Emerging photovoltaic materials and devices

Citation preview

Emerging Photovoltaic Materials

Scrivener Publishing 100 Cummings Center, Suite 541J Beverly, MA 01915 Publishers at Scrivener Martin Scrivener ([email protected]) Phillip Carmical ([email protected])

Managing Editors: George Mishra and Sophie Thompson

Emerging Photovoltaic Materials Silicon & Beyond

Edited by

Santosh K. Kurinec Rochester Institute of Technology, NY, USA

This edition first published 2018 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA © 2019 Scrivener Publishing LLC For more information about Scrivener publications please visit www.scrivenerpublishing.com. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions. Wiley Global Headquarters 111 River Street, Hoboken, NJ 07030, USA ucts visit us at www.wiley.com. Limit of Liability/Disclaimer of Warranty n preparing this work, they make no repWhile the publisher and authors have used their best resentations or warranties with respect to the accuracy or completeness of the contents of this work and y disclaim all warranties, including without limitation any implied warranties of merchantability or particular purpose. No warranty may be created or extended by sales representatives, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or understanding that the publisher is not engaged in rendering professional services. strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Neither the publisher nor authors shall be liable for any loss commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Library of Congress Cataloging-in-Publication Data ISBN Cover image: Pixabay Com Cover design by Russell Richardson Set in size of 11pt and Minion Pro by Manila Typesetting Company, Makati, Philippines Printed in the USA 10 9 8 7 6 5 4 3 2 1

Contents Preface

Part 1: Silicon Photovoltaics 1 Emergence of Continuous Czochralski (CCZ) Growth for Monocrystalline Silicon Photovoltaics Santosh K. Kurinec, Charles Bopp and Han Xu 1.1 Introduction 1.1.1 The Czochralski (CZ) Process 1.1.2 Continuous Czochralski Process (CCZ) 1.2 Continuous Czochralski Process Implementations 1.3 Solar Cells Fabricated Using CCZ Ingots 1.3.1 n-Type Mono-Si High-Efficiency Cells 1.3.2 Gallium-Doped p-Type Silicon Solar Cells 1.4 Conclusions References 2 Materials Chemistry and Physics for Low-Cost Silicon Photovoltaics Tingting Jiang and George Z. Chen 2.1 Introduction 2.2 Crystalline Silicon in Traditional/Classic Solar Cells 2.2.1 Manufacturing of Silicon Solar Cell 2.2.2 Efficiency Loss in Silicon Solar Cell 2.2.3 New Strategies for the Silicon Solar Cell 2.3 Low-Cost Crystalline Silicon 2.3.1 Metallurgical Silicon 2.3.2 Upgraded Metallurgical-Grade Silicon 2.3.2.1 Properties of Upgraded MetallurgicalGrade Silicon 2.3.2.2 Production of Upgraded MetallurgicalGrade Silicon

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Contents 2.3.2.3 Development of Upgraded MetallurgicalGrade Silicon Solar Cells 2.3.3 High-Performance Multicrystalline Silicon 2.3.3.1 Crystal Growth 2.3.3.2 Material Properties of High-Performance Multicrystalline Silicon 2.3.3.3 Solar Cell Based on High-Performance Multicrystalline Silicon 2.4 Advanced p-Type Silicon—in Passivated Emitter and Rear Cell (PERC) 2.4.1 Passivated Emitter Solar Cells 2.4.1.1 Passivated Emitter Solar Cell (PESC) 2.4.1.2 Passivated Emitter and Rear Cell 2.4.1.3 Passivated Emitter, Rear Locally Diffused Solar Cells 2.4.1.4 Passivated Emitter, Rear Totally Diffused Solar Cells 2.4.2 Surface Passivation 2.5 Advanced n-Type Silicon 2.5.1 Interdigitated Back Contact (IBC) Solar Cell 2.5.2 Silicon Heterojunction (SHJ) Solar Cells 2.5.2.1 The Device Structure and the Advantages of HIT Solar Cells 2.5.2.2 Strategies of Achieving High-Efficiency HIT Solar Cell 2.6 Conclusion References

3 Recycling Crystalline Silicon Photovoltaic Modules Pablo Dias and Hugo Veit 3.1 Waste Electrical and Electronic Equipment 3.2 Photovoltaic Modules 3.2.1 First-Generation Photovoltaic Modules 3.3 Recyclability of Waste Photovoltaic Modules 3.3.1 Frame 3.3.2 Superstrate (Front Glass) 3.3.3 Metallic Filaments (Busbars) 3.3.4 Photovoltaic Cell 3.3.5 Polymers 3.3.6 Recyclability Summary

36 37 37 39 40 41 41 41 42 43 44 45 46 47 50 51 52 53 54 61 62 65 66 69 70 71 72 73 74 75

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3.4 Separation and Recovery of Materials: The Recycling Process 3.4.1 Mechanical and Physical Processes 3.4.1.1 Shredding 3.4.1.2 Sieving 3.4.1.3 Density Separation 3.4.1.4 Manual Separation 3.4.1.5 Electrostatic Separation 3.4.2 Thermal Processes—Polymers 3.4.3 Separation Using Organic Solvents 3.4.4 Pyrometallurgy 3.4.5 Hydrometallurgy 3.4.6 Electrometallurgy 3.5 New Trends in the Recycling Processes References

Part 2: Emerging Photovoltaic Materials 4 Photovoltaics in Ferroelectric Materials: Origin, Challenges and Opportunities Charles Paillard, Grégory Geneste, Laurent Bellaiche, Jens Kreisel, Marvin Alexe and Brahim Dkhil 4.1 Physics of the Photovoltaic Effect in Ferroelectrics 4.1.1 Conventional Photovoltaic Technologies 4.1.1.1 The p–n Junction 4.1.1.2 The Shockley–Queisser Limit 4.1.2 Mechanisms of the Photovoltaic Effect in Ferroelectric Materials 4.1.2.1 The Bulk Photovoltaic Effect 4.1.2.2 Barrier Effects 4.2 Opportunities and Challenges of Photoferroelectrics 4.2.1 To Switch or not to Switch 4.2.1.1 Switchability 4.2.1.2 Influence of Defects 4.2.2 The Bandgap Problem 4.2.3 Application of Light-Induced Effects in Ferroelectrics: Beyond Solar Cells 4.2.3.1 Photovoltaics and ICTs 4.2.3.2 Photo-Induced Strain: Toward Optically Controlled Actuators 4.2.3.3 Photochemistry for Clean Energy and Environment

76 76 77 77 79 82 82 84 86 90 90 93 94 98

103 105 106 106 106 109 110 110 118 123 124 124 125 127 129 130 130 131

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Contents 4.3 Conclusions Acknowledgements References

5 Tin-Based Novel Cubic Chalcogenides: A New Paradigm for Photovoltaic Research Sajid Ur Rehman, Faheem K. Butt, Zeeshan Tariq and Chuanbo Li 5.1 Introduction 5.2 Cubic Tin Sulfide (π-SnS) 5.2.1 Application π-SnS in Solar Cells 5.2.2 Application of π-SnS in Optical Devices 5.3 Cubic Tin Selenide (π-SnSe) 5.3.1 Application of π-SnSe in Solar Cells 5.3.2 Application of π-SnSe in Optical Devices 5.4 Cubic Tin Telluride (π-SnTe) 5.4.1 Application of π-SnTe in Optical Devices 5.5 Conclusion Acknowledgement References 6 Insights into the Photovoltaic and Photocatalytic Activity of Cu-, Al-, and Tm-Doped TiO2 Antonio Sánchez-Coronilla, Javier Navas, Elisa I. Martín, Teresa Aguilar, Juan Jesús Gallardo, Desireé de los Santos, Rodrigo Alcántara and Concha Fernández-Lorenzo 6.1 Introduction 6.2 Materials and Methods 6.2.1 Experimental 6.2.2 Computational Framework 6.3 Cu-TiO2 Doping 6.3.1 Photovoltaics of the DSSCs 6.4 Al-TiO2 Doping 6.5 Tm-TiO2 Doping 6.5.1 Photovoltaic Characterization 6.5.2 Photocatalytic Activity 6.6 Conclusions References

133 134 134 141 142 145 145 147 153 153 154 157 158 160 160 161 165

166 167 167 169 170 175 177 181 184 186 187 189

Contents 7 Theory of the Photovoltaic and Light-Induced Effects in Multiferroics Bruno Mettout and Pierre Tolédano 7.1 Insufficiency of the Traditional Approach to the Bulk Photovoltaic Effect 7.2 Theoretical Approach to the Photovoltaic and LightInduced Effects 7.3 Response Functions under Linearly Polarized Light 7.3.1 Mean Symmetry of the Light Beam 7.3.2 Response Functions 7.3.2.1 Achiral and Nonmagnetic Materials 7.3.2.2 Chiral and Magnetic Materials 7.4 Selection Procedures 7.4.1 External Selection 7.4.2 Internal Selection 7.5 Application of the Theory to the Photovoltaic and Photo-Induced Effects in LiNbO3 7.5.1 Second-Order Photovoltaic Effect 7.5.2 Photovoltaic Effects in LiNbO3 7.5.3 Optical Rectification, Photomagnetic, and Photo-Toroidal First-Order Effects 7.5.4 First-Order Photoelastic and Photo-Magnetoelectric Effects 7.6 Magnetoelectric, Photovoltaic, and Magneto-Photovoltaic Effects in KBiFe2O5 7.6.1 Magnetoelectric Effects in KBiFe2O5 in Absence of Illumination 7.6.2 Photovoltaic and Magneto-Photovoltaic Effects in KBiFe2O5 7.7 Photo-Magnetoelectric and Magneto-Photovoltaic Effects in BiFeO3 7.7.1 Photo-Magnetoelectric Effects 7.7.2 Photovoltaic Effects in BiFeO3 7.7.3 Magneto-Photovoltaic Effects in BiFeO3 7.8 Photorefractive and Photo-Hall Effects in Tungsten Bronzes 7.8.1 The Photorefractive Effect 7.8.2 The Photo-Hall Effect 7.9 Summary and Conclusion Acknowledgement References

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8 Multication Transparent Conducting Oxides: Tunable Materials for Photovoltaic Applications Peediyekkal Jayaram 8.1 Introduction 8.2 Multication Film Growth and Analysis 8.3 Structural Analysis 8.4 Raman Spectra 8.5 Surface Morphology (AFM) 8.6 Optical Properties: UV-Vis Transmittance Spectra 8.7 Electrical Properties 8.8 Conclusion References

Part 3: Perovskite Solar Cells 9 Perovskite Solar Cells: Promises and Challenges Qiong Wang and Antonio Abate 9.1 The Scientific and Technological Background 9.1.1 The Share of Silicon Solar Cells and Thin Film Solar Cells in Photovoltaic Market 9.1.2 The Bottleneck of Dye-Sensitized Solar Cells and Organic Solar Cells 9.1.3 From a Cost-Effective Alternative to the Highly Efficient Solution 9.2 The Fast Development of PSCs 9.2.1 The Fundamental Optoelectronic Properties of Hybrid Organic–Inorganic Lead Halide Perovskite Materials 9.2.1.1 Optical Properties 9.2.1.2 Electronic Properties 9.2.2 Composition Adjustment of Perovskite 9.2.2.1 Mixed Halides 9.2.2.2 Multi-Cations 9.2.2.3 Phase Segregation 9.2.3 Versatile Deposition Methods of Perovskite Film 9.2.3.1 Solution-Processed Methods 9.2.3.2 Vapor Deposition Methods 9.2.4 Charge Selective Contacts in PSCs 9.2.4.1 Electron Selective Contacts 9.2.4.2 Hole Selective Contacts

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261 263 264 264 266 269 270 271 272 276 288 288 292 297 297 298 306 308 309 311

Contents 9.2.5 Evaluation of PSCs 9.2.5.1 J–V curve 9.2.5.2 Maximum Power Point Tracking (MPPT) 9.2.6 The Systematic Understanding of PSCs 9.2.6.1 Moisture Vulnerability of Perovskite Materials 9.2.6.2 The Role of Grain Boundaries 9.2.6.3 Ion Migration and Hysteresis 9.2.6.4 Interface/Bulk Defects and Passivation 9.2.7 PSCs in a Tandem 9.2.7.1 Structures of Perovskite Tandem Cells 9.2.7.2 Transparent Contacts and Recombination Contacts 9.3 Remaining Challenges and Prospects of PSCs 9.3.1 Lead-Free PSCs 9.3.2 Stable and Cheap Contact Materials 9.3.3 Strategies toward Stable PSCs 9.3.3.1 Against Moisture 9.3.3.2 Against UV Light 9.3.3.3 Against Heat 9.3.4 Large-Area Production of Highly Efficient PSCs References 10 Organic–Inorganic Hybrid Perovskite, CH3NH3PbI3: Modifications in Pb Sites from Experimental and Theoretical Perspectives Javier Navas, Antonio Sánchez-Coronilla, Juan Jesús Gallardo, Jose Carlos Piñero, Teresa Aguilar, Elisa I. Martín, Rodrigo Alcántara, Concha Fernández-Lorenzo and Joaquin Martín-Calleja 10.1 Introduction 10.2 Low Doping on Pb Sites 10.2.1 Materials and Methods 10.2.1.1 Experimental 10.2.1.2 Computational Details 10.2.2 Properties of the Perovskite Prepared 10.2.2.1 XRD 10.2.2.2 Diffuse Reflectance UV-Vis Spectroscopy 10.2.2.3 X-Ray Photoelectron Spectroscopy 10.2.2.4 SEM and Cathodoluminescence

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Contents 10.2.3 Theoretical Analysis 10.2.3.1 Structure and Local Geometry 10.2.3.2 DOS and PDOS Analysis 10.2.3.3 ELF Analysis 10.3 High Doping on Pb Sites 10.3.1 Properties of the Perovskite Prepared 10.3.1.1 XRD 10.3.1.2 Diffuse Reflectance UV-Vis Spectroscopy 10.3.1.3 X-Ray Photoelectron Spectroscopy 10.3.2 Theoretical Analysis 10.3.2.1 Structure and Local Geometry 10.3.2.2 Electron Localization Function 10.3.2.3 DOS and PDOS Analysis 10.4 Conclusions References

Part 4: Organic Solar Cells

371 371 372 376 378 379 379 384 386 388 388 391 393 397 397

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11 Increasing the Dielectric Constant of Organic Materials for Photovoltaics 403 Viktor Ivasyshyn, Gang Ye, Sylvia Rousseva, Jan C. Hummelen and Ryan C. Chiechi 11.1 Introduction 404 11.2 Increasing the Dielectric Constant 415 11.2.1 Methodology of Dielectric Constant Measurement 415 11.2.2 High Dielectric Constant Materials 421 11.2.2.1 High Dielectric Constant Donor Materials 422 11.2.2.2 High Dielectric Constant Acceptor Materials 429 11.3 Conclusions and Outlook 435 References 436 12 Recent Developments in Dye-Sensitized Solar Cells and Potential Applications Devender Singh, Raman Kumar Saini and Shri Bhagwan 12.1 Solar Energy and Solar Cells 12.2 Types of Solar Cells 12.2.1 First-Generation Photovoltaic Cells 12.2.1.1 Silicon Single-Crystal-Based Solar Cells 12.2.1.2 Polycrystalline Silicon Based Solar Cells 12.2.1.3 Gallium Arsenide (GaAs)-Based Solar Cells

443 444 445 445 445 445 447

Contents

12.3 12.4 12.5

12.6

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12.2.2 Second-Generation Photovoltaic Cells 447 12.2.2.1 Amorphous Silicon (a-Si)-Based Solar Cells 447 12.2.2.2 Cadmium Telluride (CdTe)-Based Solar Cells 448 12.2.2.3 Copper Indium Diselenide (CuInSe2, or CIS)Based Solar Cells 448 12.2.3 Third-Generation Photovoltaic Cells 449 12.2.3.1 Copper Zinc Tin Sulfide (CZTS) and (Its Derivatives) CZTSSe and CZTSe Solar Cells 449 12.2.3.2 Organic Solar Cells 449 12.2.3.3 Perovskite Solar Cells 450 12.2.3.4 Quantum Dot Solar Cell 450 Dye-Sensitized Solar Cells (DSSCs) 450 Operation of DSSCs 452 12.4.1 Working System of DSSCs 454 Fabrication of DSSCs 455 12.5.1 Substrate Selection and Preparation 456 12.5.1.1 Cutting of the Substrate 456 12.5.1.2 Cleaning of the Substrate 456 12.5.1.3 Masking of the Substrate 456 12.5.2 Film Deposition on Substrate 456 459 12.5.2.1 Preparation of TiO2 Paste 12.5.2.2 Depositing the TiO2 Layer on the Glass Plate 460 12.5.3 Dye Impregnation on the Electrode 460 12.5.4 Preparation of Counter Electrode 460 Various Materials Used as Essential Components of DSSCs 461 12.6.1 Transparent Conducting Substrate 461 12.6.2 Photoelectrodes 462 462 12.6.2.1 Titanium Oxide (TiO2) 12.6.2.2 Zinc Oxide (ZnO) 463 464 12.6.2.3 Niobium Pentoxide (Nb2O5) 12.6.2.4 Ternary Photoelectrode Materials 465 12.6.2.5 Other Metal Oxides 465 12.6.3 Photosensitizers 466 12.6.3.1 Metal Complexes as Sensitizers 467 12.6.4 Electrolytes 471 12.6.4.1 Liquid Electrolytes 472 12.6.4.2 Solid-State Electrolytes 473 12.6.4.3 Quasi-Solid Electrolyte 474

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Contents 12.6.5 Counter Electrodes 12.6.5.1 Platinized Conducting Glass 12.6.5.2 Carbon Materials 12.6.5.3 Conducting Polymers 12.7 Advantages and Applications of DSSC 12.8 Future Prospect of DSSC 12.9 Conclusions References

13 Heterojunction Energetics and Open-Circuit Voltages of Organic Photovoltaic Cells Peicheng Li and Zheng-Hong Lu 13.1 Introduction 13.2 Ultraviolet Photoemission Spectroscopy 13.3 Energy Level Alignment at Heterojunction Interfaces 13.3.1 Schottky Barrier, Interfacial Dipole, and Slope Parameter 13.3.2 Interfacial Dipole Theory 13.3.3 Mapping Energy Level Alignment at Heterojunction Interface 13.4 Open-Circuit Voltage of Organic Photovoltaic Cell 13.4.1 Two-Diode Model 13.4.2 Quasi Fermi Level Model 13.4.3 Chemical Equilibrium Model 13.4.4 Kinetic Hopping Model References 14 Plasma-Enhanced Chemical Vapor Deposited Materials and Organic Semiconductors in Photovoltaic Devices Andrey Kosarev, Ismael Cosme, Svetlana Mansurova, Dmitriy Andronikov, Alexey Abramov and Eugeny Terukov 14.1 Introduction 14.2 Experimental 14.2.1 Fabrication of PECVD Materials 14.2.2 Fabrication of Organic Materials 14.2.3 Configurations and Fabrication of Device Structures 14.2.4 Characterization of Materials 14.2.5 Characterization of Device Structures 14.3 Material Results 14.3.1 Structure and Composition 14.3.2 Optical Properties 14.3.3 Electrical Properties

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14.4 Results for Devices 14.4.1 Devices Based on PECVD Materials 14.4.2 Devices Based on Organic Materials 14.4.3 Hybrid Devices Based on PECVD-Polymer Materials 14.4.4 Hybrid Devices Using Crystalline Semicinductors, Non-Crystalline PECVD, and Organic Materials (HJT-OS Structures) 14.5 Outlook Acknowledgment References

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Part 5: Nano-Photovoltaics 15 Use of Carbon Nanotubes (CNTs) in Third-Generation Solar Cells LePing Yu, Munkhbayar Batmunkh, Cameron Shearer and Joseph G. Shapter 15.1 Introduction 15.1.1 Energy Issues and Potential Solutions 15.1.2 Categories of Photovoltaic Devices and Their Development 15.2 Carbon Nanotubes (CNTs) 15.3 Transparent Conducting Electrodes (TCEs) 15.3.1 ITO and FTO 15.3.2 CNTs for TCEs 15.4 Dye-Sensitized Solar Cells (DSSCs) 15.4.1 CNTs-TCFs for DSSCs 15.4.2 Semiconducting Layers 15.4.2.1 Nanostructured TiO2 Materials 15.4.2.2 Semiconducting Layers with CNTs 15.4.3 Catalyst Layers 15.4.3.1 Platinum (Pt) and Other Catalysts 15.5 CNTs in Perovskite Solar Cells 15.6 Carbon Nanotube–Silicon (CNT–Si) or Nanotube–Silicon Heterojunction (NSH) Solar Cells 15.6.1 Working Mechanism 15.6.2 Development of Si-CNT Devices 15.6.3 Origin of Photocurrent 15.6.4 Effect of the Number of CNT Walls 15.6.5 Effect of the Electronic Type of CNTs 15.6.6 Effect of CNT Alignment in the Electrode 15.6.7 Effect of the Transmittance/Thickness of CNT Films

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Contents 15.6.8 Effect of Doping 15.6.9 Intentional Addition of Silicon Oxide Layer 15.6.10 Enhancement of Light Absorption 15.6.11 Application of Conductive Polymers 15.6.12 Discussion 15.7 Outlook and Conclusion References

16 Quantum Dot Solar Cells Xiaoli Zhao, Chengjie Xiang, Ming Huang, Mei Ding, Chuankun Jia and Lidong Sun 16.1 Introduction 16.2 Quantum Dots and Their Properties 16.2.1 Fundamental Concepts 16.2.2 Size-Dependent Quantum Confinement Effect 16.2.3 Multiple Exciton Generation Effect 16.2.4 The Kondo Effect 16.2.5 Applications 16.3 Synthetic Methods for Quantum Dots 16.3.1 Hot Injection 16.3.1.1 Theoretical Evaluation of Nucleation and Growth 16.3.1.2 Influence Factors 16.3.1.3 Features 16.3.2 Chemical Bath Deposition 16.3.2.1 Theoretical Evaluation of the CBD Method 16.3.2.2 Influence Factors 16.3.2.3 Features 16.3.3 Successive Ionic Layer Adsorption and Reaction 16.3.3.1 Theoretical Evaluation of SILAR Method 16.3.3.2 Influence Factors 16.3.3.3 Features 16.4 Quantum Dot Solar Cells 16.4.1 Schottky Junction Solar Cells 16.4.1.1 Device Structure 16.4.1.2 Preparation Route 16.4.1.3 Materials Selection 16.4.1.4 Photovoltaic Performance 16.4.2 Depleted Heterojunction Solar Cells 16.4.2.1 Device Structure 16.4.2.2 Preparation Route

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Contents 16.4.2.3 Materials Selection 16.4.2.4 Photovoltaic Performance 16.4.3 Quantum-Dot-Sensitized Solar Cells 16.4.3.1 Device Structure 16.4.3.2 Preparation Route 16.4.3.3 Materials Selection 16.4.3.4 Photovoltaic Performance 16.4 Challenges and Perspectives References 17 Near-Infrared Responsive Quantum Dot Photovoltaics: Progress, Challenges, and Perspectives Ru Zhou, Jun Xu and Jinzhang Xu 17.1 Introduction 17.2 Physical and Chemical Properties 17.2.1 Multiple Exciton Generation 17.2.2 Quantum Size Effect 17.2.3 Other Features 17.3 Materials and Film Processing 17.3.1 In Situ Strategy 17.3.2 Ex Situ Strategy 17.3.3 A Comparison between In Situ and Ex Situ 17.4 NIR Responsive QDs and Photovoltaic Performance 17.4.1 Binary Lead Chalcogenides 17.4.2 Binary Silver Chalcogenides 17.4.3 Ternary Indium-Based Chalcogenides 17.4.4 Ternary and Quaternary Alloyed Compounds 17.5 Strategies for Performance Enhancement 17.5.1 Light Management 17.5.1.1 Nanophotonic Structuring 17.5.1.2 Plasmonic Enhancement 17.5.2 Carrier Management 17.5.2.1 Band Structure Tailoring 17.5.2.2 Surface Engineering 17.5.2.3 Charge Collection Optimizing 17.6 New Concept Solar Cells 17.6.1 Multiple-Junction CQD Solar Cells 17.6.2 Flexible Solar Cells 17.6.3 Semitransparent Solar Cells 17.6.4 QD/Perovskite Hybrid Solar Cells

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17.7 Conclusions and Perspectives Acknowledgments References

Part 6: Concentrator Photovoltaics and Analysis Models 18 Dense-Array Concentrator Photovoltaic System Kok-Keong Chong, Chee-Woon Wong, Tiong-Keat Yew, Ming-Hui Tan and Woei-Chong Tan 18.1 Introduction 18.2 Primary Concentrator: Non-Imaging Dish Concentrator 18.2.1 Geometry of Non-Imaging Dish Concentrator (NIDC) 18.2.2 Methodology of Designing NIDC Geometry 18.2.3 Coordinate Transformation of Facet Mirror 18.2.4 Computational Algorithm 18.3 Secondary Concentrator: An Array of Crossed Compound Parabolic Concentrator (CCPC) Lenses 18.4 Concentrator Photovoltaic Module 18.5 Prototype of Dense-Array Concentrator Photovoltaic System (DACPV) 18.6 Optical Efficiency of the CCPC Lens 18.7 Experimental Study of Electrical Performance 18.7.1 Current Measurement Circuit 18.8 Cost Estimation of the Dense-Array Concentrator Photovoltaic System Using Two-Stage Non-Imaging Concentrators 18.9 Conclusion Acknowledgments References 19 Solar Radiation Analysis Model and PVsyst Simulation for Photovoltaic System Design Figen Balo and Lutfu S. Sua 19.1 Introduction 19.1.1 Solar Energy in Turkey 19.1.2 Climate, Solar Energy Potential, and Electric Production in Erzincan 19.2 Data Analysis Model for Solar Radiation Intensity Calculation 19.2.1 Horizontal Surface

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Contents 19.2.1.1 19.2.1.2 19.2.1.3 19.2.1.4

Daily Total Solar Radiation Daily Diffuse Solar Radiation Momentary Total Solar Radiation Momentary Diffuse and Direct Solar Radiation 19.2.2 Calculating Solar Radiation Intensity on Inclined Surface 19.2.2.1 Momentary Direct Solar Radiation 19.2.2.2 Momentary Diffuse Solar Radiation 19.2.2.3 Reflecting Momentary Solar Radiation 19.2.2.4 Total Momentary Solar Radiation 19.2.3 Data Analysis and Discussion 19.3 PVsyst Simulation for the Solar Farm System Design 19.3.1 Methodology 19.3.2 Findings Obtained with PVsyst Simulation 19.4 Conclusions References Index

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Preface The global solar market grew by 26% in 2017. According to research, the installed grid-connected photovoltaics (PV) capacity is approaching 100 gigawatts (Source: GTM Research Data Hub). The cost of solar power has declined at a rate of approximately 12% annually over the last five years. Such cost reductions are driven by continuous technological developments in achieving higher solar PV module efficiencies with improved manufacturing processes. To keep up with the increasing demand and achieve high energy return on energy invested (EROI), it is necessary for researchers to strive for lower costs, higher efficiencies and longer lifetime of PV technologies. Semiconductors are materials that generate free carriers (such as Si and GaAs) or excitons (in organics, which are dissociated to form free carriers) when exposed to photons with energies exceeding their optical bandgaps. These excess carriers are swept via a built-in electric field in the device and extracted at the contacts, which can drive a load and provide useful power output. Photovoltaic (PV) devices and modules made from crystalline silicon currently dominate the market. In the continued quest for lowering the cost, many efforts are being pursued that involve the use of alternative materials. Over the years, the development of PV technology has undergone numerous changes, which has led to cells being classified into different generations, originally defined for inorganic materials as high cost/ high efficiency (1st generation), low cost/low efficiency (2nd generation) and low cost/high efficiency (3rd generation). The U.S. National Renewable Energy Laboratory (NREL) maintains a plot of compiled values of  the highest confirmed conversion  efficiencies for research cells for a range of photovoltaic technologies from 1976 to the present, as shown in Figure 1. This chart highlights cell efficiency results within different families of semiconductors: (1)  multijunction cells, (2) single-junction gallium arsenide cells, (3) crystalline silicon cells, (4) thin film technologies, and (5) emerging photovoltaics. The graph sums up the

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Figure 1. Efficiencies of the best researched solar cell technologies. (Source: NREL, 2017.)

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historic quest of the solar industry to improve the conversion efficiencies in all PV technologies. The Light Management in New Photovoltaic Materials (LMPV) program within the Atomic and Molecular Physics (AMOLF) Institute, Amsterdam, Netherlands provides an up-to-date comparison between single junction world-record efficiencies for different materials and the fundamental Shockley-Queisser detailed-balance efficiency limit. ( HYPERLINK "http:// lmpv.amolf.nl/SQ"lmpv.amolf.nl/SQ). This figure is included on the front cover of this book. (Source: Photovoltaic materials – present efficiencies and future challenges, A. Polman, M. Knight, E.G. Garnett, B. Ehrler, and W.C. Sinke, Science 352, 307 (2016). DOI: HYPERLINK "http://science. sciencemag.org/content/352/6283/aad4424" 10.1126/science.aad4424. Emerging PV technologies, commonly referred to as the 4th generation, involve the use of non-conventional materials for photovoltaic devices, opening the possibility of tailoring material properties to create large-area, inexpensive, and efficient photoconversion devices. These include reducing the cost of monocrystalline silicon substrate, reducing the thickness of existing crystalline silicon, cultivating multi-junction and multi-gap approaches and exploring new materials/mechanisms like perovskites/ ferroelectricity. In addition, efforts towards combining polymer thin films with the stability of novel inorganic nanostructures with the aim of improving the optoelectronic properties are being aggressively pursued. This book, Emerging Photovoltaic Materials: Silicon & Beyond, focuses on recent developments in emerging 4G photovoltaic materials. The book is divided into six parts covering a broad range of impending topics in emerging PV materials. Part 1 consists of three chapters. Development of high throughput growth of monocrystalline silicon ingots with uniform resistivity using continuous Czochralski process is described in Chapter 1. Chapter 2 reviews recent research concerning the development of silicon-based materials for advanced solar cells in terms of material preparation, defect and impurity control, structure–property relationship, and material device effect in different cell structure designs of both mono- and polycrystalline silicon photovoltaics. Chapter 3 presents the recycling routes for silicon PV modules used to recover valuable materials such as silver, copper, aluminum, and high-grade silicon. Part 2 consists of five chapters dedicated to emerging new PV materials. Chapter 4 provides the fundamentals of ferroelectricity applied to photovoltaics. Ferroelectric photovoltaicity is compared to the classic semiconductor Shockley–Queisser limit. An overview of emerging cubic tin-based chalcogenides (SnSe, SnS, and SnTe) and their future potential

xxiv

Preface

are presented in Chapter 5. Chapter 6 investigates the effect of doping of TiO2 nanoparticles with Cu, Al and Tm on the photocatalytic activity of dye-sensitized solar cells (DSSC). Chapter 7 provides an in-depth phenomenological approach to the photovoltaic effect in multiferroics, describing the light-induced effects. Chapter 8 discusses the growth of multinary transparent conducting oxides from the Zn-Sn-In-Ga oxide system for application as transparent conductors in photovoltaics. Part 3 consists of two chapters dedicated to perovskite solar cells—a rapidly evolving area. The comprehensive review in Chapter 9 focuses on the properties of perovskite materials, with an emphasis on the stability of perovskite solar cells. Chapter 10 shows the low and high doping of MAPbI3 perovskite in Pb2+ sites with various bivalent cations. The perovskites are synthesized and characterized using several techniques and periodic density functional theory is performed and applied. Part 4 consists of four chapters on organic photovoltaics (OPV). Chapter 11 elucidates the principles of designing organic materials with high dielectric constants without sacrificing other properties that contribute to high power conversion efficiencies (PCEs). Chapter 12 begins with a review of crystalline, thin-film and earth-abundant PV materials and leads to recent developments in dye-sensitized solar cells (DSSC). Heterojunction energetics and open circuit voltage in organic photovoltaic cells (OPV) are described in Chapter 13. Chapter 14 deals with application of low temperature plasma-enhanced chemical vapor deposition (PECVD) for organic PV cells on flexible substrates. Part 5 consists of three chapters, ranging from quantum dot photovoltaics to novel nanomaterials and nanoprocessing, used to achieve thin films with desired photovoltaic properties. Chapter 15 focuses on carbon nanomaterials employed in new architectures using dye-sensitized solar cells (DSSC), nanotube-Si heterojunction and perovskite cells. Chapter 16 discusses the fundamentals involved in the operation of quantum dot solar cells and the prevailing synthesis of QD-HIT and QD-sensitized solar cells. Chapter 17 deals with near-infrared (NIR) responsive hybrid QD/ perovskite solar cells. Part 6 has two chapters on concentrator photovoltaics (CPV) and analysis models. Chapter 18 provides optical simulation, electrical interconnection and optimization of dense-array concentrator photovoltaics (DACVP) consisting of multijunction solar cells. Chapter 19 discusses the evaluation of panels under the given climatic conditions using PVsyst simulation software and incorporating it into the site-specific design of a photovoltaic system.

Preface

xxv

Thus, this book brings together a wealth of information that will serve as a valuable resource for researchers, scientists and engineers engaged in PV research and development. The editor expresses her sincere appreciation to the International Association of Advanced Materials, and to the authors who have contributed their knowledge and expertise to this book. Special thanks to Martin Scrivener and Linda Mohr of Scrivener Publishing for their diligent typesetting and proofing work and coordination with the authors. Santosh K. Kurinec, PhD Rochester, NY, October 29, 2018

Part 1 SILICON PHOTOVOLTAICS

Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (1–21) © 2019 Scrivener Publishing LLC

1 Emergence of Continuous Czochralski (CCZ) Growth for Monocrystalline Silicon Photovoltaics Santosh K. Kurinec1*, Charles Bopp1 and Han Xu2 1

Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester, NY, USA 2 GT Advanced Technologies, Hudson, NH, USA

Abstract

The Czochralski (CZ) process is the most commonly used method to produce single crystalline silicon for the photovoltaic (PV) and semiconductor industry. As the demand for silicon increases, the pressure on the silicon production industry grows to create higher quantities of the material at reducing prices. Currently, monocrystalline silicon (mono-Si) costs approximately 20% more than the multi-crystalline silicon (mc-Si) as Si-PV substrate. Over the years, CZ-producing vessels have increased in size to support this increased demand. The current CZ vessels are more than double the size, with the ability to produce crystals with twice the diameter and 10 times the mass of the first CZ vessels introduced in the 70s. The increase in height of the pull chamber has in turn caused the depth and width of the molten silicon feed tanks to be increased. The continuous Czochralski (CCZ) method for silicon production has the potential to greatly reduce the cost of silicon wafers. It is an effective method to address the current issues in standard CZ fabrication. With these and cell structure advances, the average manufacturing cost difference between mono- and multi-Si cells is now at US$ 0.015/W. These factors along with higher conversion efficiency rates have resulted in mono-Si cells reaching a dominant position in generation costs. The purpose of this chapter review is to inform what CCZ offers, and the advantages the method provides through engineering advancements as well as through performance of cells constructed with CCZ grown ingots. In addition, CCZ opens the door for reducing the cost of n-type silicon for PV.

*Corresponding author: [email protected] Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (3–21) © 2019 Scrivener Publishing LLC

3

4

Emerging Photovoltaic Materials

Keywords: Continuous Czochralski (CCZ), Mono-Si, Ingot resistivity uniformity, Ga doping in silicon

1.1 Introduction It is predicted that mono-Si will attain a share of 60% by 2027 over multi-crystalline Si for photovoltaics [1]. Historically, because in the early days of its development, the solar technology was mainly used for space applications and the p-type structure had better resistance to radiations for space applications. P-type wafers are also cheaper due to the CZ ingot process described in the following sections. However, most high-efficiency solar cells realized today are n-type solar cells due to their higher carrier lifetime. The n-type technology is also immune to light-induced degradation (LID), which is caused by formation of boron–oxygen defects in p-type Si. When using n-type solar cells, doped with phosphorus, this effect disappears. Also, n-type solar cells are less prone to metallic impurities of the silicon because of the absence of the boron–oxygen defect. It is predicted that the market share for n-type mono-Si will grow (Figure 1.1). Current mono-Si solar cells are pseudo squares with dimensions 156  156 mm2, projected to increase to 161.75  161.75 mm2 by 2027. The current CZ crystallization process can produce total ingot mass of 800 kg,

100% 90% n-type

80% 70% 60%

p-type

50% 40% ITRPV2017

30% 20% 10% 0%

2016 p-type mc

2017 p-type HPmc

2019

2021

p-type monolike

2024 p-type mono

2027 n-type mono

Figure 1.1 Predicted market share of different wafer types for silicon solar cells [1].

Emergence of CCZ Growth for Mono-SI PVS

5

which will increase to 1000 kg by 2019. The continuous CZ process has the potential to move far beyond 1000 kg total ingot mass [1]. The following sections describe CZ and CCZ processes.

1.1.1 The Czochralski (CZ) Process Monocrystalline silicon ingots are grown in a reactor furnace by the Czochralski method named after the Polish scientist Jan Czochralski, who discovered this method in 1916 [2]. The process starts with the stacking of a quartz crucible with polysilicon silicon feedstock, which is then loaded into a furnace. The silicon is heated to around 1500°C to ensure the melting [3]. While the temperature is raised, the air is pumped out of the furnace chamber, and argon is purged through the system. This is done to obtain an inert atmosphere, and the desired pressure is in the range of 15–50 mbar during the pulling process [4]. Then, a rod or cable with a silicon seed is dipped into the molten silicon, and as it is drawn up, a monocrystalline silicon crystal is grown on the seed crystal. Figure  1.2 illustrates the concept of CZ pulling. The vertical pulling movement of the seed rod or cable enables freezing of silicon in monocrystalline form with the seed as the template. The maximum pull rate, vpmax is determined by the heat balance between the heat conducted from the melt to the crystal plus the latent heat of fusion of silicon during freezing and the heat conducted/radiated away by the crystal. It is given by

v pmax

1 L S

2

kMTM5 3r

where vpmax = maximum pull rate in cm/s L = latent heat of fusion, for Si = 430 cal/g = density of solid silicon = 2.328 g/cm3 S = Stefan Boltzmann constant = 5.67  10–5 erg/cm2 s K4 = emissivity of Si = 0.55 kM = thermal conductivity of molten Si = 0.048 cal/cm s K TM = melting temperature of Si = 1690 K r = crystal radius (cm) 1 erg = 2.39  10–8 cal

(1.1)

Heat shield

Seed

Seed crystal

Heater

Si single crystal Direction of pull >

Emerging Photovoltaic Materials

Chamber (cooled)

6

Neck

Melted Si Graphite/ quartz-crucible

Crown

(b)

Body

Schematic of crystal growth

Tail

(a) Commercial CZ puller

(c)

(d)

Silicon charge

Stages of ingot growth

(e) Ingot

(f) Pseudo square wafer

Figure 1.2 (a) Picture of a commercial crystal puller; (b) crucible with molten Si; (c) polysilicon charge; (d) different stages of CZ growth; (e) grown ingot; (f) shaping pseudo square wafer sawing [7].

Substituting for the values above, the maximum pull rate for silicon crystal growth is obtained as

v pmax

64.8 r

cm/h

(1.2)

The pull rates are adjusted to shape the crystal. Initially pulled quickly, a thin crown is formed that serves as the break off point when the crystal is fully grown. Pull rate then decreases slowly, resulting in a widening of the crystal, producing a taper. When the taper reaches the desired size of the silicon wafer, the pull rate remains constant, growing the body used for wafer production. When the melt is nearly depleted, the pull rate is again increased to form the bottom, which is cone shaped to provide stability in the large crystal [5]. The crystal can then be removed, and the process is repeated. In a typical run, over 100 kg of silicon is added to the crucible. It takes approximately 5 h for the silicon to melt and for the process to begin. The crystal is typically grown at a rate of 2.4 to 3.5 inch per hour for an 8 -diameter ingot [6].

Emergence of CCZ Growth for Mono-SI PVS

7

The crucibles used in the CZ process are made of fused silica [8]. Highpurity crystalline quartz sand or amorphous quartz powder is first poured into a rotating mold and heat is applied from an electric arc, and the quartz is melted to an amorphous glass. The fusion starts in the inside and spreads out to the mold walls. Gas bubbles of SiO are produced in the melt– crucible interface. The crucible can also react with the carbon in the graphite hot zone parts to form silicon monoxide. The two reactions producing SiO are

SiO2 (s) + C (s) → SiO (g) + CO (g) SiO2 (s) + Si (s) → 2SiO (g) In the CZ process, it is unavoidable that a certain amount of oxygen is incorporated from the quartz crucible. In order to remove most of the oxygen and silicon monoxide, a low-pressure argon gas is purged through the furnace chamber. The inert gas removes up to 98%–99% of the oxygen that is dissolved from the crucible [3]. As a result of this, only 1%–2% of the dissolved oxygen from the crucible ends up in the silicon ingot (Figure 1.3). For most semiconductor applications, this is not a concern. However, for high-efficiency solar cells, oxygen impurity is undesirable as oxygen forms precipitates that act as recombination centers, reducing the minority carrier lifetime. In addition, the silicon monoxide reacts with the carbon in the graphite support to produce silicon carbide and carbon monoxide through the following reactions [9]:

3C (s) + SiO (g) → SiC (g) + 2CO (g) The minority carrier lifetime in the silicon wafers produced from the ingots grown by the CZ process is greatly influenced by the amount of carbon in the silicon. To achieve long lifetime in the silicon wafers, the oxygen and carbon content has to be reduced by controlling the gas formation in the crucible–melt interface. One method is to apply a strong magnetic field to control the convection in the silicon melt. This is called the MCZ method [10]. Since hot melted silicon conducts electricity, it is subjected to a force created by the interaction between the flow of the melted silicon and the magnetic field. As a result, the flow of the melted silicon is altered. Crystal properties are controlled by taking advantage of this characteristic. It reduces the dissolution of the crucible in the melt by controlling the melt convection. However, the MCZ method becomes expensive, requiring very high magnetic flux densities of ~103 G superconducting magnets

8

Emerging Photovoltaic Materials

Low pressure Argon gas CO, CO2

CO, CO2 SiO

SiO

O

O

O

SiO2 Graphite heater

Graphite

Figure 1.3 Oxygen source from the quartz crucible. Most (>98%) of the dissolved oxygen evaporates as SiO. The remainder is incorporated into the silicon crystal. Carbon comes from the graphite parts.

with cooling systems. It exceeds the recommended maximum 600 G for 8 h exposure recommended by the American Conference of Governmental Industrial Hygienists (ACGIH). In general, most impurities tend to segregate into the liquid during crystallization, leaving the solid proportionally purer. As the solidification (crystallization) proceeds, impurity distribution changes in the resulting solid silicon. For a silicon liquid/solid interface under equilibrium, a ratio of the impurity concentration in the solid (CS) to that in the molten silicon (CL) is defined as the equilibrium segregation coefficient, k0, as

k0

CS CL

(1.3)

It implies that with k0 < 1, impurity is rejected into the melt and with k0 > 1, impurity is drawn into the solid. Almost all impurities have k0 < 1 in silicon except oxygen. It is observed that the equilibrium segregation coefficient k0 is strongly correlated to the tetrahedral covalent radius. The covalent radius, rtet, is a measure of the size of an atom that forms part of one covalent bond. Large atoms

Emergence of CCZ Growth for Mono-SI PVS

9

are not easily incorporated into a silicon crystal, resulting in a small k0. Correspondingly, k0 has a strong correlation to the maximum solubility, represented by Cs,max

5.2 1021 k0

(1.4)

except for oxygen, carbon, nitrogen and cadmium [11] (Table 1.1). Defining the following parameters in a crystal growth process: V0 = initial volume of melt I0 = initial number of impurity atoms in the melt C0 = initial concentration of impurities in the melt IL = number of impurity atoms in the melt at a given time CL = concentration of impurities in the melt at a given time Vs = volume of crystal solidified Cs = concentration of impurities in the solid Table 1.1 Equilibrium segregation coefficient k0, maximum solubility Cs,max and covalent radius rtet of common elements in silicon. Impurity

Group

k0 2  10

Cs,max (cm−3)

rtet (A)

19

2.0  10

1.26

Al

IIIb

As

Vb

0.3

1.8  1021

1.18

B

IIIb

0.8

20

6.0  10

0.88

Ga

IIIb

8.0  10−3

4.0  1019

1.26

C

IVb

0.07

3.0  1017

0.77

Cu

1b

4.0  10−4

1.5  1018

1.35

Cd

IIb

1.0  10−6

0.1–0.3  1016

1.48

Fe

VIII

8.0  10

16

3. 0  10

1.23

N

Vb

7.0  10−4

4.5  1015

0.70

O

VIb

0.25–1.25

18

3.0  10

0.66

P

Vb

0.35

1.3  1021

1.10

Sb

Vb

0.023

7.0  1019

1.36

Si

IVb

−3

−6

1.17

10

Emerging Photovoltaic Materials The impurity concentration in the solid is given by the Scheil equation

Cs

C0 k0 (1 f )k0

1

(1.5)

where f is the fraction of volume solidified. In deriving the Scheil equation, the following assumptions are made: i.

Well mixed approximation: The impurity concentration in the melt is uniform. ii. Impurities, once incorporated in the solid, do not diffuse. iii. Steady-state equilibrium condition is assumed. iv. Sublimation of impurities from the melt is negligible. Assumption (i) can be achieved by constant stirring of the molten silicon. To incorporate diffusion effects, the Scheil equation is modified by considering a boundary layer, , between the solid/liquid interface and defining an effective segregation coefficient keff

k0

keff

k0 (1 k0 )exp

v D

(1.6)

where v is the pull velocity and D is the diffusion coefficient in the melt [12]. For slow solidification rate and thorough stirring (δ → 0), v /D 1, keff = 1. It implies that an increase in growth rate increases the segregation coefficient. In practical crystal growth conditions, effective segregation coefficient should be applied. The resistivity of the ingot as a function of the fraction solidified f is given as

(f)

1 qCs (Cs )

(1.7)

where is the carrier mobility, which is a function of doping concentration. Figure 1.4 shows the calculated resistivity for boron and phosphorus for an initial melt concentration of 1.5  1015 cm−3 in each case using Equation 1.5 and Equation 1.7. Since CZ is a batch process, each time an ingot is produced, the silicon must be heated to produce the melt. This is an energy-intensive process and is the main production cost in producing high-quality silicon for semiconductor and photovoltaic applications. In addition, varying resistivities can

Emergence of CCZ Growth for Mono-SI PVS

11

12 Resistivity (Ohm.cm)

Boron 10 8 6

Phosphorus

4 2 0 0.0

0.2

0.4

0.6

0.8

1.0

Fraction Solidif ied

Seed end

Tail end

Figure 1.4 Calculated resistivity as a function of fraction solidified for boron and phosphorus with C0 = 1.5  1015 cm−3.

cause high quantities of waste to be produced, as not all the silicon is fit for production leading to increased wafer costs. The solution to this problem has existed for nearly half a century, but until recently has had little demand for implementation. Recently, by controlling the heat flow of the ingot growth chamber and at the solid–liquid interfaces in a CZ process, a 15% increase in pulling speed of wafers with high quality has been reported [13].

1.1.2 Continuous Czochralski Process (CCZ) CCZ on the other hand is a continuous process. It was patented first in 1954 by G.W. Rusler, Minneapolis-Honeywell Regulator Company [14] and presently many configurations are being explored. Instead of requiring a large reservoir of molten silicon, the CCZ method takes advantage of the continuous addition of new silicon and uses a shallow reservoir decreasing the melt height, which offers many advantages. By continuously charging the polysilicon and dopant, the resistivity of the growing crystal is tightly controlled. The resistivity of the CCZ crystal is given by

k0C0

0

Cr (Cr

kV k0C0 )exp 0 s V0

(1.8)

12

Emerging Photovoltaic Materials

where 0 is the initial crystal resistivity at Vs = 0 and Cr is the incoming melt replenishment concentration. It can be observed that if Cr = koC0, the exponential term in Equation 1.8 is eliminated and the resistivity remains constant. The purity of the melt can be higher because of the constant addition of pure silicon, which controls the impurity and dopant concentrations, and the resistivity, which was problematic in the standard batch CZ method [15]. CCZ leads to better-quality wafers produced with reduced energy cost, since the process can be continuous if desired without the need to restock and re-melt silicon. The already molten silicon is used to melt the silicon that is being continuously added, which greatly reduces the energy cost for the system. It is much more energy efficient, with only a small fraction of the total energy consumed in melting additional silicon. The difficulty in obtaining cheap silicon wafers is mostly due to the kinetics involved in the batch process. The increasing melt height in CZ vessels introduces convection patterns in the melt that affect the impurity buildup, resistivity, and cell performance. All of which have been studied intensely with promising results. CCZ allows for multiple crystals to be produced in each furnace while operating at lower melt heights due to the replenishment of the silicon used [16]. This increases the efficiency of the process as the solidification of the silicon can be done at increased rates. Decreasing melt height has many benefits, it reduces the dissolved oxygen in the crystal, which hampers performance while also allowing for more homogenous distribution of impurities and dopants (Figure 1.5) [17]. Contrary to what one can imagine, there is a slower buildup of impurities in a CCZ melt as compared to a CZ melt. This is because of the reduced amount of silicon Large melt/quartz contact 16

Lowering melt/quartz contact

Oxygen (ppma)

15.5 15 Evaporation area reduction

14.5 14 13.5 13

CCZ

12.5 12 0.1

0.2

0.3

0.4 0.5 0.6 Fraction Solidif ied

0.7

0.8

Figure 1.5 Oxygen incorporation in CZ and CCZ as a function of fraction solidified.

Emergence of CCZ Growth for Mono-SI PVS

13

and impurity concentration in the crucible any moment in production. It also allows for fewer oxygen atoms to be introduced to the crystal because less oxygen can dissolve in smaller volumes of silicon. These factors impact the resistivity of the ingot, and since the crystal is more uniform, there is also a more consistent resistivity for the entire ingot [16].

1.2 Continuous Czochralski Process Implementations There have been multiple different feed arrangements tested for CCZ, with the most popular two being solid pellets and liquid feeds (Figure 1.6). The liquid feed system was one of the earliest attempted methods for CCZ and involved a two-crucible method. The first crucible served as the feed tank where the silicon was melted and stored before being pumped into the second crucible where the crystals are grown [13]. This system demanded a large amount of space and energy increasing the initial starting cost of production. To remedy this, a solid feed system was developed where small 1-mm-diameter polysilicon pellets are introduced into the melt via a feeding mechanism [5]. The solid pellets are introduced in an outer section of the feed tank, which is separated by baffles from the center where the crystal is grown. The baffles are necessary to prevent pellets from drifting toward the crystal where they can combine, a fatal error resulting in failure to produce a single crystal. The baffles have their own issues, such as extra oxygen evolution and flow oscillations, reducing the quality of the crystal. To remedy this, experiments have been carried out with the hopes of removing the baffles. The CCZ setup without baffles instead uses the convection as well as crucible drum rotation to prevent the pellets from contacting the crystal [5]. Calculations were performed, and it was determined that for 6 -diameter ingots pulled at a typical rate of 50 mm/h, a feed rate of 34 g/min was necessary to have a consistent melt height. The energy required to melt the Crystal puller

Silicon feed

Crystal puller

Silicon feed

Feed region separated by baf f les

Melt tank

(a)

(b)

Figure 1.6 (a) A dual tank system. (b) The more commonly used baffle system.

14

Emerging Photovoltaic Materials

pellets was calculated to be 1.8 kJ/s, which was approximately 2% of the total energy used in a CZ grower [6]. The crucible was rotated to provide uniform heat to melt these pellets; without rotation, the energy required for the phase transition would produce cold spots, causing solidification in the melt itself. Since the crystal itself is a cold spot, pellets experience a force toward the center due to the surface tension of the melt [14]. Surface tension decreases when temperature increases; it becomes less likely for the particles to become submerged and melt at an adequate rate. Experiments have been run on the temperature control of CCZ. The use of multiple heaters has been suggested, as well as the use of a cooling sleeve around the crystal itself to reduce thermal stresses from the melt. It was found that the introduction of a cooling sleeve did in fact reduce thermal stress, since it allowed less heat to be transferred through the crystal due to the lower temperature gradient. The temperature gradient through the melt increased by 20% radially, which allows for the crystal growth rate to be increased accordingly [15]. Multiple heaters have also been employed to help reduce the turbulent flow inside of the melt caused by temperature gradients. In practice, a single heat source was not capable of providing the even heating required. The walls of the crucible have the highest temperature, and the temperature gradient decreases toward the center. It is for this reason that some CZ producers employ the use of magnetic fields to decrease this effect. The magnetic fields required add additional operating cost to the process, which is undesired [16]. When a series of three heaters were employed, the maximum temperature deviation was reduced greatly, resulting in a more uniform and well-mixed melt. Typically, in CCZ, the melt is in a state of turbulence, or oscillatory, which means that it is in the transition phase between laminar and turbulent flow. The oscillatory flows become influenced by crystal rotation and, in most situations, become turbulent. When this happens, impurities are increasingly likely to be introduced into the crystal [17]. This has the noted effect that the outer edges of the crystals have higher impurity concentrations than the center. Despite this, the CCZ method produces crystals with greater axial uniformity compared to traditional CZ [18]. The purpose of this rotation is to counteract temperature gradients in the melt, but even at high rotation rates, the effects are limited. The optimal rotation was found to be between 5 and 10 RPM. When operating at 5 RPM, oxygen concentration in the melt is at a minimum, while 10 RPM is optimal for the best crystal structure. Due to even heating from rotation, it was determined that the mean time to melt added pellets is between 1 and 2 s. The amount of feed that could be added to the melt was determined to be unaffected by the rotation of the crucible. High feed rates produced clumps of pellets that

Emergence of CCZ Growth for Mono-SI PVS

15

Feeder

Feeder Growing Crucible

Figure 1.7 Schematic of a commercial CCZ process (left); actual CCZ system (right). Courtesy of GTAT.

aggregated and do not melt as desired [5]. Schematic of a commercial CCZ process and actual CCZ system is shown in Figure 1.7.

1.3 Solar Cells Fabricated Using CCZ Ingots In the current market, it is more cost-effective to produce p-type silicon rather than n-type. For this reason, n-type silicon makes up an extremely small amount of market share. The high cost of n-type Si is due to phosphorus’ low segregation coefficient of 0.35 compared to boron’s 0.8, giving more resistivity variation along the n-Si ingot. Moreover, p-type mono-Si products come with inherent disadvantages of having higher cell-to-module (CTM) loss and higher light-induced degradation (LID) [19, 20]. In addition, light-induced degradation (LID) due to boron–oxygen (B–O) complexes in boron (B)-doped, p-type monocrystalline silicon solar cells can result in significant loss in power output [21]. It has been reported that n-type Si has higher tolerance for the most common metallic impurities like iron [22].

1.3.1 n-Type Mono-Si High-Efficiency Cells Current research on n-type silicon cells have shown that it outperforms p-type silicon in terms of efficiency, with efficiencies greater than 25%. To shift the market toward n-type, it must be possible to create n-type wafers at a cost that can compete with the industry standard p-type wafers. The oxygen concentration in the crystal also varies, but in a much more interesting fashion. In standard CZ, the top of the crystal has an extremely high oxygen concentration that decreases down the crystal until approximately 60%

16

Emerging Photovoltaic Materials

of the crystal has been pulled. The concentration then begins to increase again until the crystal is fully grown. This can cause up to 75% of the crystal to be unfit for the semiconductor industry [17]. CCZ provides the perfect solution for allowing low-cost production of n-type wafers. Many highefficiency cell configurations are being reported, which include n-PERT (passivated emitter rear totally diffused) n-Pasha (passivated all sides H-pattern [23], and HJT (heterojunction) [24, 25] shown in Figure 1.8. Many studies have investigated the minority carrier lifetime (MCLT), as well as open-circuit voltage (Voc), short circuit current (Jsc), and the fill factor of the cell (FF) of n-type cells grown by CCZ (Figure 1.9). Since the addition of polycrystalline can be controlled in CCZ, it is possible to maintain more constant resistivities as well as a low and uniform Contact grid

Ni/Cu/Ag Dielectrics

Passivating and anti-reflection coating Ag TCO a-Si:H (p+) a-Si:H (i) c-Si (n)

p+ emitter

p n-Si

n-type Si wafer n+ BSF

Dielectrics Al

Contact grid

(a)

n-Si

a-Si:H (i) a-Si:H (n+) TCO Ag

n+

Passivating coating

(b)

(c)

1,1 1,05 1 0,95 0,9 0,85 0,8 0,75 0,7

Voc [V]

Normalized Eff

Figure 1.8 Schematics of (a) n-PERT (passivated emitter rear totally diffused), (b) n-Pasha (passivated all sides H-pattern), and (c) HJT (heterojunction) solar cells.

Top

Middle

Tail

0,74 0,72 0,7 0,68 0,66 0,64 0,62 0,6

Cz

Top

Top

Middle

(c)

Tail

Cz

Tail

Cz

(b)

1,1 1,05 1 0,95 0,9 0,85 0,8 0,75 0,7

Normalized FF

Normalized Jsc

(a)

Middle

Tail

Cz

1,1 1,05 1 0,95 0,9 0,85 0,8 0,75 0,7 Top

Middle

(d)

Figure 1.9 The Jsc, Voc, FF, and normalized efficiency of HJT n-type cells made from CCZ ingots [23].

Emergence of CCZ Growth for Mono-SI PVS Current density [mA/cm2]

Rs [ohm-cm]

6,0 5,0 4,0 3,0 Top

Middle

Tail

2,0 0

20

40

Wafer Number

60

17

40 30 Ef f: 22.2% Voc: 0.726 V Jsc: 38.49 mA/cm2 FF: 79.4%

20 10 0 0

0,2

0,4 0,6 Voltage [V]

0,8

Figure 1.10 (a) The resistivity over the length of a CCZ ingot; I–V curve of an HJT cell made from a CCZ ingot [23].

oxygen concentration. The ability of multiple crystals to be pulled in succession in CCZ also allows for more crystals to be produced with less downtime, increasing the production rate. Over 800 kg of ingots can be pulled from one single CCZ run [17]. Currently, nPERT and n-pasha are the highest-performing n-type cells currently being explored, and an experiment was performed to determine just how CCZ performs. The ingots produced by CCZ had a much more consistent resistivity, which was found to contribute to the enhanced minority carrier lifetime (MCLT) reported. On HJT cells produced from the wafers, as well as recorded on the length of the ingot, the MCLT only decreased by 8%, from 93% to 85% of the reference value [23]. Additionally, there was no noticeable difference between wafers cut from different sections of the same ingot and when compared to the wafers grown with traditional CZ. This uniformity greatly increases the amount of controllability in the manufacture of HJT cells, since one bad cell limits the entire stack’s performance. There were no noticeable differences between HJT cells made with CZ and CCZ; the efficiency of 22.2% was reported for the CCZ cells [23] (Figure 1.10). In another experiment, nPERT and n-Pasha cells were created from trimmed 6 wafers produced from the last three ingots of a five-ingot CCZ run. The efficiency, Jsc, and FF of the cells produced by CCZ were comparable to the CZ grown reference of 4.7 Ω cm. Surprisingly, the Voc in some of the CCZ cells were slightly higher than those of the reference, with the majority performing better than the top 50% of wafers from the reference [17].

1.3.2 Gallium-Doped p-Type Silicon Solar Cells An approach to prevent the formation of B–O complexes is to replace the boron with the gallium (Ga) as the dopant in silicon. However, gallium has a very low segregation coefficient in silicon (k0 = 0.008), which gives rise

18

Emerging Photovoltaic Materials

to much higher resistivity variation along the length of the crystal using conventional CZ process. Figure  1.11 plots Ga concentration and ingot resistivity as a function of fraction solidified for an initial Ga melt concentration of 1018 cm−3. As is observed, this limits the yield of usable crystal for making the solar cells. Low yield increases the wafer production cost. The CCZ process can overcome this by continuous feeding of silicon feedstock, enabling crystals with extremely uniform resistivity distribution regardless of segregation coefficient as shown in Figure 1.12 [26].

Resistivity (Ohm·cm)

8 × 1016 2.00

7 × 1016 6 × 1016

1.50 1.00

5 × 1016 4 × 1016

0.50

3 × 1016 2 × 1016 1 × 1016

Ga Concentration (cm–3)

2.50

0.00 0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 Fraction solidif ied

Figure 1.11 Calculated Ga concentration and resistivity of CZ grown as a function of fraction solidified.

3.5

Resistivity (W-cm)

3.0 2.5 2.0 Center

1.5

Edge

1.0 0.5 0.0 0

500

1000

1500

2000

Distance from ingot crown (mm)

Figure 1.12 Resistivity uniformity in Si ingot grown using CCZ process with Ga containing melt [26].

Emergence of CCZ Growth for Mono-SI PVS

19

To achieve > 1, where τdi is the dielectric relaxation time that describes kinetics of changes of space charge electric field) can be expressed as a function of the spatial frequency as follows (Equation 14.3) [20]:

Jp

K emf

2 2 De

1 K L

1 K 2 L2Dh

(14.3)

Fitting experimental data in Figure 14.11 by Equation 14.1, a majority and minority carrier diffusion length can be determined from the conditions K LDe = 1 and K LDh = 1. Using the values of characteristic spatial frequency K ≈ 3.22 μm−1 and K ≈ 5.37 μm−1 the carrier diffusion lengths can be

536

Emerging Photovoltaic Materials

estimated as LDe ≈ 0.31 μm and LDhx ≈ 0.19 μm, respectively [21, 22]. Taking De ,h e ,h into account the expressions for the diffusion lengths LDe ,h [here De,h is electron (hole) diffusion coefficient] and assuming the validity of the Einstein relation between the mobility and diffusion coefficient D/μ = kBT/e (here, kB is the Boltzmann constant, T is the absolute nearroom temperature, and e the electron charge), electron and hole mobilitylifetime products of the studied a-Si:H films may also be calculated, giving the values μeτe = 3.88 μm2/V and μhτh = 1.44 μm2/V. Non-steady-state photo-EMF in organic semiconductors: A theoretical model for the non-steady-state pEMF effect was developed [27] for monopolar organic photoconductors, and it was shown experimentally that the number of important photoelectric parameters (such as mobilitylifetime μτ product, photocarrier lifetime τ, dielectric relaxation time τdi, quantum efficiency of charge generation ϕ, etc.) can be determined using this technique. Regarding the determination of the transport length by using the pEMF technique, it was shown above that by measuring the dependence of the pEMF signal on the spatial frequency K, it is possible to obtain the electron and hole diffusion length LDe,h. However, this method can hardly be used in organic photoconductors; due to their very disordered structure, the carriers’ diffusion lengths are too short (LDe,h < λ / 2) to be measured for reasonable beam crossing angle θ. However, the ambipolar μaτa product μaτa = μeτe + μhτh and effective drift length Lda = μaτa can be determined from the external DC field E0 dependence of the pEMF signal. Assuming the validity of the Einstein relation in low field regime, the carriers’ diffusion length LDe,h can then be evaluated. Figure 14.12 shows an example of p-EMF signal on external electric DC field E0, which allows determination of the majority carrier diffusion length in organic semiconductor thin films based on the mixture of polymer and fullerene. It is observed that for small fields, the signal is almost constant. At the increasing dc field, the output signal drops quadratically and reaches the minimum at the DC field E01

kBT / e h h

. At this point, “drift” and

e e

“diffusion” components of the pEMF current nearly balance each other and the signal changes its sign (dip in Figure 14.12). Using the above expression for E01, the mobility-lifetime product of the majority carriers μhτh can be evaluated from the minimum position. Assuming the validity of the Einstein relation, the diffusion length of the majority carrier can be estimated. When the external bias continues to increase, the signal begins to grow quadratically until it reaches the saturation level.

Ω Photo - EMF Jemf RL (V)

PECVD and Organic Semiconductors in PV Device 537

1E-3

1E-4 0

1 × 107 External DC field, E0 (V/m)

Figure 14.12 Photo-EMF signal as a function of the external dc field for different sensitizer concentrations: 5 wt.% ( ), 10 wt.% ( ), and 15 wt.% ( ). The solid lines are a guide to the eyes.

It can be observed that minima position varies with the increasing sensitizer concentration, indicating variation of the transport length. For high sensitizer concentrations, the photo-EMF signal at zero dc field changes its sign, indicating the change on the type of the majority carrier (from holes at low sensitizer concentration to electrons at high sensitizer concentration). Note that combining these data with the experiments on the modulated photocurrent, where the characteristic time of the photoconductivity response can be directly measured from the photocurrent frequency dependence, the drift mobility of the majority carriers can also be evaluated.

14.4 Results for Devices 14.4.1

Devices Based on PECVD Materials

The possibility of doping in PECVD films pioneered by Spear and Le Comber [28] resulted in the development of PV devices first with the Schottky barrier and then with p–i–n junctions. The most developed devices are triple junction from Uni Solar [29] and “micromorph” [30]. Let us consider two representatives of PV devices based on PECVD materials. The first is triple tandem fabricated by means of a roll-to-roll

538

Emerging Photovoltaic Materials

process on stainless steel substrate. The structure and the fabrication technology have been developed by Uni Solar [29]. It comprises nine PECVD semiconductor layers forming three series-connected p–i–n junctions with a-SiH and a-SiGe:H as intrinsic semiconductors, a semitransparent frontal electrode (made of indium tin oxide, ITO), a conducting grid electrode to improve current collection, and some additional layers. Three p–i–n junctions are formed with specially developed intrinsic a-Si:H, a-SiGe:H films with optical gaps and thicknesses of the films designed to optimize optical absorption in a wider wavelength range than that for one semiconductor, thus improving photon absorption and photocarrier collection. The optimization also includes adjustment of absorption and thicknesses in such way that each p–i–n junction collecting its part of solar spectra should generate the same current; otherwise, mismatching would create losses and reduce efficiency. The best efficiency achieved (certified) was PCE = 13% [29] for a module area of about 1 m2. Another PV structure developed for commercial application is called the “micromorph” structure [30]. The structure comprises two PECVD p–i–n junctions with amorphous a-Si:H and microcrystalline silicon mk-Si:H. Because of the difference in optical bandgap (Eg  = 1.75 eV for a-Si:H and Eg = 1.1 eV for mk-Si:H), the structure provides collection of both the visible part of spectra and a substantial part of the NIR spectrum, resulting in an increase in photocurrent and efficiency. In micromorph devices, optical optimization of the frontal part and rear contact has been applied for effective light trapping and better harvesting penetrated photons. The micromorph structures have been reported with double (one junction with mk-Si:H) and triple (two junctions with mk-Si:H) junctions with stabilized efficiencies of 11.2% and 12%, respectively [30].

14.4.2

Devices Based on Organic Materials

Organic photovoltaic (OPV) solar cells based on solution-processable compounds, predominantly polymers but most recently also small molecules, are increasingly being investigated. This technology promises theoretically low-cost printable PV devices on flexible substrates. The main difference between organic and inorganic active layer is related to the creation of a rather stable exciton by absorbed photon in an organic molecular or polymer absorber in an organic photovoltaic (OPV) device. The diffusion length of excitons is typically of the order of 10 nm, around a tenth of the thickness of the active layer required to absorb a high

PECVD and Organic Semiconductors in PV Device 539 proportion of the incident light. As a result, the majority of the photogenerated excitons in a planar heterojunction system decays before their collection and contribution into current in an external circuit [31]. Bulk heterojunction (BHJ) active layers have been proposed to solve this problem. BJH concept involves the self-assembly of nanoscale heterojunctions by spontaneous phase separation of the donor (polymer) and the acceptor (fullerene). Because of this spontaneous phase separation, chargeseparating heterojunctions are formed throughout the bulk of the active layer. These mechanisms provide separation of charges (destruction) of exciton and appearance of mobile charge carriers. However, external electric field for transportation of the separated charges is required and provided by two electrodes with different work functions. After the introduction of the BHJ concept, pioneering researchers started to recognize the importance of precise control of morphology because the device performance is extremely sensitive to the nanomorphology of the BHJ film induced by spontaneous phase separation of the D:A blends [32–35]. A variety of processing techniques, such as thermal/ solvent annealing and processing additives [35–37], have been devised, and those attempts have enabled us to rather fine-tune 3D nanostructured BHJ morphologies. For further optimization of organic semiconductors, research interests have moved to interface engineering, that is, inserting interfacial layers (IFLs) between the BHJ film and the electrodes [38–42]. By developing new organic/inorganic interfacial materials or introducing already-developed materials used in other research fields, substantial studies have demonstrated that those materials function as chargetransporting/blocking layers, surface modifiers, and optical spacers, which increase the conversion efficiency of devices with organic semiconductors. More significant advances have been achieved by developing new device architectures [43–47]. For example, multi-junction structures, in which two or more sub-cells with different absorption regions are vertically stacked and interconnected in series or parallel, have allowed a broad solar spectrum to be harvested. Furthermore, the development of various donor materials with different bandgaps and fullerene/nonfullerene acceptors has also been devoted to substantially improving the efficiency of devices with organic semiconductors [48–53]. The combination of new material designs/syntheses and the previously mentioned methods has led to remarkable efficiency enhancements, reaching values over η > 11% [47, 54]. Considering that BHJ organic semiconductors have impressive advantages, such as low-cost printability and extreme mechanical flexibility, when compared to those of amorphous silicon solar cells,

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Emerging Photovoltaic Materials

the efficiency η > 11% represents an acceptable efficiency level for flexible solar cells and further commercialization of devices with organic semiconductors [55].

14.4.3

Hybrid Devices Based on PECVD-Polymer Materials

Organic–inorganic hybrid solar cells are an alternative to pure organic or inorganic PV devices. Figure 14.13 shows an example of a new concept of hybrid photovoltaic structure based on a-Si:H and polymer organic conductor ITO/PEDOT:PSS/(i) a-Si:H/(n) a-Si:H. Structure was fabricated on indium tin oxide (ITO)-coated glass substrates. The PEDOT:PSS precursor was prepared with 1:6 weight ratio. Mixed solution was filtered with a PVDF filter with pore sizes of 0.45 μm. The PEDOT:PSS layer was deposited in N2 ambient by spin coating. The PEDOT:PSS films with a thickness of 45 nm were obtained from 45 μL of a solution deposited at a rotation speed of 2500 rpm. Inorganic layers were deposited using a cluster multichamber PECVD system with RF discharge at frequency f = 13.56 MHz. The intrinsic a-Si:H layer was deposited from a 10% SiH4 + 90% H2 gas mixture at pressure P = 550 mTorr. The 20-nm-thick n-layers were deposited using 0.01% PH3 + 9.9% SiH4+ 90.09% H2 gas mixtures at pressure P  = 550 mTorr. Finally, the 6-nm-thick p-layer was deposited using the 0.26% B2H6 + 21% CH4 + 53% SiH4 + 25.74% H2 mixture at pressure P = 690 mTorr. The deposition temperature was fixed at Td = 160°C and power at W = 3 W. The deposition of the top contacts was performed by sputtering of Ag through a metal shadow mask with an area of 0.09 cm2. The cross-section scanning electron microscopy (SEM) image (in secondary electron regime) of the hybrid photovoltaic structure on a flexible

Frontal electrode (ITO)

Rear electrode (Ag) (n) a-Si:H (i) a-Si:H (p) PEDOT:PSS

Contact

Substrate

Light

Figure 14.13 Hybrid photovoltaic structure based on a-Si:H and polymer organic conductor ITO/ PEDOT:PSS/(i) a-Si:H/(n) a-Si:H. PEDOT:PSS film deposited by spin coating (45 nm) 45 μL. Inorganic layers deposited by multi-chamber PECVD system with RF PECVD.

PECVD and Organic Semiconductors in PV Device 541

190 nm Ag (n)Si:H 400 nm (i)Si:H 250 nm PEDOT

510 nm AZO

500 nm

Figure 14.14 Cross-section scanning electron microscopy (SEM) image (from secondary electron regime) of the hybrid photovoltaic structure on flexible substrate (PEN/AZO/ PEDOT:PSS/(i) a-Si:H/(n) a-Si:H/Ag stack).

substrate is shown in Figure 14.14. The AZO layer has a columnar structure, and the PEDOT:PSS layer, deposited on AZO, is rather inhomogeneous at the PEDOT:PSS/a-Si interface. However, the PEDOT layer “heals” the rather rough AZO surface, preparing a smooth and planar surface for the deposition of amorphous silicon film. It is interesting to note that the substrate defect (crack) is translated through the AZO layer, and this is interrupted due to the organic polymer layer. As described in Section 14.3.3, the electronic characteristics of PEDOT:PSS can be modified by dilution method. Thus, the performance characteristics of devices can be controlled by modification of the PEDOT:PSS film. Figure  14.15 shows the J–V characteristics and performance characteristics (Voc and Jsc) of hybrid ITO/ PEDOT:PSS/(i) a-Si:H/(n) a-Si:H photovoltaic (PV) structures incorporating the postdeposition isopropanol (IPA)-dipped PEDOT:PSS films. The structure with PEDOT:PSS film with 45 min of IPA dipping time showed the best performance with Jsc = 15.29 mA/cm2, Voc = 0.61 V, FF = 36.5%, and PCE = 3.40%. Figure 14.15b displays the values of Jsc and Voc for untreated and IPA-dipped samples as a function of dipping time. The values of Jsc show an increase from 9.52 mA/cm2 for the untreated PEDOT:PSS structure to 15 mA/cm2 for the IPA-dipped PEDOT:PSS structure with 45 min dipping time; this may be due to the decrease of the resistivity of their IPA-dipped PEDOT:PSS films. It is interesting to note some of the maximum values

542

Emerging Photovoltaic Materials 0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Current density Jsc (mA/cm2)

0 2 4 6 8 Dipping time: 0 min 15 min 30 min 45 min

10 12

14 16 Voltage, Voc (V) (a)

0.8

Current density Jsc (mA/cm2)

16

0.7 0.6

12

0.5 0.4

10 –5

Voltage, Voc (V)

14

0

5

0.3 10 15 20 25 30 35 40 45 50 Dipping time, tdt (min) (b)

Figure 14.15 (a) J–V characteristics (at AM 1.5) of hybrid solar cells structures for different dipping times in alcohol isopropyl (IPA) and (b) Jsc and Voc control as a function of dipping time by alcohol isopropyl dilution method.

such as JSC ~15 mA/cm2 obtained in these structures. The values are very similar to those in the best p–i–n structures based on a-Si:H or even better [16]. However, the shunt and serial resistances in the PEDOT:PSS/(i) a-Si:H structures are the main issue to be solved in order to increase the FF values above 50%. The substitution of the p-type a-Si:H:B by a PEDOT:PSS layer results in improvement of frontal interface properties and a simplification of fabrication process of p–i–n structures based on amorphous silicon.

PECVD and Organic Semiconductors in PV Device 543

14.4.4

Hybrid Devices Using Crystalline Semicinductors, Non-Crystalline PECVD, and Organic Materials (HJT-OS Structures)

The combination of a well-developed crystalline silicon (c-Si) solar cell with PECVD layers has provided substantial improvement in efficiency from 17% to 24% [56]. The structure is noted as a heterojunction transition (HJT) structure. Therefore, in this section, we consider an example of such HJT device structure comprising both crystalline semiconductor and PECVD layers schematically shown in Figure 14.16a. The base of the structure is n-doped c-Si wafer. On the top of the wafer intrinsic a-SixC1−x:H film (with optimized x), intrinsic a-Si:H films are deposited. Above that it is p-doped microcrystalline silicon and then transparent conductive oxide (ITO) covered finally with electrode grid. Thus, some junctions—(a) between p-mk-Si:H and a-Si:H film and (b) between a-Si:H and c-Si (because of the optical gap difference)—are created, forming electric field on the frontal side that improves collection of charge carriers generated by short-wavelength photons. On the rear (back) side, a-Si:H and n-doped mk-Si:H form a junction with built-in electric field improving transport of photo-generated charges and also contribute to photocurrent because of carrier photo-generation due to absorption of long-wavelength photons. Thus, better harvesting of both short wavelength (on the frontal side) and long wavelength (on the rare side), together with improving charge collection, results in significant improvement in efficiency of up to PCE = 26% [57]. Here, it is worth noting that p-mk-Si:H, a-Si:H, a-SixC1−x:H, and n-mk-Si:H layers are deposited by the PE CVD Illumination AZO (PEDOT:PSS)

4

(i) a-Si:H (n) a-Si:H AZO Glass ITO (p) a-Si:H (i) a-Si:H

Illumination 3 2

ITO 2 (p) a-Si:H (i) a-Si:H (n) c-Si

(n) c-Si (i) a-Si:H (n) c-Si:H ITO Ag

(i) a-Si:H (n) a-Si:H ITO Ag 1

1

(a)

(b)

Figure 14.16 Cross-sectional view of HJT device with crystalline silicon and (a) PECVD materials and (b) HJT with OS incorporated.

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Emerging Photovoltaic Materials

technique. An example of current–voltage characteristics J(U) under sun illumination is presented in Figure  14.17a. As seen, the HJT structure shows short-circuit current density Jsc= 39.2 mA/cm2 and excellent current collection up to voltage U ≈ 0.73 V. Figure  14.18a represents the spectral dependence of external quantum efficiency (EQE) for the same sample of HJT solar cell (see the structure in Figure  14.16a). This graph demonstrates effective harvesting of photons by the structure in the range of wavelength from λ ≈ 450 nm

0.0

0.1

0.2

Voltage (V) 0.3 0.4 0.5

0.6

0.7

0.8

Current density, J (mA/cm2)

0 VOC = 0.735 V

5 10 15 20 25 30 35

JSC = 39.2 mA/cm2

40

HJT

(a) 0.0

0.1

0.2

Voltage (V) 0.3 0.4

0.5

0.6

0.7

Current density, J (mA/cm2)

0

5

h-nip

10

VOC = 0.665 V JSC = 15.7 mA/cm2 HTJ*

2 VOC = 0.495 V JSC = 11.2 mA/cm

15

Tandem

VOC = 0.185 V JSC = 13.0 mA/cm2 (b)

Figure 14.17 Current–voltage J(U) characteristics under sun illumination for HJT solar cell. (The structure has been fabricated by TF TE RDC.)

PECVD and Organic Semiconductors in PV Device 545 1

EQE (a.u.)

EQE (a.u.)

1

0.1

h-nip HJT* Tandem

0.1

HJT 200

400 600 800 1000 Wavelength, λ (nm) (a)

1200

200

400

600 800 1000 Wavelength, λ (nm) (b)

1200

Figure 14.18 EQE spectral dependence for the HJT structure.

to 1100 nm (practically the entire visible and partly NIR part of the sun spectrum). Better shortwave response has been reported in hybrid structures with organic semiconductors in the frontal part of the device structure [16]. Therefore, it would be of interest to fabricate a tandem structure with top junction with organic semiconductors. An example of cross-section diagram for such a structure is presented in Figure  14.16b. The bottom junction is the reproduced HJT structure (see Figure  14.16a), on the top of which the hybrid junction is placed. The latter comprises a glass substrate, a transparent conductive layer (aluminum-doped zinc oxide, AZO), n-type a-Si:H, an intrinsic a-Si:H, p-type organic semiconductor PEDOT:PSS, and a second transparent conductive oxide (AZO). We could expect better current collection for short wavelengths, because frontal built-in electric field is determined by the (PEDOT:PSS)–(i-a-Si) interface. The current–voltage I(V) characteristics of these structures represented in Figure  14.17b are measured for the bottom HJT junction, the top hybrid junction, and tandem. The structure has not been optimized to achieve high current; therefore, Jsc is significantly less, mostly because the top junction works as an optical filter; however, both the junctions demonstrate their functions and the open-circuit voltage is equal to the sum of both junctions. Spectral characteristics of the tandem are shown in Figure  14.18b; one can see that the HJT OS tandem demonstrates better response in the range of λ = 300–450 nm. It should be noted also that fabrication of the tandem demonstrates compatibility of fabrication processes for crystalline silicon, PECVD materials, and organic semiconductors.

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14.5 Outlook In this chapter, we have briefly described and analyzed two classes of materials: PECVD and organic semicondcutors. Both are artificial materials with impressive possibilities for material engineering. However, they have different levels of both characterization (data volume, interpretation of the results, etc.) and understanding of physical processes determining device performance. We have also considered some examples of these materials in photovoltaic devices in different combinations including structures with crystalline silicon. One very important advantage of both PECVD and organic materials is that technologies of their fabrication are compatible with each other and both allow fabrication of device structures on crystalline semiconductors (e.g., on crystalline silicon). This paves the way for a great variety of hybrid device structures. At present, advantages of hybrid devices are difficult to predict but new territory in material science and related devices has definitely appeared for further exploration and commercialization.

Acknowledgment The authors greatly appreciate Dr. Y. Kudriavtsev (CINVESTV, Mexico) for many years of collaboration in application of advanced SIMS techniques to study non-crystalline materials, we would like to thank our PhD students Hiram Martinez (Electronics Department of INAOE) and Antonio J. Olivares-Vargas (Optics Department of INAOE) for their dedication to work with both PECVD and organic semiconductors for PV devices and permission to use their data; also, many thanks to engineer Adrian Itzmoyotl for his technical service during fabrication of materials and devices.

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PECVD and Organic Semiconductors in PV Device 549 29. J. Yang, A. Banerjee, and S. Guha, Triple junction amorphous silicon alloy solar cell with 14.6% initial and 13.0% stable conversion efficiencies. Appl. Phys. Letters, 70, 2975–2977, 1997. 30. M. A. Shah, A. V. Shah, H. Shade, M. Vanecek, J. Meier, E. Vallat’Sauvain, N. Wyrsch, U. Kroll, C. Droz, and J. Bailat, Thin film silicon solar cell technology. Prog-Photovolt : Res. Appl., 12, 113–142, 2004. 31. J. Kanicki and T. A. Skotheim, Handbook of Conducting Polymers, Vol. 1. Marcel Dekker, New York, 1985. 32. J. S. Moon, C. J. Takacs, Y. Sun, and A. J. Heeger, Spontaneous Formation of Bulk Heterojunction Nanostructures: Multiple Routes to Equivalent Morphologies. Nano Lett., 11, 3, 1036, 2011. 33. X. Yang, J. Loos, S. C. Veenstra, W. J. H. Verhees, M. M. Wienk, J. M. Kroon, M. A. J. Michels, and R. A. J. Janssen, Nanoscale Morphology of HighPerformance Polymer Solar Cells. Nano Lett., 5, 579, 2005. 34. J. Peet, J. Y. Kim, N. E. Coates, W. L. Ma, D. Moses, A. J. Heeger, and G. C. Bazan, Efficiency enhancement in low-bandgap polymer solar cells by processing with alkane dithiols. Nat. Mater., 6, 497, 2007. 35. W. Ma, C. Yang, X. Gong, K. Lee, and A. J. Heeger, Thermally Stable, Efficient Polymer Solar Cells with Nanoscale Control of the Interpenetrating Network Morphology. Adv. Funct. Mater., 15, 1617, 2005. 36. G. Li, V. Shrotriya, J. Huang, Y. Yao, T. Moriarty, K. Emery, and Y. Yang, High-efficiency solution processable polymer photovoltaic cells by selforganization of polymer blends. Nat. Mater., 4, 864, 2005. 37. J. K. Lee, W. L. Ma, C. J. Brabec, J. Yuen, J. S. Moon, J. Y. Kim, K. Lee, G. C. Bazan, and A. J. Heeger, Processing additives for improved efficiency from bulk heterojunction solar cells. J. Am. Chem. Soc., 130, 11, 3619, 2008. 38. X. Guo and T. J. Marks, Plastic solar cells with engineered interfaces. Proc. SPIE., 8622, 86220K, 2013. 39. H. Zeng, X. Zhu, Y. Liang, and X. Guo, Interfacial Layer Engineering for Performance Enhancement in Polymer Solar Cells. Polymers, 7, 333, 2015. 40. R. Steim, F. R. Kogler, and C. J. Brabec, Interface materials for organic solar cells. J. Mater. Chem., 20, 2499, 2020. 41. H. Choi, H.-B. Kim, S.-J. Ko, J. Y. Kim, and A. J. Heeger, An organic surface modifier to produce a high work function transparent electrode for high performance polymer solar cells. Adv. Mater., 27, 892, 2015. 42. J. Y. Kim, S. H. Kim, H. H. Lee, K. Lee, W. Ma, X. Gong, and A. J. Heeger, New Architecture for High-Efficiency Polymer Photovoltaic Cells Using SolutionBased Titanium Oxide as an Optical Spacer. Adv. Mater., 18, 572, 2006. 43. A. Hadipour, B. de Boer, J. Wildeman, F. B. Kooistra, J. C. Hummelen, M. G. R. Turbiez, M. M. Wienk, R. A. J. Janssen, and P. W. M. Blom, Solution-processed organic tandem solar cells. Adv. Funct. Mater., 16, 1897, 2016. 44. J. Y. Kim, K. Lee, N. E. Coates, D. Moses, T.-Q. Nguyen, M. Dante, and A. J. Heeger, Efficient tandem polymer solar cells fabricated by all-solution processing. Science, 317, 222, 2007.

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45. S. Sista, Z. Hong, M.-H. Park, Z. Xu, and Y. Yang, High-Efficiency Polymer Tandem Solar Cells with Three-Terminal Structure. Adv. Mater., 22, E77, 2010. 46. L. Dou, J. You, J. Yang, C.-C. Chen, Y. He, S. Murase, T. Moriarty, K. Emery, G. Li, and Y. Yang, Tandem polymer solar cells featuring a spectrally matched low-bandgap polymer. Nat. Photonics, 2012, 6, 180, 2012. 47. C.-C. Chen, W.-H. Chang, K. Yoshimura, K. Ohya, J. You, J. Gao, Z. Hong, and Y. Yang, An efficient triple-junction polymer solar cell having a power conversion efficiency exceeding 11%. Adv. Mater., 26, 5670, 2014. 48. M. M. Wienk, J. M. Kroon, W. J. H. Verhees, J. Knol, J. C. Hummelen, P. A. van Hal, and R. A. J. Janssen, Efficient methano[70]fullerene/MDMO-PPV bulk heterojunction photovoltaic cells. Angew. Chem. Int. Ed., 42, 3371, 2003. 49. C. Winder and N. S. Sariciftci, Low bandgap polymers for photon harvesting in bulk heterojunction solar cells. J. Mater. Chem., 14, 1077, 2004. 50. R. Kroon, M. Lenes, J. C. Hummelen, P. W. M. Blom, and B. de Boer, Small Bandgap Polymers for Organic Solar Cells (Polymer Material Development in the Last 5 Years). Polym. Rev., 48, 531, 2008. 51. E. Bundgaard and F. C. Krebs, Low band gap polymers for organic photovoltaics. Sol. Energy Mater. Sol. Cells, 91, 954, 2007. 52. Z. Zhu, D. Waller, R. Gaudiana, M. Morana, D. Mühlbacher, M. Scharber, and C. Brabec, Panchromatic Conjugated Polymers Containing Alternating Donor/Acceptor Units for Photovoltaic Applications. Macromolecules, 40, 1981, 2007. 53. A. Facchetti, Mater. Polymer donor–polymer acceptor (all-polymer) solar cells. Materials Today, 16, 123, 2013. 54. J. Zhao, Y. Li, G. Yang, K. Jiang, H. Lin, H. Ade, W. Ma, and H. Yan, Efficient organic solar cells processed from hydrocarbon solvents. Nat. Energy, 1, 15027, 2016. 55. L. Dou, J. You, C.-C. Chen, G. Li, and Y. Yang, Plastic Solar Cells: Breaking the 10% Commercialization Barrier. Proc. SPIE, 8477, 847702, 2012. 56. M. Naguchi, A. Yano, S. Tohoda, K. Matsuyama, Y. Nakamura, T. Nishiwaki, K. Fujita, and E. Maruyama, 24.7% Record efficiency HIT solar cell on thin silicon wafer. IEEE J. Photovoltaics, 4, 1, 96–99, 2014. 57. K. Yamamoto, K. Yoshikawa, W. Yoshida, T. Irie, H. Kawasaki, K. Konishi, T. Asatani, M. Kanematsu, R. Mishima, K. Nankano, H. Uzu, and D. Adashi, High efficiency a-Si/c/Si heterojunction solar cells, Abstract book, ICANS-2, Seoul, S. Korea, p. 92, 2017.

Part 5 NANO-PHOTOVOLTAICS

Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (551–609) © 2019 Scrivener Publishing LLC

15 Use of Carbon Nanotubes (CNTs) in Third-Generation Solar Cells LePing Yu,1 Munkhbayar Batmunkh,1 Cameron Shearer2 and Joseph G. Shapter1,3* 1

Centre for Nanoscale Science & Technology (CNST), Flinders University, Australia 2 Department of Chemistry, The University of Adelaide, Australia 3 Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Queensland, Australia

Abstract

In the future, energy production will have to be cheap, readily accessible and deployable in a vast array of locations and circumstances, while minimizing any influence on the greenhouse effect on climate. Of all the options available, photovoltaics offer the highest probability of delivering a meaningful and sustainable change in the way society produces its energy. Third-generation photovoltaics offer real opportunities to deliver energy to broad sections of society, which will ultimately provide energy security. This technology offers opportunities for cheap production, flexibility (and hence a range of deployment opportunities) and tunability of light absorption. Many efforts to improve these photovoltaic systems have involved the use of carbon nanotubes (CNTs). This chapter will primarily focus on those efforts. Carbon nanotubes have been used in virtually every component of the devices to help charge conduction, improve electrode flexibility, and, in some cases, as active light-absorbing materials. Keywords: Solar cells, carbon nanotubes, CNTs, dye-sensitized solar cells, DSSCs, photovoltaic devices, CNT–Si photovoltaics, nanotube–silicon heterojunctions, NSH solar cells

*Corresponding author: [email protected] Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (553–609) © 2019 Scrivener Publishing LLC

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15.1 Introduction 15.1.1

Energy Issues and Potential Solutions

The world’s energy consumption has increased dramatically in recent decades due to the rapidly growing global population, improving standard of living and development of modern technologies. The U. S. Department of Energy predicts that the world’s energy demands will double by 2050 and triple by 2100 [1]. The current world energy production of ~16.4 TW is principally met by burning fossil fuels [2]. Environment damage due to the fuel burning processes has become a serious problem. This has the potential for disastrous consequences and solutions need to be pursued with urgency. Considerable developments have been made in this respect, including energy technologies based on wind power [3], biofuels [4], solar cells [5], and fuel cells [6]. Only solar energy is present in all parts of the world; thus, harnessing it is the only really worldwide solution to the global energy challenge. One option is to use this energy in solar thermal applications using large mirrors to concentrate the solar energy onto a material such as molten salts that are capable of storing significant energy. While relatively simple, these solar thermal installations are hindered by the need to convert that thermal energy stored in the molten salts into electricity using a steam turbine and the requirements of a steady water supply.

15.1.2

Categories of Photovoltaic Devices and Their Development

Another solar energy option is photovoltaic (PV) cells, which convert sunlight directly into electricity. PV cells are generally classified into three main generations. In brief: (1) the first-generation solar cells based on crystalline (poly + single) silicon, which make up ~90% of the commercial production at present, are estimated to deliver power with approximately 20% efficiency, but they suffer from high manufacturing, installation, and material costs; (2) the second-generation cells (referred as a thin-film technology) are more cost effective than the traditional PV cells, but their lower performance is the main concern and still the subject of considerable research [7]; and (3) the third-generation PV cells, which include, for example, organic solar cells (OPVs), dye-sensitized solar cells (DSSCs), and perovskite solar cells (PSCs) are designed to further lower the costs achieved for second-generation cells potentially to less than US$ 0.1/kWh, by maintaining the economic and environmental aspects while increasing

Use of CNTs in Third-Generation Solar Cells 555 the performance [8, 9]. This drive to lower energy costs has led to a keen interest in finding solutions to improve efficiencies in all solar cell architectures. Additionally, the latest generation of cells offers the potential to be very cheap, flexible, semitransparent and still productive in low light conditions. Despite the first deliberate fabrication of a photovoltaic device by Fritts in 1883 [10], it was not until 1954, when Chapin and co-workers at Bell Labs developed a 6% efficient silicon p–n junction solar cell [11], that the photovoltaic industry was born. Initially, photovoltaics were only utilized in specialist applications where conventional power sources were unavailable or undesirable such as satellites and high-end electronic devices. In 1985, with the development of the first ~20% efficient solar cells such as by Green and co-workers [12], the field of photovoltaics established itself as a serious energy resource capable of supplying domestic demand. These devices were so-called first-generation solar cells. The high conversion efficiency (up to ~25% in the lab, up to ~22% for commercial modules), stability of high-purity silicon, excellent charge transport properties, and the mature processing technologies have led to silicon dominating the photovoltaic market [13–15]. However, the manufacturing process of highefficiency silicon solar cells suffers from low throughput and thus these solar cells are costly, preventing silicon PV from contributing significantly as a source in the world’s energy. In order to solve some of these issues, thin-film solar cells, secondgeneration solar cells, such as CdTe, CuInxGa1−x S(Se)2 (CIGS), Cu2ZnSnS4 (CZTS), and thin-film silicon have become the subject of intense research [14–16]. The heavy metal Cd is toxic and the metal In is expensive, thus limiting the development of CdTe- and CIGS-based solar cells, respectively [17, 18]. Low-cost materials such as CZTS were introduced but are still underdeveloped [19]. For thin-film silicon solar cell technology, the low efficiency and instability from the Staebler–Wronski effect may restrict its long-term usage in solar cells [15]. The trade-off between the cost and the performance of these solar cells is still a great barrier to wide-scale commercial application. Therefore, it is essential to search for alternative materials to be applied in various components of the many types of solar cells now commercially available or under development in research labs around the world. Carbon nanotubes are an attractive option because of their exceptional conductivity in a light weight form that can be incorporated into many materials at low loadings and still significantly change the material properties to improve the required performance. This chapter will thus focus on third-generation solar cells and the application of carbon nanotubes (CNTs) to improve their performance.

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These cells have the potential to be cheap, efficient, flexible and deployable in virtually any location or situation. In particular, dye-sensitized solar cells (DSSCs) and the related perovskite cells (PSCs) as well as carbon nanotube– silicon heterojunction solar cells (CNT–Si) [which are also referred as nanotube–silicon heterojunction (NSH) solar cells] will be discussed.

15.2 Carbon Nanotubes (CNTs) Ever since Iijima’s seminal report, CNTs have attracted considerable attention from the scientific as well as industrial communities due to their remarkable physical and optoelectronic properties [20, 21]. Much of this effort has been in the development of solar cells due to the CNT’s unique structure, excellent conductivity, good transparency, high catalytic activity, low cost and abundance. There are many excellent reviews of CNTs in the literature and hence a summary of their properties, production and so on will not be provided in this chapter [22–24].

15.3 Transparent Conducting Electrodes (TCEs) Most solar cells, and many other electronic devices, require an electrode that is both transparent and highly conductive as an integral part of the structure. Because of the excellent conductivity and high degree of transparency of bulk CNT materials, they have been employed in a variety of approaches to build these electrodes, and this work is summarized in the following section before specific solar cell architectures are discussed. TCEs are used in both the photoelectrode and counter electrode (CE) of DSSCs and as an integral part of the CNT–Si junction in NSH solar cells.

15.3.1

ITO and FTO

TCEs are a necessary component in a wide range of modern optoelectronic devices such as organic light-emitting diodes (OLEDs), e-paper, touch screens, liquid-crystal displays (LCDs), and thin-film PV cells, all of which are growing rapidly in popularity [25–27]. Currently, the two most common materials used to meet the transparency and conductivity requirements of the electrodes are indium tin oxide (ITO) (preferred) and fluorine tin oxide (FTO) (less effective but cheaper). An ideal TCE should possess a very low sheet resistance (Rsheet) with high transmittance and be composed

Use of CNTs in Third-Generation Solar Cells 557 of cheap and abundant materials. ITO and FTO are the most widely used TCEs due to their high conductivity and optical transparency but there are a number of issues including cost and a lack of flexibility. These shortcomings of the current TCEs have inspired researchers to seek other easily processable and sustainable electrode materials that could exhibit comparable sheet resistance at high transmittance while still being readily available, cheap, highly flexible, and lightweight. In the past few years, a number of alternative materials, including conductive polymers [28], metal grids [29], metallic nanowires [30], graphene [31], and CNTs [32], have been developed to replace ITO and FTO. For a broad perspective of the field, there are several comprehensive reviews of TCEs available [33–38]. Among the aforementioned alternative materials, CNTs are considered a promising replacement for conventional transparent conducting oxides (TCOs) because they exhibit properties such as low resistivity, a high specular transmittance in very broad spectral range from ultraviolet (UV) to the mid-infrared (MIR), superior flexibility and the electrodes can be made using simple fabrication techniques [39–47]. Carbon nanotubes also form sheets, often called buckypaper, with a mesh-like three-dimensional topology with morphology similar to a bird’s nest, which allows charge collection from a large surface area, not just a planar interface like from usual TCO electrodes. The high thermal conductivities that provide heat dissipation combined with stability during exposure to light make CNTs an ideal electrode material [48]. CNTs have a remarkably high level of electronic mobility and work function similar to that of the TCOs, which makes them an ideal candidate for use in the hole extraction layer (or hole transporting layer) of PV cells. Hence, CNTs are generally, but certainly not exclusively, used for hole transport [49, 50].

15.3.2

CNTs for TCEs

Typically, the preparation methods of transparent conductive CNT films can be separated into dry processes and wet processes depending on the sample condition [51]. In the dry processing method, CNT films can be prepared by the following two routes: (i) depositing a CNT aerosol made in a chemical vapor deposition (CVD) reactor to form a thin film and transferring onto the substrate using dry-transfer technique [52–55] and (ii) drawing from a superaligned CNTs forest [56–58]. Due to the excellent performance of these TCFs, transparent conductive CNT electrodes produced by the dry processing methods have been used in a variety of applications, including the transparent electrode in Si-CNT solar cells [59]. Though the dry processed CNT films possess good conductivity, they

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have some disadvantages in film production such as complicated experimental control, requirement of high temperature, limited substrates, and high cost. Preparing transparent conductive CNT films using the wet processing method is of great interest because the solution processable techniques are simple, compatible with low-temperature processes, applicable for various substrates as well as cost-effective. Since the preparation method of CNTbased TCFs using filtration-transfer and dip-coating techniques was first reported by Wu et al. [32] and Saran et al. [60] in 2004, several leading research groups and companies have put considerable effort into this area. Many solution processing methods such as vacuum filtration followed by transfer printing [32, 46, 61], dip coating [60, 62], spin coating [42, 43], spray coating [43, 44, 61, 63, 64], electrophoretic deposition (EPD) [65, 66], printing (rod coating, inkjet printing, and slot coating) [40, 67, 68], and, recently, brush painting [69] have been developed to fabricate CNT-based TCFs. Of course, all of these methods have advantages and disadvantages. Comprehensive reviews of the solution processing techniques for the fabrication of CNT-TCFs can be found elsewhere [35, 36, 70–72]. The resistance of a CNT network is related to the resistance of each individual CNT and the contact resistance between individual CNTs in the network. Chemical doping can improve the conductivity of both individual CNT and the contacts by shifting the Fermi level to increase the density of states (DOS) of charge carriers (holes or electrons determined by the type of the dopants, either p-type or n-type). In addition, it has been shown that the shift of the Fermi level can reduce the Schottky barrier height between metallic and semiconducting SWCNTs [73]. Therefore, doping reduces the Rsheet of CNT TCFs by improving the conductance of each individual CNT and enhancing charge percolation within the network. Theoretically, the Fermi level of semiconducting species is normally located at an equipotential position between the valence and conduction band, and therefore both p-type and n-type doping with electronwithdrawing and -donating effects can be achieved by different dopants. Practically, p-type doping is more widely studied since the oxygen in the air has a slight p-doping effect on CNTs under ambient conditions [74]. Whether a dopant introduces p- or n-type doping is dependent on either the electronegativity (when they are atomic dopants) or the electrochemical potential (when they are molecules and inorganic materials) [73]. There are many different types of dopants for p-doping, such as NO2 [75], H2SO4 [76, 77], H2SO4 [76], HNO3 [63, 78–86], SOCl2 [46, 76, 78, 80, 87], the combination of HNO3 and SOCl2 [88], SOBr2 [87], HCl [64], Br2 [89], Nafion [79], tetrafluorotetracyano-p-quinodimethane (F4TCNQ)

Use of CNTs in Third-Generation Solar Cells 559 [90], MoOx [91], oleum [40], iodine [76], bromine [92], triethyloxonium hexachloroantimonate (OA) [93], and bis-(trifluromethanesulfonyl)imide (TFSI) [94]. The doping process is normally performed by immersing the CNT TCF into a concentrated solution of dopant for a period of time (ranging from 10 s to a few hours) or exposing the films to an atmosphere when gaseous dopants are applied. Table 15.1 shows the optoelectronic properties of CNT films before and after chemical doping (p-type). Among these dopants, H2SO4 doping seems to have the highest reduction in resistance by percentage (5800%), but this value is probably overexaggerated since the starting resistance is so high. TFSI is particularly promising, giving a reduction in Rsheet by 15 times without affecting the transmittance of the film [94]. Recently, a comprehensive study about doping mechanisms was published by Puchades et al. [95]. In their study, more than 40 types of dopants were used to dope SWCNT films and the change in conductivity was used to characterize the doping effect. They noticed that the amount of enhanced electrical conductivity due to doping is dependent on the relative potential difference between the redox potential of the chemical dopant and the SWCNT electronic transitions (in detail, the lower the redox potential, the worse the dopant). Based on this idea, one may deduce that Table 15.1 Influence of the chemical dopants (p-type) on the optoelectronic properties of the CNT films before and after doping. Without doping

With doping

T

Rsheet (Ω sq )

T

Rsheet (Ω sq−1)

93.1%

50,500

93.3%

1010

83%

600

83%

48.5

79.6%

2800

79.6%

330

SOCl2 [46]

87%

380

87%

160

HNO3 + SOCl2 [80]

80%

300

80%

105

SOBr2 [87]

77.6%

184

77.6%

56

MoOx [91]

85%

1000

85%

100

Oleum [40]

90%

800

90%

300

OA [93]

80%

200

80%

90

TFSI [94]

85%

600

85%

38.4

Dopants H2SO4 [76, 77] HNO3 [84] HCl [64]

−1

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the effect of the dopants might be different with different chiral species of the SWCNTs. Then, it is possible to finely control the conductivity by intentionally choosing a chemical dopant with the required redox potential in a SWCNT film of mixed chiralities. Other mechanisms of the most prevalent chemical dopants of CNTs are listed in Table 15.2 with simple explanations. In most cases, the transmittance of the CNT films does not change significantly after doping [88]. Through the visible light wavelength range, T is maintained at the same level after doping while there can be changes around 1.5 eV (at about 830 nm) with certain types of CNTs or dopants, such as HNO3 and SOCl2. In most cases, the Rsheet of films decreases significantly after doping. Typically, in p-doping process, there is a downshift of the Fermi level into the valence band by electron-withdrawing from the CNT to the dopants (corresponding to the increase of the work function of the CNT from 4.5 to 4.8 eV to more than 5 eV) [65]. Since there are more charge carriers available, the charge percolation is reinforced with a resulting lower Rsheet. In contrast, n-type dopants, such as nitrogen, raise the Fermi level by ~1.21 eV in the DOS, while the nitrogen states are just above the Fermi level [98]. Some studies show that the contact resistance from one individual CNT to another is decreased during acid treatments and the conductivity of the CNT-based network is improved because of the removal of the insulating dispersing agents, including SDS, during the preparation of the suspension [63, 82]. Furthermore, some intercalated dopants can act as bridges, which electrically connect individual CNTs. In detail, the trigonal channels are filled with closely packed ionic chains by alkali metals, which act as the dopants in most cases (such as potassium) [99]. Therefore, charge carriers move along outside the tube wall with the overlapping of the K 4s related hybridized bands with the Fermi level [100]. However, one of the largest concerns is that the chemical doping effect by most of these dopants are not long-lasting since these dopant molecules are only weakly adsorbed on the shells of CNT and they have the potential to desorb [80]. The undoped film has much better stability than that of the doped counterpart, though their Rsheet is higher than that of the doped sample. This poor stability will be a practical issue for commercial purposes. It has been shown that a PEDOT:PSS capping layer is able to suppress the degradation of the film properties effectively [80]. Doping ClO4− ions on the wall of SWCNTs by an electrochemical method in LiClO4/acetonitrile solution can achieve a similar protection purpose, and as a result, the Rsheet of the doped film was stabilized for more than 20 days under atmosphere conditions [101]. The incorporation of MoOx

Use of CNTs in Third-Generation Solar Cells 561 Table 15.2 Mechanisms of some prevalent dopants for p-doping CNT. Chemical dopants

Mechanism and effect

H2SO4

Intercalated SO3/SO42− attracts the electrons from CNT and lowers the Fermi level (by 0.5 eV) with the creation of more holes in valence band [96]. It helps to remove some amphipathic/ polymeric dispersant and thus reconstruct the network to reduce the contact junction between CNTs with tighter contacts.

HNO3

Physisorbed HNO3/NO2 molecules on the surface and bundles of SWCNTs enable the transfer of electrons from CNT to NO3− groups, which shifts the Fermi level by 0.2 eV [96]. An enhanced contact between individual CNTs is achieved by removal of impurities, including carbon black, metal catalysts, organic solvents (NMP etc.), and others adsorbed on the walls of CNTs.

HCl

HCl doping is similar to that of H2SO4 and HNO3 via intercalation. It can shift the Fermi level by 0.1 eV [96]. The desorption of HCl is faster than that of H2SO4 and HNO3 [96].

SOCl2

The hole doping effect is due to the electronwithdrawing nature of the decomposition of SOCl2 (2SOCl2 + 4e− → S + SO2 + 4Cl−). The conduction mechanism changes from thermionic emission to tunneling through the barriers.

SOBr2

SOBr2 is larger than SOCl2. Br− anions are chemically bonded to the side walls of CNTs and interact with metallic SWCNT more easily than the semiconducting species. The oxidation of Br− anion occurs during the process, which is the driving force of the electron transfer. (Continued)

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Table 15.2 Mechanisms of some prevalent dopants for p-doping CNT. (Continued) Chemical dopants

Mechanism and effect It may cause the formation of -C-S-C- bond with the possibility of cross-linking SWCNTs [97]. The formation of new transport paths via S atoms between CNT is possible.

MoOx

Electron transfer from CNT to MoO3 via the following interaction: MoO3 + CNT → CNT + + MoOy − [91]. The stability of this doping effect can be enhanced by thermal activation.

Triethyloxonium hexachloroantimonate (OA)

OA is an one-electron oxidant. P-type doping is achieved via the following scheme with the formation of a chargetransfer complex: SWCNT + OA → SWCNT +[Sb(Cl)6]− + C2H5Cl + SbCl3 + (CcH5)2O [93].

Bis(trifluromethanesulfonyl) imide (TFSI)

Different acidic derivatives of TFSI dopants can adsorb onto defects or the sidewalls of CNTs depending on their chemical structure. They can accept electrons from CNTs and shift the Fermi level down. Among all three types of derivatives, bis(trifluoromethanesulfonyl)amine is the most effective dopant [94].

with CNTs to form a composite is also capable of improving the stability of Rsheet. In detail, the activation of the charge transfer from CNT to MoOx is realized by annealing at high temperature (at 450°C) and the prepared CNT films show great stability under various conditions [91]. The incorporation of MoOx produces a film with much better stability in terms of Rsheet when compared to conventional chemical doping approaches, such as (2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane) (F4-TCNQ), especially when heated in ambient conditions at high temperature (300°C). In air, the upper limit of the stability under heating condition of Rsheet for MoOx incorporated CNT films is at ~390°C, which is due to the oxidization of CNTs. The non-volatility below 390°C contributes to the excellent

Use of CNTs in Third-Generation Solar Cells 563 thermal stability. In short, it will be essential to solve the stability concern of the doped CNT TCFs before commercial applications in industry.

15.4 Dye-Sensitized Solar Cells (DSSCs) DSSCs have gained much attention not only because of the simple fabrication method, low manufacturing cost, and eco-friendliness, but also due to their relatively high efficiency (13% [102] to 14% [103] for DSSCs) compared to OPVs (~12% [104]), although it should be pointed out that these efficiencies are continuously increasing. Since the breakthrough work on DSSCs published in the early 1990s [105], there has been a great deal of research to maximize the power conversion efficiency (PCE) of DSSCs but progress beyond 12% has been very slow [106, 107]. Several companies (namely, Solaronix from Switzerland, GreatCell Solar from Australia, and Dyenamo from Sweden) have been established to contribute to DSSC commercialization. Moreover, in 2009, G24-Power (the world leader in the design and manufacture of DSSCs) introduced the world’s first commercial production of DSSCs using a roll-to-roll manufacturing process [108]. The basic design of a standard DSSC is shown in Figure 15.1a. Briefly, sunlight passes through a transparent electrode to excite dye molecules adsorbed onto semiconducting nanoparticles (generally TiO2). The generated photoelectrons are extracted by the semiconducting layer and leave the cell through the transparent conducting electrode. The circuit is completed by an electrolyte (typically I−/I3−), which replaces the electron on the dye and then in turn is reduced at the counter electrode, which is typically made of Pt. CNTs have been used in each component of the DSSC design. They have been used as the conducting films in either the counter electrode or the photoanode. CNTs have also been used to make standalone photoactive elements as well as in hybrids to make better-conducting photoanodes or with catalysts to make counter electrodes. Indeed, the best efficiency to date (>10%) of carbon-based DSSCs (among sole materials or non-hybrids) was obtained by a vertically aligned CNTs (VACNTs) counter-electrode-based cell [109]. On the other hand, among carbonaceous material-incorporated TiO2 photoelectrode-based cells, DSSCs fabricated with a CNTs/TiO2 electrode is the champion cell.

15.4.1

CNTs-TCFs for DSSCs

Even though considerable advancements have been made in CNTs-TCFs, reports on the application of these films as the conducting electrodes in

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Light

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Figure 15.1 (a) Schematic of a typical DSSC structure. Reproduced from Ref. [110] with permission from Hindawi Publishing. (b) J–V characteristics of the best-performing DSSCs using different CEs. (a) Carbon nanotube aerogel (CAN) CE, (b) CNA-3.75 wt% Pt CE, (c) conventional Pt CE, and (d) MWCNT CE. Reproduced from Ref. [111] with permission from The Royal Society of Chemistry. (c) TEM image (scale bar: 100 nm) (inset shows the HRTEM and SAED pattern of the CoSx) of heteroelectrocatalyst [cobalt sulfide (CoSx)] decorated nitrogen and sulfur co-doped carbon nanotubes. Reproduced from Ref. [112].

DSSCs are rare. There are very few reports available on the application of CNTs as the conducting component of the counter electrode of DSSCs [113–116]. Aitola et al. [113] synthesized single-walled carbon nanotubes (SWCNTs) using an aerosol CVD method and deposited a film on a polyethylene terephthalate (PET) plastic substrate. The resulting CNT film with an Rsheet of 60 Ω sq−1 was used as a counter electrode (TCO-free and Pt-free) in a DSSC. However, this DSSC fabricated with CNT counter electrode had energy conversion efficiency at a light intensity of 100 mW cm−2 of only 0.74%, which was far less than that (4.4%) obtained with the reference cell. Tantang et al. [116] were able to improve the performance of Pt-free and TCO-free counter-electrode-based DSSCs by using nitrogendoped (N-doped) CNTs. Doped CNT films were prepared from solution processable N-doped CNTs samples using an air-spray technique. The N-doping on CNTs forms one free electron, which can easily be supplied to the reduction of electrolyte and thus improved the performance of

Use of CNTs in Third-Generation Solar Cells 565 DSSCs. After N doping of the CNTs, the efficiency of DSSC was improved to 1.53%, which was better than that of the undoped CNT counter electrode reported by Aitola et al. [113] but still ~2.5-fold lower than the reference Pt-based device. Furthermore, Liu et al. [114] used CNTs as an alternative to TCO material in the Pt-based counter electrode of DSSCs. The dispersant (poly(oxyethylene)-backboned polyimide) was vital for preparing a good dispersion of the de-bundled CNTs and platinum salts in liquid. Highly dispersed Pt/CNTs hybrids were drop coated on the substrates to fabricate the FTO-free counter electrode. The efficiency of the DSSC fabricated with the Pt/CNT counter electrode was as high as 6.96%. This performance was very close to that (7.02%) of the cell fabricated with a conventional Pt/FTO counter electrode and is the highest efficiency yet reported for the TCO-free counter-electrode-based DSSCs. To our knowledge, only three papers have been published using CNTs as transparent and conductive component of the substrate for DSSC photoelectrodes [117–119]. Among them, the authors of two papers [117, 118] have used ZnO nanoparticles, while the other one [119] used TiO2 nanoparticles as a semiconducting layer. Wei et al. [118] were first to report TCO-free photoelectrode in DSSCs. They fabricated a flexible DSSC composed of CNTs/PET as the TCE, ZnO nanoparticles as dye adsorbing semiconductor, black dye, iodide electrolyte, and Au as catalyst. Due to the suitable energy levels of the materials used in this study, a high PCE was expected. The CNTs-TCF fabricated in this study showed an Rsheet of 250 Ω sq−1 at 65% transparency, and its cell was able to deliver a shortcircuit current (Jsc) of only 2.23 mA cm−2 and an open-circuit voltage (Voc) of only 0.23 V. This poor performance was due to CNTs promoting the backward reaction due to iodine reduction, which limited the continuous electron transfer. Recently, Du et al. [117] made further improvement to this DSSC and obtained a PCE of 2.5% by applying electrodeposited CNT film with a relatively high Rsheet (470 Ω sq−1) at high transparency. On the other hand, Kyaw et al. [119] were able to reduce the charge recombination of CNTs with electrolyte by using a TiOx layer. In their study, the DSSC was fabricated with CNT film–TiO2 semiconducting layer–TiOx blocking layer-based photoelectrode and delivered an efficiency of 1.8%.

15.4.2 15.4.2.1

Semiconducting Layers Nanostructured TiO2 Materials

The heart of the DSSCs is the semiconducting electron transport layer that collects and transfers the photo-generated electrons from the dye

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molecules and transfers them to the TCE, which is connected to the external circuit. A mesoporous TiO2 structure made with 20-nm-diameter nanoparticles is used as the conventional semiconductor in the photoelectrode of DSSCs [105]. Many alternative oxide semiconductors such as ZnO [120, 121], SnO2 [122, 123], Nb2O3 [124], SrTiO3 [125], and BaSnO3 [126] have been studied widely as the electron transport layer in DSSCs owing to their suitable energy levels and high conductivity. A number of reviews of these materials for DSSCs have been published [127–130]. However, none of these materials have outperformed the conventional TiO2 nanostructures because of their low surface area-to-volume ratio compared to the TiO2 nanoparticles [130–132]. Indeed, TiO2 nanoparticles still remain the material of choice for the DSSC photoelectrode. Unfortunately, nanostructured semiconducting materials used in the photoelectrodes have three main disadvantages: (i) significant recombination of the injected electrons with both the dye and oxidized species of the electrolyte, (ii) slow electron transport caused by the large number of grain boundaries, and (iii) ineffective light harvesting. In order to solve these drawbacks, several strategies have been developed, and they are briefly discussed in one of our previous reviews [133].

15.4.2.2

Semiconducting Layers with CNTs

The use of CNTs in the semiconducting layer of DSSC was first reported by Jang et al. [134] who incorporated acid-functionalized SWCNTs in nanocrystalline TiO2 film. These authors observed a good enhancement (25%) in the Jsc and a slight improvement in the Voc after the incorporation of SWCNTs in the unmodified (TiO2-only based) film. This improvement was believed to be due to the fact that CNTs significantly reduce the resistance of the films and facilitate the electron transport within the cell. Therefore, during the electron transport through the TiO2 film, the photo-generated electrons can directly be transferred to the TCO without having to cross numerous grain boundaries. Moreover, the authors stated that the light scattering ability of the TiO2 film was enhanced by adding SWCNTs and thereby improved the cell performance. However, the DSSC fabricated by these authors showed Jsc and Voc of only ~2.3 mA cm−2 and ~0.44 V, respectively. Although the performance of DSSC fabricated in this study was very low, this work has inspired many studies in this area [135–138]. By incorporating SWCNTs, the amount of adsorbed dye molecules into the film fabricated in Jang et al. [134] increased by up to only 2%, which is considered to be negligible (no effect) for the cell performance. Several authors have seen a similar result and concluded that no significant changes

Use of CNTs in Third-Generation Solar Cells 567 in the dye loading of the films can be observed by adding CNTs structures [137, 139–157]. These authors argued that the performance improvement achieved by adding CNTs does not result from an increased amount of adsorbed dye molecules and the improved performance must be due to the improved electron transport and enhanced light scattering efficiency. On the other hand, Bakhshayesh et al. [141] recently reported that the amount of adsorbed dye onto the film decreased when CNTs were added, whereas some others [143, 144, 146] claimed that the dye adsorption of the nanocrystalline TiO2 film improved with the presence of CNT material. For instance, Zhang et al. [143] compared the dye loading of three different photoelectrode films (namely, TiO2-only, acid-functionalized CNTs, and O2-plasma-treated CNTs). The result revealed that both acid-treated and O2-plasma-treated CNT-incorporated TiO2 films adsorbed a higher amount of dye molecules than the pure TiO2-based films. Because of the improved dye loading, these authors achieved a DSSC efficiency improvement (compared to the efficiency of TiO2-only based cell) of 28% and 75% by acid-treated CNTs/TiO2 and O2-plasma-treated CNTs/TiO2 films, respectively. They suggested that the improvement in the dye adsorption of films is due to the fact that the high surface area-to-volume ratio of CNTs provides more active sites that enable adsorption of more dye. If this is the reason for greater dye loading, the adsorption of dye molecules should be improved in all studies that used CNTs materials. Based on the available literature, we summarize that the adsorption mechanism of dye into CNTincorporated TiO2 films cannot be explained by the high surface area-tovolume ratio of CNTs. It could be hypothesized that the dye adsorption of the films can be improved after incorporating only functionalized or chemically treated CNTs in TiO2 films because the functional groups generated on CNTs would be capable of increasing adsorption of dye molecules through hydrogen bonding to the CNT functional groups [145]. In contrast, when non-functionalized CNTs were added into the TiO2 films, the dye loading is reduced as compared to the TiO2-only film. This is associated with the absence of the CNT active sites for dye adsorption. In addition to this hypothesis, another possibility is that dye molecules can be adsorbed on CNTs by strong π–π interaction [147]. If our explanation is correct, highly functionalized CNTs may result in higher amount of dye adsorption. However, this may be offset by the fact that functionalization is well known in general to lower conductivity. Although the incorporation of CNTs significantly increases the electron transport within the film, too high a concentration of CNTs decreases the performance of DSSCs. Therefore, it is necessary to find an optimum content of CNTs for high-performance cells. Lee et al. [148] incorporated

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various CNT concentrations (0–0.5 wt%) in nanocrystalline TiO2 films and compared the cell performance. The result showed that the highest PV efficiency (5.02%) of DSSC was achieved by using a 0.1 wt% CNTs/TiO2 photoelectrode-based cell. Furthermore, Yen et al. [150] also compared the influence of different concentrations of CNTs on the TiO2-film-based DSSCs. In their work, the best DSSC with an energy conversion efficiency of 4.62% was obtained by incorporating 0.3 wt% CNTs in the TiO2 film. This optimized efficiency was significantly higher than that (2.87%) recorded for a typical cell. The optimized concentration of CNTs in several other studies was also within this range (0.1–0.3 wt%) [137, 151, 156]. Very high energy conversion efficiency (10.29%) was recorded for the CNTs/TiO2 photoelectrode-based DSSC fabricated by Sawatsuk et al. [149] while their benchmark cell with TiO2-only photoelectrode achieved a 6.31% efficiency. In this CNT/TiO2 composite film, the concentration of CNTs was optimized at 0.025 wt%. Furthermore, several authors have made a similar observation on this optimized value of CNTs content and suggested that a concentration range between 0.01 and 0.03 wt% CNTs in TiO2 films is suitable to achieve high-performance DSSCs [141, 154, 155]. It is surprising that this optimized CNTs concentration is an order of magnitude smaller than that found in some other work (0.1–0.3 wt%) [137, 151, 156]. After a careful examination of the experimental method associated with each work, we once again attribute this difference in the optimized CNT content to the functionalization of the CNTs. It seems that the optimal concentration of the functionalized CNTs ranges from 0.1 to 0.3 wt%, while that of the non-functionalized CNTs is between 0.01 and 0.03 wt%. Indeed, the authors of all these studies have seen dramatic decreases in the photocurrent and efficiency of DSSCs when the concentration of CNTs exceeds the optimized value. In these studies, this phenomenon was believed to be due to the light-harvesting competition that affects the light absorption of the dye sensitizers. Chen et al. [152] recently argued that the explanation, attributed to the competition between light harvesting with dye, is an incomplete elucidation and is unsatisfactory. In their work, several DSSCs were fabricated with functionalized CNTs/TiO2 photoelectrodes with varying CNT concentrations (0–0.35 wt%) and have been studied to explain the role of CNTs on the PV characteristics. As a result, the DSSC assembled with 0.172 wt% CNTs/TiO2 photoelectrode exhibited the highest PV efficiency of 5.15%, which was 18.6% (relative) higher than the efficiency obtained by the benchmark cell. However, this high efficiency (5.15%) declined when the concentration of CNTs was further increased. These authors attributed their findings to (i) the effect of Schottky barrier height on the electron transport through the CNTs–TiO2

Use of CNTs in Third-Generation Solar Cells 569 network and (ii) electron leakage via the naked CNTs. Though CNTs can facilitate the electron transport, the performance of DSSCs fabricated with CNTs will decrease when too high a concentration is used because the catalytic activity of CNTs causes significant charge recombination at the interface of CNT containing photoelectrode and liquid electrolyte. It is well known that carbonaceous materials including CNTs possess excellent catalytic activity for the reduction of the electrolyte [158]. However, the application of CNTs in the photoelectrode brings undesirable loss of photo-generated electrons by reducing I3– to I– because the CNTs in the composite cannot be fully covered by the TiO2 particles. To our knowledge, Dang et al. [153] were first to report using s-SWCNTs in TiO2 films and studied the PV characteristics of their DSSC devices. In their work, s-SWCNTs/TiO2 nanocrystal core-shell nanocomposites were synthesized with the support of a genetically engineered virus (called M13) as a template. By using this superior photoelectrode, these authors achieved an energy conversion efficiency of 10.6%. This result is the highest efficiency reported to date of carbonaceous material-incorporated TiO2-filmbased DSSCs. Moreover, they also explored the effect of metallic single wall CNTs (m-SWCNTs) added TiO2 films on the DSSC performance. Dang et al. [153] concluded that the s-SWCNTs can significantly improve the power conversion efficiency of DSSCs, whereas the m-SWCNTs decrease the performance of typical TiO2 photoelectrode-based cells. Furthermore, at least two other studies have used s-SWCNTs in TiO2 photoelectrodes of DSSCs and made a similar observation [139, 157]. The reason for this interesting phenomenon was explained by these authors as follows: s–SWCNTs increased the electron diffusion length, which leads to improved electron collection and resulted in an improved cell performance. The s-SWCNTs have a certain bandgap energy that can be adjusted by the several parameters including a diameter of nanotubes. Therefore, s-SWCNTs collect the electrons from the conduction band of TiO2 and transfer them quickly to the external circuit without significant recombination or back transfer. Contrarily, m-SWCNTs have no bandgap. So, though the m-SWCNTs can transport the electrons more quickly owing to the better conductivity than s-SWCNTs, the charge transport is disrupted with an accelerated recombination of electrons to the dye or increased back reaction to the electrolyte. In addition, we assume that in s-SWCNTs/TiO2 photoelectrodes, the photo-generated electrons would not be injected to only the TiO2 conduction band, they could also be injected to the conduction band of s-SWCNTs from the photo-excited dyes at the time because the functionalized s-SWCNTs themselves may have adsorbed some dye molecules. This may mean that the electron collection from the dye molecules to the

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semiconductors in such s-SWCNTs/TiO2 composite electrodes could be very good and thereby results in high photocurrent density.

15.4.3 15.4.3.1

Catalyst Layers Platinum (Pt) and Other Catalysts

In DSSCs, the counter electrode serves an essential role in collecting electrons from the external circuit and reducing I3– to I– for the regeneration of dye sensitizer. For the optimized DSSC, the counter electrode material should possess the highest possible electrical conductivity and excellent electrocatalytic activity for the reduction of the redox electrolyte. Other environmental and economic considerations include material abundance and stability, ease of preparation, and chemical nontoxicity. In a typical cell, Pt deposited on FTO is used as the counter electrode owing to its simple preparation and high electrochemical activity for the reduction of triiodide [159, 160]. In the past few years, a wide range of Pt architectures have been developed and used to improve the cell performance [161–165]. However, Pt is a very rare, expensive material. In addition, the slow dissolution of the Pt-deposited film in the corrosive redox electrolyte deteriorates the cell stability [166]. Therefore, substitution of Pt with other cost-effective materials that are readily available for use and can exhibit comparable or higher catalytic property for the reduction of electrolyte in DSSCs is required to lower the production cost of devices. Since the first fabrication of a Pt-free counter electrode for DSSCs reported by Grätzel’s group in 1996 [167], various materials have been employed as alternatives to Pt counter electrodes in DSSCs, but this chapter will just consider CNTs. CNTs are very promising candidates for the counter electrode of DSSCs. It should be noted that just a brief overview of CNTs as a catalyst layer for DSSCs is provided here, as there are a number of excellent reviews available on this topic [33, 157, 160, 168–173]. The first successful application of CNTs as a counter electrode material of DSSCs was reported in 2003 by Suzuki et al. [174] who deposited SWCNTs on a Teflon membrane filter substrate for the DSSC fabrication. Despite the fact that no optimization was done on the cell fabricated in this study, SWCNT counter-electrode-based DSSCs exhibited a very promising result (PCE of 4.5%), which was even comparable to the Pt sputtered cell (PCE of 5.4%). This early work proved that CNT materials naturally possess excellent electrocatalytic activity and high conductivity and have the potential to perform a catalyzing role in DSSCs. Furthermore, Lee and co-workers were able to significantly improve this result to obtain a PCE of over 7%

Use of CNTs in Third-Generation Solar Cells 571 by using MWCNTs/FTO [175, 176]. The improved performance of DSSCs in their studies was mainly ascribed to the low charge transfer resistance (Rct) of MWCNT films, which was comparable to that of Pt electrodes. In particular, these authors prepared a bamboo-like structured MWCNT film on an FTO substrate for use in the counter electrode of DSSCs [175]. Defect-rich edge planes of CNTs can facilitate the electron-transfer kinetics and enhance the catalytic rate at the counter electrode–electrolyte interface. Raman spectroscopy (the intensity ratio of D band to G band was 0.9825) in this study confirmed that in this bamboo-like CNT structure, the CNTs possess plenty of defects. As for the result, the Rct of the defectrich MWCNTs-based counter electrodes was more than two times lower than that of the Pt-based film. Even though the MWCNT film showed a lower Rct than the Pt-based electrode, the Pt counter-electrode-based DSSC (7.83%) exhibited a slightly higher PV efficiency than that (7.67%) of the DSSC fabricated with the bamboo-like structured CNT-based electrode. This was due to the following reasons: (i) the quasi-transparent Pt film slightly reflects the unabsorbed portion of light incident toward the photoelectrode and (ii) smaller diffusion impedance of redox species. Nevertheless, the energy conversion efficiency achieved by this MWCNT counter-electrode-based DSSC was comparable to the benchmark DSSC. Based on this study, it is clear that the defect density of CNTs plays a critical role in DSSCs when they are used in the counter electrode. For instance, it is well established in the case of graphene oxide that highly functionalized graphene structures possess excellent catalytic properties for the I3– reduction [177–179]. So, it is not surprising that acid treatment on nanotubes would also be a reasonable strategy to improve the catalytic properties of CNT films because carbonaceous materials such as CNTs, graphite, and graphene share the same chemical structure [180]. However, high levels of functional groups on the CNTs significantly decrease the electrical conductivity of materials. Since the pioneering work of the Lee group [175, 176], many studies have attempted to improve the efficiency of CNT counter-electrode-based DSSCs. Recent work has seen the performance of CNT-based counter electrodes match the performance of the Pt electrodes. For example, Chen et al. used a carbon nanotube aerogel (CNA) as the counter electrode to obtain a conversion efficiency of 8.35%, which was higher than that obtained for Pt and the addition of a small amount of Pt (3.75 wt%) yielded further gains in efficiency (see Figure 15.1b) [111]. Even more complex counter electrodes using a heteroelectrocatalyst based on cobalt sulfide (CoSx) decorated nitrogen, sulfur co-doped carbon nanotubes (see Figure 15.1c) coated with few layer black phosphorous sheets outperformed the Pt-based DSSCs in terms of PV efficiency [112].

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Highly purified CNTs have been well aligned on an FTO substrate using a catalytic CVD method to make the counter electrode of I–/I3– redox couple-based DSSCs [109]. This well-aligned CNT counter-electrode-based DSSC exhibited an energy conversion efficiency of 10.04%, which was considerably higher than those of the cells fabricated with screen-printed CNTs (8.03%) and benchmark Pt counter electrodes (8.80%). These authors hypothesized that this high performance (especially the high FF of 0.73) of DSSC with a direct-grown CNT counter electrode could be due to the faster redox reaction on the cathode. Therefore, they suggested that the thermal CVD process, used to prepare the well-aligned CNT electrodes, also provides a significant improvement in the electron conduction path between the electrolyte and the FTO glass. DSSCs assembled with the VACNT counter electrodes show very comparable and/or even higher PCE than the expensive Pt-electrode-based cells. However, reports on the exploration of the VACNT counter electrodes for DSSCs are still sparse. Further improvement in the DSSC performance may be possible by developing these vertically grown CNTs structures. Other work has used horizontally aligned films generally based on CNT yarns or fibers. Such alignment enhances conductivity and hence counter electrodes based on these freestanding aligned CNTs structures have been used to produce DSSCs with high efficiencies [181–188]. The twisting of CNTs into fibers or yarns was pioneered over 10 years ago [189]. Recently, this approach has been applied in DSSCs to produce fiber and wire-shaped DSSCs [190–197]. This approach has meant that the traditional planar structure of the cells can be expanded into new geometries. These cells have also received considerable attention due to their flexible and lightweight format, which is required in modern electronic devices. CNT-based materials have been proven to be promising candidates for this class of DSSCs because of their highly aligned structure [198, 199].

15.5 CNTs in Perovskite Solar Cells Perovskite solar cells are a novel type of device, which was first fabricated in 2009 [200] and several structures have been reported [201]. A typical structure is provided in Figure  15.2a. Excitons are created after light absorption in the perovskite material, which are then separated into holes and electrons to be collected at the metal electrode and the FTO-coated glass electrode, respectively. There are two possible ways to separate the excitons, either by thermal energy in the perovskite material or at the interface between perovskite material and TiO2 or hole transport material.

Use of CNTs in Third-Generation Solar Cells 573 The major advantages of the application of CNTs in perovskite solar cells are the possible realization of flexible devices, the economic fabrication process and material, and the potential of devices suitable for two-side illumination. A recent review of CNTs in PSCs has been published [202]. TCFs made from CNTs have been used in perovskite solar cells [203, 204] to replace the expensive metal electrode (usually Au) in the fabrication of perovskite solar cells [205]. In all cases, the CNT network is part of the hole collection side of the cell. The efficiency improved from 5.14% to 6.87% after replacing the Au with CNT because CNT films can provide stronger driving force for the hole injection according to the band alignment. The sparsity of the CNT network allows the device to be illuminated from both sides, which makes the application of solar cell as a window a possibility (see Figure  15.2b). By adding spiro-OMeTAD (hole transporting substances), the performance of the devices was further improved to 9.9%. Although the PCE of this device was not as high as that from some other literature, it shows the potential to achieve a semitransparent and flexible perovskite solar cell without the energy-consuming process of Au deposition. Additionally, acting as the hole transporting layer with poly(3-hexylthiophene-2,5-diyl) (P3HT), poly(methylmethacrylate) (PMMA)-functionalized SWCNTs were found to improve the thermal stability significantly due to their better stability compared to the organic hole transport layer [206]. A partially functionalized SWNCT film has been used as a front transparent conducting electrode in place of the TCO electrode in perovskite solar cells. The fabricated device structure was glass or PET/SWCNTs/ PEDOT:PSS/CH3NH3PbI3/PC61BM/Al, in which the SWCNT film acted as a conducting film. The transparent conducting SWCNT electrode-based planar heterojunction perovskite solar cell achieved a PCE of 6.32%, which is 70% of an ITO-based device (9.05%). A flexible perovskite solar cell made using SWCNT on a PET substrate exhibited a promising PCE (5.38%) [207]. Recent work has demonstrated flexible cells with CNTs used for both electrodes [208]. While the efficiency is modest (~10%), production costs are lowered dramatically. A variety of strategies have been developed to improve the electron transport properties of PSC photoelectrodes [211–213]. In particular, graphene and its derivatives for use in the photoelectrodes of PSCs have recently attracted increasing attention due to graphene’s availability, high conductivity, and suitable energy levels [214–216]. Although PSCs based on photoelectrodes with various graphene derivatives incorporated have shown enhancement in the performance compared to their control devices, the obtained efficiencies are still limited probably due

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Figure 15.2 (a) Schematic of a typical perovskite solar cell. Reproduced from Ref. [209] with permission from Nature Publishing Group. (b) The light J–V curves of a perovskite device from two different sides after substituting the Au electrode by CNT TCF. Adapted with permission from Ref. [205]. Copyright (2014) American Chemical Society. (c) J–V curves of the best-performing PSCs fabricated with and without SWCNTs (0.10 wt%) in the photoelectrodes measured under 100 mW cm−2 (AM 1.5G) illumination. Adapted with permission from Ref. [210]. Copyright (2017) American Chemical Society. (d) Plot Jsc of the PSCs as a function of SWCNT concentration in the TiO2 films. Adapted with permission from Ref. [210]. Copyright (2017) American Chemical Society.

to the structural defects of the graphene sheets created during the production process. In this regard, carbon nanotubes (CNTs), particularly single-walled (SWCNTs), are expected to exhibit significant enhancement in the PCE of PSCs because of their unique structure and excellent properties. It is worth noting that in dye-sensitized solar cell systems, CNTs have been shown to be more effective in enhancing the PCE than other carbon materials [51, 153]. CNTs have exhibited promising results when they are used as a hole transporting material (HTM) and cathode in PSCs [205, 206, 217–220].

Use of CNTs in Third-Generation Solar Cells 575 Moreover, CNTs are promising candidates for fabricating flexible fibershaped PSCs [221–224]. Integrating highly conductive CNTs into 1D structured TiO2 for use in the photoelectrode of PSCs is an alternative approach to provide an ultrafast electron transport pathway to enhance device performance. The influence of CNTs on the performance of PSCs fabricated with 1D TiO2 nanofibers (NFs) showed a significant enhancement (~40%) in device performance as compared to the control cell fabricated without CNTs [225]. PSCs fabricated with SWCNT-TiO2 NFs exhibited reduced hysteresis and improved stability both under light and during storage under humid conditions with respect to the control devices without SWCNTs. In parallel work, incorporating SWCNTs into the TiO2 nanoparticle-based mesoscopic structured PSCs yielded very impressive efficiencies (see Figure 15.2c) and as in the case for the DSSCs, the optimal SWCNT loading was very low (0.1% wt%) (see Figure 15.2d) [210].

15.6 Carbon Nanotube–Silicon (CNT–Si) or Nanotube–Silicon Heterojunction (NSH) Solar Cells In this section, the working mechanism and the origin of photocurrent will be provided firstly, which will be followed by the discussion of the effect of CNT types (in terms of the number of walls as well as electronic properties) and properties of CNT electrodes (film transmittance, alignment of individual CNTs, and influence of chemical doping). This section will then cover some unique design strategies of the devices, including the introduction of silicon oxide layer at the interface between CNT and Si, enhancement of light absorption, as well as the application of conductive polymers.

15.6.1

Working Mechanism

In nanotube–silicon heterojunction (NSH) solar cells, the CNTs not only transport charge carriers but also act as a photoactive material according to some reports [226–228]. A typical cell design is given in Figure 15.3a, with details produced in several reviews [228, 229]. In a typical heterojunction device formed by a layer of p-type CNT on top of a layer of n-doped Si, light passes through the CNT layer and the Si is the light-absorbing layer where excitons are produced and diffuse to the interface of the two layers. Under the influence of the built-in potential at the interface, the separation

576

Emerging Photovoltaic Materials PEDOT: PSS-CNT CNT

Psynergy

PEDOT:PSS +

Ag paste

EGaln

+–

n-Si

SiO2 Si

+– –

–

Hole: +

+

+ +– –

+–

N

Electron: – (b)

(a)

–4.2 eV

CNT

Si

– –4.05 eV

Probe

–4.8 eV

Pump

–

–5.17 eV i

+ CNT SiO2 n-Si

CNT

+

Tunneling

+

+

Interface –

+ –

Si

ii (c)

Efficiency (%)

12 Interface

10

SOCI2 HCi

8

HNO3 CuCI2 H SO HClO4 2 4 AuCl2

AgNWs Untreated

6 0

5 10 15 Electronegativity (d)

20

Figure 15.3 (a) Schematic of a typical NSH structure. Reproduced from Ref. [231] with permission from Elsevier. (b) Schematic of the mechanism of hybrid PEDOT:PSS-CNT/ n-Si solar cell. Reproduced from Ref. [231] with permission from Elsevier. (c) Mechanism of charge carrier transport in an NSH cell. (i) Overview of charge transport pathways. Reproduced from Ref. [232] with permission from the Royal Society of Chemistry. (ii) Nanoscale charge transport pathways showing electrons moving through oxygen. Adapted with permission from Ref. [233]. Copyright (2017) American Chemical Society. (d) Efficiency of HSH cells as a function of the electronegativity of the doping species used. Reproduced from Ref. [232] with permission from the Royal Society of Chemistry.

of excitons occurs with individual holes (or electrons) transported via CNT electrode (or Si layer) and collected at front metal contact (or back contact) (see Figure 15.3c,i) [230].

15.6.2

Development of Si-CNT Devices

The first such cells were designed by Wei et al. in 2007 [227, 228, 234] using DWCNTs deposited via water expansion and aqueous film transfer of an as-grown CVD film [227, 228]. While these cells only had a photoconversion efficiency of 1.3% (compared to commercial cells at 20%–30%), many improvements have since been made to the cell design and doping methods, with 15% efficiencies reported in 2012 [235] and 17% efficiencies reported in 2015 [236, 237]. Thus, in less than a decade, the cell efficiency was improved by a factor of 10. Recently, cells with a record 100% internal quantum efficiency (IQE) were reported demonstrating the highly efficient ability of the system to separate the generated charge carriers [238]. Such rapid improvement is unsurprising for a system based on the already

Use of CNTs in Third-Generation Solar Cells 577 mature field of silicon PV. However, in addition to the fundamental physics of the nanotube–silicon junction, interest in these solar cells is based largely on the potential to replace the costly and energy-intensive ion diffusion component of current manufacturing processes. The typical architecture for these cells is much like that of a single-junction n-type crystalline silicon solar cell with a front side emitter layer replaced by a film of p-doped CNTs [228]. While the initial design used DWCNTs, most designs use SWCNT electrodes; however, MWCNTs may also be used [226, 239]. In all cases, the CNT film acts as a component of the heterojunction, setting up a built-in potential to enable charge separation, as a highly conductive network for charge collection and transport, and as a transparent electrode to allow good light illumination of, and photocurrent generation in, the silicon base [226]. The energy generation within photovoltaic devices is a complex process that involves several steps including photon absorption, electron–hole diffusion, charge separation, carrier transport, and collection [240]. As such, there are a variety of effects that must be balanced in order to attain higher efficiency cells. Following Wei’s first report in 2007, the first significant improvement by Jia et al. [226], who achieved an efficiency of 7.4% from DWCNT/Si cells, came largely by substituting the original mica window with a much thinner silicon oxide (SiOx) window, allowing the nanotube film to sit more smoothly on the silicon surface [228]. In 2008, Li et al. [241] found that treatment of the SWCNT layer with the p-dopant thionyl chloride (SOCl2) post-fabrication increased the power conversion efficiency of the cells by over 45% (relative) by lowering the sheet resistance and increasing the short-circuit current density and open-circuit voltage. Hall effect measurements showed that the SOCl2 treatment led to an increase of carrier density from 3.1 × 1015 to 4.6 × 1017 cm−2 and an improvement from 0.23 to 1.02 cm2 V−1 s−1 of the effective mobilities [228, 241]. In addition, it was found that SOCl2 treatment adjusted the Fermi level and shifted the major conduction mechanism in the SWCNT layer from hopping toward tunneling [242, 243]. This work was the first of many in the field to focus on improving performance on a variety of silicon substrates and device designs through the use of doping and other strategies applied to nanotube films to improve their conductivity/transparency relationship.

15.6.3

Origin of Photocurrent

Wadhwa et al. suggested that the mechanism of photocurrent generation in the CNT/Si heterojunction solar cell is consistent with the Schottky–Mott

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model, that is, via thermionic emission over a barrier formed at the interface of a metal and a semiconductor [244]. However, the performance enhancement via Fermi level modulation could apply to both Schottky and p–n junctions [228]. Work done by Ong et al. [245] found that there was a possible correlation between an SWCNT absorption band [S11, the first interband transition for the (7,6) and (8,6) chiralities] and a photocurrent band at around 1150 nm. This seems to imply that the nanotubes are involved in the production of the photocurrent as a light absorber, and not simply as a charge separator, transporter, and collector, which indicates that the cell architecture is that of a p–n junction [228, 245]. However, as shown in a later study by Tune et al., the feature in the photocurrent spectrum could have other origins (probably due to the application of nonohmic back contact) [246]. In 2007, Tzolov et al. [247] achieved a broad photoresponse in the mid-IR range separate from the expected strong silicon response at photon energies of 1.1–1.2 eV. It was claimed that this response was proof that CNTs participate in exciton generation themselves. However, in addition to questions about whether or not the tubular carbon material formed via their template method was, in fact, carbon nanotubes in the usual sense, this feature could also be due to free carrier absorption in the silicon base [228, 248, 249]. Thus, neither the work of Tzolov et al. or Ong et al. conclusively proves that the light adsorption in the nanotubes contribute to the photocurrent and thus create a p–n junction [228, 246]. Recent work using transient optical spectroscopy on the femtosecond timescale has shown that oxygen-related states at the interface act as entrapping centers for the photoexcited electrons, thus preventing recombination with holes that can flow from Si to CNT across the SiOx layer (see Figure 15.3c,ii) [233].

15.6.4

Effect of the Number of CNT Walls

Jia et al. [250] performed the first comparison between SWCNTs, DWCNTs, and MWCNTs for use in CNT/Si cells in terms of the area density of the films. It was found that SWCNTs are superior to MWCNTs at low densities. It was also found that the density (and thus optical transmittance) is vastly important in the performance of these cells. Increasing film transparency (lowering CNT density) increases the efficiency of the cells by allowing more light to reach the silicon, while decreasing the transparency (increasing the CNT density) increases the efficiency by lowering the sheet resistance across the film [228, 250]. Thus, there must exist some optimal thickness to achieve maximum efficiency. This research team also found their DWCNT cells to be significantly superior to both the SWCNT

Use of CNTs in Third-Generation Solar Cells 579 and MWCNT cells. However, their DWCNT films were produced using a different method to the SWCNT and MWCNT films [250]. This makes it difficult to draw a good comparison, as the nanotube film properties are highly dependent on film morphology [228].

15.6.5

Effect of the Electronic Type of CNTs

The majority of research performed on nanotube/silicon cells is performed with a mixture of nanotube types to form the film, as nanotubes are grown as a mixture of types. Tune et al. [243] investigated the effects of fabricating cells with pure metallic or semiconducting nanotubes versus cells with an as-grown mix of types. It was discovered that, initially, the films containing purely metallic nanotubes significantly outperformed both the semiconducting and unsorted films. However, after the films were treated with SOCl2, the situation became very different. The p-dopant greatly improved the efficiency of the semiconducting and mixed film cells, but had a much smaller effect on the metallic film cells [243]. This is expected since the SOCl2 both lowers the contact resistance between the nanotubes and increases the Fermi energy of the semiconducting nanotubes such that the Fermi level drops from a point where there are no states (in the gap) to well within the valance band/first van Hove singularity, where the density of states is very high. However, although there is a comparable improvement in contact resistance in the metallic films, the reduction potential of SOCl2 is insufficient to lower the Fermi level of the metallic nanotubes far enough to reach the first van Hove singularity. This means that the SOCl2 treatment does not result in any appreciable change in the density of states at the Fermi level and also does not increase the Fermi energy to the same extent as in the semiconducting nanotubes [243]. Similar observations have been made by Harris et al. in their comparison of semiconducting and metallic nanotube films on silicon [251]. Overall, it is evident that the metallicity of the nanotube film plays a significant role in the cell operation.

15.6.6

Effect of CNT Alignment in the Electrode

One of the potentially limiting factors in the performance of the CNT/ Si heterojunctions discussed so far is the film morphology. Generally, the films formed consist of a random array of nanotubes, which can suppress some of the film properties. This is because a random alignment of tubes can lead to “charge traps” and holes within the film, which can inhibit charge carrier transport across the network. For this reason, there has been much research done in order to produce highly ordered, aligned carbon

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nanotube films. Many techniques have been tried such as solution shearing from superacids (chlorosulfonic acid) [252, 253], the controlled collapsing of vertically aligned CVD-grown CNT forests [254–256], horizontal CNT growth from lithography controlled CVD [257], exfoliation of CVDgrown CNT forests [258], and evaporation-driven self-assembly of CNTs via surfactant stabilization, sidewall functionalization, polymer wrapping, and floating evaporative self-assembly [259–263]. Jung et al. [264] and Li et al. [252] have used the chlorosulfonic acid, and Tune et al. have similarly used sodium nanotubide polyelectrolytes to form true solutions (rather than metastable suspensions) of SWCNTs at volume concentrations high enough to generate a nematic liquid crystal phase, allowing the nanotubes to be aligned on a surface when a droplet of the solution is sheared rapidly between two glass slides [252, 264, 265]. This ordered alignment of the SWCNTs allows a thin, highly transparent, very smooth film to be produced, which does not suffer from the drawbacks of thin films produced via other methods (such as poor contact with the silicon substrate and a poorly formed nanotube network with many electronic charge traps and physical holes in the film). These films were found to benefit the cells by allowing more light to reach the silicon while also providing morphological uniformity, greatly improving the maximum solar cell efficiency compared to disordered films on the same devices.

15.6.7

Effect of the Transmittance/Thickness of CNT Films

A 2013 study by Tune et al. [266] found the optimal film transmittance for the type of SWCNTs used (large-diameter arc-discharge nanotubes with high carboxyl functionality). It was determined that a film transmittance of 70% gave the optimal efficiency, and this was found to taper significantly for films with higher transmittance. This was due to a decrease in the amount of SWCNT/Si contacts for charge separation and an exponential increase in the sheet resistance of the film as the conduction mechanism became dominated by the limited percolation pathways in highly transparent nanotube films [266].

15.6.8

Effect of Doping

Jia et al. [59] experimented with doping the nanotube film using nitric acid (HNO3) in 2011. Post acid-doped cells achieved very high power conversion efficiencies of over 13% while the undoped cells exhibited much lower efficiencies of 6.2%. The increase in efficiency was attributed to a reduction of the series resistance in the CNT network, producing J–V curves with

Use of CNTs in Third-Generation Solar Cells 581 a higher fill factor than in undoped cells (0.72 vs. 0.47). This decrease in series resistance is thought to be caused by p-type doping via oxidation, plus the removal of residual molecules (such as surfactant) from the network [59, 63, 267, 268]. It is known that HNO3, like SOCl2, injects large hole densities into CNTs and thus lowers the Fermi level in SWCNT films [78, 269]. A recent study examined many of the commonly used doping methods and showed that their effectiveness in improving the efficiency of devices is related to the electronegativity of the species available (see Figure 15.3d) [232]. Doping using CuCl2/Cu(OH)2 colloidal ethanol solution looks to be a particularly promising approach and demonstrates considerable stability compared to many of the other approaches [270]. Other p-dopants can be used in the treatment of CNT films in order to increase the efficiency of the CNT/Si heterojunction cell including gold chloride (AuCl3) [271]. It may be assumed that AuCl3 functions as a p-dopant because the high reduction potential of the Au3+ ion allows it to extract valance electrons from the CNTs, resulting in the formation of gold nanoparticles throughout the film. However it is also proposed that the Au3+ ions act as a precursor for Cl− ion adsorption allowing for further electron extraction from the CNTs [271]. Several other groups [251, 252, 264] have performed AuCl3 treatment and observed the expected increase in short-circuit current density, leading to improved efficiencies to above 10% in both cases. In addition, Li et al. found that if a large amount of gold nanoparticles were deposited on the nanotube film, the cell performance would degrade due to a “shorting” effect in which the Au particles form contacts with the silicon substrate [252].

15.6.9

Intentional Addition of Silicon Oxide Layer

One issue with current CNT/Si heterojunction solar cells is the formation of a silicon oxide layer between the silicon substrate and the CNT film. Of course, cells with a thick insulating oxide cannot function. However a tunneling barrier in the form of a thin passivating oxide can inhibit surface recombination, increasing the minority carrier lifetime and blocking majority carrier transport, thus suppressing the dark saturation current, and ultimately leading to higher voltages, larger photocurrents, and improved fill factors [240, 272]. The HNO3 treatment used by Jia et al. was shown to produce an oxide on the silicon surface with a thickness of approximately 1 nm, which is optimal for a tunneling barrier [240]. In addition, Jia et al. [240] encapsulated a SWCNT/Si device with a poly(dimethylsiloxane) (PDMS) coating and found that this improved the performance stability over a period of 20 days. However, after this point, there was a slight

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Emerging Photovoltaic Materials

reduction in efficiency, which the authors attributed to the growth of an oxide layer that was too thick for tunneling [228, 240].

15.6.10 Enhancement of Light Absorption Front-side reflectance detracts significantly from the photocurrent production of photovoltaic devices [273]. Smooth silicon is a very reflective surface, with an average reflectance of 36% in the UV-visible region [235, 273–275]. This is caused by the large difference in refractive index between air and silicon [276]. As such, efforts to subdue the reflective properties of silicon have been of high priority in solar cell research [277, 278]. The usual industry methods of reducing light reflectance are by a combination of refractive index matching with a coating of silicon nitride (SiNx), and an alkaline etching process producing a random pyramid surface that acts as a scattering layer [278]. Random pyramids in the CNT/Si heterojunction design do improve the efficiency [279] while the use of silicon nanowires has also been investigated by Petterson et al. [280] with significant improvements in surface reflectance and performance observed. Jung et al. [264] also showed that hemispherical droplets of liquid resting on the cells’ active area act as lenses to give a light concentrating effect, artificially inflating the calculated photocurrent density and thus power conversion efficiency. This calls into question the validity of some earlier reports of improved performance when a droplet of acid was placed on the cells [252]. A recent approach to reduce the silicon reflectance involved spin coating of a TiO2 colloid giving a nanoparticulate layer of 50–80 nm in thickness on the surface. This method had previously been used to lower the reflectance of silicon solar cells, leading to greatly reduced reflectance (approaching 0.04%) and improved cell efficiencies of up to 44% relative when coated with thermal SiO2 and a TiO2 thin film [281]. In the case of the nanotube/ silicon cells, the layer subdued the light reflection significantly (decreased reflectance from 30% to 40% to below 5% in some wavelength regions) and increased the incident photon to current efficiency (IPCE) from 60% to 90%, while still allowing post-fabrication doping treatments to reach the nanotube network. Together with nitric acid and hydrogen peroxide doping, this antireflection layer allowed for the record high cell efficiencies of above 15% [235]. The authors asserted that the TiO2 layer improved performance through better light management in the front surface, acting as an interference coating by creating destructive interference at the interface,

Use of CNTs in Third-Generation Solar Cells 583 instead of the light scattering and trapping effects of patterned silicon surfaces [235]. Recently, Wang et al. investigated the application of molybdenum oxide (MoOx) and zinc oxide (ZnO) as cheap, environmentally friendly antireflection layers [236]. In addition to the antireflection properties, these layers also assisted with carrier doping of the nanotube film and helped to improve the carrier transport efficiency across the junction between the nanotubes and the front-side metal electrode in both the standard p-SWCNT/n-Si cell and the n-SWCNT/p-Si cell. Using these films allowed the team to set a record efficiency for CNT/Si solar cells of 17% (albeit with a sub-millimeter active area and no aperture during testing) and achieve a relatively high efficiency for a cell using n-doped nanotubes of 4% [236]. The MoOx coating improved the properties of the standard CNT/Si cell, with a higher Jsc and much improved diode properties. Another method of reducing light reflection in CNT/Si solar cells is via the use of a polymer coating over the CNT film [237]. In this way, the polymer layer can be doubly effective, both by reducing the reflectance and by protecting the nanotube film and the nanotube/silicon interface from the environment to some degree [237]. In addition, this method does not damage the silicon surface, thus causing no interference between the CNT film and the silicon [235]. Polymeric anti-reflection (AR) layers can also assist in the stability of carbon nanotube/silicon cells, by reducing the amount of oxygen that can pass through to the silicon surface. Atmospheric oxygen can react with the silicon surface in the regular cell design, growing a silicon oxide layer between the silicon and the carbon nanotube film, which, if it becomes thick enough, can lead to a decrease in cell performance [237]. As well as preventing oxygen from getting to the interface, polymer encapsulation can assist in preventing beneficial adsorbates such Cl− and SO2 from getting out, dedoping the nanotubes and again leading to a decrease in performance. Li et al. [273] used a coating of PMMA as an antireflection layer for a CNT/Si junction. This film improved efficiency from 7.1% to 11.5%. This was mainly due to a large increase in the short-circuit current density in the cell, which was correlated with the PMMA’s antireflection properties (from 24.3 to 35.6 mA cm−2). The external quantum efficiency (EQE) increased from 60% at wavelengths of 400–900 nm to above 80% from 500 to 800 nm, indicating that more photon–electron conversion was taking place [273]. Yu et al. [237] used poly(dmiethylsiloxane) (PDMS) and polystyrene (PS) in addition to PMMA as antireflection coatings. It was found that, while all the polymers performed successfully as antireflection

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Emerging Photovoltaic Materials

coatings and managed to increase the efficiency of the cell design, the effect was dependent on the thickness of the coating.

15.6.11 Application of Conductive Polymers In addition to using polymer layers as an anti-reflection strategy, research has been done on the use of a thin, conductive layer of polymer placed in between the CNT layer and the silicon substrate [282]. Polyaniline (PANI) has previously been studied as a transparent electrode material by spin coating a thin film on a silicon substrate [283, 284]. These junctions suffered due to the limited lateral conductivity in the PANI film. CNT films can overcome this issue due to their good conductivity [282]. Tune et al. [282] reported a cell design combining a first layer of PANI and then a second one of SWCNTs on an n-silicon substrate. The SWCNT–PANI– Si junctions showed a maximum efficiency of 9.7%, three orders of magnitude higher than when only PANI was used (0.005% efficiency) and three times higher than the SWCNT/Si cells in that study (3.3%). This was attributed to the combined properties of both substances, the improved depletion region due to more complete surface coverage provided by the polymer, and the high conductivity and current carrying capacity of the SWCNT film [282]. Other work used a poly (3,4-ethylene dioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) film to co-form-coordinate heterojunctions with silicon and have developed a hybrid PEDOT:PSS-CNT/n-Si solar cell (see Figure 15.3b) [231] that gave power conversion efficiencies of 10.2%, which is higher than that from using the individual components separately.

15.6.12 Discussion Despite all these advances, and the clear interest in carbon nanotube–silicon solar cells from a fundamental point of view, one may well question the real benefit of adding what is still an expensive commodity nanomaterial onto an already costly product. However, with current commercial silicon PV module efficiencies nearing laboratory-scale records, which are themselves already near fundamental limits, and with the very steep cost reductions due to economies of scale involved in recent massive expansion of worldwide production capacity yielding prices, which are not far above wholesale material costs, meeting the market demand for continued improvements in the levelized cost of energy to the consumer will require more than simply following the price learning curve to plateau. The cost of carbon nanotubes is only now starting to benefit from economies of

Use of CNTs in Third-Generation Solar Cells 585 scale, and this material is reasonably predicted to become very cheap as capacity ramps up and production technologies mature. As well, the quantity of material required in carbon nanotube–silicon solar cells is miniscule, on the order of milligrams per square meter. Taking these factors into account, it is not difficult to envisage a scenario where carbon nanotubes replace the intrinsically costly and throughput-limiting ion diffusion processes used in current state-of-the-art silicon PV, when our understanding of the junction physics improves alongside technological advancements in high-throughput methods of incorporating them into the fabrication sequence.

15.7 Outlook and Conclusion While an extensive body of work using CNTs in solar cells already exists as detailed in this chapter, there are still many avenues of investigation to be pursued. The ability to sort nanotubes both in terms of the electronic characteristics (metallic versus semiconducting) and further according to their chirality [285–296] presents opportunities to tune conduction pathways and select bandgaps and/or light absorption/transmission wavelengths. As with most nanomaterials, an important factor determining performance is the morphology of the carbon nanotube films, and future investigations will have to pay particular attention to characteristics such as the smoothness of the nanotube film to obtain the best performance. Various schemes to align carbon nanotubes on surfaces have been demonstrated recently, and this provides the opportunity to significantly increase the conductivity of films that already have exceptionally high transparency. The use of such aligned films in solar cells is an area worthy of further study. Hybrid structures combining carbon nanotubes with other nanomaterials present many possibilities, and there is little doubt this space will be explored extensively to find optimal solutions for various components of solar cells. Chemical doping is known to be a powerful method to improve the carbon nanotubes’ properties including conductivity and catalytic activity [297–299], but the effects are often short-lived. Work to improve the long-term stability of the performance enhancement, especially in air, would be of great value. Semiconducting nanotubes have a Fermi level in the middle of the bandgap and could thus be termed “intrinsic” similarly to undoped silicon. However when exposed to air, they develop p-type characteristics due to the electron-withdrawing nature of adsorbed oxygen molecules. Even in ultra-high vacuum, this adsorbed oxygen is very difficult to remove

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and has likely skewed the results of much research carried out to date [300]. In addition, SWCNTs can be chemically doped p-type by electronwithdrawing species such as strong oxidizers or oxidizing acids [267, 269], or n-type by electron-donating species such as alkali metals [301], hydrazine [269, 302], nitrogen-rich polymers [303], and nitrogen-rich aromatic compounds [304]. Substitutional doping has also been demonstrated with boron (p-type) [305] and nitrogen (n-type) [306, 307]. This raises the exciting prospect of all-nanotube photovoltaics based on p–n or p–i–n homoor heterojunctions, although such architectures are yet to be reported for other than single-tube devices [308]. There can be little doubt that carbon nanotubes will play a key role in the development of solar cells that will provide energy at competitive costs compared to current energy production approaches. New processes are continually being reported, and these will present opportunities for innovation in both research and commercial development.

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16 Quantum Dot Solar Cells Xiaoli Zhao,1 Chengjie Xiang,1 Ming Huang,1 Mei Ding,2 Chuankun Jia2,3* and Lidong Sun1,3* 1

State Key Laboratory of Mechanical Transmission, School of Materials Science and Engineering, Chongqing University, Chongqing, P.R. China 2 College of Materials Science and Engineering, Changsha University of Science and Technology, Changsha, P.R. China 3 Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), Nankai University, Tianjin, P.R. China

Abstract

Quantum dot solar cells are capable of delivering a theoretical power conversion efficiency of about 44%, far beyond the Shockley–Queisser limit, and thus have been extensively studied as the third-generation photovoltaics. This chapter aims to introduce quantum dots and their application in solar cells, which is divided into four sections. Section 16.1 starts with the fundamental concept of quantum dots and then discusses their intriguing properties including size-dependent quantum confinement effect, multiple exciton generation effect, and Kondo effect. This is to answer what are quantum dots and what are they used for. In Section 16.2, three prevailing synthesis methods are introduced with brief historical developments: (1) hot injection for colloidal quantum dots of monodisperse feature, (2) chemical bath deposition for high surface coverage with random size distribution, and (3) successive ionic layer adsorption and reaction for high surface coverage and better size control. The characteristics of the resulting quantum dots are discussed separately and compared with different synthesis routes. In Section 16.3, corresponding photovoltaic devices are discussed with three major categories: (1) Schottky junction solar cells, where colloidal quantum dots directly contact with conductive electrodes; (2) depleted heterojunction solar cells, in which colloidal quantum dots are prepared on compact or mesoporous electron transporting layer (e.g., TiO2 nanoparticles); and (3) quantum-dot-sensitized solar cells, where the quantum dots are adsorbed onto mesoporous substrates with the hole

*Corresponding authors: [email protected]; [email protected] Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (611–658) © 2019 Scrivener Publishing LLC

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transporting materials (or redox couple electrolytes for liquid cells) being penetrated inside the mesopores. The three systems are discussed separately with reference to the state-of-the-art reports, including the device structure, preparation route, materials selection, and photovoltaic performance. Section 16.4 highlights the current challenging issues and future perspectives on quantum dot solar cells. This chapter covers the fundamental concepts, synthesis methods, and photovoltaic devices, which are beneficial to both students and researchers working on photovoltaics, optoelectronics, and related areas. Keywords: Quantum dot, solar cell, hot injection, chemical bath deposition, SILAR

16.1 Introduction Photovoltaic devices draw enormous scientific and technological attention, because of the fossil fuel depletion and global warming. As one of the third-generation photovoltaics, quantum dot solar cells exhibit many attractive optical and electronic properties, such as high extinction coefficient, tailorable bandgap energy, and solution-based process, and thus have been extensively studied. This chapter first discusses the fundamental concept of quantum dots (QDs), including the size-dependent quantum confinement, multiple exciton generation (MEG) effect, and Kondo effect. Three prevailing synthesis methods are then presented in detail. Three kinds of solar cells, including Schottky junction solar cells, depleted heterojunction solar cells, and quantum-dot-sensitized solar cells, are highlighted and analyzed. Finally, the challenges and future development toward highly efficient and cost-effective quantum dot photovoltaic systems are discussed.

16.2 Quantum Dots and Their Properties 16.2.1

Fundamental Concepts

Quantum dots are quasi-zero-dimensional semiconductor nanostructures, the size of which in three spatial dimensions is comparable to or smaller than the de Broglie wavelength of the excitons in corresponding bulk materials. They are usually composed of 103–109 atoms; in this case, most of the electrons are bound with just few free electrons [1]. In theory, the energy structure of an atom is discrete, whereas that of a semiconductor bulk exhibits continuous bands. The energy structure of a quantum dot well situates in between, as shown in Figure 16.1 [2]. It contains discrete

Quantum Dot Solar Cells 613 atomic-like states with certain width, and the energy spacing generally enlarges as the QD size decreases [3]. In the case of extremely small quantum dots, the energy spacing is so large that the thermal energy is unable to excite the charge carriers at the lowest electronic states. In such a strong confinement regime, the electronic properties, including excited states, ionization potential, and electron affinity, are greatly dependent on the QD size. This results in the quantized motion of charge carriers [4]. Besides, one extra electron can only be added to the dot when an adequate energy is supplied to overcome the Coulomb repulsion between the electrons.

16.2.2

Size-Dependent Quantum Confinement Effect

Quantum dots endow a wide regime of photoresponse to the solar spectrum via controlling their size. This is attributed to the quantum confinement effect. The quantum confinement is derived from the density change of electronic states in consideration of position and momentum in free and confined particles [5]. In free particles, the energy and crystal momentum can be precisely defined except for the position. In confined particles, the energy may be accurately defined, with the uncertainty in position being reduced. This leads to no longer well-defined momentum. The discrete energy eigenfunctions of the particle can be regarded as the superposition of bulk momentum states. A series of nearby transitions of slightly energy difference in bulk is thereby converted into a single and intense transition in a quantum dot. This shifts in absorption onset and contributes to the tuning of photoresponse to solar spectrum. For example, the bandgap energy of Cu2ZnSnS4 nanocrystals is increased from 1.48 to 1.89 eV by reducing the crystal size from 10.5 to 3 nm [6]. One exciton in a quantum dot is bound by the confinement effect other than the Coulomb interaction. It is reported that the quantum confinement in IV–VI nanocrystals, such as PbS, PbSe, and PbTe, is many times stronger than that in most II–VI and III–V nanocrystals [2]. The lead salt nanocrystals may be the only materials that the electronic energies are mainly decided by quantum

Density of states

Bulk

Ideal QD

Real QD

Energy

Figure 16.1 Density of electron states in bulk and size-quantized semiconductor [2].

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confinement; in these QDs, the energy spacing is much larger than their corresponding bulk materials. The quantum confinement in doped semiconductors may result in the localization of impurity states as well as the disorder effect producing the band tails [7]. The impurities can interact with each other and form subbands near corresponding band edges (conduction for n-type and valence for p-type). Generally, for n-type doping, the absorption onset is blue-shifted by the reason of conduction band-filling with donated electrons. For p-type doping, the absorption is red-shifted because of the high density of states near the edge of valence band. This is attributed to the Moss–Burstein effect, which is often conquered by the red shift due to band-tailing. Taking the Cu-doped InAs nanocrystals as an example [8], a blue shift in the absorption spectrum is observed, being consistent with the increase in density of states because of the addition of new impurity bands fractionally filling with electrons from Cu impurities. In contrast, a red shift is observed in Ag-doped InAs nanocrystals of p-type feature [9]. On the basis of different doping types, well-tuned electronic properties of QDs are obtainable for various optoelectronic applications.

16.2.3

Multiple Exciton Generation Effect

In general, a semiconductor produces one electron–hole pair upon absorbing one photon with energy higher than its bandgap; in this case, the excessive photon energy is lost as heat through electron–phonon coupling, subsequent phonon relaxation, and energy consumption. The multiple exciton generation is a process that two or more electron–hole pairs are created with only one photon absorption, because of the impact ionization process, as illustrated in Figure 16.2 [10]. It is also referred to as carrier multiplication, or direct carrier multiplication. By absorbing a photon with energy higher than the lowest energy required for the excitonic transition, an electron–hole pair is generated and excited to high energy levels above the minimum one, which are named hot carriers. The excessive energy can dissipate in the following ways [11]: (1) lost as heat through electron– phonon interactions or Auger processes, (2) produce another electron– hole pair, and (3) converted to electrical free energy via photovoltaic effects or stored as additional chemical free energy. The multiple exciton generation is created through Process (2); a highly excited carrier relaxes to the band edge with the excessive energy exciting another carrier across the bandgap. In general, the MEG rate of the excited holes is larger than that of the electrons. However, it is dominated by the excited electrons, due to

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Γe

Initial state

Γh

Final state

Initial state

Final state

Figure 16.2 Schematic diagram of MEG decay paths for an excited electron (left) and an excited hole (right). Several degenerate final state configurations may exist and contribute to the MEG decay rate [10].

a larger excessive energy of the photoexcited electrons. The exciton recombination is an inverse process of multiple exciton generation, which accelerates the energy loss by wiping out carriers of higher energy [12], and the two processes govern the exciton dynamics. The MEG efficiency ( MEG) is defined as a ratio between the minimum energy required to create an electron–hole pair (i.e., the bandgap) and the actual energy required to produce an additional electron–hole pair after the MEG threshold is passed. It can be expressed as MEG  = Eg/εeh [13], where εeh and Eg are creation energy of electron–hole pairs and the bandgap energy, respectively. It is reported that the MEG in quantum dots is more efficient than that in the corresponding bulk semiconductor. For example, the MEG in PbSe quantum dots is larger than that in bulk PbSe [14, 15]. In quantum dots, the following properties affect the MEG process because of the quantum confinement [13]. (1) Crystal momentum is no longer a certain quantum number; under such conditions, single and multiple exciton states may be coupled to form a superposition state, whereas the coupling is not possible in bulk due to the well-defined momentum. And, the absorption selectivity is changed. (2) The discrete energy band and controllable surface states of quantum dots can be utilized to alter carrier relaxation rates and therefore increase the MEG rate. (3) Enhanced Coulombic coupling between excitons in quantum dots can promote the MEG process. In addition, the MEG efficiency is also dependent on the size of quantum dots. The MEG increases with the decrease of the QD size due to the enhanced quantum confinement. For PbS quantum dots [16], the MEG increases from 0.26 to 0.40 while the radius decreases from 4.7 to 2.1 nm. The MEG efficiency is closely related to the materials as well. Different quantum dots with comparable radius present different MEG.

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The MEG of PbSe QDs is larger than that of PbS QDs under the same radius [16]. Besides the MEG efficiency, the quantum yield (QY) is another important factor, which is defined as the average number of excitons created per absorbed photon. The PbSe QDs exhibit a QY of 300% when excited at 4Eg, manifesting that three excitons are generated per photon absorption [17]. A quantum yield larger than 100% is an indication of the multiple exciton generation. Delerue et al. [18] proved that the number of created excitons per absorbed photon in bulk semiconductor is larger than that in corresponding quantum dots, whereas the energy of the excitons is higher in quantum dots than that in bulk. In addition, the photon energy can be utilized more effectively in QDs. The quantum yield depends weakly on QD size, and is only a function of Eh /Eg, where Ehν is the photon energy [19].

16.2.4

The Kondo Effect

The Kondo effect is a many-body effect, which results from the spin interaction between the localized magnetic impurities and conduction electrons. It presents the notion of asymptotic freedom [20]. When the tunnel coupling between the spin of a localized impurity and conduction electrons is anti-ferromagnetic, the screening of the localized magnetic impurity spin is controlled by the Kondo energy (EK). There is a linear relation between the Kondo energy and the Kondo temperature (TK) [21], TK  = EK/k, where k is the Boltzmann constant. At the temperature below TK, the impurity is screened by the conduction electrons as the temperature approaches zero, while above TK, the impurity behaves like a free spin. In addition, the external magnetic field accelerates the spin degeneracy of an impurity energy level, and the Kondo peak in density of states would split within a quantum dot [22]. When the Kondo effect is considered in QDs connected to external leads by tunnel junction, the localized spin is formed by electrons within the QDs. The number of electrons is determined by the Coulomb blockade and made to be a well-defined integer values N. The Kondo system only exists when the number of electrons is odd in the QDs [23, 24]. The Kondo effect is also investigated in double or multiple quantum dots. This contains two probable sources, including spin and orbital degeneracies, because of the strong Coulomb correlations. The orbital states can serve as pseudospin states whose degeneracy leads to the Kondo screening. When spin and orbital degeneracies occur synchronously, the Kondo effect

Quantum Dot Solar Cells 617 reaches its maximum [25]. In an artificial quantum dot molecule, electrons within a series of coupled quantum dots are added gradually onto the dots. The spin status of multiple quantum dots is in accordance with electron spin in a double dot system. In this case, the Kondo resonance peaks display obvious splitting [20].

16.2.5

Applications

Quantum dots have been widely applied in the fields of environment, biology, photovoltaics, and photoelectronics. A few typical examples are discussed below. Heavy metal ions, such as the soluble Hg2+, are of high toxicity and severe poison to the environment and health. The bioaccumulation of mercury leads to several toxicological effects, including cognitive and motion disorders, brain damage, kidney failure, and so on. Quantum dots are capable of detecting metal ions because of their good photostability, large surface-to-volume ratio, high emission quantum yields, and sizedependent emission properties. The nitrogen-doped carbon quantum dots are sensitive chemosensors for Hg2+ detection with a high quantum yield of 15.7% [26]. This kind of detection is based on the fluorescence quenching mechanism. The graphitic carbon nitride quantum dots with high blue fluorescence are also sensitive to Hg2+ because of the “superquenching” of fluorescence and thus are applied for the detection of Hg2+ and I− in aqueous media [27]. The graphene quantum dots have high ability for optical detection of Fe3+ ions [28]. Besides, the detection of biomacromolecules and small molecules also draws much attention. The 4-nitrophenol has been used extensively in daily life and chemical industry and is of high toxicity and carcinogenicity. A polymer-capped Mn-doped ZnS QDs with good selectivity can detect 4-nitrophenol based on fluorescence quenching. The detection limit is up to 76 nM for 4-nitrophenol in water [29]. Quantum confinement and edge effect of small QDs contribute to the photoluminescence. This has been widely used in the biological field. Zhu et al. [30] reported that graphene QDs with low toxicity and good biocompatibility exhibit strong fluorescence and are always considered to be the perfect bio-imaging agents. The Si-doped carbon QDs show high visible fluorescence and possess excellent bio-labeling ability and good capacity in resistance to photo-bleaching [31]. Quantum dots capped with molecules of functional groups can be utilized to immobilize macromolecules and small molecules. Graphene quantum dots have been applied for enzyme immobilization, due to good biocompatibility and high surface-to-volume ratio [32].

618

Emerging Photovoltaic Materials

Quantum dots have also been extensively used in photovoltaic and photocatalytic applications, because of the quantum confinement effect and multiple exciton generation. Graphene QDs (3–5 nm) are promising electron acceptor materials, which greatly improve the performance of P3HT-based solar cells [33]. The PbS QDs exhibit a wide photoresponse to solar spectrum and have always been employed as a light absorption layer in photovoltaics [34]. The CuInS2 QDs have been used in light-emitting diodes, due to its deep red emission, nontoxicity, and large Stokes shift performance [35]. Graphitic carbon nitride QDs with strong blue emission have been applied in metal-free photocatalytic systems under visiblelight-driven conditions [36].

16.3 Synthetic Methods for Quantum Dots Quantum dots attract extensive interests for fundamental research and advanced application, in light of their excellent physical and chemical properties. The synthesis of high-quality quantum dots is of great importance. To date, several methods have been reported [37–40], such as solid-state reaction, solvothermal, thermolysis, successive ionic layer adsorption and reaction, hot injection, and chemical bath deposition. In this section, three major synthetic methods are introduced with their corresponding historical developments and features: (1) hot injection for colloidal quantum dots with monodisperse feature, (2) chemical bath deposition for high surface coverage with random size distribution, and (3) successive ionic layer adsorption and reaction for high surface coverage and good size control.

16.3.1

Hot Injection

The hot injection was first practiced to synthesize semiconductor nanocrystals by Murray et al. in 1993 [41]. This method begins with the fast injection of organometallic precursors into a hot coordinating solvent [tri-n-octylphosphine oxide (TOPO)] to produce an instantaneously isolated nucleation. The nuclei grow up to form monodisperse nanocrystals. Thereafter, the hot injection has been modified in different ways. A few typical examples are listed below: (1) introduction of co-surfactants with linear and shorter chains that are less bulky, such as hexadecylamine (HDA) [42], octadecene (ODE), oleylamine (OLAM), and oleic acid (OA) [43], to synthesize nanocrystals with narrow size distribution; (2) ligand exchange (replacing primary capping materials with thiols,

Quantum Dot Solar Cells 619 amines, mercaptopropionic acid, or others) to improve the solubility of as-prepared nanocrystals; (3) water-based synthesis in consideration of biological environments; (4) inorganic passivation to improve the optical properties of quantum dots, such as CdSe/ZnS core-shell [42], InP/ZnS [44], CuInS2/ZnS [45], and so on. The hot injection introduces a cold precursor into a hot surfactant solution, which includes nucleation and growth processes [46]. Taking the synthesis of CdSe quantum dots as an example, a precursor solution of CdMe2 and Se in trioctyl phosphine was first prepared at room temperature [47]. The CdSe QDs were then fabricated by injecting the precursor solution into hot (300 C) trioctylphosphine oxide liquid. This resulted in the formation of CdSe nuclei, whereas subsequent nucleation was impeded on account of lowered temperature. A suspension of monodisperse CdSe nuclei was formed along with abundant free Cd and Se precursors. Subsequently, the CdSe nuclei gradually grew up as the temperature increased (below 300 C). The QD size increased accordingly. The TOPO molecules play an important role in controlling the growth rate by forming a spatial barrier for reactants. The as-prepared CdSe quantum dots can be transferred and dissolved in a reasonable organic solvent, finally forming colloidal suspensions. The suspensions are spatially stabilized, because of the TOPO molecules bonded to the surface Cd atoms. The nucleation and growth processes are completely isolated in hot injection. A size dispersion of (H1z)i,j (H3y)i,j+1 > (H1y)i,j + G

Yes

No

Yes

j = j +1 No

(My)i,j+1 = (My)i,j+1 – 0.05 (Mz)i,j+1 = (Mz)i,j+1 – 0.05

If j = n Yes

Yes

If i = m

(My)i,j+1 = (My)i,j+1 + 0.05 (Mz)i,j+1 = (Mz)i,j+1 + 0.05

No

j=1

End

Calculate the tilting angles, and , and orientation for Mi,j and Mi+1,j

if (H4z)i+1,j = (H2z)i,j (H4x)i+1,j = (H2x)i,j + G Yes

No

if (H4z)i+1,j > (H2z)i,j (H4x)i+1,j > (H2x)i,j + G

Yes

No

i=i+1 (Mx)i+1,j = (Mx)i+1,j – 0.05 (Mz)i+1,j = (Mz)i+1,j – 0.05

(Mx)i+1,j = (Mx)i+1,j + 0.05 (Mz)i+1,j = (Mz)i+1,j + 0.05

Figure 18.6 A flow chart to illustrate the special computational algorithm to compute the geometry of the non-imaging dish concentrator, which defines the initial orientations of all facet mirrors at the same height and then obtains final orientations of facet mirrors with gradually increased height so that all the facet images remain superimposed at the common receiver without sunlight blocking and shadowing among adjacent mirrors.

732

Emerging Photovoltaic Materials

used to calculate the final position as well as the two tilted angles, σi,j and γi,j, of each facet mirror. After obtaining the tilted angles of the facet mirror, coordinate transformation is applied to determine the orientation of the facet mirrors. The process of designing the position of facet mirrors is twofold: the first involves virtual lifting of the facet mirrors arranged in row sequence (j = 1, 2, 3 … n) along the same column in y–z axes, and the second involves lifting of the facet mirror arranged in column sequence (i = 1, 2, 3 … m.) along the same row in x–z axes. Figure 18.7a shows how to determine the new position of facet mirrors in the (j + 1)th row along y–z axes and it is considered free from sunlight blocking and shadowing effects when the following formulas are fulfilled.

(H3z)i,j+1 = (H1z)i,j

(18.15a)

(H3y)i,j+1 = (H1y)i,j + G

(18.15b)

Figure 18.7b shows how to determine the new position of facet mirrors in the (i + 1)th row along x–z axes, and it is considered free from sunlight blocking and shadowing effects when the following formulas are fulfilled (18.16a) (18.16b) In the simulation, important parameters must be inserted, such as focal distance of the NIDC (F), width of the facet mirror (w), and gap between the adjacent facet mirrors (G). As the squared facet mirror is considered in our case study, the length is equal to the width of the facet mirror. The gap between the adjacent facet mirrors is set to be 5% of the width or length of a single facet mirror. The coordinate of the facet mirror located closest to the origin, M1,1, is (½w+½G, ½w+½G, 0). Considering that the concentrator consisted of 2m columns and 2n rows, the computational algorithm will start to compute the final position of the facet mirrors located at the first column, i = 1 with row sequence starting from j = 1 to j = n. The same procedure continues for the following column from i = 2 to i = m. Details of the computational algorithm to simulate the configuration of the facet mirrors in the NIDC are summarized in the flow chart as shown in Figure 18.6.

Dense-Array Concentrator Photovoltaic System 733 Z

(H1)i,j+1 (H3)i,j+1 (H1)i,j

(H1)i,j+1

(H3)i,j

(H3)i,j+1 Y

O

(a)

Z (H2)i+1,j (H4)i+1,j (H2)i+1,j

(H2)i,j (H4)i,j

(H4)i+1,j X

O (b)

Figure 18.7 Conceptual drawing to illustrate on how the facet mirrors are virtually lifted up for eliminating sunlight blocking and shadowing in the computational algorithm. (a) Along y–z axes. (b) Along x–z axes.

18.3 Secondary Concentrator: An Array of Crossed Compound Parabolic Concentrator (CCPC) Lenses There are two major requirements for the geometrical design of secondary concentrators. The first requirement is to ensure that an exit aperture can match the shape and dimension of a CPV cell well. The second requirement is to ensure that the acceptance angle of the secondary concentrator is larger than the rim angle of NIDC so that the aperture of secondary optics is sufficiently large to subtend all the sunrays reflected by NIDC and maximize the sunlight to be concentrated onto the CPV cell. The high-efficiency multi-junction CPV cell, which is commercially available, is mostly either square or rectangle in shape. The CPV cells used in our study are a product of Spectrolab, with detailed specifications listed in Table 18.1 [24]. Thus, a square exit aperture is highly recommended instead of a circular exit aperture for the convenience to map the

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Emerging Photovoltaic Materials

Table 18.1 Specifications of non-imaging dish concentrator, crossed compound parabolic concentrator lens, secondary concentrator, CPV cell assembly, and CPV cell. Primary concentrator: Non-imaging dish concentrator (NIDC) Type of reflector

3 mm mirror with back metallic coating

Number of facet mirror

96 units

Dimension of facet mirror

20 cm × 20 cm

Array arrangement

Facet mirrors arranged into 10 rows and 10 columns with 4 facet mirrors in central region are removed

Focal distance

210 cm

Total reflective area

3.84 m2

Total projection area of reflector

3.76 m2

Range of solar rays reflected angle

8.6° to 36.7°

Crossed compound parabolic concentrator (CCPC) lens Dimension of entrance aperture

24 mm × 24 mm

Dimension of exit aperture

9.8 mm × 9.8 mm

Length, L

37.78 mm

Geometrical concentration ratio

5.998

Half-acceptance angle,

24.1°

i

Angular half-acceptance angle, θi

37.77°

Dielectric material

B270 superwite

Refractive index of dielectric material

1.5

Transmittivity of dielectric material

87.5%

Secondary concentrator: Array of CCPC lenses Array of CCPC lenses

8×8

Entrance aperture size

195.5 mm × 195.5 mm

Gap spacing between CCPC lenses

0.5 mm

Dense-Array Concentrator Photovoltaic System 735 CPV cell assembly (Spectrolab product: CCA 100 C3MJ Concentrator Cell Assembly) Dimension of CPV cell assembly

25 mm × 21 mm (Note: Original size is 25.5 mm × 21.0 mm as provided in the specification but we trim it to 25 mm × 21 mm)

Typical performance efficiency

38.5%

Ceramic carrier

Direct bonded copper with Au/Ni surface plating (front and back surfaces) on a Al2O3 substrate

Bypass diode

12A Schottky

CPV cell (Spectrolab product: CDO 100 C3MJ) Typical performance efficiency

38.5%

Dimension of cell aperture (active area)

9.85 mm × 9.89 mm (98.9 mm2)

Mechanical dimension of cell (including bus bar, etc.)

11 mm × 10 mm

Voc (1000 W/m2 irradiance)

2.77 V

Isc (1000 W/m2 irradiance)

14 mA

Operating temperature of CPV cell

−40°C to 100°C

concentrated sunrays across the CPV cell and to produce uniform illumination throughout the whole active surface area. For this reason, a typical candidate for the secondary concentrator with a square exit aperture would be a crossed compound parabolic concentrator (CCPC), which is formed by intersecting two symmetrical 2-D compound parabolic concentrators (CPC) orthogonally. In the perspective of geometrical optics for CCPC, all the sunrays that successfully enter the CCPC within the acceptance angle will emerge at the exit aperture. A dielectric filled CCPC with square cross sections in both entrance and exit apertures is tailored to match the dimension of the CPV cell assembly as shown in Figure 18.8. Each CPV cell assembly consists of a CPV cell, a bypass diode, and direct bonded copper with Au/Ni surface plating (front and back surfaces) on Al2O3 substrate. On the other hand, B270 superwite is selected as the dielectric material for CCPC lens as it is a clear

736

Emerging Photovoltaic Materials Crossed compound parabolic concentrator lens

Bypass diode External wire connector

CPV cell Direct bonded copper

Figure 18.8 A 2 × 2 array of CPV + CCPC assembly sets. Each CPV + CCPC assembly set is an integrated concentrator photovoltaic cell assembly and crossed compound parabolic concentrator lens. Each concentrator photovoltaic (CPV) cell assembly consists of a triple-junction CPV cell, a bypass diode, and direct bonded copper with Au/Ni surface plating (front and back surfaces) on Al2O3 substrate.

high-transmission crown glass (modified soda-lime glass) available in various forms and is affordable. A systematic process as shown in the flow chart described in Figure 18.9 has been applied to design the dimension of the CCPC lens well tailored to our application. Referring to Figure 18.10, Equations 18.17, 18.18, and 18.20 were derived by Winston et al., and Equation 18.19 can be derived from Snell’s law [25].

2a

i

(18.18)

sin 1 (n sin i )

i

CR

(18.17) i

a (1 sin i )cos sin 2 i

L

a a

2a sin

2

1 sin

2

i

(18.19)

n sin

2 i

(18.20)

In our design, the CCPC lens should have an exit aperture size of 2a  = 9.8 mm, which is slightly smaller than the active area of the solar cell, 9.85 mm × 9.89 mm, so that all sunrays arriving at the exit aperture can reach the active area of solar cell including the sunlight exiting near the

Dense-Array Concentrator Photovoltaic System 737 Determine the size of exit aperture, 2a’ of CCPC lens to match with the size of CPV cell

Determine the size of entrance aperture, 2a of CCPC lens to match with substrate size of CPV module to ensure the thickness of CCPC lens is minimum

Calculate the half acceptance angle, θ’i of CCPC lens based on the size of exit aperture, 2a’ and size of entrance aperture, 2a using Equation 1

Calculate length, L of CCPC lens using Equation 2 and angular half acceptance angle, θi of CCPC lens using Equation 3

End

Figure 18.9 Flow chart to show systematic process in designing dielectric filled CCPC geometry.

Exit aperture i

2a

’i

2a’

CCPC side wall

Entrance aperture L

Figure 18.10 Dielectric filled crossed compound parabolic concentrator with angular half-acceptance angle, θi of 37.77 . The square entrance aperture size, 2a is 24 mm; square exit aperture size, 2a is 9.8 mm; and the total length, L is 37.78 mm.

edge of the exit aperture. In the case study, the size of entrance aperture, 2a = 24 mm, is selected in order to match the dimension of the CPV cell assembly, 25 mm × 21 mm, as listed in Table 18.1 with the configuration as shown in Figure 18.8. The purpose of this selection is to ensure that the CPV cell assembly can be arranged closely to each other with a small

738

Emerging Photovoltaic Materials

tolerance of 0.5 mm in every side and to minimize the thickness of the CCPC lens because the absorptivity of sunlight by the dielectric material of CCPC is proportional to the entrance aperture size. The entrance aperture size of CCPC must be either the same or larger than the size of the CPV cell assembly so that all CCPC lenses can be arranged tightly to each other. The integrated design of CCPC and CPV is more efficient as compared to that of DACPV in terms of packing factor by reducing the percentage of sunlight that fell on the non-active area that incurs losses to the whole system. The final geometrical design of the CCPC lens is shown in Figure 18.10. The half-acceptance angle, θ i of CCPC geometry can be computed using Equation 18.17 as 24.1 . For the dielectric filled CCPC lens made of B270 glass material with refractive index 1.5, the angular half-acceptance angle, θi, of the CCPC lens can be calculated as 37.77 using Equation 18.19. There are two advantages of the CCPC lens against a reflector: it increases the acceptance angle due to refraction effect at the air–dielectric interface and it allows total internal reflection without any reflectivity loss. Since the focal distance (f ) is inversely proportional to the rim angle (θ) based on Equation 18.21, the rim angle can be reduced by increasing the focal distance in the case of the rim angle larger than the acceptance angle of CCPC (2θi). By fixing the acceptance angle of CCPC, the adjustment of focal length is necessary to ensure that all the concentrated sunlight from NIDC can be fully guided to the exit aperture. The length, L, of the lens is 37.78 mm, calculated with Equation 18.18. The geometrical concentration ratio of CCPC, defined as CR, is expressed in Equation 18.20 and is determined as 5.998. The sunlight concentrated by NIDC will be further concentrated by the CCPC lens. From Figure 18.11, the relationship between rim angle and focal distance can be expressed in the following equation:

2 tan

1

D 2f

(18.21)

where θ is the rim angle, D is the largest distance of central points between the two facet mirrors (the mirrors usually are located in opposite corners of the facet array), and f is the focal distance of the primary concentrator. Figure 18.12 shows a graph of difference between the acceptance angle and the rim angle, Δθ = 2θi – θ, versus optical power received by the DACPV receiver. The optical power impinging on the CPV cells will be increased when the difference between acceptance angle and rim angle is greater. In addition to optical loss, the larger tilted angles of primary facet mirrors at high rim angle can also increase the cosine loss.

Dense-Array Concentrator Photovoltaic System 739 The end of lines meeting at central point of entrance aperture of secondary concentrator

f

X

Z

D Y

Figure 18.11 Schematic diagram of non-imaging dish concentrator to show the dimension of rim angle ( ), focal distance (f ), and largest distance of central points between two flat facets located at opposite corners (D).

Difference between acceptance angle and rim angle (°)

The secondary concentrator is composed of CCPC lenses arranged into rows and columns to form a 2-D array as shown in Figure 18.13. The primary focused image size of 22.6 cm × 22.6 cm produced by the NIDC can be obtained from the simulated result as plotted in Figure 18.22a. The entrance aperture is placed at the focal plane of NIDC for collecting the concentrated sunlight from NIDC and each of the CCPC lenses will further focus the sunlight on their respective CPV cell. An array of 8 × 8 dielectric filled 20 15 10 5 0 –5

–10

3000

2950

2900

2850

2800

2750

2700

2650

2600

2550

–20

2500

–15

Optical power (W)

Figure 18.12 Graph to show the difference between acceptance angle and rim angle, Δθ = 2θi − θ, versus optical power accepted by DACPV receiver.

740

Emerging Photovoltaic Materials Row Column

(1,1)

Figure 18.13 An array of 8 × 8 dielectric filled CCPCs is arranged closely with a gap spacing of 0.5 mm between two adjacent lenses to form a secondary concentrator so that the total surface area 19.55 cm × 19.55 cm of the entrance aperture can match the primary focused image of NIDC. The lenses are divided into four symmetrical quadrants.

CCPC lenses is arranged closely with a gap spacing of 0.5 mm between two adjacent lenses to form a secondary concentrator so that the total surface area 19.55 cm × 19.55 cm of the entrance aperture can match the primary focused image of NIDC. The entrance aperture of the secondary concentrator is purposely designed to be slightly smaller than that of the primary focused image. Due to the solar disc effect, the peripheral region of the primary focused image with much lower solar concentration ratio as compared to that of the central region is omitted. It is to avoid imbalance in current generation by those CPV cells located in the peripheral region as compared to that of the central region and to subsequently cause current mismatch problem affecting the overall conversion efficiency of the whole module.

18.4 Concentrator Photovoltaic Module The CPV modules employed in this study are supplied by Spectrolab with the specification as listed in Table 18.1. The CPV module consists of a CPV cell and an aluminum oxide (Al2O3) substrate sandwiched by direct bonded copper substrates (DBC) on both sides with dimensions of 25 mm × 25 mm. The CPV cell was soldered on the surface of DBC to form a complete CPV module. Then, the CPV module was attached to the heat sink via Arctic Silver Adhesive. According to Spectrolab, the solar cell comprises three different types of p–n junctions that are sensitive to different spectral ranges of the solar spectrum, that is, GaInP (1.88 eV) at the top junction responsive to the range from 300 to 700 nm, GaInAs (1.41 eV) at middle junction responsive to the range from 500 to 900 nm, and Ge (0.67 eV) at the bottom junction responsive to the range from 800 to 1800 nm. The three junctions are

Dense-Array Concentrator Photovoltaic System 741 connected in series and hence the operating current of the solar cell is limited by the junction generated by the least current. In general, the optimal electrical performance of the solar cell is designed based on AM1.5 direct spectral irradiance as shown in Figure 18.14, and it is mainly described by the measured current versus voltage curve. When the solar cell is applied under local spectral irradiance different from AM1.5 standard spectrum, the electrical performance of the solar cell will be varied from the datasheet provided by Spectrolab due to the spectral mismatch. According to the datasheet from the manufacturer, current measurement demonstrates far better linearity than voltage measurement under different solar concentration ratio (SCR). The short-circuit current produced by the solar cell increases linearly with solar concentration ratio (SCR) from 1 sun to as high as 900 suns and thus the solar flux map on the receiver can be determined by purely measuring the short-circuit current of the solar cell. To protect CPV cells from reverse-bias breakdown that could cause permanent damage to the cells, every solar cell must be connected in parallel with a bypass diode in opposite polarity. When the cell is shaded or receives lower solar irradiance, the bypass diode is forward biased so that the current of the array can safely pass through the combination of cell– bypass–diode. For an array exposed to non-uniform solar irradiance, the role of bypass diode is very vital to avoid those CPV cells receiving low irradiance be the load of other CPV cells receiving high irradiance. The bypass diode creates an alternative path for the current so that the underperforming CPV cell is protected. When the array current passes through the bypass diode, the diode will turn on and hold the corresponding cell or group of cells to only a small negative voltage, which can help limit any further drop in the total voltage of the whole array [26]. External quantum efficiency (%)

100 90 80 70 60 50

InGaP

40

Ge

InGaAs

30 20 10 0 200

400

600

800

1000

1200

1400

1600

1800

2000

Wavelength (nm)

Figure 18.14 External quantum efficiency of the solar cell with respect to its wavelength of incident sunlight.

742

Emerging Photovoltaic Materials

18.5 Prototype of Dense-Array Concentrator Photovoltaic System (DACPV) To verify the principle of NIDC, a prototype of the DACPV system was constructed in the campus of Universiti Tunku Abdul Rahman, Malaysia, as shown in Figure 18.15. The primary concentrator of the DACPV system is an NIDC composed of 96 identical flat facet mirrors acting as optical apertures to collect solar irradiance from the sun and to superimpose all the facet images at the focal plane to form a reasonably uniform focused image. For the case study, we consider an NIDC configuration consisting of an array of 10 × 10 facet mirrors with dimensions of 20 cm × 20 cm each, and four facet mirrors in the central region under the shadow of receiver are omitted. The total reflective area of the NIDC is 3.84 m2, while the projection area of the facet mirrors is 3.76 m2 and the focal distance of the NIDC is 210 cm. A dual-axis sun-tracking method is employed to ensure that incident sunlight is always aligned with the optical axis of the NIDC prototype. Each flat facet mirror is tilted at two orientation angles based on its location in NIDC to reflect incident sunrays to a common target and thus different facet mirrors reflect incident sunlight at different angles of reflection. A Windows-based sun-tracking program has been developed to calculate the sun position angles using a general sun-tracking formula [27, 28]. Azimuth axis Computer Stepper motor

Optical encoder Elevation axis Stepper motor Optical encoder

Optical encoder adapter Stepper motor driver

Figure 18.15 Schematic diagram to show detailed control strategy of dense-array concentrator photovoltaic (DACPV) prototype in which the sun-tracking algorithm can communicate with a stepper motor driver and an optical encoder adapter via a computer. The DACPV prototype consisted of a non-imaging dish concentrator (NIDC) and a DACPV receiver. Inset picture is the DACPV receiver composed of an array of 8 rows × 8 columns of CPV + CCPC assembly sets installed at the focal plane of NIDC and the focal distance is 210 cm.

Dense-Array Concentrator Photovoltaic System 743 The dual-axis sun-tracking system is a structurally closed-loop control system, which can calculate the sun position angles according to date, time, and geographical information. During sun tracking, the program reads the orientation angles of the tracker by using two units of 13-bit optical encoders with each fixed at azimuth and elevation axes. Then, the program compares the readings with the calculated values of sun position angles. If the discrepancy is more than the encoder resolution, the program will command the stepper motor driver to drive the stepper motor in a sequential manner where it rotates the stepper motor in elevation axis followed by the other stepper motor in azimuth axis. Figure 18.15 shows a schematic diagram illustrating the detailed control strategy of the sun-tracking system in which the tracking algorithm can communicate with the stepper motor driver and the optical encoder adapter via a computer or microcontroller. The sunrays reflected by the facet mirrors at four corners have the largest incident angle relative to the receiver plane and thus the rim angle of NIDC is defined as the angle subtended by the light rays reflected by the two most distant facet mirrors, which are located at the top-left corner and bottom-right corner. Figure 18.11 shows a facet mirror located at one corner of the NIDC where its distance from the center of the NIDC in the x-direction and y-direction is 92.25 cm and 96.25 cm, respectively. The shortest vertical distance in the z-direction from the center of entrance aperture of secondary optics to the line joining the central points of two most distant facet mirrors is 183.86 cm. The rim angle is calculated as 71.9° by using Equation 18.21. The CPV cells assembled in the receiver of our prototype are a product of Spectrolab with mechanical dimensions of 11 mm × 10 mm and an active area of 9.85 mm × 9.89 mm. In this prototype, the CCPC lens was designed to have an exit aperture size of 9.8 mm, which is slightly smaller than the active area of the solar cell. The entrance aperture has a dimension of 24 mm so that it can match the dimension of a single-CPV module that consists of a CPV cell, a bypass diode, a ribbon bond connection, and a DBC substrate, 25 mm × 21 mm, as shown in Figure 18.8. The angular half-acceptance angle of CCPC lens is determined as 37.77° and the length of the lens is 37.78 mm. The CCPC lenses were fabricated using a dielectric material, B270 superwite, with refractive index, n = 1.52, and the geometrical concentration ratio of CCPC (defined as CR) is 5.998. The secondary concentrator is composed of CCPC lenses arranged into rows and columns to form a 2-D array as shown in Figure 18.16. A primary focused image size of 22.6 cm × 22.6 cm produced by the NIDC prototype can be obtained from the experimental result using an optical scanner. The entrance aperture is placed at the focal plane of NIDC for collecting the

744

Emerging Photovoltaic Materials

Figure 18.16 The DACPV receiver consisted of an array of 8 rows × 8 columns of CPV + CCPC assembly sets with a gap spacing of 0.5 mm between two adjacent CCPC lenses. The total aperture area of the DACPV receiver is 19.55 cm × 19.55 cm and all the CPV + CCPC assembly sets are fixed to copper heat sink via thermal adhesive.

concentrated sunlight from NIDC and each of the CCPC lenses will further focus the sunlight on their respective CPV cells. The CPV + CCPC assembly sets (assembly sets of a single dielectric filled CCPC lens coupled with a CPV module) are arranged closely in an array of 8 × 8 matrix with a gap spacing of 1 mm between two adjacent lenses to form a DACPV receiver with a total receiver area of 19.9 cm × 19.9 cm acting as the entrance aperture. Table 18.1 shows the specifications of the primary concentrator, the secondary concentrator, and the CPV cell of the DACPV prototype.

18.6 Optical Efficiency of the CCPC Lens Before the DACPV receiver has been constructed, optical analysis has been carried out to study the uniformity of solar flux distribution on each solar cell after the CCPC lens and the impact toward the performance. Figure 18.17 shows the simulated solar flux distribution on the receiver planes at the exit apertures of CCPC lenses located in the top-left quadrant of the full array. The flux distribution pattern and solar concentration ratio of the other three quadrants are similar to the simulated result in which their relationships are mirror symmetry to each other. Among all the concentrated flux at exit apertures, the SCR for the exit aperture of CCPC at the four corners of the complete array is the lowest when it is compared to the SCR for other CCPC lenses. It was reflected by the flux distribution

Dense-Array Concentrator Photovoltaic System 745 Row 952

(1,1)

Column

(1,2)

(1,3)

(1,4)

816

680

(2,1)

(2,2)

(2,3)

(2,4)

544

408

272

(3,1)

(3,2)

(3,3)

(3,4) 135

9.8 mm 0

(4,1) 9.8 mm

(4,2)

(4,3)

(4,4)

Solar concentration ratio (SCR)

Figure 18.17 Solar flux distribution at the exit aperture of the top left quadrant (first four rows and first four columns) of the CCPC array for the case of without pointing error during sun tracking.

pattern of the primary focused image with the lowest average SCR at the corner edge. The total average SCR at the CCPC position (4, 4) or central region of the secondary concentrator is 416 suns while the SCR is lower for those CCPC lenses located in the outermost ring with the lowest SCR at four corners. The overall uniformity of the solar flux distribution pattern is acceptable, in which the value of the peak-to-average ratio (PAR) of all exit apertures ranges from 2.08 to 2.35 as listed in Table 18.2. For the solar flux distribution in the full CCPV array, the average SCR for a 6 × 6 array of CCPC located in the central region of the receiver is 416 suns, but the average SCR ranges from 346 to 381 suns for CCPCs located at four edges of the 8 × 8 array. Baig et al. had done an extensive study on the non-uniform illumination in both concentrating solar cell and module. According to Baig et al., the non-uniform incident flux illuminated on the solar cell would affect the fill factor (FF) of the solar cell, which can reduce the maximum power output. In fact, it is very difficult to obtain uniform illumination as there are many factors that can cause non-uniformity such as the imperfection of optical geometry, aberration, geometrical error of concentrator profile caused by a

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Emerging Photovoltaic Materials

Table 18.2 The position of the crossed compound parabolic concentrator (CCPC) lens in the top-left quadrant of the full array and its corresponding peak-to-average ratio (PAR).

CCPC position

PAR

CCPC position

PAR

(1,1)

2.35

(3,1)

2.14

(1,2)

2.26

(3,2)

2.22

(1,3)

2.35

(3,3)

2.09

(1,4)

2.33

(3,4)

2.08

(2,1)

2.21

(4,1)

2.20

(2,2)

2.16

(4,2)

2.17

(2,3)

2.14

(4,3)

2.14

(2,4)

2.11

(4,4)

2.11

manufacturing defect, inaccurate sun tracking, optical misalignment of the solar concentrator, mechanical failures, and so on [29, 30]. To quantify different profiles of non-uniformity, Herrero et al. had introduced a parameter called peak-to-average ratio (PAR). They had characterized the non-uniform light patterns produced by optical systems and reproduced them on CPV cells in experiment to obtain the fill factor under different profiles of non-uniformity in which the percent variation of fill factor (FF) versus PAR of the multi-junction (MJ) solar cell is provided in Figure 18.18 [31].

Relative decrease in FF

0.16

Mask + MJ cell Fesnel lens + Pyramid + MJ cell Fesnel lens + Dome + MJ cell Fesnel lens + MJ cell

0.14 0.12 0.10 0.08 0.06 0.04 0.02 0

1

2

3

4

5

PAR

6

7

8

9

10

Figure 18.18 Percent variation of fill factor (FF) versus peak-to-average ratio (PAR) of the multi-junction (MJ) solar cell [31].

Dense-Array Concentrator Photovoltaic System 747 Considering CCPC located at (4, 4) with a peak SCR of 952 suns and an average SCR of 416 suns, the peak-to-average ratio (PAR) is only 952 ÷ 416 = 2.29. The PAR of illumination at the exit apertures of the CCPC lenses ranges from 2.08 to 2.35 in our study. From Figure 18.18, the nonuniformity with PAR below 2.5 will not significantly affect the fill factor of the CPV cell. The optical efficiency of the CCPC lens was determined by comparing between short-circuit currents generated by the CPV + CCPC assembly set and short-circuit currents generated by the CPV module in which both CPV cells were the same type. Since the concentrated solar flux illuminated on the DACPV receiver is only a direct component of solar irradiance, the relationship between the short-circuit current of the CPV module and direct normal irradiance (DNI) is important in the study of solar concentrator system performance. A calibration work was carried out to find out the short-circuit current of the CPV module that exposes to only DNI. When both CPV module and CPV + CCPC assembly set are directed toward the sun, they receive global solar irradiance (GSI) consisting of both direct and diffuse components of sunlight. The acceptance angle of the CPV module (180°) is much larger than the CPV + CCPC assembly set (75.54°). Hence, there is a need to develop an unbiased method to measure the short-circuit current generated by both the CPV module and the CPV + CCPC assembly set exposed to DNI only. To limit the acceptance angle of the CPV + CCPC assembly set, a rolled sand paper shaped into a tube with the rough surface inside was employed to limit the incident angle of 5° at the entrance aperture of CCPC, which is same as the acceptance angle of the pyrheliometer for measuring DNI only. By limiting the acceptance angle to 5°, the measured short-circuit current of the CPV + CCPC assembly set exposed to DNI only can be obtained as I scCCPC . For measurement done under a condition of 1 sun, the short-circuit current of the CPV module contributed by DNI only, I scDNI, can be computed using the following equation:

I scDNI

I scmeasured

DNI GSI

(18.22)

where I scmeasured is the measured short-circuit current of the CPV module (mA) exposing to GSI, DNI is the direct normal solar irradiance reading from the pyrheliometer (W m−2), and GSI is the global solar irradiance reading from the pyranometer (W m−2).

748

Emerging Photovoltaic Materials

After obtaining both I scDNI and I scCCPC, the measured solar concentration ratio of the CCPC lens, CRmeasured, can be computed using the following equation:

CRmeasured

I scCCPC I scDNI

(18.23)

Figure 18.19 shows an experimental setup of acquiring CRmeasured of a CPV + CCPC assembly set where the rolled sand paper tube is placed on the CPV + CCPC assembly set during data collection. From the measurement, the measured concentration ratios of CPV  + CCPC assembly sets range from 3.96 to 4.22. The small variation of CRmeasured can be explained by two reasons: (1) the alignment between the CCPC lens and the CPV cell is not exactly the same for different CPV + CCPC assembly sets; (2) the responsivity of the CPV cell can be slightly different from each other. The average CRmeasured was found to be 4.07, which is only 67.9% of the geometrical concentration ratio of 5.998 caused by optical losses. The optical losses can be grouped into the following reasons: (1) the absorption loss of the dielectric material; (2) Fresnel losses in the interfacing layers: between air and glass medium, between encapsulant

CPV + CCPC assembly set

CPV module

Pyrheliometer

Figure 18.19 Experimental setup for measuring the optical efficiency of a dielectric filled CCPC. Both the CPV + CCPC assembly set and a CPV module are mounted on the pyrheliometer to ensure their entrance apertures are normal toward the incident sunlight during measurement.

Dense-Array Concentrator Photovoltaic System 749 and CPV cell, and so on; (3) the loss caused by light rays with incident angle ranging from 26° to 37.77° (half of acceptance angle) escaping from the side wall of the CCPC lens. Fresnel losses in the interfacing layers can be analyzed using the Fresnel equation, which only happens when the sunlight travels from one medium to another medium with different refractive indices. For convenience, we consider the Fresnel losses in the case of normal incidence with Fresnel equation as expressed in the following [32]:

R

n1 n2 n1 n2

2

(18.24)

where n1 and n2 are the refractive indices for medium 1 (incident medium) and medium 2 (transmitted medium), respectively. According to Figure 18.20, for light rays traveling from air (n1 = 1) to the CCPC lens (n2 = 1.52) [33], the reflection loss at the entrance aperture of the CCPC lens can be calculated as 4.3%. For light rays traveling from the encapsulant (n1 = 1.46) [34] to the CPV cell (n2 =3.3) [35], the reflection loss is computed as 15%. The reflection loss ascribed to rays traveling from the CCPC lens to the encapsulant is negligible as refractive indices of both materials are quite similar. The absorption loss of the dielectric material, B270 superwite, is 12.5% and optical loss caused by light rays escaping from the sidewall is 3.1%. By taking into account the aforementioned losses, the total optical loss is 31%, which is 1.1% different from the measured optical loss. This small difference may be caused by the manufacturing error of the CCPC lens (slope error of sidewall surface) as well as misalignment between the CCPC lens and the CPV cell.

n1 = 1.52 (B270)

n3 = 3.3 (CPV cell)

n2 = 1.46 (Encapsulant)

Figure 18.20 Schematic diagram to show the sequential arrangement in cross-sectional view for the dielectric filled CCPC (B270 superwite), the encapsulant, and the CPV cell with their respective refractive indices.

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Emerging Photovoltaic Materials

18.7 Experimental Study of Electrical Performance The electrical interconnection of CPV + CCPC assembly sets in the DACPV receiver was designed based on the measured result of solar flux distribution at the receiver aperture of the NIDC prototype. It is important to minimize the current mismatch existing in dense-array CPV cells under non-uniform flux distribution so that the overall electrical output power can be maximized. For this purpose, we measured the concentrated flux distribution of the NIDC prototype using a high solar flux scanner with the experimental setup as shown in Figure 18.21 [36]. Figure 18.22b shows the scanned result of the concentrated solar flux with a total image area of 23 cm × 22.8 cm and a uniform illumination area of 17.0 cm × 16.8 cm in which the average solar concentration ratio within the uniform illumination area is 76 suns. By comparing between simulated and measured flux distribution as shown in Figure 18.22, the total image size agrees well with each other, but the uniform illumination area of the measured flux is about 2 cm smaller than that of the simulated flux in both x and y directions. This difference can be explained as the influence of imperfection in real conditions, that is, the circumsolar effect and slope error of facet mirrors. For effective power conversion, an optimized circuit layout of CPV + CCPC assembly sets was designed based on the measured flux distribution, which is worthwhile to highlight that it is the same as the optimized circuit layout based on simulated flux distribution as shown in Figure 18.23. A special method has been developed to determine I–V and P–V curves of the DACPV receiver for evaluating its on-site performance including

(a) NIDC prototype

(b) Concentrated solar flux scanner

Figure 18.21 Experimental setup for the measurement of the concentrated solar flux distribution of the NIDC prototype.

Dense-Array Concentrator Photovoltaic System 751

Y-Axis (cm)

10 8

90

6

80

4

70

2

60

0

50

–2

40

–4

30

–6

20

–8

10

–10 –8

–6

–4

–2

0 2 4 X-Axis (cm) (a)

6

8

10

X-Axis (cm) (b)

22.8 21.6 20.4 19.2 18.0 16.8 15.6 14.4 13.2 12.0 10.8 9.6 8.4 7.2 6.0 4.8 3.6 2.4 1.2 0

Y-Axis (cm)

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

–10

Solar concentration ratio

80–85 75–80 70–75 65–70 60–65 55–60 50–55 45–50 40–45 35–40 30–35 25–30 20–25 15–20 10–15 5–10 0–5 Solar concentration ratio

Figure 18.22 Solar flux distribution of the primary focused image produced by the nonimaging dish concentrator: (a) the simulated result; (b) the scanned result using a high flux scanner.

maximum output power and PCE. The proposed method of evaluating on-site performance begins with an important process in which three parameters must be measured concurrently for each basic module because they are highly dependent on DNI: short-circuit current Isc-module, open-circuit voltage Voc-module, and short-circuit current of the CPV module exposed to DNI only under 1 sun condition I scDNI-1sun . From the measured parameters of Isc-module and I scDNI-1sun at a particular DNI, the total solar concentration

752

Emerging Photovoltaic Materials (+)

(–)

Reference basic module

Figure 18.23 Optimized layout design for the electrical interconnection of CPV + CCPC assembly sets in the DACPV receiver.

ratios (SCRmodule) of each basic module can be computed using the following expression:

SCRmodule

I sc module I scDNI-1 sun

(18.25)

where SCRmodule is also defined as the summation value of solar concentration ratios for all individual CPV cells connected in parallel within the corresponding basic module. Please note that SCRmodule is used as a calibration constant, which allows us to compute the Isc-module at any particular DNI. Despite the DNI changing from time to time dependent on the weather condition, we can still compute Isc-module for any particular DNI using SCRmodule as expressed in Equation 18.25 after we have obtained SCRmodule

Dense-Array Concentrator Photovoltaic System 753 for all the basic modules. According to the Shockley equation with verification via our measurement, Voc-module of the basic module does not change noticeably for solar concentration ratio in the range between 250 suns and 350 suns (the range of solar concentration ratios after the CCPC lens in our prototype). If the parameters such as Isc-module and Voc-module for all the basic modules are known at any particular DNI, we can simulate the I–V and P–V curves of the full assembly module in the DACPV receiver using Simulink (see Figure 18.24). In order to validate the accuracy of the aforementioned method, we also conducted direct measurement to determine the operating current and voltage of the DACPV receiver connected to a load. The load applied in our measurement was made up of 11 units of wire wound resistors with a specification of 22 Ω and 100 W each. By connecting 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11 wire wound resistors in parallel, we can produce the load with effective resistance values of 11 Ω, 7.33 Ω, 5.5 Ω, 4.4 Ω, 3.67 Ω, 3.14 Ω, 2.75 Ω, 2.44 Ω, 2.2 Ω, and 2.0 Ω, respectively. The direct measurement of electrical performance for the DACPV receiver was carried out during the day of excellent clear sky with constant DNI for a long period of time to ensure that the operating condition of each load value is the same. After data collection on the operating currents and voltages for different load values within 20 min, we plotted the measured results on the simulated I–V and P–V curves at a particular DNI as shown in Figure 18.24. 18

500

16 400

12 300

10 8

200 6

Power (W)

Current (A)

14

I-V (experiment) P-V (experiment)

4

100

I-V (simulation)

2

P-V (simulation) 0

0 0

10

20

30

40

50

Voltage (V)

Figure 18.24 I–V and P–V curves of the DACPV receiver in our prototype where the maximum power is 503 W at a DNI of 789 W/m2 and a GSI of 973 W/m2. The direct measurement of electrical performance for the DACPV receiver was carried out during the day of excellent clear sky with constant DNI for a long period. The simulation curves produced via Simulink can match well with 11 measured operating points (indicated as triangle and square markers).

754

Emerging Photovoltaic Materials

18.7.1

Current Measurement Circuit

A current measurement circuit was designed and fabricated to measure short-circuit currents of multiple basic modules simultaneously. The circuit consists of two boards: a signal acquisition board and a transducer board. A transducer board consists of 13 units of Allegro ACS713 DC current sensors that can measure photocurrent using the Hall effect. The photocurrent flows through a copper conduction path generated by a magnetic field, which is sensed by the integrated Hall IC before it is converted into a proportional voltage. The Allegro ACS713 DC current sensor can measure photocurrents up to 30 A with an output sensitivity of 185 mV/A. The output voltage of the current sensor is then acquired by the signal acquisition board, which consists of Microchip PIC18F4550 40-pin USB microcontrollers and the 13-channel of a 10-bit Analog-to-Digital Converter (ADC) module. The microcontrollers communicate with a computer to carry out data acquisition from the transducer board. A command is sent from the computer to start the process of reading and converting analog voltage from the output of the Allegro ACS713 DC current sensor. The data are temporally stored in the memory of a microcontroller before they are finally saved to the computer in an Excel sheet. Figure 18.25 shows the schematic diagram for the configuration of the current measurement circuit. Figure 18.26 reveals the circuit layout of the current measurement circuit consisting of CPV modules, ACS713 DC current sensors, and a microcontroller. CPV + CCPC assembly set

Computer

Control command

Current (Analog signal)

Digital data

Microcontroller board

Hall effect sensor

Voltage (Analog signal)

Figure 18.25 Schematic diagram to show the configuration of the current measurement circuit for acquiring the short-circuit current of each basic module Isc-module in the DACPV receiver.

Dense-Array Concentrator Photovoltaic System 755 Current sensor 1 I+ Vout CPV module 1

I– Gnd

Microcontroller 10-bit ADC

D+

CH0

D–

USB

CH12

Current sensor 13 I+ Vout CPV module 13

I– Gnd

Figure 18.26 Circuit layout of the current measurment circuit consisting of CPV modules, current sensors, and a microcontroller.

Table 18.3 lists the measurement result of SCRmodule and Voc-module for all the basic modules in the DACPV receiver. The open-circuit voltages are almost the same for all basic modules because the open-circuit voltage does not change significantly with solar concentration ratio. Based on the measured data, we can calculate the average cell efficiency for each basic module, ηcell. The optical power incident onto solar cells in Table 18.3 SCRmodule, Voc-module, and average cell efficiency (ηcell) of each basic module according to their positions in the DACPV receiver. The measurement was carried out at a DNI of 826 W/m2 and a GSI of 985 W/m2. (*Shaded cells indicate that the rows of the module are connected in parallel.) 1136 suns, 3.92 V, 36.0%

1408 suns, 3.92 V, 35.0%*

1106 suns, 3.92 V, 36.1%

1105 suns, 3.92 V, 36.1%

1102 suns, 3.92 V, 36.1%

1110 suns, 3.92 V, 36.1%

1125 suns, 3.92 V, 36.0%

1111 suns, 3.92 V, 36.1%

1112 suns, 3.92 V, 36.1%

1110 suns, 3.92 V, 36.1%

1115 suns, 3.92 V, 36.1%

1117 suns, 3.92 V, 36.1%

1106 suns, 3.92 V, 36.1%

1105 suns, 3.92 V, 36.1%

1130 suns, 3.92 V, 36.0%

1408 suns, 3.92 V, 35.0%*

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Emerging Photovoltaic Materials

any basic module can be obtained by the multiplication of three parameters including SCRmodule, DNI, and active area of the solar cell (98.9 mm2). Electrical power generated by solar cells in any basic module can be simulated using Simulink provided that Voc-module and Isc-module are inserted into the model circuit. Finally, the average cell efficiency can be determined from the following expression:

Average cell efficiency ,

cell

Electrical power generated by solar cells Optical power incidentt onto solar cells (18.26)

Referring to Table 18.3, the average cell efficiencies for all basic modules in the DACPV receiver range from 35.0% to 36.1%, which has validated the claim made by Spectrolab in the specification sheet for this batch of triple-junction solar cells with a cell efficiency of 38.5%. With the measurement result, the values of Voc-module and Isc-module for all basic modules are inserted to the Simulink modeling circuit to simulate the I–V and P–V curves of the DACPV receiver as shown in Figure 18.24. From Figure 18.24, the measured operating point matches correctly the simulated I–V and P–V curves using Simulink where the maximum power is 503 W at a DNI of 789 W/m2 and a GSI of 973 W/m2. The system efficiency of the dense-array concentrator photovoltaic prototype is calculated as 17% using the following equation where the total projection area of NIDC is 3.76 m2.

Overall system efficiency ,

system

Maximum electrical output power DC DNI Total projection area of NID (18.27)

Table 18.4 The experimental data of the DACPV prototype under different weather conditions; DNI from 740 to 801 W/m2 in different days for repeatability test.

DNI (W/m2)

GSI (W/m2)

Vmp (V)

Imp (A)

Pmp (W)

740

949

36.10

13.41

484

17.4

764

1010

38.17

12.66

483

16.8

789

973

38.08

13.21

503

17.0

801

1010

36.11

13.41

484

16.1

system

(%)

Dense-Array Concentrator Photovoltaic System 757 The experiments have been repeated four times in different days for repeatability tests. It is well known that the major parameter to influence the output electrical power of the DACPV receiver is the DNI. For this purpose, we measured the system efficiency of the DACPV prototype, which is reasonably consistent, ranging from 16.1% to 17.4% under different weather conditions with DNI ranging from 740 to 801 W/m2. Table 18.4 shows the power conversion efficiency for four different cases with different DNI and GSI. In practical condition, the PCE of the DACPV system should be constant throughout the year.

18.8 Cost Estimation of the Dense-Array Concentrator Photovoltaic System Using Two-Stage Non-imaging Concentrators Table 18.5 provides a breakdown of the cost for constructing a single unit of the DACPV prototype consisting of NIDC and the array of 8 × 8 CPV + Table 18.5 Summary of the breakdown of the cost for constructing the prototype of the dense-array concentrator photovoltaic system. The quoted cost is based on the price of building one unit only. USD Aluminum frame

400.00

Bearing

87.50

Bolt, nut, and spring

75.00

CPV modules

960.00

An array CCPC lenses

380.00

Water pump

50.00

Cooling block

350.00

Worm gearboxes (2 units)

200.00

Stepper motors (2 units)

400.00

Optical encoders (2 units)

540.00

Flat facet mirrors

100.00

Control system

150.00

Total cost

3692.50

758

Emerging Photovoltaic Materials

CCPC assembly sets. The electrical power generated by the prototype is 503 W at a DNI of 789 W/m2 and the electrical power can be normalized to 638 W at a DNI of 1000 W/m2. The cost per watt of electricity produced by the proposed prototype is USD 5.8/W based on the price of building one unit only. The cost per watt can be further reduced when it involves mass production, optimizing the mechanical design and improving the overall PCE. From the feasibility study in terms of technical and economic analyses, the DACPV prototype has great potential to be cost competitive, compared with other types of renewable power generation systems in the future with appropriate efforts.

18.9 Conclusion The theoretical and experimental analyses of the DACPV prototype consisting of NIDC and the array of 8 × 8 CPV + CCPC assembly sets have been reported in detail. The dielectric filled CCPC is found as the most suitable type of secondary concentrator to increase the packing factor, acting as an optical funnel to guide the concentrated sunlight onto the CPV cell. Optical and electrical characterizations of the DACPV system have been carried out to evaluate the effects of different rim angles and pointing errors. Furthermore, the average cell efficiencies for all basic modules in the DACPV receiver were measured onsite in the range from 35.0% to 36.1%, which is very close to the laboratory test result conducted by Spectrolab at 38.5%. However, the system efficiency of our prototype system was determined in the range between 16.1% and 17.4% at DNI ranging from 740 to 801 W/m2. Consequently, the system efficiency only achieves almost half of the cell efficiency, which is mainly caused by the optical and electrical losses. Optical losses include primary concentrator loss attributed to imperfect reflectivity and soiling effects (normally added up to around 10%) and secondary concentrator loss (it was measured as 32.1%, where the measured average concentration ratio of CCPC lens is only 4.07 as compared to a geometrical concentration ratio of 5.998). The optical loss of CCPC can be reduced by fabricating the CCPC lenses using a low absorption material with anti-reflective coating at the interfacing layer. On the other hand, electrical loss is mainly caused by current mismatch in the electrical interconnection of CPV + CCPC assembly sets in the DACPV receiver. Therefore, we can conclude that our system efficiency has not reached its full potential yet, and there is still room for improvement to be made in the future.

Dense-Array Concentrator Photovoltaic System 759 The fabrication cost of a single-unit DACPV prototype is only USD 5.8/W, which is not very far from the commercial cost of a flat PV panel in a large-scale power plant. According to an International Renewable Energy Report in 2016, the cost of setting up on-grid commissioned and planned utility-scale flat PV projects between 2014 and 2018 ranges from USD 1.2 to USD 4.9/W depending on the capacity of the solar power plant. To analyze the future potential of the proposed DACPV technology, we can improve the economic prospect in five aspects. First, we can increase the PCE of the DACPV system, which is possible to be done by reducing the optical and electrical losses as well as using the latest multi-junction solar cells with a higher conversion efficiency at 46% (around 7.5% higher than our current solar cell). Second, the fabrication cost of the DACPV can conservatively be reduced at least by half if the whole system can be mass produced in the factory. Third, the sun-tracking mechanism equipped to the DACPV system can produce around 30%–40% more energy as compared to the fixed flat PV system. Fourth, the DACPV system allows waste recollection in the form of hot water at a temperature of 60°C–70°C that can be used in hot water showers in residential homes and in producing desalinated water or powering adsorption chillers in industries. Last, the cost of solar cells can be negligible if we can increase the solar concentration ratio to above 1600 suns with the current design by increasing primary focusing to more than 400 suns. We are currently working on an ultra-high solar concentration ratio of the DACPV system, but the effective cooling system is a very critical research problem for reducing the solar cell temperature to below 100°C. The DACPV system allows the use of an active cooling system that is a more effective method to cool down the solar cells operating under ultra-high concentration ratios. As a conclusion, our proposed DACPV system is still in the initial stage of development and it has great potential as an alternative photovoltaic technology to provide more options in harnessing the clean energy from the sun for sustainable development.

Acknowledgments The authors would like to express their gratitude to the Ministry of Energy, Green Technology and Water (AAIBE Trust Fund) with vote account 4356/001 and UTAR Research Fund 2016 Cycle 2 with project number IPSR/RMC/UTARRF/2016-C2/C04 and vote account 6200/CC2 for their financial support.

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References 1. Green, M.A., Emery, K., Hishikawa, Y., Warta, W., Dunlop, E.D., Solar cell efficiency tables (version 47). Prog. Photovolt.: Res. Appl., 23, 805–812, 2016. 2. Chong, K.K., Siaw, F.L., Wong, C.W., Wong, G.S., Design and construction of non-imaging planar concentrator for concentrator photovoltaic system. Renew Energy, 34, 1364–1370, 2009. 3. Chong, K.K., Wong, C.W., Siaw, F.L., Yew, T.K., Solar flux distribution analysis of Non-Imaging Planar Concentrator for the application in concentrator photovoltaic system. Conf. Rec. IEEE Photovolt. Spec. Conf., 132, 3013–3018, 2010. 4. Chong, K.K., Wong, C.W., Yew, T.K., Tan, M.H., Solar Concentrator Assembly, US Patent Application no: 13/901,519, (pending) filed on 23rd May 2013. 5. K.K. Chong, C.W. Wong, T.K. Yew, M.H. Tan, Dense-array concentrator photovoltaic system utilizing non-imaging dish concentrator and array of crossed compound parabolic concentrators, US Patent Application no: 14/462,891, (pending) filed on 19th August 2014. 6. Wong, C.W., Chong, K.K., Tan, M.H., Performance optimization of densearray concentrator photovoltaic system considering effects of circumsolar radiation and slope error. Opt. Exp., 23, A841–A857, 2015. 7. Yew, T.K., Chong, K.K., Lim, B.H., Performance study of crossed compound parabolic concentrator as secondary optics in non-imaging dish concentrator for the application of dense-array concentrator photovoltaic system. Sol. Energy, 120, 296–309, 2015. 8. Siaw, F.L., Chong, K.K., Wong, C.W., A comprehensive study of dense-array concentrator photovoltaic system using non-imaging planar concentrator. Renew Energy, 62, 542–555, 2014. 9. Chong, K.K., Lau, S.L., Yew, T.K., Tan, C.L.P., Design and development in optics of concentrator photovoltaic system. Renew Sustain Energy Rev., 19, 598–612, 2013. 10. Tan, M.H., Chong, K.K., Wong, C.W., Optical characterization of nonimaging dish concentrator for the application of dense-array concentrator photovoltaic system. Appl. Opt., 53, 475–486, 2014. 11. Tan, M.H., Chong, K.K., Influence of self-weight on electrical power conversion of dense-array concentrator photovoltaic system. Renew Energy, 87, 445–457, 2015. 12. Chong, K.K., Wong, C.W., Siaw, F.L., Yew, T.K., Optical characterization of nonimaging planar concentrator for the application in concentrator photovoltaic system. J. Sol. Energy Eng., 132, 011011-1–011011-9, 2010. 13. Lim, B.H., Chong, K.K., Lim, C.S., Lai, A.C., Latitude-orientated mode of non-imaging focusing heliostat using spinning-elevation tracking method. Sol. Energy, 135, 253–264, 2016.

Dense-Array Concentrator Photovoltaic System 761 14. Chong, K.K., Tan, M.H., Range of motion study for two different sun-tracking methods in the application of heliostat field. Sol. Energy, 85, 1837–1850, 2011. 15. Chong, K.K., Tan, M.H., Comparison study of two different sun-tracking methods in optical efficiency of heliostat field. Int. J. Photoenergy, 1–10, 2010. 16. Chen, Y.T., Chong, K.K., Bligh, T.P., Chen, L.C., Jasmy, Y., Kannan, K.S., Lim, B.H., Lim, C.S., Alias, M.A., Noriah, B., Omar, A., Sahar, S., Shk. Abd. Rezan, S.A.H., Tam, C.M., Tan, K.K., Non-imaging focusing heliostat. Sol. Energy, 71(3), 155–164, 2001. 17. Chen, Y.T., Chong, K.K., Lim, B.H., Lim, C.S., Study of residual aberration for non-imaging focusing heliostat. Sol. Energy Mater. and Sol. Cells, 79(1), 1–20, 2003. 18. Chen, Y.T., Chong, K.K., Lim, C.S., Lim, B.H., Tan, B.K., Lu, Y.F., Report on the second prototype of non-imaging focusing heliostat and its application in food processing. Sol. Energy, 79(3), 280–289, 2005. 19. Chen, Y.T., Chong, K.K., Lim, C.S., Lim, B.H., Tan, K.K., Omar, A., Bligh, T.P., Tan, B.K., Ghazally, I., Report of the first prototype of non-imaging focusing heliostat and its application in high temperature solar furnace. Sol. Energy, 72(6), 531–544, 2002. 20. Chen, Y.T., Kribus, A., Lim, B.H., Lim, C.S., Chong, K.K., Karni, J., Buck, R., Pfahl, A., Bligh, T.P., Comparison of two sun tracking methods in the application of heliostat field. ASME J. Sol. Energy Eng., 126(1), 1–7, 2004. 21. Chong, K.K., Optical analysis for simplified astigmatic correction of nonimaging focusing heliostat. Sol. Energy, 84(8), 1356–1365, 2010a. 22. Chong, K.K., Optimization of nonimaging focusing heliostat in dynamic correction of astigmatism for a wide range of incidence angles. Opt. Lett., 35(10), 1614–1616, 2010. 23. Chong, K.K., Lim, C.Y., Hiew, C.W., Cost-effective solar furnace system using fixed geometry non-imaging focusing heliostat and secondary parabolic concentrator. Renew Energy, 36(5), 1595–1602, 2011. 24. Spectrolab Inc.,CCA 100 C3MJ concentrator cell assembly, http://www. spectrolab.com, 2010. 25. Winston, R., Minano, J.C., Benitez, P., Nonimaging Optics, pp. 50–57. Elsevier Academic Press, Burlington, 2005. 26. Karatepe, E., Boztepe, M., Colak, M., Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells. Sol. Energy, 81, 977–992, 2007. 27. Chong, K.K., Wong, C.W., General formula for on-axis sun tracking system and its application in improving tracking accuracy of solar collector. Sol. Energy, 83, 298–305, 2009. 28. Chong, K.K., Wong, C.W., Siaw, F.L., Yew, T.K., Ng, S.S., Liang, M.S., Lim, Y.S., Lau, S.L., Integration of on-axis general sun-tracking formula in the algorithm of open-loop sun tracking system. Sensors, 9, 7849–7865, 2009. 29. Baig, H., Heasman, K.C., Mallick, T.K., Non-uniform illumination in concentrating solar cells. Rew. Sustain. Energy Rev., 16(8), 5890–5909, 2012.

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30. Baig, H., Sarmah, N., Heasman, K.C., Mallick, T.K., Numerical modelling and experimental validation of a low concentrating photovoltaic system. Sol. Energy Mater. Sol. Cells, 113, 201–219, 2013. 31. Herrero, R., Victoria, M., Dominguez, C., Askins, S., Anton, I., Sala, G., Concentration photovoltaic optical system irradiance distribution measurements and its effect n multi-junction solar cells. Prog. Photovoltaics Res. Appl., 20, 423–430, 2012. 32. Quimby, R.S., Photonics and Lasers: An Introduction. Wiley, Hoboken, 2006. 33. Schott Desag, Specification: Physical and Chemical Properties B270 Superwite, 2000. 34. Norris, A., Powell, N., Ketola, B., Cotsell, J.M., McIntosh, K.R., Advanced silicone photovoltaic Encapsulants, http://www.downcorning.com/content /publishedlit/Advanced_Silicone_Photovoltaic_Encapsulants_-_FuturePV .pdf, 2010. 35. Diedenhofen, S.L., Grzela, G., Haverkamp, E., Bauhuis, G., Schermer, J., Gomez Rivas, J., Broadband and omnidirectionnal anti-reflection layer for III/V multi-junction solar cells. Sol. Energy Mater. Sol. Cells, 101, 308–314, 2012. 36. Wong, C.W., Chong, K.K., Solar flux distribution study if non-imaging dish concentrator using linear array if triple-junction solar cells scanning technique. Sol. Energy, 125, 86–98, 2016.

19 Solar Radiation Analysis Model and PVsyst Simulation for Photovoltaic System Design Figen Balo1* and Lutfu S. Sua2 1

Industrial Engineering Department, Firat University, Elazig, Turkey 2 Industrial Engineer, Turkey

Abstract

Transportation problems of the conventional energy sources bring out the use of renewable energy sources. Environmental issues also play a role in the choice of the use of renewable energy sources. Yet today, rather than environmental requirements, the use of renewable energy has become increasingly important because of strategies used by the developed countries to meet their energy demands. Correspondingly, in recent years, all countries have been working to increase the share of renewable energy among other energy production methods to ensure energy independence. In this study, in order to design photovoltaic (PV) system for maximum efficiency under climatic conditions, solar radiation analysis for a chosen area is conducted. The system is then modeled through the PVsyst simulation software before the PV system is actually set up. Various panels are evaluated in order to determine the ones that are more efficient than the others under the circumstances in which the system is installed. Additionally, by using PVsyst simulation software, information is provided not only about gains and losses of the system but also about system efficiency. The aim of this study is to model a PV system under a set of circumstances and ensure the most appropriate and efficient panel selection under the environmental conditions to achieve results closer to real environment conditions of the PV system through the PVsyst simulation program. This research involves three stages. The solar energy characteristics and potential of a selected region is initially evaluated based on the available data. In the second stage, solar radiation analysis is conducted on Matlab platform using radiation models. Numerous models exist in the literature to calculate the amount of solar radiation reaching any surface on the Earth. Solar radiation models aim to reach solutions taking the conditions of

*Corresponding author: [email protected] Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (763–785) © 2019 Scrivener Publishing LLC

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specific regions into consideration. Solar radiation is a significant determinant of the feasibility of solar energy systems to be installed. Due to the lack of meteorological data available for various reasons, a large number of models have been developed to estimate the levels of solar radiation. However, the appropriateness of these models greatly depends on the climatic and environmental characteristics. This is in fact one of the main reasons that increases the number of available models. Finally, the PV system is simulated using PVsyst software. The values of solar radiation in this case are evaluated to be at acceptable efficiency levels to design a photovoltaic system. Although data for a specific case is used here for the purpose of model verification, this study aims to establish a reference for choosing the most efficient solar panel by relying on the solar radiation values obtained for the most efficient photovoltaic system design. The analysis can be further extended to the various cities in existing climatic regions of countries and develop country-wide solar radiation models. Keywords: Photovoltaic systems, solar energy, panel efficiency, renewable energy, data analysis, pvsyst simulation

19.1 Introduction Energy consumption is gradually increasing worldwide and is related with population increase, industrialization, and technological advances. In relation with this fact, current potential of non-renewable energy resources is decreasing. Using 0.1% of known fossil-based energy resources, based on the current consumption rates obtained by calculations, the available resources are expected to be used up in less than 100 years [1]. Solar energy has the greatest potential among the other energy resources in terms of application fields [2]. The popularity of solar energy as an energy topic on which intensive researches have been conducted continues to increase. This has a lot to do with solar energy not only being a relatively new and renewable energy source but also eliminating hazardous wastes and not requiring complex technology [3]. The sun is an energy source of radiation equal to the black mass at 6000°C. The level of temperature reaches up to 20,000,000°C at its center. At such high temperatures, the hydrogen is split into smaller atoms, releasing electrons [4]. Energy reaching the Earth in one day is 15,000 times greater than the world’s consumption [5].

19.1.1 Solar Energy in Turkey The solar energy potential of Turkey is highly competitive compared to many countries due to it being geographically close to the equator. Based

Solar Radiation Analysis Model and PVsyst Simulation 765 on the studies measuring the solar energy potential of Turkey, it is possible to take advantage of solar energy for 10 months in 63% and 12 months in 17% of the country [6–7]. Turkey has seven geographic regions, and each of them has different climate conditions due to different geographic conditions and altitude effect. The annual total solar energy period and the amount of solar energy in each of these regions are presented in Figure 19.1a. As presented in Figure 19.1b, more than half of Turkey possesses high potential of sunshine. Based on the study carried out by the General Directorate of Electrical Power Resources (EIE), the average annual sunshine duration in Turkey is calculated to be 2640 h (daily total of 7.2 h) and the average radiation intensity is 1311 kWh/m² year (daily total of 3.6 kWh/m²). The installed solar energy system power of Turkey is expected to reach the level of 3360 MW when all the licensed and unlicensed systems that have been approved and/or in the process of being built become online by 2017. Annualy, 4.905 billion kWh of renewable energy will be produced from the sun. This amount of production currently totals up to 1.85% of the electricity demand of Turkey [8]. The amount of solar radiation of Turkey is presented in Figure 19.2a. In Figure 19.2a, the annual average is observed to be 4175 kWh/m2 day. Moreover, this value is being exceeded in April, May, June, July, August, and September.

Considering the average hourly sunshine period in months, the annual average sunshine is 7,49 h while it is higher in May, June, July, and August as shown in Figure 19.2b.

Annual Total Solar Energy in 1168 Geographic Regions (kWh/m2 - year) S.E. Anatolia

1120

1460

2409

Sunshine Duration of Regions (Hours/year)

1971

2993

Mediterranean

S.E. Anatolia Mediterranean Eastern Anatolia

Eastern Anatolia Central Anatolia Central Anatolia

1304

1365

1314

Aegean Aegean Marmara Black Sea

Marmara

2738

2664

2628

Black Sea

2956

(a)

(b)

Figure 19.1 (a) Annual total solar energy in Regions (kWh/m2 year). (b) Annual total solar energy period (hour year).

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7

12

6

10

5

8

4 3 2

6 6.576.5 6.14 5.81 4.93 4.81

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1

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0

4

11.31 10.81 10.7 9.1 9.23

(a)

January February March April May June July August September October November December Annual Average

766

(b)

Figure 19.2 (a) Daily total solar radiation of Turkey (kWh/m2 day) [8]. (b) Daily total sunshine duration of Turkey [8].

19.1.2 Climate, Solar Energy Potential, and Electric Production in Erzincan The land and sunshine period are of great significance for facilities to be established based on solar energy. Thus, comprehensive investigation about climate, solar energy potential, and current facilities needs to be undertaken. For the purpose of this study, Erzincan with continental climate characteristics is chosen. The region shows variance due to its geographic structure and it being surrounded with mountains. It has a warmer climate than almost all other cities in its region. The annual temperature average is 16.6°C. The average in January—the coldest month—is −3.7°C, while the average in August is 23.9°C. Erzincan has longer summers with higher temperature levels compared to the surrounding cities. The annual humidity average is 62% [9]. Erzincan, with a total of 1600–1700 kW/m2 year solar radiation, has a higher sunshine potential than most of the cities in Turkey. Monthly values of total solar radiation and sunshine period during the day are presented in Figure 19.3a and b, respectively. Comparing the figures in Figure 19.3 with Turkey averages, the daily total of solar radiation is close to Turkey’s average overall, while the daily total of the sunshine period is usually higher than the average of Turkey. According to the sunshine intensity shown above, the installed power of electricity plants in Erzincan is 307 MW. These plants generate around

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8 7 6 5 4 6.37 6.74

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Figure 19.3 (a) Monthly total solar radiation a day in Turkey (kWh/m2 day) [8]. (b) Monthly total sunshine period a day in Erzincan [8]. (c) Daily and hourly radiation comparison of Erzincan and Turkey.

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909 GW of energy annualy. The ratio of this production level to the installed power is 0.41%. It is also equal to 0.36% of consumption in Turkey [9]. The next section aims to analyze solar radiation data of the region in Matlab software so that it can be used in the simulation stage of the research.

19.2 Data Analysis Model for Solar Radiation Intensity Calculation 19.2.1 Horizontal Surface 19.2.1.1 Daily Total Solar Radiation Average solar radiation, radiation function frequency, radiation function phase shift, and latitude values for the region are provided below: Iort (MJ/m2 day): FGI (MJ/m2 day): FKI: Latitude:

12.3 6.90 2.46 39.44

Total solar radiation on a horizontal surface on a given day can be calculated using the equation below [10]:

I

I ort FGI cos

2 (n FKI) 365

(19.1)

where n: days, FKI: radiation function phase shift, FGI: radiation function frequency, and Iort: annual average of daily total radiation.

19.2.1.2 Daily Diffuse Solar Radiation Daily total diffuse solar radiation on a horizontal surface can be calculated using Equation 19.2.

Io = I(1 − B)2 (1 + 3B2)

(19.2)

Solar Radiation Analysis Model and PVsyst Simulation 769 where, Io: out-of-atmosphere radiation, B: transparency index.

19.2.1.3 Momentary Total Solar Radiation Momentary total solar radiation on a horizontal surface can be calculated using Equation 19.3.

Io

24

I s cos(e )cos(d )sin w s

w s sin(e )sin(d ) f

(19.3)

where Is (W/m2) is the solar constant, e is the latitude angle, ws is the sunrise hour angle, f is the solar constant correction factor, and d is the declination angle, which can be calculated using the related tables and equations. Out-of-atmosphere radiation can be calculated using Equation 19.4 [11].

I ts

Ats cos

t gi

(t 12)

(19.4)

where Its: momentary total solar radiation Ats: function frequency, and tgi, : imaginary day length.

19.2.1.4 Momentary Diffuse and Direct Solar Radiation The amount of momentary diffuse and direct solar radiation on a horizontal surface can be calculated using Equations 19.5 and 19.6 [12–13], where Ays is the function frequency.

I ys

Ays cos

tg

(t 12)

Ids = Its − Iys Iys: momentary diffuse solar radiation Ids: momentary direct solar radiation

(19.5)

(19.6)

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19.2.2 Calculating Solar Radiation Intensity on Inclined Surface 19.2.2.1 Momentary Direct Solar Radiation Momentary direct solar radiation on inclined surfaces (30°–60°–90° angles) can be calculated using the equations below [13–15].

Ibc = IbRb

(19.7)

Ibc: momentary direct solar radiation

Rb

cos cos

(19.8) z

cos z = sin d sin e + cos d cos e cos w

(19.9)

cos = sin d sin (e − ) + cos d cos (e − ) cos w

(19.10)

19.2.2.2 Momentary Diffuse Solar Radiation The value of momentary diffuse radiation on an inclined surface can be calculated using the equation below [13–16].

Iye = RyIys

(19.11)

Iye: momentary diffuse solar radiation The conversion factor Ry for diffuse radiation can be calculated using the equation below:

Ry

1 cos(a) 2

(19.12)

The Ry parameter provides the slope of the surface. For vertical surface (a = 90 ), the Ry value is 0.5. This way, momentary values of diffuse radiation on inclined surfaces with 30°, 60°, and 90° angles in Erzincan for a 24-h time period can be calculated.

Solar Radiation Analysis Model and PVsyst Simulation 771

19.2.2.3 Reflecting Momentary Solar Radiation Reflecting radiation on an inclined surface [13–16] can be calculated using the equation below:

I ya

I ts p

1 cos(a) 2

(19.13)

Iya: momentary reflecting solar radiation The environment reflection rate is shown with the ρ parameter and used with the average value of ρ = 0.2 in calculations.

19.2.2.4 Total Momentary Solar Radiation The momentary total radiation on an inclined surface [13–16] can be calculated using the equation below:

It = Ide + Iye + Iya

(19.14)

19.2.3 Data Analysis and Discussion Figure 19.4 provides the values of (a) change in annual momentary total solar radiation values for a 24-h time period, (b) change in annual momentary diffuse solar radiation values per hour, and (c) change in annual momentary direct solar radiation values for a 24-h time period on a horizontal surface in Erzincan. As it can be seen in Figure 19.5, the highest value of momentary total solar radiation on a horizontal surface in Erzincan is 1.4742 W/m2 observed on the 355th day of the year, at 12:00. Figure 19.5 provides the daily changes of (a) total solar radiation values per day, (b) declination angle, (c) hourly angle for sunrise, (d) solar constant for correction factor, (e) solar radiation values out of atmosphere, (f) graph of function frequency (Ays), (g) diffuse solar radiation (Ats), and (h) transparency index (B) in Erzincan for a horizontal surface. The highest value of function frequency for a horizontal surface in Erzincan is observed as 1.3984 on the 355th day. The highest values of declination angle, sunrise angle, and out-of-atmosphere radiation are observed to be 21.4848 , 108.9178 and 257,601 W/m2, respectively, on the 172nd day of the year. While the transparency index reaches its peak

Emerging Photovoltaic Materials

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0

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0

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Figure 19.4 Change of annual solar radiation values for a 24-h period on a horizontal surface.

(0.1518) on the 80th day, its lowest value (0.0039) is seen on the 266th day. The lowest (0.9670) and highest (1.0322) values for the solar correction factor occur on the 182nd and 365th days, respectively. Values of momentary direct radiation with three different angles (30 , 60 , and 90 ) for a 24-h time period are provided in Figure 19.6. The

Momentary total radiation (It)

1.15 1.14 1.13 1.12 1.11 1.10 1.09 0

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×103 3.0 2.5 2.0 1.5 1.0 0.5 0 –0.5 –1.0 –1.5 –2.0 0 50

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Figure 19.5 Solar radiation on a horizontal surface.

highest values for all three angles are obtained on the 355th day at 12:00, while the lowest values are obtained on the same day at 03:00. Idbmax values are measured as 1.3299, 1.0690, and 0.7127 W/m2 for 30 , 60 , and 90 , respectively. Idbmin values are 1.3216, 1.0624, and 0.7082 W/m2 for the same angles.

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(c)

Figure 19.6 Annual momentary direct radiation values on an inclined surface for a 24-h period at (a) 30°, (b) 60°, (c) 90°.

Values of momentary direct radiation with three different angles (30 , 60 , and 90 ) for a 24-h time period are provided in Figure 19.6. The highest values for all three angles are obtained on the 355th day at 12:00, while the lowest values are obtained on the same day at 03:00. Idbmax values are measured as 1.2880, 1.0363, and 0.7127 W/m2 for 30 , 60 , and 90 ,

Inclined surface momentary diffuse radiation (IbB)

Solar Radiation Analysis Model and PVsyst Simulation 775

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(b)

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Days (d) (c)

Figure 19.7 Annual momentary diffuse radiation values for inclined surfaces at (a) 30°, (b) 60°, (c) 90°.

respectively. Idbmin values are 1.3216, 1.0624, and 0.6913 W/m2 for the same angles. Annual momentary diffuse radiation values for three angles (30 , 60 , and 90 ) are provided in Figure 19.7. The lowest values are measured on the 175th day at 02:00 as −0.2533, −0.2538, and −0.2554 W/m2, respectively.

Inclined surface momentary radiation [hourly] (IrB)

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(b)

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300

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Days (d) (c)

Figure 19.8 Annual total momentary radiation values for an inclined surface at (a) 30°, (b) 60°, (c) 90°.

Annual values of total momentary solar radiation for 24-h periods are provided in Figure 19.8. The lowest values for 30 , 60 , and 90 angles are measured on the 355th day at 03:00 as −0.0585, −0.2185, and −0.4352 W/m2, respectively. Total momentary solar radiation for annual angle and hours are provided in Figure 19.9.

Momentary total radiation based on annual angle and hourly (It)

Solar Radiation Analysis Model and PVsyst Simulation 777

1.5 0.1 0.5 0 –0.5 –1.0 –1.5 400

350

300

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50

Days (d)

0

0

5

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Figure 19.9 Total momentary radiation for annual angle and hours.

19.3 PVSyst Simulation for the Solar Farm System Design 19.3.1 Methodology This section aims to provide a simulation of the PV system, using the real data and analysis conducted. One of the most important equipment of solar energy systems is the panels. They have a significant impact on the efficiency of the energy facility. Photovoltaic panels are built with connecting PV modules (serial or parallel) composed of solar batteries. The efficiencies of the panels are in constant increase. The efficiency level of 4% in the 1950s has increased up to around 15% today [9]. The increased efficiency of the panels used in the system results in a smaller number of panels, which means a smaller area to build the system. Thus, initial investment cost decreases consequently. There are many researches being conducted by universities and organizations worldwide to increase the panel efficiency above 15% [18]. PVsyst is the most popular software for PV system simulation and data analysis. Simulations run on the software are based on the real and updated data on its database, which results in highly realistic outputs. It imports the radiation data of the area that the system would be built on from the database of Metenorm. Topographic characteristics of the area can also be defined into the system. This software also enables drawing conclusions on the energy efficiency considering the panel difference [19]. Within the context of this study, panel comparison is made using the PV system simulation PVsyst software. An appropriate location where energy efficiency can be high is selected based on the solar energy potential atlas. A solar field of 20,000 m2 within the Erzincan University campus

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is determined for this purpose, and system design simulation is run using diffrerent panel types of 1-MW power. The coordinates of the area is as follows: latitude, 39.81; longitude, 39.38; height, which is another factor affecting the panel efficiency, is 1353 m [20]. The selected area is 10 km away from the city center. The selected region’s radiation temperature and wind values per square meter are shown, via the PVsyst program, in Figure 19.10. These values are added into the system memory from the meteonorm database via PVsyst. Annual global radiation, diffuse radiation, temperature, and wind values in 2015 are obtained from the system as 1486.9 kW/m2 mth, 616.1 9 kW/ m2 mth, 10.4 C, and 2.0 m/s, respectively. In 2015, the highest temperature values were measured in July and August while the global radiation value has reached its peak in August, and wind speed was the highest in April. While designing the system, the slope and direction of the panel must be determined first; 32 of panel slope and 0 azimuth were determined experimentally while the optimum slope and azimuth are given in Figure 19.11. Panel slope and azimuth angle are observed at the optimum point as indicated in Figure 19.12. System elements are chosen after determining the panel angle and slope. For the 1-MW system, an invertor (Power-one brand) with 28 kW power, a monocrystalline of 260 Wp power (Jinkosolar), a monocrystalline panel with the same power (Zhinesolar), and finally 260-W monocrystalline panels (Phonosolar) are chosen for research purposes. A total of 33 invertors, 22 panels serially tied to each other, and 198 series established from this group of panels were put together in the system. Consequently, the efficient design of the system is approved. A

Figure 19.10 Monthly values of global irradiation, diffuse, temperature, and wind for Erzincan-Yalnizbag.

Solar Radiation Analysis Model and PVsyst Simulation 779

Figure 19.11 Optimum panel and azimuth angle.

Figure 19.12 Screen where PVsyst system components are defined.

total of 4356 panels are used. Figure 19.12 presents the screen where system elements of PVsystem are defined. Natural cooling, dust, and particle ratio are defined to be 1%, since the system is on the ground and outdoors. In the city center, this value is 2% and higher. For facility maintenance and shortages, a loss ratio is also

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Emerging Photovoltaic Materials

defined. Moreover, cable loss and electrical transformer loss are chosen to be 2.5% and 1%, respectively. Invertors are also in need of energy when the system is installed. This is known as loss of night work, and it shows how much energy the invertor consumes during the night. The value for the invertor chosen in this research is 8 W, which results in 264 W loss during the night since there are 33 invertors in the system.

Figure 19.13 Variation of shading amount depending on the angle of solar rays.

Figure 19.14 Horizon graphic.

Solar Radiation Analysis Model and PVsyst Simulation 781

19.3.2 Findings Obtained with PVsyst Simulation After designing the system, the simulation is executed and the results are discussed. The shading effect is of great significance for solar energy designs. The amount of shading on panels lined up with a 9-m distance from each other is provided in Figure 19.13. The shading of the system with 0 azimuth angle does not occur until it decreases down to 10 ; 80% shading is seen under 2 , but the sun starts to fade at 2 . Hourly data can be obtained in case of showing shading analysis with a horizon graphic. The shading analysis horizon diagram is presented in Figure 19.14.

(a)

(b)

(c)

Figure 19.15 (a) PVsyst analysis outcome productivity of (a) Jinkosolar, (b) ZNshinesolar, (c) Phonosolar brand invertor.

System production

1583 MWh/year

1584 MWh/year

1547 MWh/year

Panel

Jinko

Znshine

Phono-solar

1366 kWh/kWp/year

1392 kWh/kWp/year

1398 kWh/kWp/year

Specific production

Table 19.1 Panel types and productivity values.

0.818

0.833

0.837

Performance ratio

0.63 kWh/kWp/day

0.55 kWh/kWp/day

0.54 kWh/kWp/day

Array losses

0.20 kWh/kWp/day

0.21 kWh/kWp/day

0.21 kWh/kWp/day

System losses

782 Emerging Photovoltaic Materials

Solar Radiation Analysis Model and PVsyst Simulation 783 The area numbered 1 on the horizon graph in Figure 19.14 shows summer days, whereas the 7th area shows winter. The steepest angle on line 1 is measured to be approximately 74 between 11:00 and 12:00. During winter, when the sun’s angle of incidence drops down to 30 , the panels are exposed to shade because of the lines under the shading line. The system productivity of panel brands Jinko 260W, Phonosolar 260W, and Znshine 260W monocrystal modules is presented in Figure 19.15. Significant values obtained from the abovementioned simulation results are provided in Table 19.1.

19.4 Conclusions There is no doubt that solar energy systems will contribute to the global energy supply at a greater extent in the future. In order to catch up with advances in this technology, the knowledge and skill available on solar battery technology and PV systems need to be disseminated effectively. Especially in large field projects like solar energy stations, the system parameters need to be assessed critically and the most appropriate system elements must be chosen. The choice of panel, which has a greater impact on efficiency among other system elements, has vital importance from this aspect. For a 1-MW solar energy station modeled in this study, an appropriate solar field is chosen as a first step. System parameters are entered into the simulation software and finally the panels of various brands are compared using the simulation while keeping the rest of the system elements constant. As indicated in Table 19.1, the amount of specific production is observed to be maximum (1398 kWh/kWp/year) with the Jinkosolar brand. This value shows that 1398 kWp production can be possible by installing a facility of 1 kWp, which results in 1583 MWh/year of annual energy production. The system performance of Jinkosolar is 0.837, and since a minimum loss in the series is desired, the brand with the closest value to this is determined, and desired results are evaluated with Jinkosolar. In conclusion, considering the highest value for specific production, which is the most important value for system performance in the PVsyst-supported design study, the 260W monocrystalline Jinkosolar brand is determined as the most appropriate panel. This research involves three stages. The solar energy characteristics and potential of a selected region is initially evaluated based on the available data. In the second stage, solar radiation analysis is conducted on a Matlab platform and finally the PV system is simulated using PVsyst software. The values of solar radiation in the Erzincan case are evaluated to be at

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acceptable efficiency levels to design a photovoltaic system. Although data for a specific case are used here for the purpose of model verification, this study aims to establish a reference for choosing the most efficient solar panel by relying on the solar radiation values obtained for the most efficient photovoltaic system design.

References 1. Ozdemir, B.B. Sürdürülebilir Çevre İçin Binaların Enerji Etkin Pasif Sistemler Olarak Tasarlanması, Yüksek Lisans Tezi, İ.T.Ü. Mimarlık Fakültesi, İstanbul, 2005. 2. Kılıc, A. and Ozturk, A. Solar Energy. Kipas Publ, 1980. 3. Altın, V. Energy. Sun, Science and Technical Journal, 446: 17–19, 2002. 4. Erkul, A. Monokristal, polikristal, Amorf Silisyum Güneş Panellerinin Verimliliğin İncelenmesi ve Aydınlatma Sistemine Uygulanması, Yüksek Lisans Tezi. Gazi Üniversitesi Fen Bilimleri Enstitüsü, Ankara, 2010. 5. Kiziroglu, I. Alternative Energy Resources Saving Humanity. Popular Science Journal, 12: 50–54, 2005. 6. Buldum, B. and Kulekci M. Solar energy potential of Mersin. VII. National Clean Energy Symposium, UTES, 385–394, Istanbul, 2008. 7. Yİlmaz, A. (Nisan 2016). Türkiye Güneş Enerjisi İstatistikleri http://www. enerjiatlasi.com/haber/turkiye-gunes-enerjisi-istatistikleri, 2016. 8. www.eie.gov.tr, 2016. 9. Vikipedi, https://tr.wikipedia.org/wiki/Erzincan, 2016. 10. Unal, A., Tanes, Y., Onur, H.Ş. Günlük Ortalama Güneş Işınımı Ve Sıcaklık Değerlerinin Yıllık Değişiminin Sürekli Fonksiyonlarla İfadesi, Fonksiyon Parametrelerinin Türkiye’deki Dağılımı, Isı Bilimi Ve Tekniği Dergisi, Cilt 8, Sayı 4, Sayfa 37–45, Ankara, 1986. 11. Deris, N. Heating Technique with Solar Energy Water. Sermet, Istanbul, 1979. 12. Tamer, S. Klima Ve Havalandırma. Meteksan A.Ş., Ankara, 1972. 13. Derse, M.S. Batman’ın İklim Koşullarında Eğimli Düzleme Gelen Güneş Işınımının Farklı Açı Değerlerinde Belirlenmesi Sayfa 37–47 Batman, 2014. 14. Miguel, A.D., Bilbao, J., Aguiar, R., Kambezidis, H., and Negro, E. Diffuse solar irradiation model evaluation in the North Mediterranean belt area. Solar Energy, 70: 143–153, 2001. 15. Notton, G., Poggi, P., and Cristofari, C. Predicting hourly solar irradiations on inclined surfaces based on the horizontal measurements: Performances of the association of well-known mathematical models. Energy Conversion and Management, 47: 1816–1829, 2006. 16. Erbs, D.G., Klein, S.A., and Duffie, J.A. Estimation of the diffuse radiation fraction for hourly, daily and monthly-average global radiation. Solar Energy, 28(4): 293–302, 1982.

Solar Radiation Analysis Model and PVsyst Simulation 785 17. Mercan, O. Marketing Photovoltaic Solutions in Turkey, Masters Thesis, Istanbul Bilgi University, Istanbul, 2013. 18. Colak, S.C. Fotovoltaik paneller yardımı ile güneş enerjisinden elektrik enerjisi üreriminin maliyet analizi ve gelecekteki projeksiyonu, Yüksek Lisans Tezi. Yıldız Teknik Üniversitesi, Istanbul, 2010. 19. PVsyst Access Date: 08.07.2016.

Index 1 Sun, 280, 285, 293, 317, 341 5-ammoniumvaleric acid (5-AVA), 343 Absorbance, 175–176, 184 Absorber layer, 266–267, 309 Absorption, 165, 177, 182, 188 Absorption coefficient, 272–273, 279, 309, 331–332, 335 Absorption onset, 269, 287, 289, 292, 318–331, 613–614 Absorption spectroscopy, 492 Absorption spectrum, 272–273, 276, 293 Acceptor, 488–490, 493, 496, 498–507 Activation energies, 322 Aggregation, 623, 627, 632 Al back field, 47 Al2O3, 317 Allegro ACS713 DC current sensor, 754 Alloying, 686 Aluminum, 66–68, 70, 73, 75–77, 80, 82, 85, 87, 90–93, 96 Aluminum oxide substrate, 740 Aluminum-Doped Zinc Oxide (AZO), 541, 543, 545 AM1.5 direct spectral irradiance, 741 Ambient air, 268, 274, 337, 343 Amorphous silicon, 266, 272 Analog-to-digital converter, 754 Anatase, 170–175, 178–183, 187–188, 190, 192–193 Annealing, 167, 177–178, 188 Antireflection coating, 28, 32, 41, 48 Anti-solvent dripping method, 300–302 Asymptotic freedom, 616

Atmospheric pressure, 264 Atomic Force Microscopy (AFM), 321, 516, 522, 525–526 Atomic layer deposition (ALD), 307 Average cell efficiency, 756 Azimuth angle, 778–779, 781 B270 superwite, 743 Band edge, 466 Band structure tailoring, 684 Bandgap, 165–167, 169, 172, 175–179, 182, 184, 186–188, 265, 269, 272–276, 286–292, 295, 297, 328–329, 331, 335–336, 339, 495, 497 Bandgap engineering, 127–129 Bandgap of silicon, 24 Band-to-band recombination, 273 Basic module, 751, 752 Basic polymer, 326–327 BaTiO3, 196 BiFeO3, 195, 197, 224–229, 235 Bi-molecular recombination, 283 Binary lead chalcogenides, 662, 669 Binary silver chalcogenides, 662, 674–675 Binding energy, 267, 283–284, 286, 288, 331, 335 Blochl corrections, 361 Blue shift, 269, 276, 289, 292, 294 Branched polyethyleneimine (b-PEI), 281, 327 Built-in potential, 633, 636–637 Bulk heterojunction, 539, 638, 646

Santosh Kurinec (ed.) Emerging Photovoltaic Materials, (787–797) © 2019 Scrivener Publishing LLC

787

788

Index

Bulk lifetime, 264 Bulk photovoltaic effect ballistic current, 113–114 shift current, 116–117 Bulk photovoltaic effect, 195–196 Bulk-heterojunction, 488, 502 Bypass diode, 741 Cadmium iodide (CdI2), 359, 362, 364, 380–382, 384–385 Cadmium telluride (CdTe), 266 Caesium lead iodide, 274 Calcium iodide (CaI2), 359 Capacitance, electrical, 415 geometrical, 416 Capacitive current, 324 Capacity, 266 Carbon nanotubes (CNT), 337 Carbon nanotubes based transparent conducting electrodes, 557 fabrication, 557–558 properties, 558 doping, 558–563 Carbon nanotube–silicon heterojunction solar cells, 575 electronic type, 579 transmittance/thickness of CNT films, 580 application of conductive polymers, 584 CNT alignment in the electrode, 579–580 CNT wall number, 578–579 doping, 580–581 enhancement of light absorption, 582–584 history, 576–577 intentional addition of silicon oxide layer, 581–582 origin of photocurrent, 577–578 working mechanism, 575–576 Carrier lifetime, 4, 7, 16 Carrier management, 685

Carrier mobility, 282–283, 285, 639, 640 Carrier recombination, 634, 640 Chalcogenides, 141, 142, 160 Chambers, 306 Charge carrier lifetime, 277–278, 280, 319 Charge carrier recombination, 273, 318 Charge distribution, 271, 310 Charge extraction by linearly increasing voltage (CELIV), 419 Charge recombination, 687–688 Charge selective contacts, 270, 308–309 Charge-neutrality level (CNL), 496 Charge-transfer (CT) exciton, 490, 503–506 Chemical bath deposition, cluster-by-cluster, 625–627 ion-by-ion, 625–627 Chemical deposition, 146, 153 Chemical equilibrium, 498, 503 Chemical vapor deposition (CVD), 513 Chiral index, 205 Chlorine-doped MAPbI3, 277–279, 298, 306, 320, 324 Chlorobenzene, 279, 302 Closed-loop control, 743 Colloidal quantum dot (CQD), 665 Complexing agent, 624–626 Conducting substrate, 461 fluoride-doped tin oxide (FTO), 461 indium tin oxide (ITO), 461–462 Conduction band, 372, 386, 393, 395 Confocal fluorescence microscopy, 318 Continuous Czochralski (CCZ), gallium doped cells, 17–19 melt height, 11–13 process, 11–13 resistivity, 11–13, 15–16 temperature, 14 Conversion efficiency, 463 Coordination shell, 390 Copper, 63, 65, 68–69, 72–73, 75, 77, 80, 83, 85, 90–97

Index 789 Copper (I) iodide (CuI), 314 Copper indium gallum selenide (CIGS) Copper thiocyanate (CuSCN), 314 Core/shell structure, type I, 689 type II, 690 Cost per watt, 758 Coulomb blockade, 616 Coulomb repulsion, 613 Counter electrode, 474 carbon materials, 474–475 conducting polymers, 475 platinized conduction glass, 474 CPV + CCPC assembly set, 744, 748 Crossed compound parabolic concentrator, 722, 733 Crystal growth, 300, 302, 306 Crystal structure, 269–271, 275, 286, 291, 293, 296, 326, 339 Crystalline silicon, 264, 266, 272, 328 Crystallinity, 165, 167–168, 182, 186 Crystallization, 619–620, 627 Cubic phase, 275–276, 291 Cyclic voltammetry, 492 Czochralski (CZ), boron, 4, 10, 11, 15, 17, 19 Magnetic Czochralski (MCZ), 7 process, 3, 5 pull Rate, 5–6 resistivity, 10–11 Degradation, 167–169, 179–180, 186, 188, 190–192, 264, 268, 313–314, 316–318, 338–339, 341 Dense-array concentrator photovoltaic, 722, 742 Density functional theory (DFT), 272, 323 Density of state, 502, 504 Density of States (DOS), projected density of states (PDOS), 361, 371–376, 393–397 Density of states distribution (DOS), 519–520, 524

Depleted heterojunction (DH), 611–612, 633, 637–640 Device architectures, 672–673, 700 DFT calculations, DFT-periodic calculations, 361 Dielectric constant, 413–418, 421 Diethyl ether, 302 Diffuse radiation, 770, 775, 778 Diffuse reflectance UV-Vis spectroscopy, 360, 365, 370, 384, 385, 397 Diffusion coefficient, 277, 621 Diffusion length, 24, 31, 43, 263, 277–280, 284–285, 307, 327 Dimethyl sulfoxide (DMSO), 298 Dipropyl sulfide, 314 Direct bandgap, 273, 335 Direct bonded copper substrate, 740 Direct normal irradiance (DNI), 747 Direct transition, 273 Directional solidifcation, 26, 34–38 Dislocation, 38, 40 Dissipative terms, 208 Dissolution, 620 Dissolved oxygen, 4, 7–9, 12–15, 17 Domain wall photovoltaics, 120–123 Donor, 488–490, 493, 496, 498–504 Donor-acceptor heterojunction, 488, 501 Donor-acceptor interface, 488–490, 493, 499–500, 503–504, 506 Dopant, 264, 312–313, 339 Dopant-free HTMs, 313, 319 Doping, 359, 361, 366, 684–685 DOS, 170, 173–175, 179–180, 183–184 Double cation, 292–295, 341 DSSC, 165–166, 172, 175–177, 185, 188 Dye-sensitized solar cell (DSSCs), 450, 452–456, 458, 461–469, 472, 477 n-type DSSCs, 455, 466 p-type DSSCs, 454–455, 467

790

Index

Dye-sensitized solar cells (DSCs), 266, 310–311, 315, 563 catalyst layer, 570–572 history, 563 semiconductor layer, 565–570 working mechanism, 563 Efficiency, 764, 777–778, 783 Efficiency, theoretical, silicon solar cell, 24 fill factor, 29, 33, 43 open-circuit voltage, 25, 30–33 short-circuit current, 29, 31–33, 37 Electrical conductivity, 145, 147, 154 Electrode-organic interface, 490, 495 Electrolyte, 267–268, 270, 318, 471 liquid electrolye, 472–473 quasi-solid electrolye, 474 soild-state elctrolyte, 473 Electromagnetic frame, 198, 200, 203 Electrometallurgy, 64, 93–94 Electron charge, 282 Electron concentration, 283 Electron localization function, 362, 372, 375–377, 390–393, 397 Electron mobility, 283, 285, 309 Electron selective contacts, 309–311 Electron transport layer, 266–267, 308, 310, 322–323, 343 Electron transport material (ETM), 308, 310 Electron trap density, 285 Electron-hole lifetime, 273, 277, 279 Electron-hole pair, 488, 499, 503 Electronic state, 613 Electron–phonon coupling, 614 Electrons, 265, 267–268, 276, 279–280, 308–309, 331 ELF, 170, 173–174, 179–180, 183 Ellipsometry, 418, 519 Emitter, 37, 40–48 Energy bandgap, 289 Energy consumption, 764 Energy diagram, 265

Energy efficiency, 777 Energy level alignment, 490–495, 497–498 Energy spacing, 613–614 Energy-dispersive X-ray spectroscopy (EDS), 517–519 Entrainment effect, 196 Equilibrium segregation coeffecient, 8–10 Euler angles, 198, 202, 203, 205, 207, 234 EVA (polymer), 66–68, 70, 74–75, 86–89 E-waste, 62–63, 65–66 Exciton, binding energy, 413–414 diffusion, 412 Exciton binding energy, 488, 505 Exciton dissociation, 488–490, 493 Excitons, 267, 283 External quantum efficiency (EQE), 269, 276, 292, 500, 521–522, 544–545 External selection, 206–208 External symmetry, 204 Extinction coefficient, 612, 641, 645 Fabrication cost, 759 Fabrication technique, 455 dye impregnation, 460 film deposition, 456–460 substrate selection, 456 Facet, 291 FAPbI3, 273, 284 Fermi level, 265, 454, 491–492, 494–496, 498, 501–503 Fermi-Dirac distribution, 502, 504 Ferroelectric polarization, 324 Fill factor, 315, 410, 745–746 Film processing, ex situ strategy, 666–667 in situ strategy, 665–668 Flash infrared annealing (FIRA), 304 Flexible solar cells, 694–695 Fluorescence quenching, 617

Index 791 Fluorine-doped tin oxide (FTO), 304 Fourier Transform infrared spectroscopy (FTIR), 302, 517, 523 Four-terminal structure, 328 Fresnel losses, 748, 749 FT209, 312 Functionals, Perdew–Burke–Ernzerhof (PBE), 361 Gamma-butyrolactone (GBL), 298 Gas-assistant method, 302–304 General sun-tracking formula, 742 Generalized gradient approximation, 155, 158, 361 Geometrical concentration ratio, 743 Glass, 64, 66–68, 71–72, 77, 80, 82–86, 95–97 Global solar irradiance (GSI), 747 Global radiation, 778 Global solar irradiance, 747 Grain boundaries (GBs), 38-40, 318 Grain size, 280, 286, 302, 307–308, 313, 320, 339, 342 Halide perovskites, 696 Hall effect, 282, 285 Hall scattering factor, 282 Hall voltage, 282 Halogen lamp, 304 Hazadous materials, 62–63 Helmholtz double layer, 629 Heterojunction, 267, 283, 331 bulk (BHJ), 408–409, 412 planar, 408–409 Hexagonal, 275 High dielectric constant materials, acceptor, 429–435 blend, 415 donor, 422–429 hybrid perovskite, 414 inorganic, 413, 415 Highest occupied molecular orbital (HOMO), 411, 488–490, 492–499, 501–503, 507

High-Performance Multicrystalline Silicon, 37–41 High solar flux scanner, 750 HIT solar cells, 50–53 Hole selective contacts, 277, 331 Hole transport material (HTM), 270, 299, 309 Holes, 265, 267–268, 279–280, 288, 300, 308–309, 331 HOMO-LUMO energy offset, 498–499, 507 Hopping, 504, 506–507 Hybrid lead halide perovskites, 274 Hybrid solar cells, 697–698 Hydrolysis, 625–626 Hydrometallurgy, 64, 90–93 Hysteresis, 264, 310, 315–316, 322–324, 328 Immersion time, 300 Impact ionization, 614 Impedance spectroscopy, 419–420 Impurities, 264, 266, 297 Incident photon-to-electricity conversion efficiency (IPCE), Indirect bandgap, 273 Indirect transition, 272–273 Indium Tin Oxide (ITO), 518, 538, 540–541, 543 Inorganic electron selective contact, 310 Inorganic hole selective contact, 314 Instrument response function (IRF), 288 Interdigitated Back Contact (IBC) Solar Cell, 47–50 Interface dipole, 497–498, 507 Interfacial state, 495–496 Intermediate phase, 301–302, 304 Internal selection, 199, 208–210 Internal symmetry, 204 Inverse photoemission spectroscpy (IPES), 492 Ion migration, 264, 322, 324, 338

792

Index

Ion-exchange, 665 Ionic radius, 273, 294 IR absorber, 302 Isopropanol (IPA), 273, 299 J-V curve, 302, 315, 325, 337 KBiFe2O5, 195, 197, 218–224 Kelvin probe force microscopy (KPFM), 321 Kramers–Kronig, 149 Kubelka Munk equation, 360, 371 Lattice spacing, 289, 291 Lead halide octahedrals, 272 Lead iodide, 359, 362, 364, 371, 380–385 Lead/tin perovskite, 271 Lead-free perovskite, 331, 336 Ligand exchange, 687–688 Light absorber, 266–267, 269, 318 Light management, 682 Light-emitting devices, 273 Light-Induced Degradation (LID), 15, 19 LiNbO3, 195, 196, 210–218 Linear polyethyleneimine (LPEI), 327 Lithium bis(trifluoromethanesulfonyl) imide (LiTFSI), 312 Local density approximation, 155, 158 Lowest unoccupied molecular orbital (LUMO), 411, 488–490, 492–499, 501–503, 507 Luminscence, cathodoluminscence, 360, 369–370 Magnetic field, 282, 284 Magnetic index, 205 Magneto Photovoltaic effect, 195, 218, 220, 222–224, 227 Majority carrier concentration, 282 Maximum power point tracking (MPPT), 316 Measured solar concentration ratio, 748

Mechanical Processes (recycling), 64, 76–84, 97 Metallurgical Silicon, 26, 33 Methyl ammonium lead triiodide (MAPbI3), 269 Methylammonium iodide, 359, 380–382 Methylammonium lead halide, 357–359, 362–368, 370–371, 373–375, 377–379, 382–386, 388–395, 397 Microchip PIC18F4550, 754 Miller-Abraham hopping, 506–507 Minority carrier lifetime, 35, 40, 49, 53 Mobility, 239, 241–242, 244, 253, 277, 281–283, 285–286, 309, 312–313, 318 Module cell, 344 Monocrystalline panels, 778 Monodispersity, 623–624, 627 Monolithic film, 301 Morphology, atomic force microscopy (AFM), 421 bulk (BHJ), 408–410 smooth interface, 421 Mott-Gurney law, 285 Multication, 239, 242 Multi-cations, 292 Multi-junction (MJ) solar cell, 693, 694, 722, 746, 759 Multiple exciton generation (MEG), 660, 662 N,N-dimethylformamide (DMF), 273 Nanoparticles, 267, 269, 304, 310 Nanophotonic structuring, 683 Narrow-bandgap, 141–142, 153 N-doped, 282 Nickel oxide (NiO), 314 “n-i-p” structure, 309–310 Non-dissipative term, 208 Non-imaging dish concentrator, 722, 723 Non-perovskite yellow phase, 274 n-type, 264–265, 282–283

Index 793 n-Type High effeciency cells, heterojunction solar cells (HJT), 17 n-PARSHA, 15–16 n-PERT, 15–16 Nucleation, 618–623, 625–626, 631 Nucleation process, 300 Nucleation rate, 302, 304 Oligo(ethylene glycol) side chains, 423–425, 429–434 One-step spin-coating method, 298 Open circuit voltage, 410–411 Open-circuit photovoltage (Voc), 270, 315 Open-circuit voltage, 490, 499, 507 Optical bandgap, 269, 272–275, 288, 290–292, 295, 331, 336, 339, 360, 365, 366, 370, 384, 386, 388 Optical encoder, 743 Optical rectification effect, 195, 199, 215 Optoelectronic applications, 273 Optoelectronic properties, 264, 269, 271, 308, 329, 331 Organic electron selective contact, 310–311 Organic hole selective contact, 312–314 Organic light-emitting diode (OLED), 493, 500 Organic molecule, 488, 492, 497, 506 Organic photovoltaics, 267–268, 311, 315, 338, 407–412, 487, 499 Organic solar cells, 407–412 Organic-inorganic lead halide perovskites, 270 Organic-organic interface, 490, 494–498 Orthorhombic phase, 274, 286–288 Ostwald ripening, 619–620, 623 Overall system efficiency, 756 P3HT:PCBM, 518 PAA, 279, 281, 327 Palladium iodide, 380–383, 386, 392, 393, 395–397

Passivated emitter and rear cell (PERC), 41–46 Passivation, 281, 324, 326–328, 689, 692 PBDTTT, 267–268 PbS, 307–308 PCBM, 267, 277–280, 311, 323, 325–326, 328–329, 331, 342 p-doped, 285 PDOS, 170, 173–174, 184 Peak-to-average ratio, 745, 746, 747 PEDOT:PSS, 268, 313, 325, 329, 337, 518, 520–521, 530–531, 533, 540–543, 545 PEH-2, 312–313, 342 Perovskite materials, 269–273, 284, 288, 300–301, 318, 329, 331, 336, 338–339 Perovskite phase, 274–275, 292–295, 300–301 Perovskite Solar Cells, 358, 572 working mechanism, 572 Perovskite solar panel, 344 Perovskite structure, cubic, 361–364, 369, 371–373, 375, 378, 382 tetragonal, 361–364, 371–380, 382–384, 388–390, 394–395, 397 PET (polymer), 74–75 Phase segregation, 297 Phase transition, 273–276, 286, 288–289 Phosphorus diffusion, 27–28, 40 Photo electromotive force (EMF), 534–537 Photo-Hall effect, 195, 231–234 Photo Magnetoelectric effect, 195, 199, 216, 224–226 Photo toroidal effect, 195, 201, 215 Photocatalysis, 131–133 Photocatalytic, 165–167, 172, 179–180, 186–188, 190–192 Photoconductivity, 145–148, 154 Photocurrent-photovoltage (J-V), 270 Photoelastic effect, 195, 199, 201, 216, 490

794

Index

Photoelectrode, 462 niobium pentoxide, 464–465 ternary photoelectrode, 465 titanium oxide, 462–463 zinc oxide, 463–464 Photoelectron spectroscopy (PS), 519 Photoemission spectroscopy (PES), 519 Photoluminescence (PL), 272–273, 278, 286, 290, 294–295 Photomagnetic effect, 195, 199, 215 Photon, 267, 269, 272–273, 309 Photorefractive effect, 195, 199, 230–231 Photosensitizer, 466–467 iridium complexes, 470–471 osmium complexes, 469 platinum complexes, 469–470 rhenium complexes, 470 ruthenium complexes, 467–469 Photostriction, 130–131 Photovoltaic (PV), 141–143, 151, 152, 160, 165–167, 172, 175, 184, 189 530, 534, 538, 540–541, 546 Photovoltaic Cells, 445 first-generation photovoltaic cells, 445 gallium arsenide (GaAs), 447 polycrystalline silicon, 445, 447 silicon single-crystal, 445 second-generation photovoltaic cells, 447 amorphous silicon (a-Si), 447–448 cadmium telluride, 448 copper indium diselenide, 448 third-generation photovoltaic cells, 449 copper zinc tin sulfide solar cells, 449 organic solar cells, 449–450 perovskite solar cells, 450 quantum dot solar cell, 450 Photovoltaic devices, 275, 294 Photovoltaic performance, 269, 288, 297, 301, 303, 305–306, 312, 315, 318, 324, 336–337, 339, 341

Photovoltaic system, 764, 784 Photovoltaic tensor, 196 Physical vapor deposition method, 306 “p-i-n” structure, 309 Planar heterojunction, 488–489, 502 Plasma-enhanced chemical vapor deposition, 264 PLD, 243–245, 249, 257 PMMA, 278–280, 327, 338–339 p-n junction, 106–108, 405–406 Poison effect, 644 Polar solvent, 270, 318 Polarization, dipolar, 417 electronic, 416–417 frequency dependence, 418 ionic, 417 surface charge, 417 Polycrystalline, 277, 281, 285–286, 318, 321, 336 Power conversion efficiency (PCE), 265, 293, 315, 410–411, 413, 488, 490, 499, 722, 757 Poynting vector, 202 Precious metals, 63, 76 Precipitation, 620, 623–625, 627 Pre-conditioning, 315–316 Precursor, 274, 280, 282–283, 286, 290, 294, 298, 300–302, 304, 307, 310, 313, 319–320, 328 PTAA, 301, 312–313, 336 p-type, 264, 282–283 Pulsed-laser deposition (PLD), 314 PV cell, displacement, 66 materials, 69, 73 recycling, 69–70, 75–76, 94 structure, 68, 73 types, 65 PV modules, 266 generations, technology, 65 lifespan, 65 materials, 66–69 reasons for failing, 65

Index 795 PVF (polymer), 66, 74–75 PVP, 279, 281, 327 Pyrochlore, 167, 170, 181–182, 185–188, 191–192 Pyrometallurgy, 64, 90, 96 Quadruple cation, 295, 342 Quantized motion, 613 Quantum confinement, 664 Quantum dot (QD), 269, 660–662 Quantum efficiency, 31 Quantum size effect, 660, 663 Quantum yield (QY), 616–617, 622–623 Quartz substrate, 273 Quasi-Fermi level, 501–503 Quaternary alloys, 662, 679–681 Quencher material, 277 Quenching, 617, 619 Radiative efficiency, 273 Raman spectroscopy, 149, 155 Recombination, 27–32, 39–44, 48, 489, 500–501, 503–504 auger recombination, 24, 29–33 SRH recombination, 30–31, 39 Recombination lifetime, 279 Recycling e-waste, 64–65 Renewable energy, 765 Rim angle, 738, 743 Roll-to-roll deposition, 514, 537 Rutile, 170–172, 178, 181–182, 186, 188, 191–193 Scan direction, 315 Scan rate, 315–316 Scanning Electron Microscopy, 360, 369 Scanning Probe Microscopy (SPM), 516 Scheil equation, 10 Schottky barrier, 118–120, 493–494, 496–497, 633–636 Schottky contact, 635–636 Schottky defects, 322 Schottky-Mott limit, 494–495

Secondary electron, 491 Secondary Electron Microscopy (SIMS), 517–519, 527, 540–541 Time of Flight (ToF), 519 Seebeck coefficient, 147, 148 Selective contacts, 406–407 SEM, 299, 301, 308–309, 329, 342 Semiconductors, 165–167, 172, 175–177, 182, 185–186, 192–193 amorphous, 527 crystalline, 512, 546 inorganic, 524, 534 intrinsic, 538 monocrystalline, 533–534 non-crystalline, 532 organic (OS), 512, 516, 519–520, 525, 534–535, 539–540, 545–546 Semitransparent solar cells, 694–695 Sensitizer, 266–268 Sequential deposition, 280–281, 299, 314 Shockley equation, 753 Shockley-Queisser limit, 109–110, 117 Short circuit current, 410–411, 500, 504 Short-circuit photocurrent density (Jsc), 270 Siemens method, 26, 34, 37 Silicon, high grade, 63, 69, 91 purity, 69 recycling, 67–70, 73, 75 solar grade, 69 wafer, 73 Silicon Heterojunction (SHJ) Solar Cells, 50–53 silicon photovoltaic, 264–265 Silicon solar cell, 24 efficiency loss, 29, 30 manufacturing, 26 theoretical efficiency, 24 Silicon solar cells, 264–266, 268, 271, 315, 328 Silicon wafer, 264, 266, 304

796

Index

Silver, 63, 68–69, 73, 77, 80, 83, 92, 94, 96 Simulation program, 763 Single crystals, 274, 284–285, 300 Single molecular layer, 267 Singlet exciton, 489 Size focusing, 619–620, 623 Slope parameter, 493–498 SnO2, 326, 329 Solar Cell, 142, 145–147, 150–151 Solar cell generations, 554 Solar concentration ratio (SCR), 741 Solar energy, 763–766, 777, 781 Solar panel, 764, 784 Solar radiation diffuse solar radiation, 768–771 momentary total solar radiation, 769, 771 total solar radiation, 766–769, 771 Solid-state dye-sensitized solar cells (ss-DSCs), 312 Solubility, 619–621, 629 Space charge limited current (SCLC), 285 Spectrum, 276, 287, 289, 293, 328, 330–331, 339 Spherical angles, 198 Spin degeneracy, 616 Spiro-OMeTAD, 267, 270, 277–280, 297, 306, 312–313, 326, 339, 342 Sputtering, 314 Stability, 700–701 Stepper motor, 743 Strontium iodide, 359 Structure, heterojunction transition (HJT), 516, 543–545 hybrid, 545 Successive ionic layer adsorption and reaction (SILAR), 611, 618, 628, 635 Sunshine, 765–767 Supersaturation, 619 Surface engineering, 687

Surface morphology, 298, 301–307 Surface Passivation, 33, 41–43, 49, 623 Surface plasmon resonance (SPR), 684 Tandem solar cells, 328–331 TAS, 285 tBP, 312 Temperature, 764, 766, 778 Ternary alloys, 662, 679–682 Ternary indium-based chalcogenides, 662, 676–678 Tetragonal, 275–276, 284, 286, 289–291, 331–332, 335 Thermal Activated Conduction (TAC) model, 520–521 Thermal Conductivity, 143 Thin film solar cells, 264, 266, 268, 271, 315, 328–330 Time-of-flight (ToF), 285 Time-resolved PL spectra, 277–279 Tin Chalcogenides, 143 Tin idodie, 359 Tolerance factor, 273, 294–296 Transient photovoltage, 278, 280 Transient THz spectroscopy, 283 Transparent conductive glass (TCO), 308 Trap density, 285 Trapping and detrapping process, 324 Trigonal phase, 275 Triple cation, 294–295, 317, 341 TTF-1, 312–313 Transparent conducting oxides, 239, 240 Tungsten bronzes, 195, 197, 229–233 Turn-on voltage, 493 Two-step coating method, 299 Two-terminal structure, 328–329 Ultraviolet photoemission spectroscopy (UPS), 490 Under-coordinated Pb atoms, 326 Universiti Tunku Abdul Rahman, 742

Index 797 Upgraded metallurgical-grade silicon, 33–37 carbothermic reduction, 33 electroreduction, 33

X-ray diffraction (XRD), 293, 342, 359, 362–364, 370, 379–384 X-ray photoelectron spectroscopy, 360, 366–368, 386–388

Vacuum flash-assistant deposition method, 304–305 Vacuum level, 491, 494 Valence band, 372–376, 393–397 Valence band electron, 490–491 Variable Range Hopping (VRH) model, 520–521 Voltage, 165, 175, 184–185, 192

-phase, 274–275, 292, 297, 331–332 -phase, 274–275, 286 -phase, 274–275, 286 -phase, 292 -SnS, absorption coefficient, 147, 158 bandgap, 145–148 carrier density, 150 external quantum efficiency (EQE), 145 optical properties, 145, 147, 149–152 refractive index, 152–153 π-SnSe bandgap, 155 debye temperature, 156 refractive index, 155–156 π-SnTe bandgap, 157, 159 refractive index, 158

Waste electrical and electronic equipment, 62 Waveguide, 418 Wigner coefficients, 205–207, 210 Wigner spherical functions, 195, 198, 204 Wind values, 778 Work function, 491, 494, 496–499, 507, 634–636