for imaging spectrographs.

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16. Kojima, J., & Nguyen, Q. V. (2010). Spontaneous Raman scattering diagnostics: applications in practical combustion systems. 125–154. 17. MacAdam, K., et al. (1992). A narrow-band tunable diode laser system with grating feedback, and a saturated absorption spectrometer for Cs and Rb. 60(12), 1098–1111. 18. Wehr, L., et al. (2007). Single-pulse 1D laser Raman scattering applied in a gas turbine model combustor at elevated pressure. 31(2), 3099–3106. 19. Hicks, Y. R., et al. (2000). Optical measurement and visualization in high-pressure hightemperature aviation gas turbine combustors. Paper presented at the Optical Diagnostics for Industrial Applications. 20. Turzhitsky, V., et al. (2014). Spectroscopy of scattered light for the characterization of micro and nanoscale objects in biology and medicine. 68(2), 133–154. 21. Nakamura, K. G., et al. (2016). Spectrally resolved detection in transient-reflectivity measurements of coherent optical phonons in diamond. 94(2), 024303. 22. Grünefeld, G., et al. (1995). Interference-free UV-laser-induced Raman and Rayleigh measurements in hydrocarbon combustion using polarization properties. 61(5), 473–478. 23. Gaigalas, A. K., et al. (2009). Procedures for wavelength calibration and spectral response correction of CCD array spectrometers. 114(4):215. 24. Jeyashekar, N. S., & Seiner, J. (2007). Design of a calibration burner for optical combustion diagnostics. Paper presented at the 45th AIAA Aerospace Sciences Meeting and Exhibit. 25. Hartung, G., et al. (2006). A flat flame burner for the calibration of laser thermometry techniques. 17(9), 2485. 26. Graves, P., & Gardiner, D. (1989). Practical raman spectroscopy. 27. Nguyen, Q. V., et al. (1996). Raman-LIF measurements of temperature, major species OH, and NO in a methane-air bunsen flame. 105(4), 499–510 28. Kojima, J., Nguyen, Q. V. (2008). Observation of turbulent mixing in lean-direct-injection combustion at elevated pressure. 46(12), 3116–3127. 29. Weigand, P., et al. (2006). Investigations of swirl flames in a gas turbine model combustor: I. Flow field, structures, temperature, and species distributions., 144(1–2), 205–224. 30. Meier, W., et al. (2006). Investigations of swirl flames in a gas turbine model combustor: II. Turbulence–chemistry interactions. 144(1–2), 225–236. 31. Barlow, R. S. (2007). Laser diagnostics and their interplay with computations to understand turbulent combustion. 31(1), 49–75. 32. Nguyen, Q. V., et al. (1993). Tomographic measurements of carbon monoxide temperature and concentration in a bunsen flame using diode laser absorption. 97(12), 1634–1642. 33. Muss, J., et al. (1994). A helium-hydrogen mixture for the measurement of mixture fraction and scalar gradient in non-premixed reacting flows. Paper presented at the 32nd Aerospace Sciences Meeting and Exhibit. 34. Kojima, J., & Nguyen, Q. V. (2003). Development of a high-pressure gaseous burner for calibrating optical diagnostic techniques. 35. Namekar, S. A., & Yadav, R. (2020). Programmable logic controller (PLC) and its applications. 6(11). 36. Haba, C. G. (2010). Extending the use of plc simulator software in student laboratory works. 10(1), 84–89. 37. Bivolaru, D., et al. (2006). Single-pulse multi-point multi-component interferometric Rayleigh scattering velocimeter. Paper presented at the 44th AIAA Aerospace Sciences Meeting and Exhibit. 38. Sutton, G., et al. (2006). A combustion temperature and species standard for the calibration of laser diagnostic techniques. 147(1–2), 39–48.

Chapter 6

Coherent Anti-Stokes Raman Scattering Zhen-Yu Tian, Vestince Balidi Mbayachi, Xu Zhang, Maria Khalil, and Daniel A. Ayejoto

6.1 Introduction Coherent Anti-Stokes Raman Scattering (CARS) spectroscopy is an important tool that has been widely used in interdisciplinary research fields such as biology, chemistry, physics, healthcare, defense, remote sensing, forensics, and material science, among others. A CARS-based microscope was demonstrated in 1982 [1], followed by a few other CARS implementations in the following years, but further adoption of the technology by the wider scientific society was hindered due to the limitation in laser technology at the time, as well as the complication in satisfying phase-matching conditions in the target sample [2]. It wasn’t until 1999 that Zumbusch and Xie showed that phase-matching could be achieved with a high numerical aperture (N.A.) objective under close focusing [3]. CARS microspectroscopy has become practical and widespread as a result of advancements in ultrafast laser technology, and the field has grown exponentially in Z.-Y. Tian (B) · X. Zhang Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China e-mail: [email protected] Z.-Y. Tian · V. B. Mbayachi · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China X. Zhang School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_6

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the following decades. On the one hand, new schemes continued to advance the technology, improve the detection range, signal level and acquisition rate, and suppress unnecessary background signals [4]. CARS has been used in a variety of research projects, including biochemical imaging of cells and tissues [5], gas-phase analysis [1], and the characterization of new materials [6]. For further reading, there are some excellent review papers focusing on the technology’s implementation and applications [7]. Figure 6.1 depicts a schematic diagram of the CARS method. In Coherent Stokes Raman scattering (CSRS), the scattered light is red-shifted. CARS and CSRS are specifically stated in the rest of the paper to differentiate the two processes. The pump and Stokes pulses excite and prepare molecules in a coherent state at the same time. The probe pulse arrives with or without delay, resulting in an anti-Stokes/Stokes signal. Contamination from Four Wave Mixing (FWM) is unfortunately inevitable. FWM is a nonlinear mechanism of the third order that is independent of molecular Raman vibrations. In the overall calculated spectral data, FWM is introduced and mixed as a non-resonant background noise, as a result, extracting pure resonant (CARS/CSRS) information from the overall data polluted with FWM is critical.

Fig. 6.1 The CARS and CSRS processes are depicted in this diagram. CARS (a) In CARS, the dispersed light is blue-shifted. (d) In CSRS, the dispersed light is red-shifted. FWM (b, e) It is a nonlinear third-order non-resonant mechanism that has little to do with molecular Raman vibrations. c, f) [8]

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This is a subject that will be looked at more thoroughly in the future. Despite the fact that a range of methods for suppressing FWM [8] non-resonant history have been proposed, the aforementioned carefully chosen experiments with broadband (fs) pump and Stokes excitation pulses with a narrowband (ps) formed and delayed probe pulse have been successfully demonstrated [9–11].

6.2 Theory Three laser beams are usually directed to a common intersection point in the CARS operation, according to a broad concept. An oscillating polarization would be induced at ωR = ω1 − ω2 , where ωR is the Raman frequency and ω1 and ω2 are the frequencies if the frequency difference between two laser beams is in vibrational or rotational resonance with a specific molecule. Three laser beams are usually directed to a common intersection point in the CARS operation, according to a general definition. The CARS signal has a frequency of CARS, which is equal to the number of ωR and ω3 , with ω3 being the frequency of the third laser beam. The CARS signal then propagates as a laser-like beam from the intersection point in the direction determined by the phase-matching condition. The signal is directed to a spectrograph after spectral isolation, and the detected spectrum contains temperature information. The molecular structure and its interaction with radiation, the Boltzmann population distribution, experimental equipment parameters, and measurement conditions all have a complex influence on the CARS spectrum [12]. CARS is divided into two types: vibrational CARS and pure rotational CARS. The signal in vibrational CARS comes from molecular resonances between states of the same rotational quantum number J (Q-branch) located in different vibrational levels, v and v + 1, while in pure rotational CARS, the resonances are between states of different rotational quantum numbers, J and J + 2 (S-branch), within the same vibrational level. Figure 6.2 shows a schematic representation of this.

6.3 Interpretation of CARS Spectra CARS spectra consist of a general theory along with the identification of the spectral structure of CARS signals. The general features of CARS spectra will be reviewed and discussed. The simple form of an equation is selected to presume the laser beam’s monochromaticity. This condition is ideal, as the assumption becomes acceptable for a specific advanced pump to laser (e.g., injection seeded Nd: YAG lasers), the bandwidth of this is considerably smaller than the linewidth of the Raman resonances. Specifically, pump lasers utilized in CARS measurements have a restricted linewidth. These parameters are comparable to or larger than the Raman widths. It is required to generalize Eq. 6.1 to the reality of the laser beams after the previous theory. Transformation of Eq. 6.1 into an intuitive spectral intricacy over the three laser profiles.

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Fig. 6.2 An energy level diagram representing different CARS processes: a vibrational CARS; b pure rotational CARS [12]

IC A R S (ωa ) = C|χ (ϖ1 − ϖs )|2 [L 1 (ϖ1 )]2 L s (ϖs ) χ (ω1 − ωs ) =

∑ j

aj

1 (Ω j − (ω1 − ωs ) − i┌ j

(6.1) (6.2)

Two lasers are supposed to degenerate with equal central frequencies, as well as the delta function which is responsible for energy conservation as in Fig. 6.3. The simplification in Eq. 6.3 can be followed by studies of Yuratich [13]. It can also be regarded as the result of Eq. 6.1 is the limit of Eq. 6.3 having very small spectral linewidths σ1 and σ2 . It is also concluded that Eq. 6.3 is used in CARS as basic studies [14–16], soon it was realized that there is the relevancy of spectral components of χ and contribution to CARS signals. This can be acknowledged by examining the expression of the susceptibility in Eq. 6.2, which assimilates the difference between the pump and the Stokes frequencies. ∫ IC A R S (ωa ) = K

|χ (ω1 − ωs )|2 L 1 (ω1 )L 2 (ω2 )L S (ωs )

δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs

(6.3)

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Fig. 6.3 Energy diagram for the transitions of a CARS process involving ω1 and ω2 pump excitations and two deexcitations at the Stokes and anti-Stokes frequencies ωS and ωaS . The real molecular levels are indicated with solid lines, whereas virtual states are represented by dashed lines [20]

The fundamental CARS process of Fig. 6.3 involves the action of two pumping fields and the field mixing is only complete if the two spectral components of χ are taken into consideration. One component depends on the difference ω1 − ωs , and the other on the difference ω2 − ωs . This was introduced during the 1980s that was empirical disagreement forms the basis of a more complex convolution to precisely interpret CARS measurements [17–19] ∫ IC A R S (ωa ) = K

|χ12S |2 L 1 (ω1 )L 2 (ω2 )L S (ωs )

δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs 1 1 χ12S = χ N R + χ1S (ω1 − ωs ) + χ2S (ω1 − ωs ) 2 2

(6.4) (6.5)

The first term of Eq. 6.5 is the so-called non-resonant susceptibility, which provides background information because the target molecule is surrounded by a large molecule. The other two terms of χ12S give off the pertinent CARS signal which includes coherent phenomena between the spectral components accessed by ω1 − ωS and ω2 − ωS , Equation 6.4 gives the most general expression for the CARS signal, the very small spectral linewidths are once again Eq. 6.1. The calculation of Eq. 6.4 is complex, to calculate the solution method is to break it into four parts as given below ∫ I1 = K χ N2 R

L 1 (ω1 )L 2 (ω2 )L S (ωs )δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs

(6.6)

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∫ 1 ∗ ∗ K χ N R (χ1S + χ2S + χ1S + χ2S ) 2 × L 1 (ω1 )L 2 (ω2 )L S (ωs )δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs

(6.7)

∫ 1 ∗ I3 = K (χ1S χ1S + χ2S χ ∗2S ) 4 × L 1 (ω1 )L 2 (ω2 )L S (ωs )δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs

(6.8)

∫ 1 ∗ ∗ K (χ1S χ2S + χ1S χ2S ) 4 × L 1 (ω1 )L 2 (ω2 )L S (ωs )δ(ω1 + ω2 − ωs − ωa )dω1 dω2 dωs

(6.9)

I2 =

I4 =

where the symbol indicates the complex conjugate and χ1S is given by Eq. 6.2, whereas χ2S is still Eq. 6.2 with ω2 replacing ω1 . A first conclusion describes that, even though the decomposition of Eq. 6.4 in four pieces has made a simpler the problem, the integrals of Eqs. 6.6–6.9 cannot be solved unless the spectral shapes of the laser beams are specified. Fortuitously, the solutions are analytical for important special cases, namely, Gaussian or Lorentzian dependence [16, 19, 21]. This is essential for practical purposes because Gaussian profiles are presumed to be close enough to the line shape of multimode lasers [22, 23]. The adjustment of this assumption to the CARS theory implies that the use of Eq. 6.10 leads to the results. ( ) ] [ Lp L P ωp = √ ex p −(ω p − ϖ p )2 /σ p2 πσp I1g = K χ N2 R L 1 L 2 L s √ 1s I2g = −K χ N R L 1 L 2 L s

∑

] [ 1 2 ex p −(ωa − ϖa )2 /σ12S π σ12S

/

1

σ2 σ12 +σ 2s

(6.10) (6.11)

] [ 2 ex p −(ωa − ϖa )2 /σ12S

a j I m[ω(z 1, j )]

(6.12)

j

] [ 1 1 2 1s I3g = − K L1 L2 Ls / ex p −(ωa − ϖa )2 /σ12S 2 σ2 σ12 +σ 2s ∑ ) ( × a j am I m{ω(z 1, j )/[Ωm − Ω j + i ┌ j + ┌m ]} j,m

(6.13)

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√ ] [ π 1 2 / = K L1 L2 Ls ex p −(ωa − ϖa )2 /σ12S 2 σ1 σ 2 σ12 +σ 2s ∑ )] [ ( )] ( ) ( ) [ ( × a j am {Re ω z 1,m Re ω z 2, j + I m[ω z 1, j ]I m[ω z 2,m

(6.14)

j,m

z 1, j

[ 2 2 ] σ1 +σ s σ12s = / (ωa − ϖa ) − Ω j + ϖ1 − ϖs + i┌ j 2 σ12s σ2 σ12 +σ 2s

(6.15)

[ 2 2 ] σ2 +σ s σ12s / − ϖ + ϖ − ϖ + i┌ − Ω (ω ) a a j 2 s j 2 σ12s σ1 σ22 +σ 2s

(6.16)

z 2, j =

The entire set of Eqs. 6.11–6.16 is pretty useful for the understanding role played by various parts of the CARS signal. For example, if attention is turned toward the situation of negligible background (i.e., χNR = 0), the signal is a sum of the main integral I3g as well as the impact of interference I4g , and the consequence of the latter might be questioned [24, 25]. ){ { ( lm w(z j )/[Ωm − Ω j + i ┌ j + ┌m ] =

1 (Ωm − Ω j )2 + (┌ j + ┌m )2

×

{(

) [ ( )] ( ) [ ( )]{ Ωm − Ω j lm w z j − ┌ j + ┌m Re w z j

(6.17) Equation 6.17 demonstrates that the spectral peaks of CARS measurements are not purely represented by the Voigt profile, unless they are largely spaced. Finally, the qualitative conclusion of Eqs. 6.11–6.16, is depicting the role of a background appearing in Eqs. 6.11 and 6.12. Understanding that Eq. 6.11 is uninspired (apart from the obvious Gaussian factor shared by all the intensities), the background in Eq. 6.12 importantly present contributes, which once again introduces an additional odd symmetry (right-hand panel of Fig. 6.4) in the CARS spectrum. In conclusion, the role of background can be summarized in the dispersive character that must be combined with the remaining terms of the whole signal.

Fig. 6.4 Behaviors of RE[w(zj )] and Im[w(zj )] as functions of the detuning (i.e., frequency difference concerning the jth Raman resonance) [20]

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6.4 Principle of CARS A nonlinear spectroscopy technique that uses two collinear lasers to illuminate a sample and lasers are strong is called CARS. Normally, frequency is kept constant to attain the frequency difference between two lasers, the frequency of a Raman-active mode of interest, as well as with the second laser tuned. To obtain the strong Raman signal, the second laser frequency can be tuned such that its frequency is equivalent to a constant frequency of the first laser minus the Raman-active rotational frequency, vibrational or other modes of frequency. This can cause the scattered light frequency to be higher than the excitation frequency, forming the anti-stroke frequency as shown in Fig. 6.5.

6.5 Molecular Parameters Having briefly explained the spectral structure of the CARS signal ICARS (ωa ), the problem is then to utilize this to accomplish a correct reconstruction of experimental measurements. To achieve that, the central task is set by the determination of the molecular parameters named the Raman shift WÄ j , the associated widths Tj, and the remaining parameters included in the amplitudes aj . In general, the Raman shifts WÄ j are known from detailed spectroscopic calculations or measurements made for the specific CARS molecule in use. There is a famous reference book by Huber and Herzberg [26] for calculations. Generally, two predominant mechanisms affect the Raman linewidths. One is easily determined by the Doppler effect caused by the thermal motion of the gas molecules named Doppler broadening [16, 27]. The other results from collisions between molecules of the same type, or with other constituents are called collisional broadening [16, 27]. Fig. 6.5 Excitation frequency forming the anti-stroke frequency [20]

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6.6 Instrumentation 6.6.1 CARS Instrumentation The instrumentation of CARS is shown in Fig. 6.6. (a) Forwards and backwards (epi-) detected CARS schematic. (b) CARS microscopy scattering behavior for various samples. A single dipole produces the well-known symmetric radiation pattern, a plane of dipoles produces a narrower radiation pattern, and a 3D array of dipoles preferentially scatters in the forward direction. Photon diffusion enables a portion of the larger forward CARS signal to be detected in the backward direction in a linearly scattered medium (such as tissue). (c) CARS picture of C. elegans’ 2845 cm−1 lipid bands, demonstrating the influence of non-resonant contributions in non-lipid regions. (d) Potential image artifacts due to interference of the coherent signal and its reflections within the sample area can be seen in this CARS micrograph at 2845 cm−1 band of 2 polystyrene beads [28].

Fig. 6.6 Instrumentation of CARS [29]

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6.6.2 BOXCARS Instrumentation Initially, the collinear phase matching geometry was used in laboratory gasphase Coherent Anti-Stokes Raman Scattering (CARS) measurements. However, when CARS was applied to combustion diagnostics, a well-defined measurement volume was needed. The construction of a cross-beam phase matching configuration (BOXCARS, as shown in Fig. 6.7) elegantly solved this problem. The CARS beam is the output of a degenerate three-wave mixing operation as such: was = 2w 1 − ws

(6.18)

was = w1 − ws + w2

(6.19)

The CARS beam for the planar configuration in Fig. 6.7a emerges next to one of w1 ’s components and is usually separated with dichroic filters or prisms. More recently, it was recognized that the step matching diagram did not have to be planar, and the folded BOXCARS configuration was developed. The folded BOXCARS

Fig. 6.7 The phase-matching diagram and real geometry of the optical beams for a planar and b folded BOXCARS are shown for CARS crossed-beam phase-matching approaches. Beams are denoted by subscripts: Pump 1, Stokes 2, and anti-Stokes 3 [30]

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layout, shown in Fig. 6.7b, has the significant advantage of spatially separating the CARS beam from the incident laser beams at w1 and ws . As a result, there is a high degree of prejudice against the incident laser wavelengths.

6.7 Experimental Set-Up Different experimental arrangements have been employed in generating CARS signals. Previous experiments applied stimulated Raman scattering to produce a Stokes beam that was mixed with the pump laser beam [31]. The development of a dye laser enhanced the continuous scanning of one beam wavelength, thus leading to spectra measurement [32, 33]. The pioneering work of Terhune and Marker used two fixed frequency beams to give a Stokes beam shift, the first beam originated from a ruby laser and the second beam was generated by stimulating Raman scattering in benzene [34]. These two beams were utilized in measuring resonant CARS signals from benzene and the study of hydrogen gas [35]. Another experiment set-up used by Wynne [36] involved a single nitrogen laser which pumped two dye lasers to generate beams of tunable wavelength at a power range from 10 to 100 KW. The advantage of the nitrogen laser-pumped dye laser setup was that the experiment was easier to perform and recorded spectra within a short period of time since the nitrogen laser operated at a higher repetition rate. However, because of poor beam quality, nitrogen laser cannot be employed as one of the lasers in the nonlinear excitation scheme [37]. Currently, the common experimental arrangement employs a doubled Nd:YAG laser at a frequency of 532 nm with a dye laser [38, 39].

6.7.1 CARS System The CARS systems consist of a laser system (Fig. 6.8), nonplanar BOXCARS for beam alignment, mirrors that relay the beams, combining optical lens for focusing and crossing the beams to generate signals, receiving optics to analyze the signals, a reference signal, a filter to block CARS signals generated outside of the reactor, a charge-coupled device (CCD) camera to detect the image of the crossing, and finally, a computer system to display, store and analyze the data [40].

6.7.2 Laser System Nd:YAG laser doubled frequency at 532 nm and dye lasers (see Fig. 6.8) are the main laser system used to generate CARS signals [42]. Compared to ruby lasers, Nd:YAG lasers are used since they have a higher repetition rate and better beam

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Fig. 6.8 Schematic diagram of CARS system and a combustion extension. A is aperture; L are lenses; SP are short-pass filter; W are windows; NF is a notch filter; SH is a shutter [41]

quality. Dye lasers are used depending on the spectral property of the sample under study [37]. Nd:YAG laser has a pulse width of 8ns and a repetition rate of about 20 Hz. A Hansch-type dye laser gives a width of 0.3 to 1.0 cm–1 , while most diatom gas species have a width of 0.01 to 0.2 cm–1 thus reduction of dye laser width to less than 0.1 cm–1 is necessary [43]. One technique involves the introduction of an etalon into the cavity and an alternative is to use a pressure-tuned dye laser which tunes the gating [44].

6.7.3 Signal Generation Incident laser beams from the pump beam (ω1 ) and stoke beam (ω2 ) interact with the nonlinear susceptibility medium to generate a polarization field which acts as a source of CARS signals (ω3 ) [45]. Practically, CARS signals are generated by frequency doubled neodymium: YAG laser (Nd:YAG) and dye lasers [46]. Nd:YAG laser emits two beams at 532 nm by doubling the first doubler into fundamental 1.06 μ and residual 1.06 μ. The energy of the primary beam is around 200 Mj / pulse and 1.0–8 second pulse duration at 10 Hertz. The second beam energy is lower and is used to pump the stroke dye oscillator. The mirror focuses the beams to the volume measurement and the system spatial resolution is maximized by a nonplanar BOXCARS beam configuration for optimum signal generation [47]. Figure 6.9 illustrates how the Nd:YAG laser (pump beam) was split into two equal beams and placed vertically on the focusing lens. Dye laser (stokes beam) was located slightly outside

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Fig. 6.9 CARS signal generation and focal configuration [48]

the focusing lens and the beams were passed through the crossing and focusing configuration to generate CARS beam [48].

6.7.4 Combustion Facility The combustion chamber normally is accessed by windows made of high-quality quartz plates to withstand a high laser power combination and to increase the amount of energy that is utilized in generating CARS signals [49]. Each plate is positioned parallel to each other through the combustor primary zone. The charge is ignited by two spark plugs mounted oppositely to the wall of combustion zone (see Fig. 6.8). The combustion zone walls are convex and the CARS probe volume is placed very close to the walls to reduce the disturbance from reflected light. Surface temperature transducer is installed in the combustion chamber to measure the temperature and heat transfer [41]. Cylinder pressure is measured at three regions of the combustion chamber, in addition, two thermocouples are installed near the surface temperature transducer and below the surface of the combustion chamber walls. The fuel and air are supplied to the combustion chamber (see Fig. 6.10). The air inlet is heated with a swirl burner prior to fuel injection to assist the vaporization [46]. The combustion tunnel is constructed of stainless steel, double-wall fitted, water cooled, and fitted with swirl burner. The tunnel is 150 cm long with an internal diameter of 50 cm, also it contains quartz windows of 6.4 × 12.8 cm dimension. The combustion tunnel can operate at a pressure of up to 4 atm. Figure 6.11 demonstrates a schematic of the swirl burner which is modeled and developed by the International Flame Research Foundation [50]. The swirl burner is made of stainless steel, and it contains a 1.5 cm diameter fuel nozzle tube, an air duct of 6.6 cm diameter, an adjustable block swirl generator, a static pressure, and a watercooling system. The flames are contained in the plug flow reactor which is insulated and the quartz windows which are fitted with optics, which reduce the thermal stress of the laser energy. The fuel is introduced to the swirl burner and then mixed with combustion air. A data acquisition system which displays thermocouple temperatures, the flow, and analyzes the CARS signals is linked to the microcomputer [51].

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Fig. 6.10 Schematic of air and fuel supplied to the swirl burner [46]

Fig. 6.11 Schematic diagram of the swirl burner [46]

6.7.5 CARS Signal Strength Since CARS is applied for temperature and concentration measurement, the transverse mode of the beam structure affects the spatial resolution, noise and signal strength [52]. Phase across the laser beam and variation of beam intensity significantly affects the CARS signal strength. To obtain strong signals it is recommended to use laser intensities near the window damage threshold. In species detectivity, low species concentration or density affects the signal strength. When the species concentration is very low, it produces weak signals which are unable to be dictated because they disappear into the dispersionless non-resonant background. However, by proper alignment of the stokes laser fields, the conventional orientation of the pump and CARS signal polarization analyzer, non-resonant background can be vanquished leaving the pure CARS signals of the probed species [45].

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6.7.6 Reference System Factors such as fluctuations in shot-to-shot pump laser, variation in dye laser output, interaction length change due to movement of beams, and dynamic change in detector response causes variability in signal intensity [53]. Reference system is used to resolve this problem by compensating the variation in signal generation efficiency. A 20% beam splitter is placed in front of the crossing and focusing lens. This beam splitter is placed at 45° to form a second focal volume in ambient air. The signals from this reference volume and signals produced from the data or flame volume are recorded simultaneously. A flat glass plate is placed in front of the slitter in the reference leg to match the beam shift caused by the splitter in the sample leg. The reference leg is adjusted optically to produce the finest correlation between the reference and sample signals. A real time program is utilized to display this correlation in the system [53].

6.7.7 Detection and Spectra of Gases High power is required to obtain CARS spectra of gas species such as H2 , NO2 , and O2 at a reduced pressure [37]. A pulse power greater than 1 KW is applied to observe CARS spectra in gases, but an exception is seen in methane which only uses cw lasers to obtain its CARS spectra.

6.7.7.1

Hydrogen Detection

Rado [54] conducted the first hydrogen gas CARS process using Ruby laser system arrangement as illustrated in Fig. 6.12 [54, 55]. He evaluated the magnitude of nonresonant susceptibility of gases by calculating non-resonant conversion efficiency comparatively to the resonance susceptibility of H2 of 2.1 × 10–13 cm3 /erg at a pressure more than 10 atm. These data were acquired from induced electric field absorption measurements. Using a ruby laser system, DeMartini et al observed that J = 1 line of H2 stimulates Raman scattering at ws to produce stokes-shift beams [56]. By changing the pressure of hydrogen gas in the stimulated Stokes cell, ws were generated and utilized in the measurements of rotational line shape. Regnier and Taran using a ruby pumped dye laser system obtained CARS signals as a function of hydrogen concentration by measuring temperature in a flame and the relative signal intensities of various rotational lines [57]. Figure 6.13 illustrates detection capability of the ruby laser system in measurement of hydrogen gas diluted in nitrogen gas at 1atm pressure from the level of 10 to 100% ppm. The resultant curve was plotted using relative antistoke signals against hydrogen gas concentration and it exhibited a slope of 2. From the curve it was demonstrated that at low concentration, the background contribution of electron polarization of nitrogen gas gave a constant

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Fig. 6.12 CARS experimental set-up used to detect and record the spectrum of H2 . PM is photomultiplier [55]

signal below 10 ppm. Whereas at high concentration the combine effect of line broadening and line shift due to increasing concentration of nitrogen gas caused the observed curvature [57]. The calibration curve was used to map the profile of hydrogen gas number density in fuel-air premixed flame. The volume of the natural gas (fuel) contained 75% CH4 and 25% ethane, with traces of hydrogen gas and other gases. From Fig. 6.14, the flame was horizontal which describes the symmetry in the hydrogen gas distribution.

6.7.7.2

Nitrogen Detection

Moya et al. [58] used ruby laser system to produce CARS spectra of nitrogen gas. They also reported on the concentration and temperature profile of N2 , O2 , and CO [58]. Antcliff and Jarrett [53] utilized Nd:YAG and broadband dye laser to completely generate Q-branch spectra. In their experiment, they used an intensifier silicon photodiode (ISPD) array controlled by a minicomputer to capture the laser shots of complete spectra [53]. A monochromator was placed in front of ISPD array detector to reject the stray beam and input light. Dynamic range of ISPD was approximately 100 counts and two factors contributed to this small value. Firstly, detector noise limited the measurement value to 200 counts and secondly, spherical lens used to focus CARS signals to the detector caused local saturation to the

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Fig. 6.13 Normalized anti-Stokes signal versus hydrogen concentration in nitrogen gas [57]

Fig. 6.14 Hydrogen gas distribution in the horizontal flame. Z is the distance in mm along the Bunsen burner axis; R is the distance in millimeter from the bunsen burner axis [57]

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detector. Two improvements were initiated to increase the dynamic range. Firstly, the spherical lens was replaced by a cylindrical lens which improved the linear dynamic range to a factor of 5. Secondly, a beam splitter was used to intensify the signal beams with different percentages of the original, thus increasing the dynamic range by a factor of 100, hence sufficient for the study.

6.7.7.3

Oxygen Detection

Photomultiplier (PMT) was used in Nd:YAG laser system by Antcliff and Jarrett [53] to detect the oxygen signals [53]. Presence of non-resonant background complicated the measurement of this signal intensities. Ranh et al. suggested that polarization selection can be used to eliminate non-resonant background [59]. Since the resonance signals have different polarization characteristics from non-resonant signals, the oxygen dye laser polarization was rotated at angle of 60° relative to the pump polarization. A polarization prism was also used in the pump beam to improve polarization properties of the beam thus producing resonant signals with the identical polarization of the pump beams (Fig. 6.15). Non-resonant (NR) signal was rotated from the pump at an angle of 30°, nonresonant signals were blocked by placing an analyzer to the non-resonant polarization axis. Since non-resonant rejection is not completely possible, a bandpass filter was used to block any stray beams from reaching the PMT.

6.7.8 CARS Thermometry Thermometry is the temperature measurement derived from the spectral shape of CARS signals [48]. Compared to concentration measurement, thermometry of molecular species are easier to perform. Fig. 6.15 Polarization configuration used for the rejection of non-resonant background [59]

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Nitrogen

Nitrogen dominates air-fed combustion processes. Conducting temperature measurements with nitrogen gas provide information on the chemical reaction and heat release during combustion [48]. Eckbreth et al. [60] examined the efficiency of CARS N2 thermometry in a premixed flame. The experimental CARS spectra were compared with a computer calculation code [14] using a given temperature slightly above that of thermocouples by 40 K in the range 1600–2100 K and a constant Raman linewidth. Figure 6.16 displays the calculated temperature variation of the nitrogen gas CARS spectrum at a spectral resolution of Δw1 = 0.8 cm–1 and Δw2 = 130 cm–1 , 1.00 cm–1 . A constant Raman linewidth of 0.1 cm–1 was taken into account during the calculation [60]. At low temperature, one can observe that the Q branches are unresolved because of the low rotational quantum number (J) Q branch transition, v = 0 → 1 band, thus ΔJ = 0. At intermediate temperature, fewer J Q branch transition are resolved and Fig. 6.16 Calculated temperature variation of the N2 CARS spectrum from 300 to 2100 K for 0.8 cm−1 pump linewidth and stokes bandwidth of 130 cm−1 , and slit width of 1.00 cm−1 [60]

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at high temperature, J Q branches stretching from Q(20) to Q(40) due to vibrationrotation interaction are resolved. For Q branches above Q(40), two prominent peaks occurred in the “hot band” due to overlap of V = 1 → 2 band transition [61].

6.7.8.2

Hydrogen

Temperature measurement of H2 CARS is relatively strength-forward because of its simple spectrum [62]. In Fig. 6.17 shows the measurement of H2 CARS spectra in a diffusion flame. Various parts within the flame were selected to illustrate the effect of temperature. The line spectra represent the component of the vibrational Q branch v = 0 → 1 band, ΔJ = 0. Due to large H2 vibration-rotation interactions, the adjacent rotational components are well separated, making the spectrum easy to interpret. Proximate temperature were deduced from CARS intensity ratio of Q(1), Q(3), and Q(5) transitions. A good agreement was deduced between the temperatures of the three CARS intensities, the standard deviation over the range of 900 to 2100 K varied from 2 to 8%. The use of line strength over peak intensity ratio would have probably resulted to a better accuracy. The results of temperature profiling using the diffusion flame are shown in Fig. 6.18. Temperatures from O2 and H2 CARS spectra are compared to radiation

Fig. 6.17 H2 CARS spectra in H2 -air diffusion flame at various temperatures determined from the relative strengths of indicated Q-branch transitions. Frequency scale corresponds to 0.60 cm−1 per dot [62]

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Fig. 6.18 Temperature measurements in a H2 -air diffusion flame. Symbols: open triangle represents H2 CARS, circle represents radiation-corrected thermocouple; and solid triangle represents O2 CARS. Dotted curve is the locus of maximum temperature [62]

corrected thermocouples. The temperatures are quite similar at the cooler part of the flame but differ largely at higher concentration because the concentration is low and there is a poor signal-to-noise ratio.

6.7.8.3

Water Vapor

Water vapor is the dormant product in hydrocarbon-fueled combustion. Its measurements give the overall combustion efficiency and gauge the extent of chemical reaction [63]. Figure 6.19 demonstrates a H2 O CARS spectrum at a resolution of 1 cm–1 post CH4 -air flame region at 1700 K. In the calculation, around 1000 vibrationrotation Q branch transitions are involved at the flame temperature. The peaks observed in the spectrum emerge from spectral overlapping of different transitions. An agreement has been drawn between the theory and experiment on a temperature range of 300 to 800 K. The observed spectrum exhibits sensitivity to temperature thus

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Fig. 6.19 Comparison of theoretical and experimental H2 O CARS spectra in CH4 -air flame at 1700 K. A pressure-broadened linewidth ┌ = 0.2 cm−1 was assumed in the calculation for all transitions [63]

making water vapor attractive to CARS thermometry. However, experiment-theory agreement is attained only for a comparatively large Raman linewidth [63].

6.7.8.4

Carbon Dioxide

Carbon dioxide is another main product of the combustion of hydrocarbons. Figure 6.20 is the CARS spectrum of carbon dioxide in the post-flame region of a CO-air flame at 1520 K. Hot bands correlate with vibrational excited initial states, furthermore they appear at larger shifts. CO2 studies on CARS spectra in various flames at a fluctuating temperature show that the hot band strength is heavily dependent on temperature, thus being useful in thermometry [48]. As shown in Fig. 6.20, the theoretical and experimental calculation at a temperature of 1520 K shows a good agreement, however, there are minor discrepancies. The calculation of rotational constant, vibrational energy levels, and spontaneous Raman cross-section follows Courtoy treatment [64]. Better agreement can be obtained if the tabulated values and rotational constants are utilized [65]. Further investigation detailing the linewidth, possibly collisional narrowing, and spectral constant will likely result in a better agreement between the theory and experiment.

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Fig. 6.20 Comparison between the experimental and theoretical CO2 CARS signatures in a flame at 1520 K [48]

6.7.9 Concentration Measurement Concentration measurement derives from CARS spectral signals if the non-resonant susceptibility is suppressed or negligible [66]. As earlier alluded, species detection is limited to CARS convectional approaches with aligned polarization because of the presence of background non-resonant susceptibility. This situation is evident in Fig. 6.21, which illustrates the computer calculation for CO at 1800 K. It can be seen that at 20% concentration the CARS resonant spectrum rises well out of

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Fig. 6.21 Computer calculation of CO CARS spectra of various concentrations at 1800 K [48]

the non-resonant background and the hot band, V = 1 → 2 is entirely prominent. As the concentration decreases, the non-resonant background and the modulation become more significant. At lower concentration, the modulation is lost into the non-resonant background until the signals of the species cannot be detectable. The concentration measurements vary among the species molecules and they depend on gas composition and temperature. For closely spaced vibrational rotational transition molecules such as O2 , NO2 , and CO at a flame temperature, the concentration range is around 0.1 to 20%.

6.7.10 Computer Control Detection system comprises a spectrograph, gate, microcomputer, floppy disk system, and printer (Fig. 6.22). Multichannel analyzer (MCA) contains diode elements. The CARS signals are dispersed to the optical multichannel analyzer (Gated intensified diode array) by a spectrograph with a holographic grating [49]. Each spectrum, either as a single shot or an average of 100 laser shot is then transferred to a microcomputer. Scanning of the ISPD is controlled by random access memory (RAM), this memory provides each pixel with instructions, and later the data is stored on a floppy disk [53].

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Fig. 6.22 Schematic diagram of the detection system with associated electronics [49]

6.7.11 Acquisition of CARS Spectra and Reduction CARS spectrum data acquisition sequence starts by establishing the ratio of data signals and reference signals to determine the density measurement. Data scans are obtained under different density and temperature conditions [53]. The stored scan data is then processed by removing the background, rationed with characteristic dye laser, and fitted with theoretical spectra to determine the temperature. Once the temperature has been obtained, the concentration of the sample can be extracted.

6.7.12 Errors The main source of errors in CARS experiment is the dye laser output. Fluctuations in dye laser output causes distortion in the spectra of species thus making it appear colder or hotter than the actual flame temperature [67]. Additionally, non-resonant background, temperature fluctuation also causes errors in CARS experiments. In low resolution, CARS spectrum is not extremely sensitive to laser linewidth which causes interference [68]. To solve this, the detector linewidth functions and system laser must be convolved into the theoretical spectra [13].

6.7.13 System Calibration The accuracy of concentration measurement can be exhibited by comparing the suppressed non-resonant susceptibility with the concentration determined from the shape of CARS spectra in the presence of background, i.e., aligned polarization on a flat flame burner [45]. Whereas, the precision of CARS temperature measurement

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Fig. 6.23 Calibration data from fiat flame burner [53]

can be demonstrated using a flat flame burner with controlled temperature profile [69]. Figure 6.23 shows the calculated and CARS values for nitrogen and oxygen density and temperature. The CARS values were the mean of 100 data shots, oxygen concentration measurement had a minimum detectable limit of around 1 × 1017 molecules/cc.

6.8 Commonly Used CARS Microspectroscopy Schemes 6.8.1 Narrowband CARS The narrowband CARS scheme uses a pair of time-synchronized laser oscillators to generate two trains of narrowband picosecond pulses with negligible time jitter [30]. The degenerate pump and probe beam are one, and the Stokes beam is the other. The difference in wavelength between the two beams can be adjusted, enabling the device to address various Raman bands. The two beams are combined to spread collinearly and sent to the microscope, where a high N.A. objective lens focuses them onto the sample. The main benefit of the narrowband CARS setup is its fast acquisition speed, which allows signal collection on a microsecond time scale, allowing for high-speed

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Fig. 6.24 Single-beam CARS with a spectral hole principle. a A frequency domain image with a narrowband probe wavelength λr and a signal wavelength sig shifted by the characteristic vibrational frequency Ω R . b pump/Stokes and probe pulse time domain picture [71]

CARS imaging [70]. Despite this, there are a few drawbacks to the scheme. The first is that only one Raman band can be handled at any given time, and selective imaging of multiple bands necessitates machine tuning, which causes instability and jitter. Second, since distinguishing the non-resonant background from the signal is difficult, most imaging is achieved with solid C-H stretching signals, which experience less background distortion. An example of a narrowband CARS is shown in Fig. 6.24 below.

6.8.2 Broadband CARS The broadband/multiplex CARS scheme, which is commonly used, provides the Stokes beam with a broadband femtosecond laser rather than a narrowband picosecond laser. A spectrometer with a multichannel detector, such as a CCD camera, is used for detection. In this way, a wide range of Raman bands can be stimulated and detected at the same time, and the scanning of the laser focus produces a hyperspectral image in which each pixel contains all the sample’s spectral information. The ability to remove the CARS signal in the context of post-processing methods such as maximum entropy [72] or the Kramers–Kronig relation [73] is a major benefit of the broadband CARS scheme. However, in comparison to the narrowband CARS scheme, the multiplex CARS setup’s unbalanced temporal duration of the picosecond pump/probe beam and the femtosecond Stokes beam results in less effective CARS signal generation, resulting in a longer integration period, usually on the order of milliseconds.

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Fig. 6.25 An energy level diagram of the dual-broadband rotational CARS process, where ω1 and ω2 are broadband lasers and ω3 is a narrow-band laser [12]

6.8.2.1

Dual-Broadband Rotational CARS (DB-CARS)

An example of the Broadband CARS is the Dual-broadband rotational CARS (DBCARS). Figure 6.25 illustrates the energy of this CARS. Arrows 1 and 2 in the figure show two broadband laser beams (typically from a dye laser with a red stable dye), while the arrow 3 represents a narrow-band beam (normally from a frequencydoubled Nd:YAG laser at 532 nm). It also shows the process with an energy level diagram as well as a schematic figure depicting laser spectral material and a rotational CARS spectrum. Single-shot measurements of the rotational CARS spectrum, even at flame temperatures, can be achieved using a laser with a very wide spectral range. Since all Raman resonances are powered by multiple pairs of laser photons, the dualbroadband method has the advantage of obtaining a spectral averaging effect [74]. The spectral averaging effect implies greater precision, which is critical in realistic measurements that involve single-shot data.

6.8.3 Time and Frequency Domain CARS While the non-resonant background signal is produced instantly during the overlapping period between the excitation pulses, the time domain CARS process allows for a specific coherence lifetime based on the decay term nm, and hence the CARS signal

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has a different decay curve than the non-resonant background signal. The scheme was able to measure the Raman free induction decay in a relatively narrow spectral region (200 cm–1 ) using a relatively narrow spectral region (200 cm–1 ). Later, using the SC from fibers, identification of a wide range of Raman bands was achieved [75]. To achieve the best signal-to-background ratio, the temporal shape of the probe pulse can be optimized using the femtosecond adaptive spectroscopic technique (FAST) [76] or a dedicated spectral filter. The key drawback of this scheme is that delay scanning is usually slow, limiting the frame rate that can be achieved in imaging. Fast scanning methods that can run up to 20000 spectra per second and scan a large field-of-view have recently been proposed, indicating the potential for high-speed microscopic applications in the future.

6.9 Phase Matching Phase matching identifies the best experimental conditions that ensure the largest CARS emission. Different techniques have been employed to achieve this condition as demonstrated in Fig. 6.26. Phase matching requires that 2k1 = k2 + k3 as shown in Fig. 6.26a, ki is the wave vector at frequency ωi with a magnitude equal to ωi ni / c, where c is the speed of light and ni is the refractive index at frequency ωi [77]. Collinear phase-matching results in often ambiguous and poor spatial resolution. Crossed-beam phase-matching method is demonstrated in most CARS applications due to its unambiguous spatial resolution. In BOXCARS schemes, the pump beam is split into two parts that are made to cross at a certain angle, determined by the focusing lens. The optical arrangement of the beams can be either coplanar (planar BOXCARS) or 3D (folded BOXCARS) (see Figs. 6.7 and 6.27). Either approach will guarantee spatial resolutions as high as 1mm, or even better.

6.10 Introduction to Femtosecond Adaptive Spectroscopic Technique CARS (Fast CARS) Due to the temporal overlap between the probe and pump/Stokes fields in the traditional CARS scheme, as shown in Fig. 6.28c, the non-resonant context is solid. In the FAST CARS scheme, the difference between long-lived vibrational coherence and instantaneous non-resonant background is exploited, and a delay on the probe relative to the pump/Stokes pulse is used to greatly suppress the non-resonant background while preserving a large portion of the CARS signal. Unlike in time-resolved CARS, where only a delay between pulses is used, the probe laser pulse in FAST CARS is also formed to increase the signal-to-background ratio. Figures 6.28b and d show the FAST CARS scheme, in which the probe pulse has its node overlapped

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Fig. 6.26 CARS phase-matching approaches. a General, b collinear phase-matching, c crossed-beam phase-matching or BOXCARS [77]

with the pump/Stokes pulse to eliminate temporal overlap and suppress non-resonant history, while the main portion of the probe pulse still interacts with the vibrational coherence and produces CARS signals [76].

6.11 Typical Examples of Vibrational CARS Spectra: N2 and Other Simple Molecules It is privileged that the general attributes of a CARS measurement are detectable in nitrogen spectra. Nitrogen is one of the main components of air-fed combustion environments which make it convenient and is observed in both cold and hot zones. Based on its omnipresence, nitrogen is liable for the extensive use of CARS in a thermometric sense, which advocates its further details. Interpretation of CARS

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Fig. 6.27 BOXCARS configurations for degenerate CARS (i.e., two pump lasers plus the Stokes shifted beam). Laser propagation is from the left to the right. In the planar set-up, one pump beam coincides with the Stokes laser. The CARS beam is in blue color [20]

depends upon accurate knowledge of the molecular parameters. According to the analysis based on the importance of nitrogen in CARS measurements, enough investigations have been operated on spectral constants and linewidth data to assist in the decoding of thermal information = [78–83]. Typical nitrogen CARS spectra, using such data, are shown in Fig. 6.29 for the case of a multimode pump laser in degenerate configuration; the distinguishing features of these spectra are summarized as follows. Nitrogen and other CARS molecules show spectral bands associated with isotropic Q-branch transitions, the rotational level J is unaltered and the vibrational level v changes by one unit here. Specifically, Fig. 6.29 shows a first (cold) band instantly below 2330 cm–1 , and a second (hot) band starting from 2300 cm–1 downward. Here, the first band groups transition from the basic vibrational level with v = 0 to the first excited level v =1; the second band does the same, but for transitions ranging from v = 1 to v = 2. The two bands are finely distinguished by the rotational manifold, although this is unresolved at T = 300 K due to the finite spectral bandwidth of the laser beams. while, at higher temperatures, the fine structure becomes visible such that increasing the temperature will results in the following main properties: (i) the cold band widens because higher rotational levels are summoned up by the higher thermal energies, (ii) a shift of the maximum which can be elucidated by the lower rotational levels to become progressively abandoned with growing temperatures, and (iii) an explanation of the virtual reputation of the hot bands that become prominent. In Fig. 6.29, the line overlaps cannot be ignored. The breakdown of the remote lines estimate is clear. The authentic appearance of a measured N2 CARS spectrum is shown in Fig. 6.30.

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Fig. 6.28 Energy diagrams of a CARS and b femtosecond adaptive spectroscopic technique (FAST) CARS processes, and temporal pictures of c CARS and d FAST CARS processes. ωp : pump; ωs : Stokes; ωPr : signal; ωsig : signal; ΩR : characteristic Raman shift [18]

Here in the data symbols were attained utilizing a set-up containing a degenerate pump and a broadband Stokes source. The rotational structure of the cold band was identifiable, on the other hand, the presence of the first hot band implies the laser surveyed a region of high temperatures Contour fitting is in order if a piece of quantitative thermometric information is required for the data of Fig. 6.31. For this, the fit is plotted with a continuous line. Particularly, interference effects, collisional narrowing, and enlarging mechanisms of linewidths were each involved in the physical type that pays to the fitting procedure. This provided a temperature of approximately 2200 K, which was sufficiently close to the adiabatic temperature of the methane-air flame considered in the example (2226 K). As Fig. 6.30 refers to nitrogen CARS measured with a multimode pump laser, a spectral overlap was predictable. In single-mode operation, however, the overlap would be effectively minimized, and the rotational structure so determined that an attempt with isolated lines might be appropriate. However, the role of the G-matrix

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Fig. 6.29 Theoretical spectra of nitrogen CARS with multimode pump laser at different temperatures [20]

Fig. 6.30 Measured nitrogen CARS (symbols) and contour fit (line) [20]

approach especially at high pressure cannot be ignored. Indeed, with nitrogen CARS being considered as the “benchmark” for the general modeling of CARS diagnostics for combustion processes, there is a surplus of studies being commenced to ascertain its widespread features. It is agreed that thermometric accuracy is on the order of a few tens of degrees Kelvin for stationary flames, with the highest value of only 9 K at approximately 2100 K [48].

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Fig. 6.31 Hydrogen CARS spectra. The horizontal axis is the same for all the plots. The vertical axis is normalized to the maximum peak of each plot [20]

The plot in Fig. 6.31a was recorded at room temperature, is characterized by a single (cold) peak, although at higher temperatures this inclined to become less important in the indulgence of the hot peaks which appeared with an evolution that could conceptually be organized to create a thermometric marker. Beyond N2 and H2 , other diatomic considered for diagnostic studies may include O2 . The spectrum of Indeed, the spectrum of O2 and N2 closely resembles (Fig. 6.32). The reason for such resemblance remains in the close numerical values of the molecular constants of nitrogen and oxygen. It is well-known that rotational CARS spectra exhibit reduced temperature sensitivity at high temperatures [84]. For each species, the time-domain response is characterized by well-defined recurrence peaks, with a period that is inversely proportional to the well-defined spacing between the lines in the respective rotational Raman frequency spectra [85]. So much attention has been paid to homonuclear diatomic, and it may be useful at this stage to consider the case of carbon monoxide, as a heteronuclear diatomic often used in CARS investigations. The typical spectrum is shown in Fig. 6.33 relative to a specific case of low CO concentrations.

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Fig. 6.32 Measurement precision in both temperature and O2 /N2 ratio as a function of peak signalto-noise ratio [84]

Fig. 6.33 Carbon monoxide CARS spectrum [20]

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6.12 General Applications There are several general applications of CARS and the practical application includes CARS temperature measurement. The first CARS application measurements on a combustion device were performed at ONERA in 1978 [86]. In the figure, there is a temperature measurement in the jet fuel in Fig. 6.34. Nowadays, the procedure is utilized in numerous scientific specialties except combustion. Within regards to the field of combustion, it includes the studies of jet engines, internal combustion engines, coal gasifiers, furnaces, exhausts in a magnetohydrodynamic (MHD) environment, propellant burning, and scramjets. Specifically, to map the internal volume of a Dry Low-NOx combustor (General Electric thermometric measurements were undertaken, model DLE for gas turbines LM 1600, 2500, and 6000). This was outfitted with a few leading methane/air nozzles in the main body, encircled by a group of secondary nozzles to steady the flame in the presence of a high air flux. The body of the chamber combustor was modified to guarantee an optical accomplishment as shown in the figure for the focusing and collecting lenses. The finishing structure is displayed at a tower with motorized translators authorized for 3D scanning in the combustion chamber. The signal of broadband N2 CARS in a planar BOXCARS configuration was accumulated by a lens of 30 cm focal length, as well as directed to a Jobin-Yvon spectrograph (model HR 640, Czerny–Turner type) operating with a holographic diffraction grating of 3000 grooves per mm. Subsequent ignitions in the burner, a series of single-shot measurements was attained for each position inside the combustion chamber. This series was controlled with a histogram (bar size 25 K), and the temperature determination was provided after statistical elaboration. The data in the figure elaborates on the general results also the maximum temperatures were close to 2000 K in the proximity of the fuel nozzles in the figure. Measurements along this axis are described in the upper right-hand graph of Fig. 6.35.

Fig. 6.34 CARS temperature measurements in a swirl burner with a jet fuel [87]

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Fig. 6.35 Pictures and thermometric results along with horizontal (top, right-hand plot) and vertical (lower, left-hand plots) lines scanned inside the combustion chamber. The picture at the top is a side view of the gas inlet. The vertical crosscuts (red) were taken at 2, 20, 40, and 50 mm from the burner head. The horizontal crosscut (blue) was scanned along the burner axis. The image at the lower right shows the combustor with some parts of the optical (focusing and collecting lenses) and mechanical (movable turret) set-up [20]

6.12.1 Application of CARS in Coal-Seeded Flames A set of single-shot coal seeded spectra obtained in a fuel-lean natural gas-air flame. Histograms are shown in Fig. 6.36 for single-shot data sets. Because of a lack of signals or poor analyzers, most of the sets are rejected. The shots were discarded which were a note of use and not incorporated in the mean temperature calculations. There is a bimodal temperature distribution at the 1.27- and 2.54-cm locations. This is because of a wrinkled flame surface that is an object of the burner. This wrinkled flame surface was not nearly as pronounced at higher coal feed rates and more fuel-rich flames [51]. The temperature distribution narrows and then starts to decrease by the 12.70-cm location when the particles and gases progress set down the reactor. This is indicated by the near Gaussian-shaped temperature profiles shown in Fig. 6.37. Steady temperature dimensions can be attained from coal-needed natural gas-air flames due to the spectra signature from this data temperature derived do not depend upon the level of background in the individual spectra. The background does not manipulate and conceal the CARS signal.

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Fig. 6.36 CARS temperature histograms for single-shot spectra obtained in a fuel-lean natural gas-air flame seeded with 46 mg/L of Alberta coal particles [51]

6.12.2 Application of CARS in Turbulent Combustion The CARS signal in turbulent combustion relies upon the temperature and gas volume density. This offers the prospect to find the concentrations by CARS. The present state of research is that concentration measurements in turbulent diffusion flames using vibrational CARS have been extensively used. Relatively its precision is low because the parameters affecting CARS intensity, mainly non-resonant background and laserbeam overlap inside the probe volume, are less accurate and are not constant. Rotational CARS in association with Fourier-transformation assessment of spectra [88] has many advantages over the vibrational CARS methods and even mixtures can be analyzed accurately in some circumstances. While understanding the dynamics of

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Fig. 6.37 CARS temperature profiles for fuel-rich natural gas-air flames seeded with Alberta coal particles [51]

turbulent reacting flows involves a measurement technique providing instantaneous measurements of medium properties at a satisfactory data rate. CARS occupies this feature also the capability to function successfully in the intimidating environments of practical combustion flames.

6.13 Advantages and Disadvantages of CARS 6.13.1 Advantages of CARS (1) High Raman conversion efficiencies can be instantly obtained. (2) Compilation efficiencies are satisfactory because CARS is generated in a laserlike beam. (3) The monochromator is not necessary as well as spectral width established by the laser linewidth. (4) Moderately high resolution is routine by CARS because lasers of such line widths are easily reasonable. (5) LIF and spontaneous emission from flames, plasmas, and discharges are usually not blocked by CARS because of the cohesion and spectral properties of the phenomenon. (6) Due to the higher conversion efficiencies innovative and interesting experiments in photochemistry, kinetics and molecular relaxation, and fluid dynamics appear to be possible. (7) CARS involves four waves, appears to be more information available in calculating polarization ratios.

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6.13.2 Disadvantages of CARS (1) The most serious problem with CARS as an analytical tool is the generation of background radiation because of the non-resonant part of the susceptibility which limits, at present, detection ~1% for the aqueous solution and about 10 ppm in gases. (2) The method is most likely not useful for media with large losses, e.g., opaque, strongly absorbing, or scattering materials. (3) Equipment is not cost-effective, packaged commercial units are available. (4) Possibility of sample damage is always high with high-power lasers. (5) CARS signal or laser power, number density, and line width dependency is strong. (6) Interactions with adjacent resonances, background, and electronic transitions may cause strong danger to the CARS spectrum.

6.14 Summary This technique is used chiefly as a tool for thermometric purposes. CARS spectroscopy does not let itself understand and is built on elementary concepts. The physical explanation of its feature was followed by a richer analysis of the CARS signal and its spectral dependencies on laser and molecular parameters. One of the most difficult parts of CARS diagnostics, namely the physical characterization of the CARS molecule, was then described. CARS spectroscopy is stranded on a third-order optical process such that three laser fields must be merged. The use of more than one laser leads to complications, including the phase-matching conditions and experimental geometry required for the CARS amplitude and spatial resolution. Regardless Of these difficulties, vibrational N2 CARS is obvious in combustion science, as well as the characteristics of high-temperature spectra have been highlighted. In conclusion, it is suggested that CARS will continue to undergo a further examination with concern to its more advanced use. These will bear a limited imaging capacity, the combination with other spectroscopic techniques, ultra-fast excitations, conceptual strategies of data handling that avoid the need for a piece of prior knowledge, and applications in micro combustion.

6.15 Exercises (1) Individual task: Find a research paper and describe the phase-matching concept. Highlights on working principle of BOXCARS. (2) Group task: In small groups, find a literature paper and make a presentation on the applications of CARS.

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6.16 Questions (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

State the two measurements that can be detected and studied by CARS. State the advantages and limitations of CARS. Describe the working mechanism of the CARS system. State the advantages of folded BOXCARS configuration over planar configuration. Illustrate on laser and signal generation in CARS. Why 2nd:YAG are most popular? Why are high-quality quartz windows used in the combustion chamber? Explain the combustion chamber used to generate CARS signals. State the factors affecting the CARS signal and how can weak CARS signal be strengthened. Why is a reference system necessary in CARS study? State the source of errors in CARS and explain how to solve them.

References 1. Roy, S., et al. (2010). Recent advances in coherent anti-Stokes Raman scattering spectroscopy: Fundamental developments and applications in reacting flows. Progress in Energy and Combustion Science, 36(2), 280–306. 2. Freudiger, C. W., et al. (2008). Label-free biomedical imaging with high sensitivity by stimulated Raman scattering microscopy. Science, 322(5909), 1857–1861. 3. Zumbusch, A., et al. (1999). Three-dimensional vibrational imaging by coherent anti-Stokes Raman scattering. Physical Review Letters, 82(20), 4142. 4. Marrocco, M. (2015). Closed-form solutions of coherent anti-Stokes Raman signals generated by means of time asymmetric probe pulses. Journal of Raman Spectroscopy, 46(8), 683–690. 5. Evans, C. L., & Xie, X. S. (2008). Coherent anti-Stokes Raman scattering microscopy: Chemical imaging for biology and medicine. Annual Review of Analytical Chemistry, 1, 883–909. 6. Koivistoinen, J., et al. (2017). Time-resolved coherent anti-Stokes Raman scattering of graphene: Dephasing dynamics of optical phonon. The journal of physical chemistry letters, 8(17), 4108–4112. 7. Cheng, J. X., & Xie, X. S. (2016). Coherent Raman scattering microscopy. CRC press 8. Ariunbold, G. O., & Altangerel, N. (2016). Coherent anti-Stokes Raman spectroscopy: Understanding the essentials. Coherent Phenomena, 3(1), 6–17. 9. Zhi, M. (2007). Broadband coherent light generation in Raman-active crystals driven by femtosecond laser fields. Texas A&M University 10. El-Diasty, F. (2011). Coherent anti-Stokes Raman scattering: Spectroscopy and microscopy. Vibrational Spectroscopy, 55(1), 1–37 11. Pegoraro, A. F. (2011). Developing single-laser sources for multimodal coherent anti-Stokes Raman scattering microscopy 12. Brackmann, C., et al. (2004). Thermometry in internal combustion engines via dual-broadband rotational coherent anti-Stokes Raman spectroscopy. Measurement Science and Technology, 15(3), R13. 13. Yuratich, M. (1979). Effects of laser linewidth on coherent antiStokes Raman spectroscopy. 38(2), 625–655

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14. Hall, R. (1979). CARS spectra of combustion gases. 35, 47–60 15. Hall, R. (1983). Coherent anti-Stokes Raman spectroscopic modeling for combustion diagnostics. 22(3), 223322 16. Goss, L., et al. (1983). 10-Hz coherent anti-Stokes Raman spectroscopy apparatus for turbulent combustion studies. 54(5), 563–571 17. Kataoka, H., et al. (1982). Effects of laser linewidth on the coherent anti-Stokes Raman spectroscopy spectral profile. 36(5), 565–569 18. Rahn, L., et al. (1984). Effects of laser field statistics on coherent anti-Stokes Raman spectroscopy intensities. 9(6), 223–225 19. Teets, R. E. (1984). Accurate convolutions of coherent anti-Stokes Raman spectra. 9(6), 226– 228 20. Marrocco, M. (2010). CARS spectroscopy. 155–188 21. Yueh, F., & Beiting, E. (1986). Analytical expressions for coherent anti-Stokes Raman spectral (CARS) profiles. 42(1), 65–71 22. Clark, R. J. H., & Hester, R. E. (Eds.). (1988). Advances in non-linear spectroscopy 23. Koechner, W. (1999). Properties of solid-state laser materials. Solid-State Laser Engineering (pp. 28–87). Springer 24. Marrocco, M. (2007). A quantitative approach to evaluate the problem of coherence of spectral components of the third-order susceptibility generating coherent anti-Stokes Raman signals. Journal of Raman Spectroscopy: An International Journal for Original Work in all Aspects of Raman Spectroscopy, Including Higher Order Processes, and also Brillouin and Rayleigh Scattering, 38(4), 452–459. 25. Marrocco, M. (2007). General criterion to discern between coherent and incoherent synthesis of broadband coherent anti-Stokes Raman spectra. Journal of Raman Spectroscopy: An International Journal for Original Work in all Aspects of Raman Spectroscopy, Including Higher Order Processes, and also Brillouin and Rayleigh Scattering, 38(10), 1338–1344. 26. Huber, K. P. (1979). Constants of diatomic molecules. Molecular Spectra and Molecular Structure, 4, 146–291. 27. Eckbreth, A. C. (1996). Laser diagnostics for combustion temperature and species (Vol. 3). CRC press 28. Min, W., et al. (2011). Coherent nonlinear optical imaging: Beyond fluorescence microscopy. Annual Review of Physical Chemistry, 62, 507–530. 29. Shipp, D. W., et al. (2017). Raman spectroscopy: Techniques and applications in the life sciences. Advances in Optics and Photonics, 9(2), 315–428. 30. Potma, E. O., et al. (2002). High-sensitivity coherent anti-Stokes Raman scattering microscopy with two tightly synchronized picosecond lasers. Optics Letters, 27(13), 1168–1170. 31. De Martini, F., et al. (1973). High-Resolution Nonlinear Spectroscopy of Molecular Vibrational Resonances in Gases. 549 32. Harvey, A., & Nibler, J. (1978). Coherent anti-Stokes Raman spectroscopy of gases. 14(1), 101–143 33. Regnier, P. (1973). Application of coherent anti-Stokes Raman scattering to gas concentration measurements and to flow visualization. (215), 92320 34. Terhune, R. W., & Maker, P. D. (1968). Lasers, Vol. 2, Ch. AK Levine 35. Regnier, P., et al. (1974). Gas concentration measurement by coherent Raman anti-Stokes scattering. 12(6), 826–831 36. Wynne, J. (1972). A new type of nonlinear spectroscopy using tunable lasers. 8(6), 607–607 37. Tolles, W. M., et al. (1977). A review of the theory and application of coherent anti-Stokes Raman spectroscopy (CARS). 31(4), 253–271 38. Begley, R., et al. (1974). Coherent anti-Stokes Raman spectroscopy. 25(7), 387–390 39. Shaub, W., et al. (1977). Direct determination of non-Boltzmann vibrational level populations in electric discharges by CARS. 67(5), 1883–1886 40. Magnotti, G., et al. (2013). Development of a dual-pump coherent anti-Stokes Raman spectroscopy system for measurements in supersonic combustion. 52(20), 4779–4791

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41. Brackmann, C., et al. (2004). Thermometry in internal combustion engines via dual-broadband rotational coherent anti-Stokes Raman spectroscopy. 15(3), R13 42. Magnotti, G., et al. (2012). Saturation and Stark broadening effects in dual-pump CARS of N2, O2, and H2. 43(5), 611–620 43. Hänsch, T. W. (1972). Repetitively pulsed tunable dye laser for high resolution spectroscopy. 11(4), 895–898 44. Wallenstein, R., & Hänsch, T. (1974). Linear pressure tuning of a multielement dye laser spectrometer. 13(7), 1625–1628 45. Eckbreth, A. C., & Hall, R. J. (1981). CARS concentration sensitivity with and without nonresonant background suppression 46. Eckbreth, A. C. (1980). CARS thermometry in practical combustors. 39(2), 133–147 47. Shirley, J. A., et al. (1980). Folded BOXCARS for rotational Raman studies. 5(9), 380–382 48. Hall, R. J., & Eckbreth, A. C. (1981). Combustion diagnosis by coherent anti-Stokes Raman spectroscopy (CARS). 20(4), 204494 49. Greenhalgh, D. A., et al. (1983). The application of coherent anti-Stokes Raman scattering to turbulent combustion thermometry. 49(1–3), 171–181 50. Beer, J. M., & Chigier N. A. (1972). Combustion Aerodynamics. Appl. Sci. Publ. LTD 51. Hancock, R. D., et al. (1991). Coherent anti-Stokes Raman spectroscopy (CARS) measurements in coal-seeded flames. 87(1), 77–88 52. Teets, R. E. (1986). CARS signals: Phase matching, transverse modes, and optical damage effects. 25(6), 855–862 53. Antcliff, R. R., & Jarrett Jr, O. (1987). Multispecies coherent anti-Stokes Raman scattering instrument for turbulent combustion. 58(11), 2075–2080 54. Rado, W. (1967). The nonlinear third order dielectric susceptibility coefficients of gases and optical third harmonic generation. 11(4), 123–125 55. Moya, F., et al. (1975). Gas spectroscopy and temperature measurement by coherent Raman anti-Stokes scattering. 13(2), 169–174 56. Demartini, F. (1971). High resolution nonlinear spectroscopy of molecular vibrational resonances in gases (Nonlinear optical effects applied to Raman vibrational resonance in gases) 57. Regnier, P. R., & Taran, J. E. (1973). On the possibility of measuring gas concentrations by stimulated anti-Stokes scattering. Applied Physics Letters, 23(5), 240–242. 58. Moya, F., et al. (1976). Flame investigation by coherent anti-Stokes Raman scattering. Paper presented at the 14th Aerospace Sciences Meeting 59. Rahn, L. A., et al. (1979). Background-free CARS studies of carbon monoxide in a flame. 30(2), 249–252 60. Eckbreth, A. C., & Hall, R. J. (1979). CARS diagnostic investigations of flames. Paper presented at the Proc. 10th Materials Res. Symp. on Characterization of High Temperature Vapors and Gases 61. Beattie, I. R., et al. (1978). An approach to rotational temperatures of nitrogen in diffusion flames using Coherent Anti-Stokes Raman scattering 62. Shirley, J., et al. (1980). Investigation of the feasibility of CARS measurements in scramjet combustion: National Aeronautics and Space Administration, Langley Research Center 63. Shirley, J., & Hall, R. (1981). Investigation of the Cars Spectrum of Water Vapor. United Technologies Research Center East Hartford Ct 64. Stull, V. R., et al. (1962). Vibrational energies of the CO2 molecule. 37(7), 1442–1445. https:/ /doi.org/10.1063/1.1733302 65. Rothman, L., & Benedict, W. (1978). Infrared energy levels and intensities of carbon dioxide. 17(16), 2605–2611 66. Roh, W. B., & Schreiber, P. W. (1978). Pressure dependence of integrated CARS power. 17(9), 1418–1424 67. Kröll, S., et al. (1989). An evaluation of precision and systematic errors in vibrational CARS thermometry. 49(5), 445–453

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68. Hall, R. J., & Boedeker, L. R. (1984). CARS thermometry in fuel-rich combustion zones. 23(9), 1340–1346 69. Roux, J., & McCay, T. (1984). Combustion diagnostics by nonintrusive methods. In: American Institute of Aeronautics and Astronautics 70. Evans, C. L., et al. (2005). Chemical imaging of tissue in vivo with video-rate coherent anti-Stokes Raman scattering microscopy. Proceedings of the National Academy of Sciences, 102(46), 16807–16812. 71. Shen, Y. (2018). Towards fast coherent anti-Stokes Raman scattering microspectroscopy 72. Rinia, H. A., et al. (2007). Quantitative CARS spectroscopy using the maximum entropy method: The main lipid phase transition. ChemPhysChem, 8(2), 279–287. 73. Liu, Y., et al. (2009). Broadband CARS spectral phase retrieval using a time-domain KramersKronig transform. Optics Letters, 34(9), 1363–1365. 74. Afzelius M., & Bengtsson P. E. (2003). Development of dual-broadband rotational CARS for practical applications Poster presented at the European Conf. on Non-linear Spectroscopy (ECONOS) (Besancon, March–April) 75. Lang, T., & Motzkus, M. (2002). Single-shot femtosecond coherent anti-Stokes Ramanscattering thermometry. JOSA B, 19(2), 340–344. 76. Pestov, D., et al. (2007). Optimizing the laser-pulse configuration for coherent Raman spectroscopy. 316(5822), 265–268 77. Eckbreth, A. C. (1978). BOXCARS: Crossed-beam phase-matched CARS generation in gases. 32(7), 421–423 78. Millot, G., et al. (1992). Collisional effects in the stimulated Raman Q branch of O2 and O2–N2. 96(2), 961–971 79. Rosasco, G., et al. (1983). Line interference effects in the vibrational Q-branch spectra of N2 and CO. 97(4–5), 435–440 80. Lavorel, B., et al. (1995). Collisional Raman linewidths of nitrogen at high temperature (1700– 2400 K). 20(10), 1189–1191 81. Porter, F., et al. (1990). A study of CARS nitrogen thermometry at high pressure. 51(1), 31–38 82. Dreier, T., et al. (1994). Collisional effects in Q branch coherent anti-Stokes Raman spectra of N2 and O2 at high pressure and high temperature. 100(9), 6275–6289 83. Gilson, T., et al. (1980). Redetermination of some of the spectroscopic constants of the electronic ground state of di-Nitrogen 14 N2 14 N, 15 N and 15 N2 using coherent anti-stokes Raman spectroscopy. 9(6), 361–368 84. Kröll, S., et al. (1990). Is rotational CARS an alternative to vibrational CARS for thermometry? , 51(1), 25–30 85. Stauffer, H. U., et al. (2012). Communication: Hybrid femtosecond/picosecond rotational coherent anti-Stokes Raman scattering thermometry using a narrowband time-asymmetric probe pulse. American Institute of Physics 86. Attal, B., et al. (1980). CARS diagnostics of combustion. 4(3), 135–141 87. Verdieck, J., et al. (1982). Some applications of gas phase CARS spectroscopy. ACS Publications 88. Seeger, T., & Leipertz, A. (1996). Experimental comparison of single-shot broadband vibrational and dual-broadband pure rotational coherent anti-Stokes Raman scattering in hot air. 35(15), 2665–2671

Chapter 7

Laser-Induced Fluorescence in Combustion Research Vestince Balidi Mbayachi, Zhen-Yu Tian, Xu Zhang, Maria Khalil, and Daniel A. Ayejoto

7.1 Introduction Laser-based diagnostics has developed the understanding of the complex combustion process which is administered by the interaction of chemistry as well as flow in the combustion with heat and mass transfer. The most sophisticated and well-reputable diagnostic tool is laser-induced fluorescence; this technique is serving as an absorption–emission process. In this process, there is resonant excitation along with laser radiation. The excited molecule can release energy due to immediate radiation emission, specifically called fluorescence. Beside, other processes can cause nonradiative because of excited particles. The mechanism depends upon the settings of the excited particles also fluorescing with special composition, pressure, and temperature. Because of the extinguishing behavior of the process in the combustion system, the measurable understanding of the LIF signal is relatively challenging. V. B. Mbayachi · X. Zhang Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China e-mail: [email protected]; [email protected] V. B. Mbayachi · Z.-Y. Tian (B) · M. Khalil · D. A. Ayejoto University of Chinese Academy of Sciences, Beijing 100049, China e-mail: [email protected] Z.-Y. Tian Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China X. Zhang School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_7

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Fig. 7.1 Experimental arrangement for 205 nm excitation of atomic hydrogen TP-LIF in flames using ns- and ps-laser pulses. The 656 nm fluorescence is imaged perpendicular to the laser propagation direction and detected by an ICCD using a Gen III intensifier. Forward-propagating SE (dashed lines) is detected with a silicon pi-n photodiode (PD). HG: third-harmonic generation; CL1: f = 1:4 50 mm camera lens; CL2: f = 1:2 50 mm camera lens; IF Hα interference filter; DM: 205 nm dichroic mirror; JM: pyroelectric joulemeter; BK7: 9:5 mm thick glass flat; ND: calibrated neutral density filters [1]

On account of the resonant character of the excitation method, large crosssectional interaction, fewer species at low concentration levels can also be explored. In this technique as shown in Fig. 7.1, molecular and atomic flame radicals or pollutant species can precisely be detected with the single-photon absorption method, for instance, OH, CH, NO, or Formaldehyde [1], or by tuning the excitation laser to the wavelength where species absorb two photons at a time, for instance, O, H, N, and CO. In addition to the aforementioned species that is present naturally in the fluorescence tracer, molecules can be further added to the combustion flame system as it acts as a gauge for specific parameters such as mixture composition or temperature. Hypothetically, various strategies occur for combustion study phenomenon by LIF retaining. In the investigation of basic chemistry mechanisms, the utilization of laminar flames and quantitative concentration or temperature measurement is performed. This is attained by step-by-step point-wise scanning of an object of examination. With the study of complex flow phenomenon, planar LIF (PLIF) is frequently employed to attain 2D information regarding mixture and flame structure at once and immediately by using the light technique. These experimentations have brought a huge amount of appreciated data concerning flow structures and the interaction between flow phenomenon and combustion chemistry. These kinds of experiments are frequently directed with the tools working at the repetitive rate of up to 100 Hz. This is applied to the turbulent combustion and pulse-to-pulse separation that is much larger than typical integral time scales of turbulent flames; moreover, this result is statistically not correlated information. Various functional data is deduced using this data as well as turbulent flames are temporary in nature and cannot be stated by stationary conditions. These also comprise spark or itself ignition, flame extermination, and the cyclic disparity in internal combustion engines. To understand this process, it is obligatory to have a sequential tracking of the flow and scalar fields. Progressively, tracking requires the

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attainment of temporally correlate data, and its rate is much faster rather than typical time scales of turbulent flows, and it is only possible with high repetition-rate laser sources and detection systems.

7.2 Theory Fluorescence can have the same frequency as the absorption or different frequencies when energy transfer to lower energy levels happens before the fluorescence is released. There are two states while considering a shortened two-level system (ground state 1 and excited state 2), the signal intensity Sf in the linear rule, here the fluorescence intensity is linearly proportional to the irradiated laser intensity as given [2]: Sf α A21 .v21 .l × N10 .Ilaser .

B12 A21 + Q 21

(7.1)

where A21 and B12 are the Einstein coefficients for spontaneous emission and absorption, n21 is the frequency of the emitted fluorescence photons, N0 1 is the initial ground state population number density of the species probed, the laser is the laser intensity, and Q21 is the quenching rate: ( ) ∑ E nf σ(λ, T)ϕ λ, T, p, χi Sf = hc/λ i

(7.2)

The equation is modified for practical purposes to introduce practically relevant quantities. In the linear regime, the fluorescence signal Sf emitted from a sample volume Ve can be calculated as ( ) ∑ Sf ∝ nf .ϕ Xi (7.3) i

where E is the laser fluence, hc/l is the energy of a photon, s(l, T) is the absorption cross-section as a function of wavelength l and temperature T, and W(l, T, p, Sxi ) is the fluorescence quantum yield (FQY) as a function of wavelength, temperature, pressure p, and gas composition xi. nf specifies the molecular number density of the molecules, which should be excited to fluorescence. For some combustion applications, pressure, temperature, and excitation wavelength are known or are considered constant. Also, the fluorescence signal Sf remains proportional to the molecular number density nf and proportional to the FQY as a function of the mixture composition: ϕ=

k f + knr

kf + kquench .n quench

(7.4)

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The FQY describes the probability of the fluorescence event of a distinctive fluorescing molecule kf k f +knr

Sf ∝ n f .

k f +knr +kquench ×n quench

k f + knr

(7.5)

It considers three different rates. kf is the rate [s−1 ] for the fluorescence event; knr is the rate for intramolecular nonradiative de-excitation processes, and kquench . nquench is the rate for quenching, which is an intermolecular nonradiative depopulation process caused by collisions with other molecules [3]. The quenching rate is proportional to the number density of quenchers; the unit of kquench is m3 s −1 . Hence, the quenching rate kquench . nquench makes the FQY a function of the gas composition. The FQY in Eq. 7.5 can be substituted by Eq. 7.6: Sf ∝ n f .

b n 1 + k Ster n−volmerquench

(7.6)

where b substitutes the nominator in Eq. 7.6 and kStern-Volmer describes the SV coefficient by k Ster n−V olmer =

kquench k f + knr

(7.7)

From Eq. 7.7, two possible quantitative LIF strategies can be derived. If kStern-Volmer is a constant for which k Ster n−V olmer .n quench ≫ 1

(7.8)

is true, then Eq. 7.6 will simplify to Sf ∝

nfuel nf ∝ nquench noxygen

(7.9)

If the fluorescing molecules are broadcasted to the fuel and the dominant quencher available is oxygen, in this case, this strategy is named fuel/air-ratio LIF (FAR-LIF). This strategy is applied to mixture analysis in an internal combustion engine, while a nonfluorescent model fuel is seeded with a special LIF tracer. Commonly used FAR-LIF tracers include toluene, benzene, xylol, and trimethylamine [4–8]. Sf ∝ n f ∝ n f uel

(7.10)

Consequently, the denominator in Eq. 7.6 is close to 1 and the fluorescence signal Sf is proportional to the tracer molecular number density. After that, the LIF signal represents the fuel molecular number density.

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Whenever kStern-Volmer-nquench is neither much bigger than 1 nor close to zero, then the quantitative interpretation of LIF signals is possible only under saturated conditions only when the laser excitation intensity is high enough to make the LIF signal insensitive toward excitation energy [9, 10].

7.3 LIF Applications 7.3.1 LIF of Combustion Species According to the experimental point of view, it’s beneficial to implement LIF measurements to use atoms or molecules present in the process under investigation. In the case of flame combustion, intermediate species-area are normally explored and they are selected fittingly selected. These species can designate the characteristic region of flame to provide information about the combustion process. Some of them are produced as transitional species during the reaction that can indicate heat release rates and the reaction boundary, although others are reactants or combustion products. There is a summary of combustion species investigated by LIF provided in the following Table 7.1. During the 1980s, the first OH was reported as the first application; several examples are describing them. As a comparison, turbulent flames are rather complex as the single species cannot provide enough information about a perfect explanation. For this, there are combinations of planar diagnostics that have been developed using PLIF of a minimum of one species. Here, the common combination is a simultaneous image of CH as well as OH radical distributions as in Fig. 7.2. Figure 7.3 shows the central region of a raw OH PLIF image (left) recorded in flame 2. The intensity distribution along the dotted line is plotted in the middle part [12]. The second pair of molecules which continue to attract interest is that of OH and formaldehyde in Fig. 7.4 because the pixel-by-pixel product of the images correlates very well in space and time with the flame heat release and variation of various peak normalized quantities at the cusp as the flow evolves in time [13, 14]. LIF is also used for the track progress of an elementary reaction to imagine the structure of the flame; here, the computational information is not necessary. In Table 7.1 Commonly used combustion species for LIF applications [11]

Species

Application

CH, C2 , HCO, CN, OH, O, H

Flame front (reaction zone)

CO, C2 H2 , CH, CH2 O, O2 , NO2 Fuel decomposition and pre-reaction zone OH, CO

Burned gas and post-reaction zone

NO, OH

Temperature

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Fig. 7.2 Simultaneous CH/OH PLIF images [11]

Fig. 7.3 Raw image (left), intensity distribution along a single-pixel line (center), binary image (right) [12]

thermochemistry, semi-computational data is required. The intensity ratio of different lines delivers information about the Boltzmann distribution and allows the derivation of temperature as in Fig. 7.5. In contrast, during the study of chemical kinetics, it is also necessary to add the quantitative concentration measures of species interest; also, there must be a deduction from the intensity of the fluorescent signal. A thorough description of quantitative LIF in flames with a discussion of influences such as quenching and

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Fig. 7.4 Variation of various peak normalized quantities at the cusp as the flow evolves in time. Plotted are heat release rate wT /wT,o , HCO mole fraction XHCO/(XHCO) [13]

Fig. 7.5 LIF temperature determination using the ratio of the fluorescence intensity Sf of two molecular levels in the initial ground state; here the Q1(35) and R1(16) lines of the NO molecule [13]

internal energy decay mechanisms is provided by Kohse-Höinghaus [15]. Several different naturally fluorescing species may also be present in the combustion systems under specific circumstances. These might include aromatics in commercial fuels [16], odor markers [17] in natural gas, or fluorescing molecules, which are generated during combustion [18] (e.g., formaldehyde as a combustion intermediate in cool flame zones before any reaction takes place).

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7.3.2 Tracer LIF The artificial addition of atoms or molecules occurs when naturally occurring species in the combustion system do not fluorescent or are not able to provide the required information and maximal LIF signal intensity. Tracers that disturb should feature the high absorption cross-section and high FQYs allowing low concentrations, and high seeding concentrations; there is the toluene-LIF signal on inverse oxygen concentration with fixed tracer number density in Fig. 7.6. A comprehensive overview of this subject is provided elsewhere [19].

7.3.2.1

Metal Salt

Metal salt is one of the tracers commonly used for LIF thermometry (temperature measurement). During the operation, metal salts such as indium chloride or indium particles are seeded using laser ablation of an indium rod to generate indium atoms in the flame. Tracers that can be applied to gas flows include indium atoms, nitric oxide (NO), and organic gaseous molecules such as aromatic hydrocarbons or ketones (e.g., toluene, acetone), whereas fluorescent dyes such as rhodamine are usually used in liquids. The temperature of flame radicals, such as hydroxyl (OH), can also be measured in particular areas of the flame. Then, depending on the spectroscopic properties of these tracers (absorption/emission, collisional quenching, temperature sensitivity, and so on), a variety of excitation and detection systems for single shot temperature imaging may be used [20].

Fig. 7.6 Dependence of the toluene-LIF signal on the inverse oxygen concentration with a fixed tracer number density [19]

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Fig. 7.7 Experimental setup for time-resolved broadband absorption measurements in the near UV at high temperatures [20]

Because of the high-temperature level, some metal salts can be atomized in the flame front when seeded into the combustion system [21]. These atoms can be excited by both ultraviolet (UV) and visible light sources after they have been formed, making them ideal for burned gas temperature measurements. However, extreme caution must be exercised in order to avoid saturating the heavy transitions. The main facilities for measuring the absorption spectra of many gases (ketones, toluene, carbon dioxide, carbon monoxide, and water) at high temperatures are depicted in Fig. 7.7.

7.3.2.2

Inorganic Molecules

Inorganic molecules are another class of tracers used for LIF thermometry (temperature measurement). They are divided into two categories which include unstable species that are generated naturally during combustion and stable molecules that must be introduced to the flow artificially. In the UV/Vis spectral field, they can be optically excited. The critical problem is the production of appropriate atoms from their (molecular) precursors, which necessitates either high temperatures (when pyrolysis is used) or extreme laser radiation (when photo-dissociation is used) [22]. Carbon dioxide’s broadband absorption spectrum changes from vacuum UV to UV at high temperatures, allowing its fluorescence to be excited with UV laser sources. Despite its toxicity, NO has been used as a LIF temperature indicator (Fig. 7.8). Evaporative cooling effects may be studied even under extremely difficult spray conditions [23].

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Fig. 7.8 Experimental setup of the multiline NO-LIF thermometry [23]

7.3.2.3

Organic Molecules

Organic tracers are added to gases in a variety of ways (for example, with a bubbler) to create a gas mixture that contains a portion of the vapor in the flow. Organic tracers can be used for mixing studies by measuring concentration directly using the LIF strength [24]. Seeding concentrations must be sufficient, which may be limited by vapor pressure at room temperature and below. LIF thermometry using singlewavelength UV excitation and single-color detection strategies can suffer from tracer concentration inhomogeneities [25]. Generally, organic molecule tracers are classified into two groups, namely aliphatic and aromatic molecules. Those having chromophores are particularly excited to fluorescence among organic molecules. Aromatic molecules, which are naturally present in regular fuels, make excellent tracers. Aromatics are commonly used as FAR-LIF tracers [26], but they have also been used in excited complex (exciplex)-LIF strategies to spectrally separate the liquid and evaporated gaseous phases [27].

7.3.2.4

Aliphatic Molecules

Amines, aldehydes, and ketones are examples of fluorescing aliphatic molecules with chromophores. Amine LIF tracers such as ethylamine, N,N-dimethyl aniline, and triethylamine can be used as FAR-LIF tracers; trimethylamine, which is gaseous at ambient temperatures, is a potential FAR-LIF tracer choice for gaseous fuel combustion systems, especially the hydrogen internal combustion engine. In the case of toluene, a dual-color detection of the temperature-dependent redshift of the UV fluorescence emission can be used for ratio-based temperature imaging to make the

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measurement independent of tracer concentration. In a motored SI engine, phaselocked measurements of the temperature distribution were obtained using two-color toluene LIF [28]. However, toluene is strongly quenched by oxygen and cannot be used for temperature measurement in air. Ketones, such as acetone and 3-pentanone, can be substituted. Acetone, for example, has a quantum yield of 0.2 percent [29], but it is not significantly quenched by oxygen, has a lower signal drop with temperature than aromatics, and has a high vapor pressure (300 mbar at room temperature), allowing for high seeding concentrations. The high vapor pressure of acetone allows for high seeding levels in gaseous combustion systems due to its low boiling point. 3-Pentanone is commonly used in liquid gasoline fuels as a LIF tracer. Since ketone tracers are not expected to be quenched by oxygen collisions, LIF signals can be quantitatively interpreted. As a result, concentration and temperature measurements, as shown in Fig. 7.9, can be performed at the same time [30]. Only toluene LIF is sufficiently known when it comes to aromatic LIF tracers to conduct simultaneous fuel/air-ratio and temperature studies [31].

7.3.3 High-Speed LIF High-speed PLIF is a form of tracer LIF that can detect combustion-generated OH radicals in the majority of cases, or only the biacetyl tracer when used in engines. Despite the fact that only a few high-speed PLIF approaches have been identified to date, they are briefly discussed here. In one of the LIF studies [33], the relative OH distribution was tracked at 1 kHz in a swirled lean premixed flame during flashback, while in another [34], the simultaneous fuel tracer biacetyl PLIF and two-component PIV were demonstrated in an atmospheric pressure jet that showed similar instabilities to vortex shedding at a repetition rate of 12 kHz. This method was also used to track the fuel distribution near the spark plug in a direct-injection internal combustion engine over time [35]. Figure 7.10 depicts the temporal evolution of the flow field interacting with the flame prior to extinction in a turbulent opposed jet flame to illustrate the new perspective enabled by planar imaging at high repetition rates. The flame front’s instantaneous position (shown as a black line) was calculated from the relative OH radical distribution in this series. The in-plane velocity elements, as determined with PIV, were used to calculate out-of-plane vorticity and 2D pressure. The time when the flame broke through was set to zero. As a result, periods prior to the extinction of the species were labeled as negative.

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Fig. 7.9 Simultaneous number density and temperature acetone LIF measurements in an internal combustion engine [32]. The fuel, but not the intake air, was seeded with acetone (inverse tracing)

7.3.4 Combined LIF Techniques Combining LIF measurements with other diagnostic techniques to probe scalar properties and/or velocity fields at the same time can reveal information about the Navier– Stokes equation approximation modeling strategies [36]. An example is the combination of LIF and PDA measurements as shown in Fig. 7.11. Two data files recorded with the same time base are provided by the combined 3cLIF-PDA method. The droplet velocity and diameters measured by the PDA correspond to one, and the fluorescence intensities incorporated into the droplet transit time within the common measurement volume for the three spectral bands of detection correspond to the other. The arrival and transit time of droplets observed simultaneously by PDA and 3cLIF was used to identify them.

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Fig. 7.10 Individual extinction events are calculated using OH PLIF/PIV at the same time. The black lines indicate the positions of instantaneous flame fronts based on relative OH distributions. The arrows point to two flow field components that were used to measure vorticity (columns 1 and 3) and strain fields (columns 2 and 4) [32]

Fig. 7.11 Combined LIF/PDA experimental setup (top view) and LIF optical setup [37]

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7.4 Instrumentation High-speed LIF being the newly introduced LIF technique with the ability for crucial prospects for future development and application in combustion [38], its instrumentation mainly consists of excitation sources and detection strategies. Figure 7.12 illustrates the experimental setup for OH PLIF imaging in a premixed turbulent jet flame [39]. A hybrid jet-type burner (LUPJ) was used to generate the jet flame, a harmonic generator served as the source of laser excitation, and a high-speed camera was used to detect the LIF signals. Fig. 7.12 Experimental setup for high-speed OH PLIF measurements in a jet flame [39]

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7.4.1 Excitation Sources Since PLIF is based on resonant excitation, both tunable lasers and second harmonic generation crystal (SHG) are compulsory for the excitation of small molecules (Fig. 7.13). On the contrary, large molecules with broad excitation broadband such as formaldehyde [40] or most used fuel tracers like amines [41], ketones [42], and aromatics [43] employ lasers with fixed emission wavelengths (see Tables 7.2 and 7.3). Laser repetition rates exceeding 1 kilohertz (kHz) are essential for the acquisition of statistically correlated data [44]. A high pulse repetition rate can be attained by using either a continuously pulsed operation with much lower single-pulse energy or pulse bursts with high single-pulse energies (Fig. 7.14). Single-pulse energy repetition rate for pulse bursts with high single-pulse energy and continuous operation with low single-pulse energy is summarized in Table 7.4. Fig. 7.13 Schematic diagram of both the tunable laser and second harmonic generation crystal (SHG) for PLIF measurements in a flame [38]

Table 7.2 LIF accessibility of small molecules with different laser sources Small molecules Defined absorption lines NO

OH

CH

CO

Excitation with tunable dye lasers or OPOs pumped with frequency doubled or tripled Nd: YAG lasers @ 532 or 355 nm, respectively

NO2 Excitation with a Nd: YAG laser @ 532 nm

Table 7.3 LIF accessibility of large molecules with their fixed laser sources Large molecules Broadband absorption CO2

SO2

Aromatics

Ketones

Amines

Formaldehyde

Lasers with fixed emission wavelengths are used for excitation. Typical laser sources are excimer lasers filled with KrF or XeCl gas with emission wavelengths of 248 or 308 nm, respectively, and Nd: YAG lasers, operated in their fourth and third harmonic frequency at 266 and 355 nm, respectively

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Fig. 7.14 Schematic diagram of the pulse burst laser [51]

Table 7.4 Excitation sources for high-speed applications [45] Pulse bursts high single pulse energy

Single-pulse energy repetition rate

100 s of mJ up to MHz within one burst; the burst repetition rate is typically ≤10 Hz

Continuous operation (all-solid state lasers) low single pulse energy Up to 10 mJ 1–30 kHz

Two types of all-solid-state lasers for continuous operation are commercially available and exhibit pulse durations of about 90 ns or below 15 nm, respectively. Intracavity frequency conversion is needed to produce either UV or visible light since long-pulse lasers produce lower intensities. Shorter pulse durations permit extracavity frequency conversion [46]. Doubled or tripled radiation frequency from all-solid-state lasers can either be used directly for LIF [47] or to pump tunable dye lasers to generate tunable radiations that can be frequency-doubled into the UV region [48–50]. Higher pulse intensities of short-pulsed pump lasers are useful for the conversion of frequencies into UV. To prevent a significant triplet-state population and any bleaching of the dye, the flow rate of the dye solution must be increased to around 12 l min−1 . Besides, the lowest possible oscillator laser thresholds are required. According to the most recent laser designs, at 10 kHz, 2.4W was attained at about 282 nm, using 50W of pump power.

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7.4.2 Detection Strategies Array detectors and suitable optics are required for the planar detection of LIF. If fluorescence is within the UV range, then the collection lens should be transparent and the array detector UV-sensitive. Complementary metal-oxide semiconductor (CMOS) cameras like charge-coupled devices (CCDs) are not UV-sensitive, hence the array detectors must be combined with image intensifiers such as fiber-coupled or lens in order to temporally discriminate the flame luminosity from the desired LIF signal. Two-stage intensifiers are often used because of the lower LIF signal intensities at high laser repetition rates. Today’s technology combines a multichannel plate (MCP) with a booster to permit a frame rate exceeding 20 kHz without depletion of electrons. Figure 7.15 illustrates the raw OH PLIF data, recorded in the flame brush of unconfined lean premixed methane–air flame. The laser ∑ system was π tuned to the Q1 (6) line within a single-pulse energy of 22 μJ and A2 + ←×2 (1–0) band. To improve the SNR by an order of magnitude, the UV lens was changed from 105/ f#4.5 to 100/f#2.0 (camera lens focal length in mm/camera lens f-number). Generally, a CCD camera can be operated at repetition rates in the MHz regime [52]; the only disadvantage is that only a small number of frames can be contained in a sequence since the in situ storage capacity is limited by the memory buffer integrated into each pixel. 100 frames can be recorded during one sequence depending on the type of the chip-design. CMOS camera can yield high frame rates [53–56]. The main difference between CCD and CMOS array detectors is that the charge-to-voltage conversion occurs at each individual pixel. The digitized images are stored in an on-board memory and, currently, the largest on-board memory has 16 GB capacity.

Fig. 7.15 Snapshots of raw OH distribution data recorded by PLIF. The efficiency of the UV lens was increased to improve SNR of similar conditions [38]

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The number of active pixels is greatly reduced even though CMOS cameras have high frame rates exceeding 500 kHz. CCDs are used in scientific grade quality, whereas CMOS cameras are applied in industries for different purposes such as automotive crash tests. CMOS cameras are much less optimized in terms of their linearity and homogeneity; these problems hinder their use in quantitative scalar imaging since calibration per pixel must be performed.

7.5 Outlook and Summary LIF represents an exemplary technique for analyzing combustion-related cases. Before combustion, LIF can assist in analyzing combustion chemistry processes, mixing phenomena of fuel–air ratio, heat release prior to combustion, determination of flame structure, and pollutants formed after combustion. Since complex combustion processes are governed by the interaction of flow and chemistry in combination with mass transfer and heat, modern LIF strategies are focused on probing multiparameters both simultaneously and in two dimensions. Combining LIF and Rayleigh scattering can lead to the determination of temperature and concentration during combustion. Besides, high-speed LIF, when combined with PIV, can provide temporally correlated information about turbulent combustion, and information on local extinction and reignition (Fig. 7.16). Oxygen quenching can be controlled using picosecond technology in detection and excitation. Another promising LIF strategy to significantly improve SNR is the application of slightly broadband laser sources, which can cover a certain spectral range and allow the simultaneous excitation of multiple transitions. Clearly, there are many potential applications of modern LIF techniques in combustion research and development yet to be explored.

Fig. 7.16 Schematic diagram of combined PIV/OH-LIF [57]

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7.6 Exercises (1) Individual task: Find a scientific paper and describe how high-speed LIF and combined LIF techniques are utilized in combustion engineering. (2) Group task: In small groups, find the latest literature paper and make a presentation on the current applications of LIF in research.

7.7 Questions (1) (2) (3) (4) (5) (6) (7) (8)

Explain the parameters studied at the reaction zone. Describe the working principle of LIF. State the advantages of planar PLF. Explain the working mechanism of PLIF and state the application of PLIF. Explain the commonly used combustion species for LIF application. Explain the principle of NO-LIF thermometry. State the uses of LIF in the research field. Illustrate the detection strategies of PLIF.

References 1. Kulatilaka, W. D., et al. (2008). Comparison of nanosecond and picosecond excitation for interference-free two-photon laser-induced fluorescence detection of atomic hydrogen in flames. 47(26), 4672–4683. 2. Eckbreth, A. C. (1996). Laser diagnostics for combustion temperature and species (vol. 3). CRC press. 3. Birks, J., et al. (1970). Energy transfer in organic systems. VIII. Quenching of naphthalene fluorescence by biacetyl. 3(3), 417. 4. Fröba, A., et al. (1998). Mixture of triethylamine (TEA) and benzene as a new seeding material for the quantitative two-dimensional laser-induced exciplex fluorescence imaging of vapor and liquid fuel inside SI engines. 112(1–2), 199–209. 5. Koban, W., et al. (2005). Oxygen quenching of toluene fluorescence at elevated temperatures. 80(6), 777–784. 6. Reboux, J., et al. (1994). A new approach of planar laser induced fluorescence applied to fuel/ air ratio measurement in the compression stroke of an optical SI engine. 1436–1445. 7. Blotevogel, T., et al. (2008). Tracer-based laser-induced fluorescence measurement technique for quantitative fuel/air-ratio measurements in a hydrogen internal combustion engine. 47(35), 6488–6496. 8. Ipp, W., et al. (2001). 2D mapping and quantification of the in-cylinder air/fuel-ratio in a GDI engine by means of LIF and comparison to simultaneous results from 1D Raman measurements. 1822–1836. 9. Daily, J. W. (1977). Saturation effects in laser induced fluorescence spectroscopy. 16(3), 568– 571. 10. Daily, J. W. (1978). Saturation of fluorescence in flames with a Gaussian laser beam. 17(2), 225–229.

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11. Li, Z., et al. (2007). Development of improved PLIF CH detection using an Alexandrite laser for single-shot investigation of turbulent and lean flames. 31(1), 727–735. 12. Kiefer, J., et al. (2008). Investigation of local flame structures and statistics in partially premixed turbulent jet flames using simultaneous single-shot CH and OH planar laser-induced fluorescence imaging. 154(4), 802–818. 13. Najm, H. N., et al. (1998). On the adequacy of certain experimental observables as measurements of flame burning rate. 113(3), 312–332. 14. Ayoola, B., et al. (2006). Spatially resolved heat release rate measurements in turbulent premixed flames. 144(1–2), 1–16. 15. Kohse-Höinghaus, K. (1994). Laser techniques for the quantitative detection of reactive intermediates in combustion systems. Progress in Energy and Combustion Science, 20(3), 203–279. 16. Fansler, T. D., et al. (1995). Fuel distributions in a firing direct-injection spark-ignition engine using laser-induced fluorescence imaging. 323–338. 17. Kazenwadel, J., et al. (2001). Fluorescence imaging of natural gas/air mixing without tracers added. 345(3–4), 259–264. 18. Krämer, H., et al. (1998). Simultaneous mapping of the distribution of different fuel volatility classes using tracer-LIF tomography in an IC engine. 1049–1060. 19. Schulz, C., et al. (2005). Tracer-LIF diagnostics: quantitative measurement of fuel concentration, temperature and fuel/air ratio in practical combustion systems. 31(1), 75–121. 20. Abram, C., et al. (2018). Temperature measurement techniques for gas and liquid flows using thermographic phosphor tracer particles. Progress in Energy and Combustion Science, 64, 93–156. https://doi.org/10.1016/j.pecs.2017.09.001 21. Sun, X. L., Zhou, J. (2002). English versions of Chinese authors’ names in biomedical journals: Observations and recommendations. 25(1), 3–4. 22. Boxx, I., et al. (2009). Simultaneous three-component PIV/OH-PLIF measurements of a turbulent lifted, C3 H8 -Argon jet diffusion flame at 1.5kHz repetition rate. Proceedings of the Combustion Institute, 32(1), 905–912. https://doi.org/10.1016/j.proci.2008.06.023 23. Cleal, J. (2005). The role of referencing policy and advice in supporting undergraduate learners. Evaluation, Innovation, & Development, 2(2), 49–55. 24. Einecke, S., et al. (2014). Measurement of temperature, fuel concentration and equivalence ratio fields using tracer LIF in IC engine combustion. Applied Physics B, 71(5), 717–723. https://doi.org/10.1007/s003400000383 25. Fajardo, C. M., et al. (2006). Sustained simultaneous high-speed imaging of scalar and velocity fields using a single laser. Applied Physics B, 85(1), 25–30. https://doi.org/10.1007/s00340006-2368-x 26. Shields, B. J., et al. (2021). Bayesian reaction optimization as a tool for chemical synthesis. 590(7844), 89–96. 27. McNamee, L., & Ledley, F. (2015). What does the current biotech stock market value? 33(8), 813–814. 28. Koban, W., et al. (2004). Absorption and fluorescence of toluene vapor at elevated temperatures. Physical Chemistry Chemical Physics, 6(11). https://doi.org/10.1039/b400997e 29. Tan, C., et al. (2017). Recent advances in ultrathin two-dimensional nanomaterials. 117(9), 6225–6331. 30. Labergue, A., et al. (2013). Study of the thermal mixing between two non-isothermal sprays using combined three-color LIF thermometry and Phase Doppler Analyzer. Experiments in Fluids, 54(6). https://doi.org/10.1007/s00348-013-1527-1 31. Wu, Q., et al. (2021). Reply to colorectal cancer and COVID-19: Do we need to raise awareness and vigilance? 32. Lee, Y. R., et al. (2013). Synthesis of metal-organic frameworks: A mini review. 30(9), 1667– 1680. 33. Papageorge, M., & Sutton, J. A. (2017). Intrusive effects of repetitive laser pulsing in highspeed tracer-LIF measurements. Experiments in Fluids, 58(5). https://doi.org/10.1007/s00348017-2323-0

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34. Peterson, B., et al. (2014). Evaluation of toluene LIF thermometry detection strategies applied in an internal combustion engine. Applied Physics B, 117(1), 151–175. https://doi.org/10.1007/ s00340-014-5815-0 35. Casiraghi, C., et al. (2007). Rayleigh imaging of graphene and graphene layers. 7(9), 2711– 2717. 36. Choi, W., et al. (2010). Synthesis of graphene and its applications: A review. 35(1), 52–71. 37. Schulz, C., & Sick, V. (2005). Tracer-LIF diagnostics: Quantitative measurement of fuel concentration, temperature and fuel/air ratio in practical combustion systems. Progress in Energy and Combustion Science, 31(1), 75–121. https://doi.org/10.1016/j.pecs.2004.08.002 38. Leipertz, A., et al. Laser-induced fluorescence. In Handbook of combustion (pp. 219–242). 39. Wang, Z., et al. (2018). Investigation of OH and CH2 O distributions at ultra-high repetition rates by planar laser induced fluorescence imaging in highly turbulent jet flames. 234, 1528–1540. 40. Li, T., et al. (2020). High-speed volumetric imaging of formaldehyde in a lifted turbulent jet flame using an acousto-optic deflector. 61(4), 1–14. 41. Bourgalais, J., et al. (2019). Product detection of the CH radical reactions with ammonia and methyl-substituted amines. 123(11), 2178–2193. 42. Ding, Y., et al. (2020). Quantitative measurements of broad-band mid-infrared absorption spectra of formaldehyde, acetaldehyde, and acetone at combustion-relevant temperatures near 5.7 μm. 248, 106981. 43. Sommerer, J., et al. (2019). The influence of selected aromatic fluorescence tracers on the combustion kinetics of iso-octane. 244, 559–568. 44. Gao, Y., et al. (2019). 10 kHz simultaneous PIV/PLIF study of the diffusion flame response to periodic acoustic forcing. 58(10), C112–C120. 45. Jiang, N., et al. (2009). Advances in generation of high-repetition-rate burst mode laser output. 48(4), B23–B31. 46. Li, D., et al. (2007). Diode-pumped efficient slab laser with two Nd: YLF crystals and secondharmonic generation by slab LBO. 32(10), 1272–1274. 47. Konle, M., et al. (2006). CIVB flashback analysis with simultaneous and time resolved PIVLIF measurements. Paper presented at the Proceedings of the 13th International Symposium on Applications of Laser Techniques to Fluid Mechanics. 48. Smith, J. D., & Sick, V. (2007). Quantitative, dynamic fuel distribution measurements in combustion-related devices using laser-induced fluorescence imaging of biacetyl in iso-octane. 31(1), 747–755. 49. Paa, W., et al. (2007). Flame turbulences recorded at 1 kHz using planar laser induced fluorescence upon hot band excitation of OH radicals. 86(1), 1–5. 50. Kittler, C., & Dreizler, A. (2007). Cinematographic imaging of hydroxyl radicals in turbulent flames by planar laser-induced fluorescence up to 5 kHz repetition rate. 89(2), 163–166. 51. Lempert, W., et al. (2002). A MHz rate imaging system for study of turbulent and time evolving high speed flows. Paper presented at the Proceedings of 11th International Symposium on Application of Laser Techniques to Fluid Mechanics, Lisbon, Portugal 52. Etoh, T. G., et al. (2003). An image sensor which captures 100 consecutive frames at 1000000 frames/s. 50(1), 144–151. 53. Hult, J., et al. (2002). Application of a high-repetition-rate laser diagnostic system for singlecycle-resolved imaging in internal combustion engines. 41(24), 5002–5014. 54. Sjöholm, J., et al. (2009). Ultra-high-speed pumping of an optical parametric oscillator (OPO) for high-speed laser-induced fluorescence measurements. 20(2), 025306. 55. Konle, M., et al. (2008). Simultaneous high repetition rate PIV–LIF-measurements of CIVB driven flashback. 44(4), 529–538. 56. Anggono, W., et al. (2013). Laminar burning velocity and flammability characteristics of biogas in spark ignited premix combustion at reduced pressure. Trans Tech Publ. 57. Troiani, G., et al. (2009). Counter-gradient transport in the combustion of a premixed CH4 /air annular jet by combined PIV/OH-LIF. Combustion and Flame, 156(3), 608–620. https://doi. org/10.1016/j.combustflame.2008.12.010

Chapter 8

Nuclear Magnetic Resonance Vestince Balidi Mbayachi, Zhen-Yu Tian, Wei-Kang Dai, Daniel A. Ayejoto, Zhi-Min Wang, Xu Zhang, and Maria Khalil

8.1 Introduction Nuclei in a strong, continuous magnetic field can be disturbed by a weak, alternating magnetic field, which causes an electromagnetic signal to be produced with a frequency that matches the magnetic field at the nucleus. This phenomenon is known as nuclear magnetic resonance [1]. NMR spectroscopy examines the chemical composition, 3D structures, and mobility of molecules and other materials. When radio frequency radiation is used to excite nuclei with non-zero spins in a magnetic field resonantly, the result is known as NMR [2]. The decadence of the nuclear spin states is removed when non-zero nuclear spin atoms are subjected to an external magnetic field, resulting in an energy difference ΔE indicated by Eq. (8.1): ΔE = γ h(1 − σ )B0

(8.1)

V. B. Mbayachi Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China V. B. Mbayachi · Z.-Y. Tian (B) · W.-K. Dai · D. A. Ayejoto · Z.-M. Wang · M. Khalil University of Chinese Academy of Sciences, Beijing 100049, China e-mail: [email protected] Z.-Y. Tian · W.-K. Dai · Z.-M. Wang Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China D. A. Ayejoto Guangzhou Institute of Energy Conversion, Chinese Academy of Sciences, Guangzhou 510640, China X. Zhang School of Energy Power and Mechanical Engineering, North China Electric Power University, Beijing 102206, China M. Khalil Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China © Science Press 2023 Z.-Y. Tian (ed.), Advanced Diagnostics in Combustion Science, https://doi.org/10.1007/978-981-99-0546-1_8

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where B0 is the intensity of the static magnetic field, σ is the chemical shielding surrounding a nucleus, and γ is the gyromagnetic ratio, an essential characteristic linked to each isotope. Then, electromagnetic radiation can generate changes between any of these nuclear spin states [3]. The electron dispersion surrounding the nucleus, which protects the nucleus from the applied magnetic field, impacts the NMR change frequencies. The shielding constant changes for several nuclei of a particular isotope in a molecule, leading to marginally varied frequencies. NMR frequencies thus indicate the sample’s chemical composition [4]. The percentage difference between the frequency of a specific nucleus and a reference substance like tetramethylsilane is often stated for NMR frequencies as a chemical shift, abbreviated as δ. Chemical shift discrepancies can vary from 10 parts per million (ppm) for 1 H to 200 ppm for 13 C to 1,000 ppm for 17 O for a specific isotope. NMR frequencies are altered along with chemical shifts by several couplings, including spin-spin scalar couplings that depend on the bond formation and are usually in the 0–1 Khz frequency range and spin-spin dipolar couplings that are based on internuclear intervals [5]. These NMR interactions are all anisotropic, meaning their strength varies depending on how the sample is oriented with the magnetic field. NMR spectra contain 3D structural data due to these orientation-dependent chemical shifts, internuclear couplings, and quadrupolar couplings. In order to determine the geometries and frequencies of motion, measurements of motionally averaged NMR spectra and motionally induced nuclear spin relaxation are used. Molecular spins partially aggregate these anisotropic connections [6]. Compared to the microwave, infrared, and ultraviolet frequencies used in rotational, vibrational and electronic spectroscopies, the radiofrequency domain of electromagnetic radiation has frequencies that are lower by orders of magnitude. The Boltzmann distribution in Eq. (8.2) indicates that the nuclear spin energy levels are about equally occupied at ambient temperature, which is consistent with the low NMR frequencies [7]. (1−σ )B0 N+ ΔE = e− kT = e−γ h kT N−

(8.2)

For instance, with a 10T magnetic field at ambient temperature, the populace of the ground state (N+ ) is only 1 in 10,000 times more than that of the higher state (N- ). Due to the minor size difference, the NMR signals are fundamentally weak, which results in low spectral signal-to-noise ratios. NMR sample quantities, detection strategies, and instrumentation must adhere to strict restrictions because of their faint signals. Conventional NMR spectroscopy has spent a lot of time developing its sensitivity [8]. One vital effective strategy is to employ more significant magnetic fields to boost ΔE. However, this is constrained by both technique and expense. Instead of scanning the frequency and detecting absorption or emission as in traditional spectroscopy, one alternative is to capture NMR spectra in the time series after a radiofrequency pulse and retrieve the spectrum by Fourier transformation [9]. Since frequency spectra instead of spatial density maps represent structural information, NMR spectra interpretations can be less straightforward than microscopy or

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Fig. 8.1 Basics of NMR spectroscopy for structural analysis of materials [5]

diffraction data. Identifying the specific atoms responsible for the frequency peaks can be difficult. NMR spectroscopy has caught the attention of chemists due to the abundance of peaks in its spectra, which reflect an excellent chemical fingerprint of molecules [10]. The chemical shifts and couplings in NMR spectra also hold 3D structural and kinematic data, providing insight into the workings of biological and chemical processes. Figure 8.1 represents the basics of NMR spectroscopy for structural analysis of materials [5]. In Fig. 8.1a, nuclear spin magnetic dipole moments (μ) appear to move around a static magnetic field (B0 ) at a frequency that is the same as the transitioning frequency between the energy state of the spins (ΔE = èω0 ). Nuclear magnetic resonance (NMR) probes are put into the center of magnets and have a radiofrequency (RF) coil coiled around the sample at the probe’s tip. The RF coil enables both the irradiation of RF pulses and the observation of the nuclear magnetic moment’s transition frequency. Angular velocity, ω = −γB. In Fig. 8.1b, the gyromagnetic ratios (γ) of various nuclear isotopes and the magnetic field (B0 = 18.8 T in this example) affect the NMR frequencies of those isotopes. The graphical NMR spectra of a stationary powder comprising three 13 C nuclei reveal the functional groups’ chemical structure. The broad powder pattern shows chemical shift anisotropy, which is identified by the sample’s magic-angle spinning (MAS) and whose geometric mean is the isotropic chemical shift. By reducing the anisotropic component of the interactions to zero and running the sample through MAS in the rotor, solids can provide high-resolution NMR spectra (Fig. 8.1c).

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8.2 Fundamental Principles of NMR The basis of NMR is that all nuclei are electrically charged and have some degree of spin. The nuclei with the odd number of neutrons, protons, or containing both will have an intrinsic nuclear spin. It is feasible for energy to move from the baseline level to a higher excited state when an external magnetic field is introduced (generally a single energy gap). When a nucleus with a non-zero spin is placed in a magnetic field, the nuclear spin can align in either the same direction or in the opposite direction as the field (Fig. 8.2). These two nuclear spin alignments have different energies, and the application of a magnetic field lifts the degeneracy of the nuclear spins. A nucleus with its spin aligned with the magnetic field will have lower energy than when its spin is aligned in the opposite direction to the field. The energy movement occurs at a wavelength equivalent to radio frequencies, and energy is released at the same frequency when the spin recovers to its minimum point. NMR spectra for the relevant nucleus are produced by various measurements and processing of the signal corresponding to this transfer.

Fig. 8.2 The basic principle of NMR [5]

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8.3 Spin Physics 8.3.1 Nuclear Spin and Magnetic Properties 8.3.1.1

Classification of Nuclear Spins and Spin Quantum Numbers

Nuclei with spins have different spin characteristics, described in nuclear physics as having different spin quantum numbers I. The value of the spin quantum number I of the nucleus is related to the atomic number (charge number) and mass number. The classification of various nuclei according to their spin characteristics is shown in Table 8.1, where the nucleus with an even mass number and charge number will exhibit no spin phenomenon, and its spin quantum number I is zero. Nuclei with odd mass numbers have spins, and the spin quantum number I is a half-integer. For example, the spin quantum numbers of 1 H, 13 C, 15 N, 19 F, and 31 P equal ½. The nuclei with spin quantum number I=½ have uniform nuclear charge distribution [11, 12]. For nuclei with even mass number and odd charge number, the spin quantum number I is a positive integer (1, 2, 3...). For example, the spin quantum number of 2 H and 14 N is 1. Nuclei with a spin quantum number greater than ½ have an inhomogeneous nuclear charge distribution [11]. A nucleus with spin is analogous to the rotation of a rigid body and has angular momentum called the spin angular momentum of the nucleus [14, 15], denoted by PN *. Every atomic nucleus with spin has a magnetic moment whose direction coincides with the axis of rotation [16]. The magnetic moment of the nucleus is denoted by μ∗N . 8.3.1.2

The Action of Magnetic Field on Magnetic Moment

In a magnetic field, the action of the magnetic moment from magnetic field B0 is related to the relative direction of the magnetic moment and magnetic field. When the magnetic moment and magnetic field are not parallel, the magnetic moment will be acted on by a torque, making it tend to rotate to the direction parallel to the magnetic field; that is, to the direction with the minimum potential energy of the magnetic moment. Only the nuclei with magnetic moments can interact with the magnetic Table 8.1 Classification of nuclei by spin characteristics [13, 14]

Nuclear charge number

Mass number

I

Typical atomic nucleus

Even number

Even number

0

12 C, 16 O, 32 S

Odd number

Odd number

½, 3/2…

1 H, 15 N, 19 F, 31 P

Even number

Odd number

½, 3/2…

13 C, 17 O

Odd number

Even number

1, 2, 3…

2 H, 14 N

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field in the magnetic field, and the nuclear magnetic resonance phenomenon occurs. Therefore, the nucleus with spin quantum number I=0 has no NMR phenomenon. If the spin quantum number I is half-integer or integer, the nuclear magnetic resonance phenomenon is observed. In particular, the nucleus with I=1/2 has a narrow NMR spectrum, which is the most suitable for NMR detection and is the main object of NMR research.

8.3.1.3

Magnetic Spin Ratio of Spin Nuclei

A nucleus with spin angular momentum also has a magnetic moment. The ratio of the magnetic moment to the angular momentum is called the magnetogyric ratio, sometimes called the gyromagnetic ratio, and is denoted by γ [17]. The magnetic spin ratio of the nucleus is represented by γ N : γN =

μ → ∗N P→N∗

(8.3)

The magnetic spin ratio of spin nuclei is a constant related to the properties of spin nuclei and is one of the essential properties of nuclei. Different spin cores exhibit different γ N values. For example, the γ N of 1 H is 26.752, and the γ N of 13 C is 6.728 [16].

8.3.1.4

Spatial Quantization and Its Rules

In a magnetic field, spin nuclei have different spin states described in NMR as having different spin states with different orientations. This phenomenon is called spatial quantization of nuclei. A nucleus with the spin quantum number I can only have (2I+1) spin state orientations in a magnetic field. The projection P of the spin angular momentum of a nucleus with the spin quantum number I in the direction of the magnetic field can only be taken as follows: PZ = m

h 2π

(8.4)

where h is Planck’s constant; m is the magnetic quantum number; m = I, I−1,…,−I+1,−I. In a magnetic field, for a nucleus with the spin quantum number I, the projection μ Z of its nuclear magnetic moment in the direction of the magnetic field can only be taken as follows: μ Z = γ N PZ

(8.5)

Figure 8.3 shows the Spatial quantization of I = 1/2, I = 1, and I = 2 atoms.

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Fig. 8.3 Spatial quantization of I = 1/2, I = 1, and I = 2 atoms [16]

8.3.1.5

Larmor Precession and Spin Nuclei Precession in Magnetic Fields

When the magnetic moment of the spin core deviates from the direction of action of the magnetic field, the action of the magnetic field torque is similar to the precession of the gravity field when the rotation axis of the gyroscope deviates from the direction of action of the gravity field, which is called Larmor precession. The precession angle frequency ω is called the Larmor frequency [12, 18]. According to the rules of spatial quantization of spin nuclei in magnetic fields, a nucleus with the spin quantum number I produces 2I+1 precession states in magnetic fields. The nuclear spin quantum number of a hydrogen atom is 1/2, and there are two spin orientations in the magnetic field corresponding to the magnetic quantum number m=±1/2; that is, some nuclear magnetic moments (α spin state or +1/2 spin state) precession with Larmor frequency O in parallel with the magnetic field. Some other nuclear magnetic moments (β spin state or −1/2 spin state) process antiparallel to the magnetic field with Larmor frequency ω [12, 16, 19]. The experiment proves that ω is proportional to the magnetic field strength B0 of the magnetic field, and has the following relation formula [16]: γN =

2π υ ω = B0 B0

(8.6)

where γ N is the magnetogyric ratio of a proton; υ is the precession frequency of the proton. So the precession frequency υ of a proton can also be expressed as [16]: υ=

γN B0 2π

So as B0 increases, ω and υ increases.

(8.7)

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8.3.2 Nuclear Energy Levels and Transitions 8.3.2.1

Energy Level Splitting of Nuclei in Magnetic Field

The proton has microscopic magnetic moment spins, and the magnetic moment’s direction coincides with the rotation axis. In the magnetic field, the orientations of the two spin states of the micromagnetic moment are different, and the energy is no longer equal. The energy level of the spin state in which the magnetic moment is parallel to the magnetic field is lower than the spin state in which the magnetic moment is antiparallel to the magnetic field. The energy difference ΔE between the two spin states is proportional to the magnetic field strength B0 : ΔE = γ

h B0 2π

(8.8)

where h is the Planck constant, B0 is the magnetic field strength of the magnetic field, and its unit is T (Tesla). According to the theory of quantum mechanics, the relationship between the energy difference ΔE between the two spin states of protons and the magnetic field strength B0 can also be expressed as ΔE =

μN B0 = 2μ N B0 I

(8.9)

where μ N is the magnetic moment of the proton, I is the spin quantum number of the proton.

8.3.2.2

Stimulated Transition Process

Boltzmann distribution is the distribution of the number of particles at the high and low energy levels in the thermal equilibrium state. Under the action of the magnetic field, the process in which the particles in the low-energy state absorb energy and transition to the high-energy state is called the stimulated transition process. In the process of stimulated transition, the number of particles between the high and low energy levels decreases exponentially. If there are no other factors, the stimulated transition of particles will make the number of particles on the two energy levels tend to be equal. For nuclear magnetic resonance, the phenomenon of nuclear magnetic resonance cannot be observed at this time.

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The Action Mode of Magnetic Field in the Process of Stimulated Transition

In the process of stimulated transition, two magnetic fields are acting. The first one is that, the constant magnetic field B0 is consistent with the z-axis direction in the constant coordinate system, Bz = B0 . And the other is a rotating magnetic field B1 (alternating magnetic field) rotating at an angular velocity of 0 on the XY plane of the constant coordinate system. B1 can be decomposed into two circularly polarized magnetic fields with opposite rotation directions, which have components in the X and Y directions. One of the rotating magnetic fields is opposite to the nuclear precession direction. The interaction time between the rotating magnetic field and the nuclear magnetic moment is very short and can be ignored. The other rotating magnetic field has the same direction and frequency as the nuclear precession, and its energy can be transferred to the nuclear magnetic moment to generate the energy level transition of the atomic nucleus. The precession angle of the protonic nucleus θ changes occurs, i.e., nuclear magnetic resonance. When γ N is positive, the clockwise component of the rotating magnetic field B1 acts. When γ N is negative, the counterclockwise component of the rotating magnetic field B1 acts.

8.3.3 Relaxation in NMR The probability of a particle in a higher energy state returning to a lower energy state by spontaneous radiation is proportional to the energy difference ΔE between the two levels. In NMR spectra, because the energy difference ΔE between the high and low nuclear magnetic moment states is minimal, the nuclear magnetic moment in the high energy state can hardly return to the low energy state by spontaneous radiation. However, the stable NMR signal can be observed in NMR experiments because of the relaxation process. In NMR, the process of continuously making the nuclear magnetic moment of the higher energy state return to the lower energy state by energy exchange so that the population of the lower energy state is always slightly larger than that of the higher energy state is called the relaxation process [16].

8.3.3.1

Longitudinal Relaxation

In the process of thermal motion, molecules around the magnetic moment of the high-energy nuclear state can generate transient small magnetic fields; that is, there are many small magnetic fields with different frequencies. If the frequency of one of them coincides with the cyclotron frequency of a nuclear magnetic moment, a transfer of energy may occur. The relaxation of the nuclear magnetic moment of the higher energy state back to the lower energy state by transferring its energy to other surrounding molecules (called lattices) is called longitudinal relaxation, also known as spin-lattice relaxation. The longitudinal relaxation reflects the energy exchange

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between the system and the environment. As far as the nuclear magnetic moment system is concerned, the result of longitudinal relaxation is an energy decrease. It takes some time to reach equilibrium through the longitudinal relaxation process, and its half-life is expressed as T1 . The smaller T1 is, the higher the longitudinal relaxation process’s efficiency. The thermal motion of solid samples is minimal and cannot effectively produce longitudinal relaxation, so the T1 value is significant, while the T1 value of liquid and gas is negligible. The magnitude of T1 affects the saturation of the nuclear magnetic moment [11, 16].

8.3.3.2

Transverse Relaxation

A nuclear magnetic moment of a high energy state interacts with another nuclear magnetic moment of the same low energy state. The relaxation of the nuclear magnetic moment of the high energy state is transferred to the low energy state, called transverse relaxation. It is also called the energy exchange relaxation or spinspin relaxation between nuclear moments of the same kind. In transverse relaxation, the total number of nuclear magnetic moments of various orientations and the total energy of the nuclear magnetic moments remain constant. And its half-life is T2 . The relative position of each nucleus in the solid sample is relatively fixed, which is conducive to the energy transfer between nuclear magnetic moments, so T2 is particularly small [11, 16].

8.3.3.3

Dependence of Relaxation Time on Spectral Line Width

The relaxation time (the smaller one in T1 or T2 ) significantly influences the width of the spectral line because of the self-uncertainty principle [16]. ΔEΔt ≈ h

(8.10)

ΔE = hΔυ

(8.11)

Δt ≈ 1/Δυ

(8.12)

On account of

Therefore

It can be seen that the width of the spectral line is inversely proportional to the relaxation time. The T2 value of the solid sample is minimal, so the spectral line is extensive. To get a high-resolution NMR spectrum, you must prepare the solution for testing.

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8.3.4 Chemical Shift and Shielding 8.3.4.1

The Concept of Chemical Shift and Shielding Effect

Chemical shift is the phenomenon in which protons or other magnetic nuclei display resonance peaks at different magnetic field strengths due to the different chemical environments in the molecule [20]. The shielding effect is the process by which the electrons in the molecule move circularly around the atomic nucleus or specific functional groups on the plane perpendicular to the magnetic field. This electronic movement will generate an induced magnetic field opposite to the direction of the magnetic field within its circulation range due to the action of the magnetic field, and generate an induced magnetic field in the same direction as the magnetic field outside its circulation range, thus having an anisotropic effect on different regions in the molecule, so that protons in different chemical environments are subjected to different magnetic fields. The electrons in the molecule generate an induced magnetic field under the action of the magnetic field, and the effect of magnetic anisotropy on different regions in the molecule is called the shielding effect [20].

8.3.4.2

Generation and Representation of Chemical Shifts

Unlike independent protons, each proton in a molecule is in a specific chemical environment. The chemical environment mainly refers to the distribution and movement of the extranuclear electrons of protons and the related electrons of other atomic nuclei or functional groups close to the protons and their influence on the surrounding space. These electrons generate an induced magnetic field under the influence of the magnetic field, which has a positive or negative shielding effect on the magnetic field in the environment where the protons are located, resulting in different magnetic field intensities received by different protons, thus generating chemical shifts. Relative values express the chemical shift, take the resonance peak of a standard sample as the origin, and measure the distance between each peak of the sample and the origin. The induced magnetic field generated by the electrons in the chemical environment under the action of the magnetic field is proportional to the magnetic field strength of the magnetic field. Therefore, the magnitude of the chemical shift caused by the shielding effect of the induced magnetic field is also proportional to the magnetic field strength of the magnetic field. Since the actual NMR spectrometer has a different frequency or magnetic field strength, and the frequency or magnetic field strength expresses the chemical shift, then different values are measured by different instruments. In order to make the chemical shift values measured on different instruments consistent, the position of the resonance spectrum line is usually represented by Eqs. 8.13 or 8.14, and its value is the chemical shift value [14, 21]. δ=

ΔH H R − HS × 106 = × 106 HR HR

(8.13)

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Or: δ=

Δυ υ R − υS × 106 = × 106 υR υR

(8.14)

In the above two formulas, H R is the resonance magnetic field strength of the standard sample, and HS is the resonance magnetic field strength of the sample. υ R is the resonance frequency of the standard sample, and υs is the resonance frequency of the sample. Multiplying 106 is because ΔH is only a few parts per million compared with H R and Δυ is only a few parts per million compared with υ R . To make this value easy to read and write, it is multiplied by 106 [14, 21]. Since the numerator is several orders of magnitude smaller than the denominator in the calculation formula of the above chemical shift, υ R is relatively close to the frequency of the nuclear magnetic resonance instrument. Therefore, the calculation method of chemical shift is also expressed as [14]. δ=

υS − υ R × 106 υE

(8.15)

where υ E is the frequency of the nuclear magnetic resonance instrument. The standard sample generally uses tetramethylsilicon [(CH3)4 Si], which has only one peak. In the early stage, the δ value of the single peak of tetramethylsilicon was set to zero, the δ value of the peak on its left was set to negative, and the δ value of the peak on its right was set to positive. At the same time, it is also expressed by the τ value. The τ value of tetramethylsilicon single peak is set as 10, so τ = 10 +δ [14, 22]. In 1970, the International Union of Pure and Applied Chemistry (IUPAC) suggested that a value should express the chemical shift. It was specified that the value of the tetramethylsilicon (TMS) single peak was zero, and the value of the peak on its left was positive. The value of the peak on its right was negative, which was just opposite to the earlier regulations [14].

8.3.4.3

The Theory of Chemical Shifts

When the proton is in the magnetic field B0 , one of its extranuclear electrons is induced to interact with B0 . Moving around the nucleus in a vertical plane generates a local magnetic field opposite to the direction of B0 and proportional to H in the area surrounded by the electron circulation. This local magnetic field cancels out part of the magnetic field. Therefore, the actual magnetic field strength of the proton is reduced [23]. The relationship is expressed as follows: B H = B0 (1 − σ )

(8.16)

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where the BH represents the magnetic field strength of the hydrogen atom nucleus, σ is the shielding constant. σ is independent of the magnetic field B0 ; its value mainly depends on the chemical structure and has a specific relationship with the solvent and medium. Therefore, if the chemical environment of protons is different and also σ value is different, then BH is also different, resulting in different chemical shifts. Although σ is independent of the magnetic field B0 , the antimagnetic field B0 generated by the extra nuclear electrons σ is directly proportional to B0 , which is why the absolute values of chemical shifts are measured by instruments with different magnetic field strengths or frequencies are different. According to this theory, their NMR conditions for protons in a specific chemical environment should be expressed as f =υ=

γN H0 (1 − σ ) 2π

(8.17)

That is, the generation of chemical shifts in NMR is affected by the shielding constant, and the shielding constant increases (equivalent to the decrease of magnetic field strength). Under the condition of fixed radiofrequency, the magnetic field strength required for resonance needs to be increased accordingly.

8.3.4.4

Common Examples of Shielding Effects

The shielding effect of bonding electron cloud density outside the hydrogen nucleus on the atomic nucleus is called the shielding effect. When there are electron repellent groups near the hydrogen nucleus, the density of the surrounding electron cloud will increase, and the shielding effect will increase, resulting in the chemical shift to the right (to the high field shift). On the contrary, when there are electrophilic groups around the hydrogen nucleus, the electron cloud density around the hydrogen nucleus decreases, and the shielding effect also decreases, resulting in the chemical shift to the left (to the low field shift) [20]. The remote shielding effect is the shielding effect of atoms or groups in molecules on the studied hydrogen through the space magnetic field. Several common remote shielding effects are described below. 1. Benzene ring. The induced magnetic field generated by a benzene ring’s π electron flow (ring current) makes the hydrogen nuclei on the ring and under the ring shielded, thus indicated by a positive sign (+). The other directions are the unshielded area, thus indicated by a negative sign (−), as shown in Fig. 8.4. 2. Carbonyl. The carbonyl shielding zone is shown in Fig. 8.5. The δ value of aldehyde protons is in the range of 8–9.5, resulting from a strong deshielding effect caused by magnetic anisotropy of the carbonyl group. 3. Double bond. The anisotropy of the double bond is shown in Fig. 8.6. 4. Alkyne bond. The shielding effect of the alkyne bond is shown in Fig. 8.7. Solvent effect: The chemical shift will change when different solvents are used. The polarity of the solvent is strong, and the effect is more pronounced. The solvent

258 Fig. 8.4 Shielding effect of benzene ring [20]

Fig. 8.5 Shielding effect of carbonyl group [20]

Fig. 8.6 Shielding effect of the double bond [20]

Fig. 8.7 Shielding effect of the alkynyl group [20]

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may produce a magnetic anisotropy effect, and there may be a hydrogen bond or Van der Waals gravitational effect between the solvent and solute. In addition, temperature, pH, and isotope effects will change the chemical shift. Hydrogen bonds and chemical shifts: The chemical shifts of protons with hydrogen bonds are more extensive than those without hydrogen bonds because forming hydrogen bonds will reduce the density of extranuclear electron clouds.

8.3.5 Spin Coupling and Spin Splitting 8.3.5.1

The Concept of Spin Coupling and Spin Splitting

In molecular organic compounds, each around a nucleus, in addition to the electronic, there are other positively charged nuclei. The nucleus of spin quantum number is not equal to zero. The interaction exists between interference. The interference effect does not affect the chemical shift of the magnetic core but has apparent effects on the shape of the nuclear magnetic resonance (NMR) map. The interference between the spins of the nuclear magnetic moment is called spin coupling, and the increase of spectral lines caused by spin coupling is called spin splitting.

8.3.5.2

Coupling Mechanism

In general, except for a few particular structural types, the standard spin coupling between magnetic nuclei occurs when the number of chemical bonds between two magnetic nuclei is less than three. The spin-coupling system AX, which consists of two magnetic cores A and X connected by A single bond, whose spin quantum number I is 1/2, is taken as an example to illustrate the coupling mechanism. Assuming that any electron on the bond between two nuclei A and X can exist at the same point in space with nucleus A (or nucleus X) for a particular time, the influence of nucleus A on nucleus X can be discussed as follows: If the spin state of nucleus A is +1/2, then the spin of the electron close to it must be −1/2; that is, the spin of nucleus A polarizes the spin of the electron. According to Pauli’s principle, the other electron in orbit must have a spin of +1/2, so when the X-core has a spin of −1/2, the second electron with a spin of +1/2 occupies the same space as the X-core. Therefore, a spin state of +1/2 for nucleus A and a spin state of −1/2 for nucleus X is advantageous. That is, the potential energy of the system decreases. On the contrary, if the spin state of the X nucleus is +1/2, the potential energy of the system increases. Since the energy of the X nucleus with spin −1/2 is higher than that of the X nucleus with spin +1/2, the effect of the A nucleus with spin +1/ 2 is to reduce the energy difference between the two energy levels of the X nucleus (Fig. 8.8a). If core A has A spin state of −1/2, then the electron close to it should have A spin of +1/2, and the other electron in orbit should have A spin of −1/2. So, when the X core has a spin of +1/2, the second electron with a spin of −1/2 occupies

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Fig. 8.8 The influence of a nucleus’s spin on the X nucleus’s spin potential energy [16]

the same space as the X core. Therefore, A spin state of −1/2 for nucleus A and +1/2 for nucleus X is advantageous. That is, the potential energy of the system decreases. Furthermore, if the spin state of X is −1/2, the potential energy of the system increases. Additionally, since the energy of X core with spin −1/2 is higher than that of X core with spin +1/2, the effect of A nucleus with spin −1/2 on X core is to increase the energy difference between the two energy levels of X core (Fig. 8.8b). As can be seen from Fig. 8.8, due to the existence of core A, there are two transitions of different energies in core X. One is that when the spin state of core A is +1/2, core X transitions from a low energy level (+1/2) to a high energy level (−1/2). Compared with the transition without the influence of core A, the energy of this transition decreases. The other is that when the spin state of the A core is −1/2, the X core transitions from a low energy level (+1/2) to a high energy level (−1/2). Compared with the transition without the influence of A core, the energy of this transition increases. Similarly, due to the existence of X core, there are two transitions of different energies in core A. One is that when the spin state of X core is +1/2, core A transitions from a low energy level (+1/2) to a high energy level (−1/2). Compared with the transition without the influence of X core, the energy of this transition decreases. The other is that when the spin state of the X nucleus is −1/2, the A nucleus transitions from a low energy level (+1/2) to a high energy level (−1/2). Compared with the transition without the influence of the nucleus, the energy of this transition increases [16]. The energy difference between the two different transitions of the A or X nuclei mentioned above is called the coupling constant, and the symbol for the coupling constant is J. If the magnetic nuclei formed a more complex structure, they would have the exact coupling mechanism, but with a more complex transition type.

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8.4 Experimental Setup 8.4.1 NMR Spectrometer Design Modern NMR spectrometer consists of three main parts: a large magnet used to produce electromagnetic field, a transmitter utilized as an alternative field B, and a receiver that detects and amplifies the magnetic resonance signal (Fig. 8.9) [24]. Furthermore, NMR contains other apparatus such as a computer for displaying and analyzing data, a shim regulator to improve S/N ratio, and a temperature regulator for controlling temperature [25].

Fig. 8.9 Schematic diagram of the modern NMR spectrometer [24]

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The Magnet

The Magnet is the source of static magnetic field B0 . Stability, strength, and homogeneity are the three main characteristics of an NMR spectroscopy magnet [26]. There are three main types of magnets: permanent, electromagnets, and superconducting. Permanent magnets are simple and cheap. They are used in typical NMR spectrometers since they don’t require electricity to operate and have high stability regarding both field homogeneity and absolute field. Unfortunately, their sample gap and maximum field of permanent magnets tend to be limited. Additionally, they lack field variability, which is vital in variable-frequency spectrometers [27]. Electromagnets are commonly used in NMR experiments. They are costly to build and operate. However, they have very high magnetic strength (1–2.5 T), which facilitates flexibility in the choice of experiments. Iron-core electromagnet is commonly used in solid-state NMR experiments. The power is supplied in coils around the iron core, and excess heat is removed by circulating water [28]. The superconducting magnets usually are solenoidal in shape. Essentially, they have good stability and a very high magnetic field of around 23.5 T, corresponding to a proton frequency of 1000 MHz (1 GHz) [25, 29]. The coil in the magnet consists of a superconducting wire usually maintained at liquid-helium temperatures. These magnets have very high maintenance and operating cost due to the cost of liquid helium, unless a closed-cycle liquid-helium recovery system is used [25]. The main advantage of these superconducting magnets is that the chemical shifts increase with B0 . Also, due to their ability to operate at high fields, the signal-to-noise ratio is proportional to B0 3/2 . For the above reasons, superconducting magnets are used in various types of experiments, including biological and chemical experiments, as well as in solid-state observations of nuclei that are hard to see because of their low concentration [30]. Ultra-high field magnets are required for structural biology research. For observation of protons that require beyond 1 GHz frequencies, newer high-temperature superconducting magnets are needed, which is the current technical challenge to manufacturers [29]. The cylindrical magnet solenoid through which high direct current flows is made of superconducting niobium-tin alloy, which develops zero electrical resistance when immersed in a cryostat of liquid helium at 4 K temperature [31]. A radiation shield and liquid nitrogen cooled in a cryostat at 77 K prevent the liquid helium loss through boiling off. A high vacuum jacket surrounds the liquid nitrogen itself (Fig. 8.10). Modern NMR assembly systems are so efficient since once energized, the magnet can operate for many years without requiring external power energy. It only requires liquid nitrogen refills between one to two weeks and liquid helium refills between 2 and 12 months, depending on the magnet age and construction [29]. The Current in superconducting coils can give an acceptable magnetic field for around ten years before decaying and need to be topped up again [32]. It is essential to get a uniform magnetic field over the sample, and three methods can achieve this through the use of uniform samples, sample spinning, and shimming [26].

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Fig. 8.10 Schematic diagram of Bruker model NMR spectrometer showing the magnet’s and probe’s essential parts [26]

Sample Preparation for NMR Spectroscopy The sample preparation is critical in NMR spectroscopy to obtain well-resolved spectra. The sample must be dissolved in a deuterated solvent and mixed well to avoid a change in magnetic susceptibility due to concentration gradient. The most common deuterated solvent include acetic acid–d4, acetone–d6, benzene–d6, toluene–d8, etc. Also, the resulting solution must be free from paramagnetic impurities and particles. This can be achieved by filtering or passing the solution through an alumina plug

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in Pasteur pipe into the NMR tube. A good NMR tube must be used to achieve good quality NMR spectra. The NMR tube must be cylindrical and of uniform wall thickness to avoid distortion of the magnetic field [31].

Sample Spinning Sample solution in the cylindrical NMR tube, usually of 5 mm wall diameter, is held in a spinner or turbine and descended into the probe head on a column of air or nitrogen [29]. The sample is typically rotated around its axis at 10–20 Hertz to improve signal resolution. In modern NMR instruments, sample spinning is often unnecessary since it may induce undesirable artifacts and additional signal modulations. Instead, improved shim technology is used.

Shimming Shimming is the process of optimizing the magnetic field homogeneity. An electrical coil (shim coil) generates its own small magnetic field used to compact the main magnetic field and remove inhomogeneity. Shimming process has two main advantages: (i) improves the field homogeneity and (ii) monitors and improves the field stability giving optimum resolution [33]. Shim coils are further classified as zero-order, first-order, second-order, third-order, fourth-order, and fifth-order zshims [31]. Zero-order coils are aligned along the superconducting solenoid coil in the NMR spectrometer and are used to adjust inhomogeneities in the main static magnetic field B0 narrowly. First-order coils (X1, Y1, and Z1) are aligned at a right angle to the static magnetic field. They produce a magnetic field as a function of x, y, and z to create a magnetic field gradient shaped like a p-orbital. Second-order coils are also called XY, X2 −Y2 , ZX, ZY, and Z2 . They produce magnetic fields as the functions xy, x2 −y2 , zx, zy, and z2 used to create a magnetic field gradient shaped like a d-orbital. There are seven third-order coils: X3 , Y3 , Z2 X, Z2 Y, ZXY, Z(X2 −Y2 ), and Z3 , which produce magnetic x3 , y3 , z2 x. z2 y, zxy, z(x2 −y2 ), and z3 are used to create a magnetic field gradient shaped like f-orbitals. Ultra-high magnetic field NMR spectrometers are equipped with fourth- and fifth-order z-shim coils.

8.4.1.2

The Probe

The probe is considered the heart of NMR since it is a specialized instrumentation whose primary function is to hold both the transmitter and receiver coils as close as possible to the sample to detect weak NMR signals [29]. The probe contains radiofrequency (rf) coils that transmit and receive electromagnetic radiation. The rf probe determines the performance of the NMR spectroscopy [34]. When selecting a probe, it is important to consider the frequency range to which the probe is tuned since this determines the number of nuclei one can observe. Also, it’s essential to consider

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Fig. 8.11 Schematic illustration of a typical NMR probe head [31]

optimizing the rf coil configuration. The rf probe consists of either a single coil or two coils (crossed-coil configuration). Rf with a single probe is used to observe one selected probe frequency and may either be tuned to a predefined frequency range or be doubly tuned to enable simultaneous observation of deuterium via the lock system [29]. Figure 8.11 shows a typical NMR probe head. The inner coil is used for X-nucleus observation, primarily covering the frequency range from 109 Ag to 31 P. This inner coil is double-tuned for 1 H observation and decoupling [31]. The glass tube supports the coil and directs the variable temperature gas flow. Thermocouples are below the sample. A dewar (a double wall glass with a vacuum between the walls) surrounds the whole system, while the ceramics are located at the top and bottom. The probe is passed with either warm or cold gas to varying temperatures of the sample, which is held at a constant value by a thermocouple. The stability of the sample temperature is vital since any changes can cause a shift in chemical shift and magnetic susceptibility resulting in poor resolution. Crossed-coil configuration has both transmitter and receiver coils. Modern NMR spectroscopy consists of two coils where one can observe a proton of a sample and another nuclide referred to as X-nucleus. The transmitter coil is connected to the power amplifier output, and the receiver coil is connected to low-noise high gain rf amplifier input [25]. The sensitivity of the receiver coil determines the ultimate S/ N ratio. In crossed-coil configuration, 1 H and the 2 H lock are observed by the inner coil, whereas the outer coil observes the X-nucleus. This type of probe is ideal for 1 H sensitivity and inverse detection of X-nucleus using techniques such as HMBC, HSQC, and HMQC. Probe Tuning and Matching Optimization of electronic properties of the coil circuit is necessary to enable the transmitter coil to transmit the rf pulse to the sample and the receiver coil to efficiently pick up the NMR signals. Adjustments are made to the tuning circuit’s capacitor

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located near the coils in the probe head. Tuning the probe can be achieved through the matching and tuning process. The tuning process assigns the coil to the relevant nucleus rf. A poorly tuned probe can lead to poor sensitivity, thus increasing the S/ N ratio. Matching refers to equalizing the coil current to that of the transmitter and receiver to achieve maximum rf energy passing through the sample. The process of probe tuning is automated with computer control. Auto-tuning configuration takes two approaches. The first approach is via remotely monitored standard units that are connected to the probe-tuning rods through flexible cables. The second approach is more complex and involves a motor built at the probe’s base to perform optimization.

8.4.1.3

NMR Tubes and Sample Volumes

The NMR tube size and diameter are determined by the probe dimensions and the rf coil of the probe. The most commonly used tube diameter is 5 mm. The NMR tube diameter 1, 1.7, 2.5, and 3 mm are used for microprobes. 10 mm tube diameter is used to observe low-sensitivity nuclei, e.g., polymer studies. The benefit of using a smaller diameter NMR tube is to increase mass sensitivity. The required sample volume of 10 mm tube diameter is about 2,500 μL. 5mm tube diameter, its sample volume is between 500 and 600 μL. For 3, 1.7, and 1 mm, its sample volume is 150, 30, and 5 μL, respectively. Figure 8.12 shows the NMR sample tube, wall thickness, and the sample cavity where the NMR signal is generated [26].

8.4.1.4

Reference Compound

A suitable reference is required to serve as an internal chemical shift reference in the spectrum. In 1 H and 12 C NMR, tetramethylsilane (TMS, 0.0 ppm) is the organic solvent used. TMS has a sharp 2-proton singlet resonance that conveniently falls to Fig. 8.12 Schematic of NMR tube, sample cavity, and wall thickness [26]

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the spectrum’s one end. Additionally, TMS is a volatile solvent; hence, it can be easily removed, and it’s chemically inert. For the study of cyclopropane and saline, TMS is unsuitable reference material. In this case, a volatile 1,4-dioxane (1 H 3.75 ppm, 13 C 67.5 ppm) can be used, which can be removed by lyophilization. Other standard references which are not added to the sample are referred to as external references. Examples of such references include H2 O for 17 O nuclide, H3 PO4 (85%) for 31 P, among others. These references are held in a separate axial capillary inside the sample solution or an outer, concentric jacket. The reference spectrum is acquired before or after the sample of interest is carried out.

8.4.2 Spectrometer Preparation and Data Collection For the spectrometer to maximize the reproductivity in terms of optimum resolution and sensitivity, the spectrometer should be prepared depending on the sample type and the nature of the experiment. Figure 8.13 summarizes the procedure spectrometer preparation for data collection. All these steps in modern NMR spectrometers can be automated via computer control, although probe tuning requires equipped autotuneable probe heads.

8.4.2.1

NMR Pulse Excitation

The probe or NMR detector system is inserted into the magnet. The rf coils in the probe cause the excitation of the nuclear spins and detection of the resultant signals as the induced magnetization decays away [24]. A short pulse of rf energy over various frequencies is used in modern NMR spectrometers to excite the nuclear resonances. The transmitter supplies this pulse as monochromatic radiation; thus, nuclear spin gives rise to different spectra in accordance with different Larmor frequencies. Based on this, it will appear that the pulse cannot simultaneously excite all resonance simultaneously. According to Heisenberg’s Uncertainty principle, a single monochromatic

Fig. 8.13 Schematic illustration for spectrometer preparation for data collection [29]

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Fig. 8.14 Pulse excitation. a A short, intense rf pulse excites over a wide frequency window, and b a longer, weaker pulse provides a more selective excitation profile [29]

rf pulse has an adequate excitation bandwidth that depends inversely on the duration of the pulse. The duration of the rf pulse Δt is usually referred to as the pulse width. A short, intense pulse can therefore excite over a comprehensive frequency profile, whereas a longer, weaker pulse provides a more selective excitation window (Fig. 8.14). Modern NMR spectrometers are designed to deliver high-power 90 degrees pulses closer to 10 ms. Figure 8.15 shows on-line and off-line resonance excitation. Offline resonance excitation occurs when the transmitter rf pulse does not precisely match the nuclear Larmor frequency. The nuclei that resonate outside the excitation bandwidth of the pulse do not experience excitation at all and get aligned along the + z-axis. A 90-degree excitation pulse ideally transfers bulk magnetization (B0 ) from the +z-axis into the x–y plane (effective rf field Beff ). In other words, a 90° pulse flips the bulk magnetization into the x–y plane, indicating that the magnetization is saturated or excited. A 180° will flip from +z to –z is referred to as the magnetization that has been inverted. The receiver is gated off during pulse excitation because rf pulse excitation can be enormous and saturated, thus damaging the receiver [35].

8.4.2.2

Signal Detection

After a 90° pulse, the bulk magnetization is tipped into the x–y plane. Once the rf pulse is switched off, the x-y magnetization is processioned about the static field B0 so that it rotates at Larmor frequency. This rotating magnetization induces oscillating electromagnetic fields (emf), which are picked up by transmitter coils. The emf is detected via a phase-sensitive detector. Since it is challenging to handle signals at oscillating rf, digitalization of these frequencies in the spectrum is needed. The reference frequency is used. The NMR signals (megahertz) from the scanner are

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Fig. 8.15 On-resonance and off-resonance excitation. a rf is on-resonance and results in the rotation of the bulk magnetization vector about the applied rf field B1 . b nuclear spins that experience off-resonance excitation are driven by an effective rf field Beff [29]

Fig. 8.16 The NMR detection process. Digitized audio frequencies are recorded and stored, subtracted from the NMR rf signal and reference signal [36]

subtracted from reference signals to produce digitized signals (kilohertz), which are in the audio frequency range (possible to hear NMR resonances). These digitized frequencies are recorded and stored (Fig. 8.16).

8.4.2.3

Receiver and RF Preamplifier

The primary purpose of the receiver is to amplify the emf induced by nuclear magnetization (in microvolts) to the data handling and display level (in volts). In this process, rf frequencies are removed by a phase-sensitive detector (PSD). The design of the receiver plays a vital role in determining the S/N ratio or spectral resolution. The initial part of the receiver consists of a low-noise rf amplifier with nearly 30–40 dB gain. The role of a low-noise rf amplifier is to amplify decaying free induction decay (FID) as soon as possible after the rf pulse. The initial stage of the preamplifier is critical in determining S/N. The later preamplifier stage is crucial in successfully operating without overload at a higher voltage. The rf amplifier recovery time can be shortened by using the smallest practical coupling capacitor between the first and final amplifier stages and also by adding back-to-back shunt diodes to the ground at each output [25].

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Noise Filtering

The digitized free induction decay (FID) contains only the audio frequencies (AF) that result from subtracting the NMR signal from the reference frequency. Nyquist Theorem or sampling of NMR state that oscillating signal can be characterized by defining two datasets per wavelength [37]. The highest recognized frequency is known as spectral width (SW), while the time difference between the sampled data points is known as dwell time (DW). Signals which are equal to or less than SW will be characterized correctly. Those signals above SW (existing outside SW) will be incorrectly described and referred to as folded back or aliased into the spectrum. In modern NMR spectrometers, digital audio bandpass filters are used to eliminate these signals outside the spectral width [29].

8.4.2.5

Analogue-To-Digital Converter

Audio frequencies (AF) are digitized by the analogue-to-digital converter (ADC) into binary numbers proportional to the magnitude of the signal, then passed through a digital signal processor (DSP), and recorded and stored on the computer (Fig. 8.17). ADC (digitizer) limits the frequence range (spectral width) one can characterize depending on the speed of the incoming signal. Additionally, ADC determines the signal amplitude that can be measured. The digital binary numbers are computer bits that translate to ADC resolution. Modern NMR spectrometer has ADC resolution that operates with 14 or 16 bits. The 16 bits digitizer can present values in the range of ±32,767. The ratio of largest to slightest detectable bit or value is 32,767:1. The most negligible signal that can be recorded has a value of 1. Any signal with an amplitude of less than one cannot trigger ADC. If the signal has an enormous value greater than the one ADC can record, the signal intensity will not be measured correctly, leading to distortions in the spectrum [29].

8.4.2.6

Digital Signal Processor

In modern NMR spectrometers, signal processing is done digitally and involves frequency filtration and quadrature detection. Analogue quadrature phase-sensitive

Fig. 8.17 Schematic diagram of NMR data collection [29]

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detection uses 2 PSDs with 90° phase shifts between the reference signals. This makes it possible to distinguish between positive and negative differences in frequency. Figure 8.18 shows the incoming rf signal from the probe and preamplifier being split into two signals, each signal being directed into separate phase-sensitive detectors whose reference frequencies are identical but differ in phase by 90 degrees. The resulting audio frequency signals are then sampled, digitized, and stored for analysis [36]. In digital quadrature detection (DQD), one radio frequency channel is digitized. Then digital data is copied and manipulated to produce a second data set which is defined as 90 degrees from the original data. Figure 8.19 shows radio frequency (RF) being digitized to create a suitable intermediate frequency (IF) that passes through ADC to generate a second channel with identical amplitude and a 90 degrees phase shift.

Fig. 8.18 Schematic illustration of the analogue quadrature phase-sensitive detection in the NMR receiver [36]

Fig. 8.19 Schematic diagram of a digital quadrature detection [36]

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Host Computer

NMR spectrometers have host computers used to acquire NMR FID and manipulate data to interpret the result. Operation systems such as Windows, UNIX, or Linux are used in these host computers. Manipulation of FID NMR involves removal of DC offset, enhancing S/N or resolution, linear reconstruction of FT, FID, phase correction and rf spectrum parts, calculation of peak areas, printing, and plotting spectra [24]. NMR data processing softwares can be bought from a manufacturer or acquired from a third-party supplier. The supplier also provides software guidelines and NMR output parameters documentation, and other packages such as molecular modeling [38].

8.4.3 Sensitivity and Resolution Enhancement The concentration sensitivity (SC ) of the system is equal to signal-to-noise (S/N) over moles of the materials. Thus the sample concentration can be improved by using more significant solution volumes (free from paramagnetic impurities and particles) within the active volume of the coil, which is the region of the sample that sits within the coil and so contributes to the detected response (Fig. 8.20). A longer or wider coil will hold more sample henceforth improve the concentration sensitivity. The rf coil’s mass sensitivity (SM ) can be enhanced using microprobes. Considering the mass sensitivity of a rf coil is inverse to the diameter of the coil, d (S/N ∝ 1/d), the use of microprobes provides a reduced pulse width leading to more uniform excitation over wider bandwidths. The alternative is to use micro-flow probes [39]. The micro-flow probe involves placing the sample within the fixed coil geometry, where the rf coil is wound directly around the capillary tube. Such probes have active volumes of as little as 5-nanoliter, which obtain a much higher mass sensitivity [signal-to-noise ratio (S/N) per micromole] [40]. Another approach to enhance detection sensitivity is reducing the background noise in spectra by cooling the probe rf detection coils and the preamplifier. This is achieved either through helium-cooled probes or liquid nitrogen-cooled probes [41]. Fig. 8.20 The NMR coil’s active (observed) volume [36]

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NMR signal detection sensitivity can be enhanced by careful choice of receiver and transmitter. Additionally, S/N or resolution can be improved by signal averaging. Signal averaging may be understood as doubling the signal-to-noise ratio to acquire four times as many scans [29]. S/N can also be improved by using a digital filter after the detector in the receiver circuit. Thermal noise can be decreased with lower temperatures; thus, the signal will increase while the noise decreases [25]. The S/N ratio can also be increased by operating the spectrometer at higher magnetization proportional to B0 3/2 . S/N ratio can further be enhanced by either decreasing spectrometer recovery time or decreasing the NMR linewidth (lengthening T2 *). Either interaction of dipolar or quadrupolar can broaden linewidth. Hence the FID decay time can be shortened and the signal reduced at the end of the recovery time following the radiofrequency pulse.

8.4.4 Field-Frequency Lock Frequency drift in NMR resonance leads to loss of resolution. The field frequency lock system can be used to overcome this problem, where the frequencies of the deuterium solvent resonance (such as C6 D6 , CDC13 , (CD3 )2CO, etc.) are monitored. The deuterated solvents for the lock have different chemical shifts, hence different lock frequencies [31]. The lock system operates parallel to the principal channel. Dispersion-mode deuterium resonance has both magnitude and sign. Therefore, they are observed rather than absorption mode signals which have only magnitude. This helps the lock to regulate the field frequency. Signal errors are caused by drift in the magnetic field. Optimizing the lock can be achieved by altering the transmitter’s frequency or magnetic field to establish the deuterium signal resonance condition. Optimizing the lock can also be performed by probe parameters such as lock transmitter power, lock gain, and lock phase. Lock transmitter power is used to excite the deuterium resonance. It should be set to maximum to maximize the 2 H S/N ratio, but not too high to avoid lock saturation. Lock gain involves amplification applied to the detected lock signal, although it should not be amplified too high to prevent lock noise. The lock phase is adjusted to enable the lock signal to produce maximum intensity [36].

8.4.5 Calibration Calibration is done when one wants to set up a new experiment or has new hardware to install. The optimum performance of the NMR spectrometer is achieved through calibration. Radiofrequency duration is known as pulse width. Rf pulse calibration is defined by a 90-degree pulse (PW90 ). PW90 in microsecond are excited over wide bandwidth hence referred to as hard or non-selective pulse. Selective or soft pulses are effective over a small frequency window and obtained over a

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millisecond range of low power. Thus, a PW90 of 10 microseconds corresponds to a rf field strength of 25KHz, which is a pulse excitation value of modern NMR spectroscopy [29]. Pulse field gradients are used for signal selection or rejection. Two approaches are used for the calibration of the field pulse gradient. One is based on the use of an image of a suitable calibration sample and the second approach involves the measurement of molecular diffusion. Molecular diffusion measurement requires applying precise experimental conditions, reference solute or solvent use, and temperature calibration. Sample temperatures are measured by thermocouples which are located within the probe head. Calibration of thermocouples results in temperature regulation of the sample. Reference material with know temperature may be used during the calibration. Neat methanol for the range 175–310 K and 1,2-ethanediol (ethylene glycol) for 300–400 K is used as the standard 1 H temperature calibration samples for solution spectroscopy [42]. For low-temperature 1 H calibration, neat MeOH is used with a trace of HCl to sharpen the resonances. In 13 C measurements, tris(trimethylsilyl)methane is used [43].

8.5 NMR Structure Analysis and Interpretation Structure elucidation and verification may be differentiated while applying NMR techniques to solve chemical problems. Elucidation is the identification of structures without prior knowledge, e.g., novel natural products. Verification is also known as confirmation and may be used to prove existing structure. Computational algorithms may aid the development of structure from NMR correlation data [36]. NMR software help to generate a variety of structures that are consistent with the NMR experimental data, which typically consist of 1 H–1 H correlation spectroscopy (1 H– 1 H COSY), total correlated spectroscopy (TOCSY), heteronuclear single-quantum correlated spectroscopy (HSQC) or heteronuclear multiple-quantum correlated spectroscopy (HMQC), heteronuclear multiple bond spectroscopy (HMBC) and nuclear overhauser effect spectroscopy (NOESY) [44]. Li et al. [45] conducted an NMR structure analysis on a water-soluble pectic polysaccharide (MP-A40). MP-A40 was dissolved in deuterium oxide (D2O, 3%, w/v) at room temperature for 3 hours and freeze-dried before NMR analysis. The spectra of 1 H, 13 C, COSY, TOCSY, HSQC, HMQC, and NOESY of MP-A40 were recorded at 60 °C. The structural features of MP-A40 were elucidated by 1D and 2D NMR analysis.

8.5.1 1D NMR 1D NMR is classified as 1 H and 13 C NMR. In Li et al. [45] experimental results, 1 H and 13 C NMR spectra were recognized in the α-configuration of the anomeric proton (H1) and anomeric carbon (C1) in MP-A40 residue. The 1 H NMR (500.13

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MHz) spectrum of MP-A40 in D2 O at 60 °C showed two anomeric proton signals at δ 4.983 and 4.794 ppm, respectively, which were designated as residue A1 and B1 [45]. Chemical shift (δ) of residue A for H-2 to H-5 were 3.634, 3.852, 4.344, and 4.953 ppm, thus labeled as A2, A3, A4, and A5. Similarly, the chemical shift of residue B for H-2 to H-5 was 3.624, 3.849, 4.293, and 4.527 ppm, and labeled B2 to B5 (Fig. 8.21a). 13 C NMR (125.78 MHz) spectrum of MP-A40 in D2 O at 60 °C showed anomeric signals (C1) of residue A at δ 99.74 ppm and residue B at 100.71 ppm, C6 of residue A at 172.5 ppm and C6 of residue B at 176.1 ppm (Fig. 8.21b). Wang et al. [44] used 1 H and 13 C NMR spectra to recognize α- or β-configuration of sugar residue’s anomeric proton and anomeric carbon. Figure 8.22 shows the anomeric regions of α-configuration, which appeared between δ 5.1–5.8 ppm (anomeric proton, H1) and δ 98–103 ppm (anomeric carbon, C1). In contrast, βconfiguration appeared between 4.3–4.8 ppm and 103–106 ppm in the anomeric regions of H1 and C1, respectively. Figure 8.22a shows signals of other groups like –CH3 , CH3 COO–, and –O–CH3 (MeO), which are revealed in the 1 H NMR spectrum. 13 C NMR spectrum experienced a broader chemical shift (δ) of polysaccharides which ranged from 0 to 180 ppm. Figure 8.22b shows other groups, such as methacetin methoxy-C-13 (MeC), observed at various 13 C NMR spectrums. Chemical shifts of C2–C6 ranged from 57 to 87 ppm [44].

8.5.2 2D NMR Considering the limiting factor of the 1 H NMR spectrum and 13 C NMR spectrum, 2D NMR techniques (COSY, TOCSY, HMQC, HMBC, and NOESY) play a vital role in the structural analysis of polysaccharides. Homonuclear 1 H–1 H correlation spectroscopy (1 H–1 H COSY) experiment contains spin coupling networks, reflecting the adjacent proton’s correlation in a sugar residue. The anomeric proton assignments of residues can be accomplished through scalar connectivity by correlating spins step-wise around the spin coupling network [44]. In Li et al. [45] experiment on water-soluble pectic polysaccharide (MP-A40), the H1-H5 signals of residue A at δ 4.983, 3.634, 3.852, 4.344, and 4.953 ppm respectively, and the H1-H5 signals of residue B at 4.794, 3.624, 3.849, 4.293 and 4.527 ppm respectively (Fig. 8.21a) were all obtained and labeled using COSY spectrum (see Fig. 8.23a). The total correlated spectroscopy (TOCSY), which is also known as homonuclear Hartmann-Hahn spectroscopy (HOHAHA), provides the complete correlation of protons within one residue ring through a J-network, which is identified by signals on the same vertical or horizontal line [46]. TOCSY spectrum was used to support the COSY spectrum assignment through well-resolved cross peaks of H-1/H-2 (4.983/3.634), H-2/H-3(3.634/3.852), H-3/ H-4 (3.852/4.344), H-4/H-5 (4.344/4.953) in residue A and similarly to residue B (Fig. 8.23b). Heteronuclear single-quantum correlated spectroscopy (HSQC) and heteronuclear multiple-quantum correlated spectroscopy (HMQC) demonstrate the correlations between proton and the directly linked carbon, especially where the

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Fig. 8.21 1D NMR spectrum of MP-A40. a 1 H NMR spectrum, b 13 C NMR Spectrum [45]

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Fig. 8.22 1D NMR spectra chemical shifts of polysaccharides. a 1 H NMR spectrum, b 13 C NMR spectrum [44]

anomeric networks are well separated [47]. HMQC spectrum revealed chemical shifts of 13 C NMR spectra of residue A from C1-C5 as 99.7, 69.1, 69.8, 79.3, and 71.3 ppm, respectively. The same applied for residue B of MP-A40 as 100.7 represented anomeric C1. Figure 8.23c showed that two cross peaks in the anomeric region (4.983/99.74 ppm and 4.794/100.71ppm) appeared, indicating that at least two spin systems existed [45]. 1 H and 1 H correlation (nuclear overhauser effect spectroscopy, NOESY) or 1 H and 13 C correlation (heteronuclear multiple-quantum correlated spectroscopy, HMBC) are utilized to figure out the sequences of sugar residues in polysaccharides [48]. HMBC spectrum can be used to determine the linkages between adjacent sugar residues, reflecting long-range coupling between protons and carbons about two or three bonds distance [44]. Figure 8.23d shows the chemical shift of C6, which was confirmed by the intra-correlation cross peaks of residue A in the HMBC spectrum. The cross peaks between H5 and C6 (4.953/171.8) were clearly observed, and residue A was assigned →4)-α-D-GalpA-(1→ (residue A) after combining all the 1 H and 13 C chemical shifts. For residue B, cross peaks H5 and C6 (4.527/176.1) were observed in the HMBC spectrum. There was a cross peak between residue B and proton with a chemical shift of 3.694 ppm on HMBC (Fig. 8.23c). This peak didn’t originate from residue B sugar ring; thus, the peak was assigned to the methoxy group of proton 3.694 and carbon 53.75 ppm. The result demonstrated that residue was present as →4)-α-D-GalpA6Me-(1→ (residue B) [45]. NOSEY spectrum presents both intra-residual and inter-residual cross peaks. In Fig. 8.23e, a cross peak was found between H1 of →4)-α-D-GalpA-(6-OMe)-(1→ (residue B) and H4 of residue A, indicating a connection between residue A and residue B through (1→4)-glycosidic linkage [44]. The sequence of glycosyl residues of MP-A40 was also confirmed by the NOESY experiment (Fig. 8.23e). In NOESY experiment, the intra-residual cross peaks were observed from AH1 to AH2, AH3, AH4, AH5; AH2 to AH3, AH4, AH5; AH3 to AH4, AH5; AH4 to AH5; BH1 to BH2, BH3, BH4, BH5; BH2 to BH3, BH4, BH5; BH3 to BH4, BH5; BH4 to

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Fig. 8.23 2D NMR spectrum of polysaccharide MP-A40. a COSY spectrum, b TOCSY spectrum, c HMQC spectrum, d HMBC spectrum, e NOESY spectrum (60 °C in D2O) [45]

BH5, alongwith inter-residual contacts from AH1 to BH1, BH2, BH3, BH4, BH5; AH2 to BH1, BH3, BH4, BH5; AH3 to BH1, BH2, BH4, BH5; AH4 to BH1, BH2, BH3, BH5 [45]. Based on the above analysis, all residue A and B chemical shifts were identified. The central repeating unit of MP-A40 was established as →4)–[α– GalpA6Me-(1→]m –[4-α-GalpA-(1→]n .

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8.6 NMR Spectroscopy NMR spectrometers come in a variety of designs, the two most popular being continuous-wave (CW) and pulsed or Fourier-Transform (FT-NMR). Pulsed FTNMR instruments have mainly superseded CW-NMR spectroscopes. Nevertheless, CW-NMR spectroscopes continue to be frequently utilized for standard 1 H NMR spectroscopy because they require less maintenance and running expenses [49]. Continuous-wave (CW) spectrometers use fixed electromagnets for 1 H NMR studies at 60 MHz. Resonance absorption signals are achieved by sweeping of frequency by varying the current in a frequency coil. On the other hand, pulsed NMR spectrometers use the Fourier transform technique to record spectra. Magnets in FT-NMR spectrometers are cooled with liquid helium, while electromagnets in low-resolution CW equipment are cooled using water.

8.6.1 Continuous-Wave (CW) Spectroscopy Continuous-wave (CW) spectroscopy was employed in the early decades of nuclear magnetic resonance spectrometers. Even though it was possible to generate NMR spectra by altering the magnetic field and electromagnetic radiation frequency in an electromagnet, it was more common to use a fixed frequency source. This method entailed observing the resonant absorption signals [50]. As CW spectroscopy explores the NMR response at distinct frequencies sequentially, it is less effective than Fourier approaches. In Fig. 8.24, the sample is placed inside the resonator. The two loop antennas excite the resonator and monitor the signal [51]. The obtained spectra have a low signal-to-noise ratio (S/N) since the NMR signal is inherently weak. Signal averaging, or combining the spectra from observational data, can help to alleviate this. The random noise increases relatively slowly as the square root of the number of spectra, whereas the NMR signal is consistent across scans and accumulates exponentially [52]. Therefore, as the square root of the number of spectra evaluated, the total ratio of the signal to the noise rises.

8.6.2 Multidimensional NMR Spectroscopy The spectroscopist can gather a wide range of data on the molecule by employing pulses of various sizes, frequencies, and periods in well-planned arrangements or pulse sequences. One type of FT-NMR that uses at least two pulses and varies the pulse sequence throughout several repetitions is known as multidimensional nuclear magnetic resonance spectroscopy [53]. The development of multidimensional NMR investigations led to practical approaches for investigating biomolecules in solution, particularly for figuring out the

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Fig. 8.24 The schematic diagram of continuous wave nuclear magnetic resonance (CW-NMR) spectrometer [51]

structures of biopolymers like proteins or even tiny nucleic acids. At a minimum, one dynamic time span and a series of pulses will be present in multidimensional nuclear magnetic resonance. Two different time periods will exist in three dimensions. Three will be different in four dimensions [54]. Such experiments are numerous. In one, these time periods permit, among other things, the transfer of magnetization between nuclei and, as a result, the identification of the specific nuclear-nuclear couplings that permitted the magnetization transmission [55]. There are typically two categories for detectable interactions. In addition to through-bond interactions, there are also through-space interactions, with the latter typically coming due to the nuclear Overhauser effect. Nuclear-overhauser experiments could make atomic-distance measurements.

8.6.3 Fourier-Transform Spectroscopy The strength of the NMR signal as a measure of frequency is used in most NMR applications. Initial efforts tried irradiating concurrently with many frequencies to collect the NMR spectrum more effectively than straightforward CW techniques [56]. However, it soon became apparent that using brief radio-frequency pulses was a more detailed approach (centered in the middle of the NMR spectrum). The span of excitation (bandwidth) is inversely related to the pulse duration. Therefore a brief square pulse with a particular "carrier" frequency consists of a frequency range centered on the carrier frequency (the Fourier transform of an approximate square wave contains contributions from all the frequencies in the neighborhood of the principal frequency). All NMR transformations are equally excited when such a pulse is applied to a group of nuclear spins. This is equivalent to tilting the magnetization vector away from its equilibrium situation in relation to the net magnetization vector (aligned

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Fig. 8.25 Fourier transformation nuclear magnetic resonance (FT-NMR) spectrometer [57]

along the external magnetic field). At the spin-specific NMR frequency, the outof-equilibrium magnetization vector precesses around the external magnetic field. An electrical signal that oscillates at the NMR frequency is produced when this oscillating magnetization produces a charge in an adjacent receiver coil. The total NMR responses from all the excited spins make up this signal, which is also referred to as the free induction decay (FID). This time-domain signal (intensity versus time) needs to be Fourier converted in order to get the frequency-domain NMR spectrum (intensity vs. frequency). Thankfully, the advancement of FT-NMR was accompanied by that of digital computers and Fast Fourier Transform techniques (see Fig. 8.25) [57]. In recognition of his contributions to FT-NMR and the creation of multidimensional NMR, Richard R. Ernst, one of the founders of pulse (FT) NMR, received the 1991 Nobel Prize in Chemistry.

8.6.4 Solid-State NMR Spectroscopy Solid-state NMR is applicable in a wide range of fields ranging from nano-interfacial multi-functional composite catalytic materials studies [58], atomic investigations of catalytic mechanism [59], measurement of protein membranes, cell wall, inorganic, organic and hydrid materials [60] to structural characterization of oxides [61]. Figure 8.26 shows the working mechanism of ssNMR based on spin active nuclei.

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Fig. 8.26 Schematics on the working principle of solid-state NMR [63]

The solid sample is added to the NMR probe head and inserted into the superconducting magnet. The nuclear spin signals generated are then amplified to produce the NMR spectra. In the solid state, where molecules are kept motionless, and each emits a distinct signal while being in slightly varied electrical environments, there exists no signal averaging by thermal motion. Due to this volatility in the electronic environment makes resolution drastically reduced, making analysis more challenging. Raymond Andrew was a pioneer in the invention of high-resolution solid-state nuclear magnetic resonance. He developed the magic angle spinning (MAS) method, which enabled a multiple-order boost in resolution. By spinning the sample at several kilohertz, the sample is averaged in MAS [62]. Since MAS is a widely used method for high-resolution spectrum, it has been used for studying the zeolites and investigating chemical reactions on zeolites [64]. Figure 8.27 illustrates how the broadening of the spectrum of a solid-state sample is avoided through a high-speed rotation about an axis that is inclined to the direction of the applied magnetic field (B0 ) by a magic angle (Pm ) of 54.7° [65]. Resolution in magic angle spinning can be affected by instrumental, residual, motional, and relaxation effects. Instrumental factors include angular instability, insufficiently fast spinning, imperfect adjustment to the magic angle, bulk susceptibility effects, and inhomogeneity of the laboratory magnetic field. Residual interaction factors include but are not limited to chemical shift distributions, quadrupole

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Fig. 8.27 Schematics showing MAS of Pm = 54.7° with reference to the magnetic field (B0 ) [65]

effects, residual dipolar and pseudo-dipolar interactions, antisymmetric tensor interactions, and higher-order multipole effects. Motional and relaxation effects involve cross-relaxation, spin-lattice relaxation, and slow internal motions [65]. By developing the cross-polarization method to improve poor availability and sensitive nuclei, Alex Pines and John S. Waugh changed the field. Highly resolved 13 C NMR spectra may be obtained from solid samples using MAS combined with crosspolarization double-resonance methods [66]. This combination of techniques was pioneered by Schaefer and Stejskal [67]. The double-resonance procedure decouples the strong proton heteronuclear dipolar interactions and heteronuclear J couplings, and using the Hartmann–Hahn condition enhances the weak I3C NMR signal by proton polarization transfer.

8.7 Applications NMR investigates the absorption of radiofrequency radiation by atoms and can analyze the composition and structure of many inorganic and organic compounds. So it plays an irreplaceable role in the development and progress of science and technology. Nuclear magnetic resonance is divided into solid nuclear magnetic resonance, liquid nuclear magnetic resonance, and nuclear magnetic resonance imaging. Because of its rapidity, accuracy, and high-resolution advantages, nuclear magnetic resonance plays a great role in scientific research activities, production, and life. It has a wide range of applications, including chemistry, biology, medicine, environment, agriculture, geology, mining, quantum computing, and many other fields. This chapter mainly summarizes the applications of NMR in solid structure analysis, biomedical fields, purity determination, and combustion chemistry.

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8.7.1 Determination of Molecular Structure in Solids Solid-state NMR can provide information about chemical composition and structure at the atomic level, and is widely used to characterize the detailed structure of solid samples, including metals, organic compounds, and inorganic compounds [68–70]. Metal-organic frame material (MOFs) is a coordination polymer that has developed rapidly over the past two decades. It has a 3D pore structure, generally takes metal ions as the connection point, and organic ligand supports to form a 3D extension. It is another significant new porous material besides zeolites and carbon nanotubes. It is widely used in catalysis, energy storage, and separation. Therefore, it is necessary to use appropriate diagnostic methods to determine the detailed structure and related properties of MOF. Previous studies have proved that solid-state NMR is powerful enough to study the detailed structure of MOF [71], and its resolution can reach the atomic level. Solid-state NMR is also used to characterize the structure of porous materials, not only on MOF but also on zeolites. Recently, Wang et al. [72] reported the latest research application of ammonia probe-assisted solid-state NMR technique in zeolites and catalysis (Fig. 8.28). When designing zeolite molecular sieves, it is necessary to achieve high activity and selectivity. So it is essential to use NMR to understand the reaction center and mechanism at the atomic level. Using the ammonia probe to assist nuclear magnetic resonance, as reported in this paper, can enhance the nuclear magnetic resonance signal strength and determine the number of reaction centers with high precision. The development of this technology can identify some ions directionally, thus opening up a new way to study zeolite molecular sieves. He et al. [73] introduced the applications of solid-state NMR techniques to investigate the structure and host-guest interactions in metal-organic frameworks. A highfield NMR spectrometer in combination with a sensitivity-enhanced solid-state NMR method facilitated the detection of metal centers containing low-γ nuclei (25 Mg, 67 Zn, 91 Zr, etc.). Multi-nuclear and multidimensional solid-state NMR spectroscopy was employed to study the chemical environment and coordination state of metal clusters and organic linkers within MOFs. The metal center plays a vital role in MOF’s stability and chemical properties. Solid state NMR can characterize the metal center Fig. 8.28 Schematics illustrating the application of NMR spectroscopy in the quantitative investigation of acid sites and carbenium ions in solid acid catalytic reaction [72]

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and obtain the detailed structure of the metal center [74]. Low-γ nuclei have resonance frequencies below 15 N, including 25 Mg, 67 Zn, 47/49 Ti, and 91 Zr, which are difficult for conventional NMR observation. The metal centers of low-γ nuclei in MOF can be analyzed using high-field spectroscopy and solid-state nuclear magnetic resonance [75, 76]. Figure 8.29 shows the structure and local Zr environment of MIL-140A. Figure 8.30 shows the framework and various Mg coordination environments. Brouwer [77] summarized the applications of solid-state NMR in siloxane polymers, glasses, and porous materials. Figure 8.31 reveals the number of citations by year citing “29 Si NMR” and “29 Si solid-state NMR”, which reflects the importance of silicon-based solid materials. Various 2D homonuclear and heteronuclear correlation experiments have investigated spatial proximities and covalent bonding networks between 29 Si spins and 29 Si and other nuclei by using solid-state NMR, providing bonding and distance information that can be used to solve the 3D structures of materials (Fig. 8.32).

Fig. 8.29 a–c Structure and local Zr environment of MIL-140A [73]

Fig. 8.30 The framework and Mg coordination environments of α-Magnesium formate [αMg3(HCOO)6] [73]

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Fig. 8.31 The number of citations by year citing “29 Si NMR” and “29 Si solid-state NMR” [77] Fig. 8.32 The Structure of the zeolite framework showing the tetra-propylammonium template cation and the cage containing the fluoride ion highlighted in red [77]

8.7.2 Bio-Medical-MRI Magnetic resonance imaging is widely used in biomedicine, including neuroimaging, angiocardiography, musculoskeletal system imaging, liver and gastrointestinal system imaging, and magnetic resonance angiography. MRI is the preferred research tool for neurological cancer because it has better resolution than CT and can better display the posterior fossa containing the brainstem and cerebellum. Because many images are milliseconds apart, they show how the brain responds to different stimuli, allowing researchers to study functional and structural brain abnormalities in mental disorders. Cardiac MRI complements other imaging techniques, such as echocardiography, cardiac CT, and nuclear medicine. Its applications include the assessment of myocardial ischemia and vitality, cardiomyopathy, myocarditis, iron overload, vascular disease, and congenital heart disease. Applications of magnetic resonance

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imaging in the musculoskeletal system include spinal imaging, joint disease assessment, and soft tissue tumors. Hepatobiliary MRI is used to detect and characterize the liver, pancreas, and bile duct lesions. MR colonography may play a role in detecting large polyps in patients with an increased risk of colorectal cancer. Magnetic resonance angiography produces arterial images to evaluate arterial stenosis or aneurysm. Magnetic resonance angiography is commonly used to assess the neck and brain arteries, thoracic and abdominal aorta, renal artery, and leg [78]. A variety of techniques can be used to generate images. The NMR signal intensity is related to the hydrogen nuclear density in the sample. If the water content ratio of various tissues in the human body is different, the number of hydrogen nuclei is different, and the NMR signal intensity is different. This difference is used as a characteristic quantity to separate all kinds of tissues, which is the nuclear magnetic resonance image of hydrogen nuclear density [78]. The difference in hydrogen nuclear density and relaxation time between different human tissues and between normal tissues and diseased tissues is the most critical physical basis for the clinical diagnosis of MRI. When a radiofrequency pulse signal is applied to the patient, the energy state of the hydrogen nucleus changes (Fig. 8.33a). After the radiofrequency, the hydrogen nucleus returns to the initial energy state, and the electromagnetic wave generated by resonance is emitted. The RF system consists of a coil, transmitter, and receiver, which analyze the signals (Fig. 8.33b). The slight difference in nuclear vibration can be accurately detected. After further computer processing, it is possible to obtain a 3D image of the composition of the histochemical structure, from which we can obtain information, including the difference between water in the tissue and the movement of water molecules. In this way, pathological changes can be recorded. Most of the weight of the human body is water, and a high proportion of water is the basis on which magnetic resonance imaging can be widely used in medical

Fig. 8.33 a Schematic illustration of the MRI system. b Configuration of the gradient coils used for spatial encoding in all 3D. Transceiver stipulates the RF system consisting of a coil, transmitter, and receiver [79]

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diagnosis. The water in the organs and tissues of the human body is different, and the pathological process of many diseases will lead to changes in the morphology of water, which can be reflected by magnetic resonance imaging. The images obtained by MRI are very clear and precise, which significantly improves the diagnostic efficiency of doctors and avoids the operation of thoracotomy or exploratory laparotomy. Because MRI does not use X-rays that are harmful to the human body and contrast agents that are prone to allergic reactions, there is no harm to the human body. MRI can provide multi-angle and multi-plane imaging of various parts of the human body, which has a high resolution, can more objectively and concretely display the anatomical tissue and adjacent relations in the human body, and can better locate and determine the focus. It is of great value in diagnosing systemic diseases, especially in diagnosing early tumors.

8.7.3 Purity Determination As one of the most critical indicators in the process of chemical quality control, purity has a crucial impact on experimental results, product quality, and quantitative analysis. Therefore, it is necessary to carry out strict purity testing and quality analysis of chemical drugs. Compared with chromatography and spectroscopy, nuclear magnetic resonance spectroscopy is a powerful tool for chemical molecular structure analysis, which is of great value in the pharmaceutical industry, agriculture, and food processing to analyze product components, isomers, and multi-component identification. Ginglinger et al. [80] started their research on the enantiomeric purity of quaternary phosphonium cations as early as 1998. They found the magnetic nonequivalence of the signals for each enantiomer using the readily accessible l H and 31 P nuclei. D, L-hexamethylpropyleneamine oxime (HM-PAO) is well known to be the effective isomer when HM-PAO is used as a radiopharmaceutical. Its diastereoisomeric purity is of great importance because meso-impurity decreases the concentration of the 99mTc-complex in the brain. Kurteva [81] used 13 C-NMR spectroscopy to analyze the determination of the diastereoisomeric purity of HM-PAO. Pedras et al. [82] studied the enantiomeric purity of the phytoalexins spirobrassinins by 1H NMR. Kagawa et al. [83] measured the purity of acetyl-L-carnitine by NMR with chiral lanthanide shift reagents. They optimized the experimental conditions to provide two significant split signals for the enantiomers, leading to a successful quantitative analysis. Gariani et al. [84] also studied the enantiomeric purity determination using NMR. They reported enantioselective synthetic methods involving chiral organic tellurium compounds by using NMR. They solved this challenge of the discrimination of enantiomers and the determination of the enantiomeric purity of a sample by using two indicators in NMR to distinguish isomers.

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Lewis et al. [85] used NMR to prove the purity of a single enantiomer. They developed a method capable of discriminating between enantiomers to resolve the question of whether racemization has occurred during the synthesis of a chiral molecule. Based on the determination of pulse length, Monakhova et al. [86] established a fast and reliable NMR spectroscopy for the quantitative determination of purity of drug reference materials. Their method has been tested on drugs including Ibandronic acid, amantadine, ambroxol, and lecanidide. The PULCON recoveries were above 94.3%. This indicates that q-NMR is a fast and reliable tool for drug quantification. Shen et al. [87] reported the application of quantitative NMR for purity determination of standard ACE inhibitors. They studied the accuracy of the quantitative NMR method for purity determination of ACE inhibitors and discovered two pairs of new diastereoisomers. In summary, NMR plays an irreplaceable role in determining the purity of substances, especially in detecting compounds with enantiomer isomerization. Rapid, sensitive, and precise detection using NMR is a powerful tool for this development.

8.7.4 Investigations of Catalytic Mechanism and Dynamics in Catalytic Reactions of Syngas 8.7.4.1

Fundamental Studies on Catalytic Reaction of Syngas

Syngas catalytic reaction is the process of transforming syngas (CO /H2 ) into highvalue-added hydrocarbons. In recent years, some experiments on syngas reactions have been performed. Ding et al. [88] investigated the effects of proximity-dependent metal migration on bifunctional composites catalyzed syngas to olefins. Zhou et al. [89] transformed syngas into ethanol by relay catalysis via DME and MA intermediates. Michel et al. [90] used Miscanthus X Giganteus (MXG) to produce syngas in different catalysts and temperatures. Among different catalytic reactions of syngas, Oxide-zeolite (OXZEO) bifunctional catalysis has become one of the most attractive methods in this field. Compared to traditional methods, oxide-zeolite (OXZEO) bifunctional catalysis has a higher target product selectivity because oxide and zeolite components tandemly cooperate in the syngas-to-hydrocarbons process. However, the mechanism of this process is limited, mainly when concerned with the initial C–C bond formation and growth on the oxide surface. The surface intermediates observed by traditional in-situ spectroscopy have been limited to C1 species, which provides no evidence of the surface C–C bond formation. Solid-state NMR (ssNMR) has been proven to be a powerful tool for exploring heterogeneous catalytic reactions.

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NMR Application in Syngas Conversion Reaction Over ZnAlOx Surface

Gao et al. [91] investigated the syngas conversion reaction over ZnAl Ox surface by using conventional 13 C solid-state NMR. During the reaction, 13 C -enriched syngas (13 C CO/H2 = 1:2) was used as the feed gas. The surface species were captured by instantly quenching the reaction with liquid nitrogen. Figure 8.34 shows 13 C directly excited (DE) and cross-polarization (CP) magic angle spinning (MAS) NMR spectra of the surface species at different temperatures and reaction times on ZnAlOx. When set reaction temperature to 423 K (4 min), signals located at 169 ppm with a shoulder peak at 166 ppm can be ascribed to forming formate species (HCOO–). Rising the temperature to 523 K leads to the appearance of up-field signals with chemical shifts of 48 and 52 ppm. Further raising the temperature to 623 K leads to an emergent peak at 60 ppm, indicating a step-wise formation process of surface formate → methoxy groups (52 ppm) → methanol (48 ppm)/DME (Methoxymethane) (60 ppm). Keeping the same temperature at 623 K while prolonging the reaction time leads to more DME formation (0.5–12 min). The abundant C1 species observed suggest a formate-intermediated syngas-to-methanol/DME pathway over the ZnAlOx surface,

Fig. 8.34 13 C DE MAS NMR spectra of ZnAlOx with 13 C-syngas reaction at varied temperatures and reaction times. The spectra were recorded at 9.4 T and MAS rate of 8 ~ 10 kHz. 5 ~ 6 thousand scans were accumulated for each NMR experiment, corresponding to 8.3 ~ 10 h per spectrum. Asterisks (*) denote spinning sidebands [91]

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Fig. 8.35 DNP enhanced 13 C CP MAS spectra at 14.1 T, 110 K (blue and red for μω on and off, respectively) and room temperature spectrum at 14.1 T (black) of ZnAlOx catalyst after reaction with 13 C-syngas at 623 K for 4 min. MAS rate was set to 12.5 kHz. The experiment time is about 15 min for the DNP and 13 min for the room temperature spectrum (256 scans). Asterisks (*) denote spinning sidebands [91]

consistent with previous infrared studies. Only C1 surface species are observed in Fig. 8.34, which cannot fully explain the C2+ species’ formation in the gas phase. Furthermore, to explore the potential surface species on ZnAlOx , they have exploited the sensitivity gained from MAS DNP (dynamic nuclear polarization) NMR, which is more sensitive than conventional 13 C solid-state NMR. Figure 8.35 shows the DNP-enhanced 13 C CP MAS NMR spectra of the ZnAlOx sample (reacted with 13 C-syngas at 623 K for 4 min) impregnated with TEKPol/1,1,2,2tetrachloroethane (TCE) solution. Due to the high sensitivity of DNP NMR, the emergence of additional signals in the range of 9 ~36 and 180 ~ 186 ppm was significantly increased. These signals indicate besides C1 species more complex surface species exist over the ZnAlOx oxide surface.

8.7.5 In Situ and Ex Situ NMR Studies of Lithium-Ion Battery (LIB) and Sodium-Ion Battery (SIB) Materials Before beginning this section, a preliminary understanding of in situ and out of situ detection techniques is required. The in situ test aims at real-time detection and tracking of the reaction process without pausing. While in the ex situ test, the

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reaction has been stopped by the time the test is done, which means the test is generally detected by sampling.

8.7.5.1

Sodium-Ion Battery (SIB)

Due to the vast abundance and low cost of sodium resources and their similar electrochemistry to the established lithium-ion batteries, sodium-ion batteries (SIBs) have attracted considerable interest as ideal candidates for grid-scale energy storage systems [92, 93]. The growth and evolution of sodium metal microstructure over time are difficult to be characterized by conventional non-in situ analysis methods [94]. To understand its influence on the electrochemical solution-deposition process of sodium metal, in situ characterization techniques are needed to study its growth and evolution process quantitatively. Therefore, this section only describes the in-situ NMR characterization process. In situ NMR Studies of Sodium-Ion Battery Bayley et al. [95] conducted an in-situ 23 Na NMR study of Na–Na symmetric cells. They revealed that electrochemical Na metal deposition (under the conditions used) continually formed HSA microstructures, even when the current was reversed (Fig. 8.36a, b). Analogously to the case of dendritic Li growth [96], Na anodes form high surface area (HSA) microstructures upon cycling. Additionally, they compared the fraction of HSA Na detected by the NMR experiment (mNMR ) and the total accumulated mass derived from Faraday’s law (meChem )—denoted as FHSA = mNMR / meChem —enabled two types of HSA Na formation (Fig. 8.36c) to be distinguished. Smooth deposition and stripping (reversed current) regime occur in FHSA ∼ 0 for low current densities (0.5 mA cm–2 ), while in FHSA ∼ 1 for current densities >0.5 mA cm–2 , a rough deposition regime with minimal removal of HSA Na upon current reversal (Fig. 8.36c). The finding helps to mitigate the microstructures prevalence and cell short-circuiting risk through management of the operating parameters.

8.7.5.2

Lithium-Ion Battery (LIB)

Lithium-ion batteries (LIBs) have become the essential, portable energy source for modern industrial products due to their high voltage and high energy density. While the energy density of LIBs continues to increase year on year, both the miniaturization of portable electronics necessitating smaller but higher energy density batteries and the transition toward vehicle electrification requiring larger, cheaper, and higher energy density batteries means that the demand for further improvement remains intense. Liu et al. [97] investigated how DMF stabilized Li3N slurry is used to manufacture self-prelithiatable lithium-ion capacitors, which exhibit excellent ultrahigh energy density of about 120 Wh kg-1 and excellent cycle stability with about 90% retention after 10,000 cycles.

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Fig. 8.36 a In situ 23 Na NMR signal of the Na metal peak grows until the cell short circuits. b Integral of the normalized 23 Na metal resonance for galvanostatic cycling at three different current densities. c Fraction of HSA Na during galvanostatic cycling at various current densities; a ratio of 1 indicates completely rough deposition, whereas 0 indicates smooth deposition [95]

In situ and Ex situ NMR Studies of Structural Changes in Si Electrodes for LIBs Graphite has historically been used as the anode of choice for LIBs, but its capacity is limited to 372 mAh/g. To exceed this limit, silicon (Si) based materials have been proposed, which offer up to ten times larger gravimetric and volumetric capacities. However, the significant volume increase of Si during lithiation and thus of Si-based anodes contributes to the mechanical failure of the cell components. Si electrodes offer the highest theoretical capacity for LIB anodes, alloying with Li to form Li15 Si4 giving a theoretical ability of 3572 mAh/g [98]. During the first lithiation, crystalline Si undergoes a crystalline-to-amorphous phase transition. Key et al. [99] combined the ex-situ 7 Li NMR on both lithium silicide model compounds and discharged samples (Fig. 8.37a, b). Distinct resonances were observed for Li in the carbon/ electrolyte/SEI above 110 mV. Moreover, additional resonances were observed from Li ions nearby isolated Si and 2–5 atom Si clusters below this potential. The resonance for Li near isolated Si increased with the increment of Li content, which indicates the Si–Si bond breaking within the clusters and the final formation of the Li15 Si4 phase. Furthermore, they laid their insights into metastable intermediates obtained through in-situ 7 Li NMR (Fig. 8.37c). The observation of a new, negatively shifted resonance revealed that upon deep discharge, the reactive Li15+δ Si4 phase would form back to the more stable Li15 Si4 . When the cell rested, the process was likely accompanied by electrolyte reduction. The nonstoichiometry and reactivity revealed by NMR highlighted one of the challenges associated with using Si in a commercial cell and motivated future studies to explore more effective binders in the self-discharge processes.

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Fig. 8.37 a Electrochemical profile of the first discharge of crystalline Si versus Li/Li + . b ex-situ 7 Li MAS NMR spectra of battery samples stopped at different potentials during the first discharge of crystalline Si vs Li/Li + . c 7 Li in situ static NMR signals of Li insertion into crystalline Si [99]

8.7.6 Solid-State NMR Studies of Nano-interfacial Multi-functional Composite Catalytic Materials Before understanding the catalyst properties and catalytic phenomena, structural characterization is a vital process. Solid catalysts differ from active components and structures, including frameworks, pores/cages, and surfaces/interfaces [100]. For example, the acid sites, including Brønsted and Lewis acid sites in zeolites, are heterogeneously distributed in zeolite channels or cavities, which correlate with the silicato-alumina ratio of a framework [101]. Solid-state NMR (ssNMR) spectroscopy is a powerful technique that investigates catalysts at the atomic level. Compared to

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X-ray diffraction (XRD), which requires long-range structural ordering, ssNMR is more sensitive to geometries and orderings in short to medium range. The elementspecific feature makes NMR a critical spectroscopic tool to detect the target nuclei microchemical environments, including the coordination state and electronic structure. Besides, ssNMR can characterize the dynamics of adsorbed molecules and frameworks in catalysts. Gong et al. [102] experimented on the adsorption of water and methanol in Mordenite Zeolite using 129 Xe NMR spectroscopy. In situ ssNMR techniques are crucial for studying catalytic reaction mechanisms under specific conditions.

8.7.6.1

SSNMR Studies of Zeolite Crystal Structures

Brouwer et al. [103] reported a strategy for solving zeolite crystal structures using a 29 Si NMR approach combined with XRD. During the process, ssNMR enables structure solution, while XRD provides crystal data (unit cell parameters and space groups) (Fig. 8.38a). 2D dipole–dipole-mediated 29 Si–29 Si DQ (double-quantum) correlation NMR was used to probe the connectivities of Si sites in a pure siliceous ITQ-4 zeolite by detecting the proximity of the nearest-neighbor and next-nearestneighbor Si sites (Fig. 8.38b). The spatially distant Si sites and covalently bonded are identified by their positions and correlated intensities. 2D 29 Si–29 Si NMR mediated by through-bond J-coupling interactions is often used as a complementary method to confirm the Si–O–Si bond. The Si-Si distances between each Si pair can be extracted from curves created by a series of 29 Si DQ correlation spectra (Fig. 8.38c). The topologies established by the NMR approach were identical to the ITQ-4 structure obtained after completion and refinement from the XRD data (Fig. 8.38d).

8.7.6.2

SSNMR Studies of Alumina Catalyst Structures

Alumina is widely used as a catalyst for many industrial catalytic reactions. However, the complex structure of alumina remains elusive. 17 O ssNMR is a powerful tool for probing the coordination environment of oxygen atoms in various oxygen-containing materials [104]. Wang Q et al. conducted a 2D 17 O–17 O DQ–SQ homonuclear correlation NMR experiment for mapping the oxygen structure of γ-Al2 O3 17 (Fig. 8.39a) [105]. Four self-correlation peaks (A–A, B–B, C–C, and D–D) observed along the diagonal line reflect the same oxygen sites. However, the cross peaks B–E, C–D, and B–D prove the spatial proximities between different oxygen species, which are clearly shown in the extracted 1D slices (Fig. 8.39b). The detected correlations mainly come from the 2-bond 17 O–Al–17 O correlation. Bulk and surface oxygen species on γ-Al2 O3 can be further differentiated by using 1 H–17 O HETCOR experiments. The 1 H–17 O through-bond J-HMQC investigations identified the exposed hydroxyl groups (–OH), while the 2D 1 H–17 O through-space D-HMQC experiments correlated the bare oxygen (without H bonded) with proximate hydroxyl groups. The experiments reveal that coordinately unsaturated oxygen species are preferentially

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Fig. 8.38 a Overview of the structure determination strategy for zeolite crystal structures by a combination of solid-state NMR spectroscopy and powder X-ray diffraction, b 2D 29 Si DQ correlation spectrum, c 29 Si DQ curves (red lines: the calculated DQ curves), and d comparison of the structure (only the silicon atoms are shown) solved by solid-state NMR (red) with the structure obtained after completion and refinement against powder XRD data (blue) [103]

formed on the γ-Al2 O3 surface. Additionally, the detailed information on oxygen speciation helps tune the properties of metal-supported γ-Al2 O3 catalysts because the metal anchoring sites are affected by the surface oxygen structure.

8.7.7 NMR Spectroscopy Applied in CO2 Capture After Combustion 8.7.7.1

Introduction to Post-Combustion Capture (PCC) System

Carbon Capture and Storage (CCS) is a technology that captures Carbon dioxide (CO2 ) produced by large power plants and stores it in various ways to prevent it from being released into the atmosphere. The technology is considered the most cost-effective and feasible way to reduce greenhouse gas emissions on a large scale and slow global warming in the future. Post-combustion capture (PCC) is the process

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Fig. 8.39 a 2D 17 OMAS DQ–SQ homonuclear correlation NMR spectrum of g-Al2 O3 recorded at 35.2 T. The deconvoluted 1D 17 OMAS NMR spectrum is shown on top. OIV (A, B, and C) and OIII (D and E) denote 4-coordinated and 3-coordinated oxygen sites, respectively. b Proposed local structure models of oxygen species in γ-Al2 O3 . A–E represents five distinct bare oxygen sites. The purple dotted arrows indicate the spatial proximities between two specific bare oxygen sites. Surface terminal (m1), doubly (m2), and triply (m3) bridging hydroxyl groups are indicated [105]

of absorbing CO2 in flue gas streams. Nowadays, the commonly used CO2 separation technology mainly includes the chemical absorption method (using acid-base absorption) and the physical absorption method (variable temperature or pressure swing adsorption). The section mainly introduces NMR application in the chemical absorption process. Aqueous amine solvents for chemical absorption of carbon dioxide (amine–CO2 – H2 O systems) are an efficient separation technology to remove carbon dioxide (CO2 ) from fuel gas streams. However, the corrosive nature of amines, the energy demands for CO2 desorption and amine regeneration, and their degradation limit the application. To improve the efficiency of post-combustion capture (PCC) by amine solvents while developing new absorption systems, an accurate understanding of the underlying chemical processes (such as reaction kinetics, equilibria present, and thermodynamics) involved in the capture and release of CO2 is needed. NMR spectroscopy allows direct access to the chemical composition of CO2 capture solvents (speciation), which provides more object functions usable for fitting parameters. Furthermore, by monitoring speciation of the whole cyclic process of CO2 capture, it is possible to obtain information on reaction mechanisms, the kinetics of the reaction, factors influencing reaction conditions (such as the chemical structures of the amines), amine capacities, and CO2 solubility.

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NMR Spectroscopy Applied in Probing MEA–CO2 –H2 O Systems

Jakobsen et al. [106] probed in a MEA (monoethanolamine or 2-aminoethanol) – CO2 –H2 O system by 13 C NMR spectra. Later, Fan et al. [107] conducted similar detection by 1 H NMR spectra. Based on their probe, an increment of amine carbamate is observed, as well as of bicarbonate and protonated amines at increasing CO2 loadings. When CO2 loadings are higher than 0.5 mol CO2 /mol MEA, the protonated amine concentration continues to rise at the expense of carbamate, and the released carbon dioxide will react to bicarbonate. Characteristic 1 H and 13 C NMR spectra of MEA at varying CO2 loadings are shown in Figs. 8.40 and 8.41. Varying the CO2 loading, most of the NMR signals change positions. The signals corresponding to the nuclei of MEA/MEAH+ shift to the left (high ppm values) in the 1 H NMR spectra and the right (low ppm values) in 13 C NMR spectra due to an increase of protonated amines. On the other hand, the 13 C signal corresponding to HCO3 − /CO3 2− moves toward lower chemical shifts due to increased bicarbonate concentration. Concerning the carbamate species, the change in 1 H and 13 C chemical shifts at increasing CO2 loadings is much smaller than that observed for the amines [108].

8.7.8 NMR Applied for Different Coals’ Combustion Character Combustion is simply defined as an oxidation reaction with heat and light. Usually, when the reaction rate is at high speed, the reaction heat is high, and there is a luminous phenomenon called combustion. Combustion is often carried out in the form of

Fig. 8.40 Stacked 1 H NMR spectra for 5.0 M MEA solution with varying CO2 loading at 295.65 K [107]

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Fig. 8.41 Stacked 293.15 K [106]

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NMR spectra for 30 wt.% MEA solution with varying CO2 loading at

gas, heavy liquid oil, solid wood, and coal need to be evaporated or decomposed to produce combustible gas, which forms a flammable mixture with air and burns when there is a source of the fire. The chemical structure of the fuel determines the combustion characteristics of the fuel. There have been many reports about the chemical structure analysis of coal, oil, and other fuels by NMR. So NMR also plays a vital role in combustion chemistry. Zhang et al. [109] used solid-state NMR to study the molecular structure of Xian coal and Inner Mongolia lignite and obtained the ignition sensitivity of two different coals. The chemical and physical structures of the compounds were characterized by X-ray diffraction and solid-state NMR, and the spontaneous combustion tendency of the compounds was evaluated by the CPT method. They also collected different coal mines from two places in Xinjiang, which have the problem of spontaneous combustion. They exposed the coal samples to 96 ml/min of dry air in the reactor.

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The heating rate of 28 °C was 0.8 °C/min, and the temperature of coal and furnace was recorded. The NMR spectra were determined at a spinning speed of 5.7 kHz using a solid cross 17 polarization/magic angle spinning (CP/MAS) probe and the total suppression of sidebands 18 sequences (TOSS). Their research expands the understanding of inertinite structure and its degree of order.

8.7.9 NMR Applied for Analysis of the Chemical Structure in Petroleum Coke In situ combustion mainly points to the injection of air or any oxygen-containing gas into the reservoir, ignites the reservoir at a high temperature, and uses the petroleum coke deposited by oxidative cracking of crude oil as fuel to maintain the combustion frontier. The combined action of heat and fuel gas will lead to oil displacement and enhanced oil recovery. The macromolecular structure and activity of various organic functional groups formed by coke in crude oil at different oxidation temperatures determine the different reactions in the conversion process. The oxygen in coke mainly exists in the carboxyl group, hydroxyl group, carbonyl group, and active or inactive ether bond, which is usually determined by solid-state nuclear magnetic resonance (NMR). This method can well analyze the distribution of carbon atoms. It is possible to study the state of oxygen connected to carbon atoms. Pan et al. [110] extracted petroleum coke with different chemical structures of oxygencontaining functional groups from naphthenic and paraffin crude oil by simulating the in-situ combustion process. The functional groups of petroleum coke obtained under different experimental conditions were identified and analyzed by solid-state NMR spectroscopy. The results show that with the increase of coking temperature, the content of oxygen-containing functional groups in petroleum coke decreases obviously, but the content of aromatic substances increases. The NMR spectra of petroleum coke have been shown in Fig. 8.42.

8.7.10 NMR Study of Combustion Characteristics of Crude Oils in Gas Turbine The index for measuring engine ignition performance generally includes derived cetane number (DCN) and motor octane number (MON) [111]. The octane number represents an agreed value for the knock resistance of ignition engine fuel, which is mainly applicable to gasoline engines [111]. Cetane number is an important index to measure the ignition performance of diesel in the compression combustion engine. The higher the cetane number, the better the ignition performance of diesel. A low cetane number indicates that combustion is complex, and a small amount of black exhaust smoke will be produced due to partial combustion.

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NMR spectra of petroleum coke at a 500 °C and b 350 °C [110]

Won et al. [112] obtained NMR spectra at 1 H and 13 C to further explain crude oil’s DCN properties and its distillation. Previous work has shown that NMR can accurately measure the chemical shifts of different atomic structures. However, crude oil contains sulfur and metal compounds, which can cause errors in the measurement. Figure 8.43 displays the 13 C NMR spectra of whole Crude 1. Ranges of chemical shift for each functional group [113]. The preferred vaporization may be related to the gas turbine’s pre-vaporization/premixed combustion behavior near the operating limit.1 H NMR and 13 C NMR spectra were also obtained from the distilled samples. A simplex-polynomial descriptor was used for QSPR regression analysis. The results show that the n-alkane CH2 group plays the most significant role in determining the global ignition tendency of crude oil.

8.8 Outlook NMR is a unique and practical technique applicable in medicine, chemistry, engineering, and other fields. Due to its rapidity, accuracy, and high-resolution advantages, nuclear magnetic resonance plays a great role in scientific research activities. This chapter has highlighted the application of NMR in various fields, such as molecular structure elucidation and purity determination of materials, catalysis, battery technology, MRI, and combustion chemistry. In the biomedical field, NMR has gained more popularity in molecular structure determination, analysis of biological materials, disease diagnostics, drug development, and disease treatment, where MRI 3D scans are useful in cancer treatment. The need for clean energy has led to the development of electrical cars. These cars require more efficient batteries with high power density, less discharge time, and a longer life cycle. NMR studies have played a vital role in energy storage research. And more studies are still being conducted to achieve more efficient batteries which will sustain our needs. Every chemical reaction requires a catalyst to be more efficient.

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NMR spectra of whole Crude 1. Ranges of chemical shift for each functional group

NMR as a characterization tool is applied to develop more efficient catalysts that use limited reactants to achieve maximum products. This also fosters the production of intermediate products which have economic importance to us. The development of NMR spectroscopy as an analytical tool for combustion processes is potentially important for catalyzed reactions within opaque media. NMR experiments on fuels such as diesel and petroleum have provided more insight into motors’ cetane numbers and octane numbers, hence designing more efficient car engines. The future development of NMR is not limited to improving accuracy (like DNP NMR), improving sensitivity and resolution, and reducing the number of samples. The advancements in computer application, multidimensional mapping in multiple pulse techniques, and other new technology push for the development of modern NMR. Combining NMR with other advanced diagnostic techniques like CP/ MAS NMR will improve the NMR characterization capacity in disease diagnostics and treatment, catalytic studies, battery technologies, and molecular structural elucidation.

8.9 Exercises (1) Individual task: Find a scientific article on the NMR instrumentation and discuss the sample preparation, spectroscopy preparation, and data acquisition process.

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(2) Individual task: Find a literature paper on NMR structure analysis and elaborate on the 1 H, 13 C, COSY, TOCSY, HSQC, HMQC, and NOESY spectra. (3) Group task: In small groups, find a research article on one application of NMR spectroscopy (in the field like MRI, combustion, catalysis, etc.), and discuss in detail the focus of that research.

8.10 Questions (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14)

Discuss the working principle of NMR. Define the chemical shift and discuss the concept of chemical shift in NMR. Define the shielding effect and illustrate with some common examples. Describe spin coupling and spin splitting mechanisms. Describe the types of magnets in NMR and state their advantages and disadvantages. While giving examples, explain the importance of deuterated solvent during sample preparation for NMR spectroscopy. Explain the importance of sample spinning in an NMR spectrometer. Describe shimming in NMR and explain its importance. State the standard reference used in NMR. Explain the importance of reference material in the NMR experiment. Describe the probe system of the NMR spectrometer. Explain how mass and concentration sensitivity can be increased in an NMR experiment. Describe how Field-Frequency Lock works. Describe ways of improving S/N in NMR. Explain the advantages and disadvantages of CW-NMR and FT-NMR.

References 1. Formica, D., & Silvestri, S. (2004). Biological effects of exposure to magnetic resonance imaging: An overview. Biomedical Engineering Online, 3, 11. https://doi.org/10.1186/1475925x-3-11 2. Ahlawat, S., et al. (2022). Solid-state NMR: Methods for biological solids. Chemical Reviews, 122(10), 9643–9737. https://doi.org/10.1021/acs.chemrev.1c00852 3. Lisitza, N. V., et al. (2009). Study of asphaltene nanoaggregation by nuclear magnetic resonance (NMR). Energy & Fuels, 23(3), 1189–1193. https://doi.org/10.1021/ef800631a 4. Bhullar, K. A., et al. (2021). Advanced spectroscopy, microscopy, diffraction and thermal analysis of polyamide adhesives and prediction of their functional properties with solid-state NMR spectroscopy. Polymer Chemistry, 12(10), 1487–1497. https://doi.org/10.1039/D0PY01 348J 5. Reif, B., et al. (2021). Solid-state NMR spectroscopy. Nature Reviews Methods Primers, 1. https://doi.org/10.1038/s43586-020-00002-1

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