Perovskite Solar Cells
Modeling the Future of Renewable Energy
Herausgeber: Swart, Arthur James; Pandey, Bishwajeet; Kumar, Keshav
Perovskite Solar Cells
Modeling the Future of Renewable Energy
Herausgeber: Swart, Arthur James; Pandey, Bishwajeet; Kumar, Keshav
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The text provides a comprehensive overview of the role of modeling in advancing perovskite solar cell technology and its implications for the future of renewable energy. It includes various aspects of perovskite solar cell modelling.
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The text provides a comprehensive overview of the role of modeling in advancing perovskite solar cell technology and its implications for the future of renewable energy. It includes various aspects of perovskite solar cell modelling.
Produktdetails
- Produktdetails
- Verlag: CRC Press
- Seitenzahl: 400
- Erscheinungstermin: 28. Oktober 2025
- Englisch
- Abmessung: 240mm x 161mm x 26mm
- Gewicht: 763g
- ISBN-13: 9781032965031
- ISBN-10: 1032965037
- Artikelnr.: 73985065
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: CRC Press
- Seitenzahl: 400
- Erscheinungstermin: 28. Oktober 2025
- Englisch
- Abmessung: 240mm x 161mm x 26mm
- Gewicht: 763g
- ISBN-13: 9781032965031
- ISBN-10: 1032965037
- Artikelnr.: 73985065
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Arthur James Swart is currently working as an Associate Professor in the Department of Electrical Electronics and Computer Engineering at the Central University of Technology, South Africa. His research interests include engineering education and alternative energy. He worked for Telkom SA and De Beers Namaqualand Mines for 4 years. He joined the Vaal University of Technology in 1995 and progressed from a Technician to a Senior Lecturer in 2007. He completed his MEd in 2007 and his DTech in 2011. He has always loved teaching, but his passion for research took time to develop. Research affords one the opportunity to engage in life¿long learning, which will always remain his primary goal and which he is currently pursuing at the Central University of Technology. Keshav Kumar is an Assistant Professor in the Department of Electronics and Communication Engineering at Pranveer Singh Institute of Technology, Kanpur, India. He is pursuing his PhD in the field of Hardware Security from Lingaya's Vidyapeeth, Faridabad, India. He has previously worked at Chandigarh University, Punjab, India (NIRF 29). He completed his Master of Engineering in ECE with a specialization in Hardware Security from Chitkara University, Punjab, India. He has also worked as a Junior Research Fellow (JRF) at NIT Patna and as an Assistant Lecturer at Chitkara University, Punjab, India. He has authored and cöuthored many books and more than 55 research papers in the fields of hardware security, green communication, low¿ower VLSI design, machine learning techniques, and IoT. He has also worked with professors from 20 different countries. His areas of specialization include deep learning, hardware security, green communication, low¿ower VLSI design, machine learning techniques, wireless sensor network (WSN), and IoT. He has experience in teaching Python programming, embedded systems, IoT, computer networks, and digital electronics. He is also associated with Gyancity Research Consultancy Pvt Ltd. He is also a member of IAENG. He has more than 600 citations (Google Scholar), 15 H¿index (Google Scholar), and 12 H¿Index (Scopus). Bishwajeet Pandey is a Professor at GL Bajaj College of Technology and Management, Greater Noida, India. He has been a Senior Member of IEEE since 2019. He holds an MTech in Computer Science and Engineering from the Indian Institute of Information Technology, Gwalior, India, and a PhD in Computer Science from the Gran Sasso Science Institute, Italy. He has taught at esteemed institutions such as Chitkara University Chandigarh; Birla Institute of Applied Science, Bhimtal; Jain University, Bangalore; Astana IT University, Kazakhstan; Eurasian National University, Kazakhstan (QS World Rank 321); and UCSI University, Malaysia (QS World Rank 265). He is a prolific researcher, with 11 published books, 196 research papers indexed in Scopus, 45 papers in SCIE, and a total of 296 papers. He has garnered over 3,600 citations and holds an H¿index of 28. His leadership roles include serving as the Research Head of the School of Computer Science and Engineering at Jain University, Bangalore (2021-2023), and as the Head of the International Global Academic Partnership Committee at Birla Institute of Applied Science, Bhimtal (2020-2021). In 2023, he was honored with the prestigious Professor of the Year Award at Lord's Cricket Ground by the London Organisation of Skills Development. Beyond his outstanding research output, his greatest strength lies in his global academic network. He has visited 49 countries, participated in 105 international conferences, and cöuthored papers with 218 professors from 93 universities across 42 nations. Sakshi Sharma is currently working as a Junior Research Fellow at the School of Advanced Engineering, University of Petroleum and Energy Studies, Dehradun, India. She is pursuing her PhD in Photovoltaic Systems from the University of Petroleum and Energy Studies, Dehradun, India. She successfully completed her Master of Engineering in ECE with the specialization in Hardware Security from Chitkara University, Punjab, India. She has also worked as an Assistant Lecturer at Chitkara University, Punjab, India.
Chapter 1. An Introduction to the Solar Energy: A Step Towards
Sustainability. Chapter 2. Fundamentals of Perovskite Materials. Chapter 3.
Technology Advancements in Solar Cells: A Summary. Chapter 4. Recent
Advances in Perovskite Tandem Solar Cells for Enhanced Solar Efficiency.
Chapter 5. Modelling Techniques of Perovskite Solar Cells. Chapter 6.
Modeling the Future of Renewable Energy: Machine Learning in Solar Energy
Prediction. Chapter 7. Optimizing Hybrid Electric Vehicle Performance by
Deep Learning for Power Distribution and Regenerative Braking Prediction in
Urban Driving Conditions. Chapter 8. Optimization of Power for Solar Panel
Optimizer Using Different FPGAs. Chapter 9. Advancing Solar Energy with
Machine Learning, Perovskite Technology, and Smart Data Systems. Chapter
10. Machine Learning for Performance Prediction and Optimization. Chapter
11. Machine Learning Applications in Solar Energy: Predicting Performance
and Efficiency. Chapter 12. A Novel Hybrid LSTM-XGBoost Model for Enhanced
Solar PV Power Generation Forecasting. Chapter 13. A Comprehensive Review
of Cybersecurity Challenges in Solar Grids. Chapter 14. Harnessing Machine
Learning for Solar Energy Forecasting: Advancing Perovskite Solar Cells and
Renewable Energy Solutions. Chapter 15. Toward Secure Solar Energy Systems:
A Cyber Perspective. Chapter 16. Thermal and Power Efficient Hardware
Design of Solar Panel on Reconfigurable Architecture. Chapter 17. Solar
Charge Controller Design on FPGA. Chapter 18. Exploring the Role of Solar
Energy in Advancing Agricultural Practices. Chapter 19. Machine Learning in
Solar Energy Prediction. Chapter 20. Real-Time Solar Panel Performance
Monitoring and Energy Forecasting. Chapter 21. Solar Energy to Sustainable
Development Goals: A Case Study. Chapter 22. Advancements and Challenges in
All-Perovskite Tandem Solar Cells: A Critical Review
Sustainability. Chapter 2. Fundamentals of Perovskite Materials. Chapter 3.
Technology Advancements in Solar Cells: A Summary. Chapter 4. Recent
Advances in Perovskite Tandem Solar Cells for Enhanced Solar Efficiency.
Chapter 5. Modelling Techniques of Perovskite Solar Cells. Chapter 6.
Modeling the Future of Renewable Energy: Machine Learning in Solar Energy
Prediction. Chapter 7. Optimizing Hybrid Electric Vehicle Performance by
Deep Learning for Power Distribution and Regenerative Braking Prediction in
Urban Driving Conditions. Chapter 8. Optimization of Power for Solar Panel
Optimizer Using Different FPGAs. Chapter 9. Advancing Solar Energy with
Machine Learning, Perovskite Technology, and Smart Data Systems. Chapter
10. Machine Learning for Performance Prediction and Optimization. Chapter
11. Machine Learning Applications in Solar Energy: Predicting Performance
and Efficiency. Chapter 12. A Novel Hybrid LSTM-XGBoost Model for Enhanced
Solar PV Power Generation Forecasting. Chapter 13. A Comprehensive Review
of Cybersecurity Challenges in Solar Grids. Chapter 14. Harnessing Machine
Learning for Solar Energy Forecasting: Advancing Perovskite Solar Cells and
Renewable Energy Solutions. Chapter 15. Toward Secure Solar Energy Systems:
A Cyber Perspective. Chapter 16. Thermal and Power Efficient Hardware
Design of Solar Panel on Reconfigurable Architecture. Chapter 17. Solar
Charge Controller Design on FPGA. Chapter 18. Exploring the Role of Solar
Energy in Advancing Agricultural Practices. Chapter 19. Machine Learning in
Solar Energy Prediction. Chapter 20. Real-Time Solar Panel Performance
Monitoring and Energy Forecasting. Chapter 21. Solar Energy to Sustainable
Development Goals: A Case Study. Chapter 22. Advancements and Challenges in
All-Perovskite Tandem Solar Cells: A Critical Review
Chapter 1. An Introduction to the Solar Energy: A Step Towards
Sustainability. Chapter 2. Fundamentals of Perovskite Materials. Chapter 3.
Technology Advancements in Solar Cells: A Summary. Chapter 4. Recent
Advances in Perovskite Tandem Solar Cells for Enhanced Solar Efficiency.
Chapter 5. Modelling Techniques of Perovskite Solar Cells. Chapter 6.
Modeling the Future of Renewable Energy: Machine Learning in Solar Energy
Prediction. Chapter 7. Optimizing Hybrid Electric Vehicle Performance by
Deep Learning for Power Distribution and Regenerative Braking Prediction in
Urban Driving Conditions. Chapter 8. Optimization of Power for Solar Panel
Optimizer Using Different FPGAs. Chapter 9. Advancing Solar Energy with
Machine Learning, Perovskite Technology, and Smart Data Systems. Chapter
10. Machine Learning for Performance Prediction and Optimization. Chapter
11. Machine Learning Applications in Solar Energy: Predicting Performance
and Efficiency. Chapter 12. A Novel Hybrid LSTM-XGBoost Model for Enhanced
Solar PV Power Generation Forecasting. Chapter 13. A Comprehensive Review
of Cybersecurity Challenges in Solar Grids. Chapter 14. Harnessing Machine
Learning for Solar Energy Forecasting: Advancing Perovskite Solar Cells and
Renewable Energy Solutions. Chapter 15. Toward Secure Solar Energy Systems:
A Cyber Perspective. Chapter 16. Thermal and Power Efficient Hardware
Design of Solar Panel on Reconfigurable Architecture. Chapter 17. Solar
Charge Controller Design on FPGA. Chapter 18. Exploring the Role of Solar
Energy in Advancing Agricultural Practices. Chapter 19. Machine Learning in
Solar Energy Prediction. Chapter 20. Real-Time Solar Panel Performance
Monitoring and Energy Forecasting. Chapter 21. Solar Energy to Sustainable
Development Goals: A Case Study. Chapter 22. Advancements and Challenges in
All-Perovskite Tandem Solar Cells: A Critical Review
Sustainability. Chapter 2. Fundamentals of Perovskite Materials. Chapter 3.
Technology Advancements in Solar Cells: A Summary. Chapter 4. Recent
Advances in Perovskite Tandem Solar Cells for Enhanced Solar Efficiency.
Chapter 5. Modelling Techniques of Perovskite Solar Cells. Chapter 6.
Modeling the Future of Renewable Energy: Machine Learning in Solar Energy
Prediction. Chapter 7. Optimizing Hybrid Electric Vehicle Performance by
Deep Learning for Power Distribution and Regenerative Braking Prediction in
Urban Driving Conditions. Chapter 8. Optimization of Power for Solar Panel
Optimizer Using Different FPGAs. Chapter 9. Advancing Solar Energy with
Machine Learning, Perovskite Technology, and Smart Data Systems. Chapter
10. Machine Learning for Performance Prediction and Optimization. Chapter
11. Machine Learning Applications in Solar Energy: Predicting Performance
and Efficiency. Chapter 12. A Novel Hybrid LSTM-XGBoost Model for Enhanced
Solar PV Power Generation Forecasting. Chapter 13. A Comprehensive Review
of Cybersecurity Challenges in Solar Grids. Chapter 14. Harnessing Machine
Learning for Solar Energy Forecasting: Advancing Perovskite Solar Cells and
Renewable Energy Solutions. Chapter 15. Toward Secure Solar Energy Systems:
A Cyber Perspective. Chapter 16. Thermal and Power Efficient Hardware
Design of Solar Panel on Reconfigurable Architecture. Chapter 17. Solar
Charge Controller Design on FPGA. Chapter 18. Exploring the Role of Solar
Energy in Advancing Agricultural Practices. Chapter 19. Machine Learning in
Solar Energy Prediction. Chapter 20. Real-Time Solar Panel Performance
Monitoring and Energy Forecasting. Chapter 21. Solar Energy to Sustainable
Development Goals: A Case Study. Chapter 22. Advancements and Challenges in
All-Perovskite Tandem Solar Cells: A Critical Review







