In silico investigation of Cu(In, Ga)Se2-based solar cells. Issue 46 (25th November 2020)

• Record Type: Journal Article
• Authors: Mirhosseini, Hossein; Kormath Madam Raghupathy, Ramya; Sahoo, Sudhir K.; Wiebeler, Hendrik; Chugh, Manjusha; Kühne, Thomas D.
• Is Part Of: Physical chemistry chemical physics. Volume 22:Issue 46(2020)
• Page Start: 26682
• Page End: 26701
• Publication Date: 2020-11-25
• Subjects: Chemistry, Physical and theoretical -- Periodicals; 541.3
• DOI: 10.1039/d0cp04712k
• Languages: English
• ISSNs: 1463-9076

Abstract

Abstract : State-of-the-art methods in materials science such as artificial intelligence and data-driven techniques advance the investigation of photovoltaic materials. Abstract : Photovoltaics is one of the most promising and fastest-growing renewable energy technologies. Although the price-performance ratio of solar cells has improved significantly over recent years, further systematic investigations are needed to achieve higher performance and lower cost for future solar cells. In conjunction with experiments, computer simulations are powerful tools to investigate the thermodynamics and kinetics of solar cells. Over the last few years, we have developed and employed advanced computational techniques to gain a better understanding of solar cells based on copper indium gallium selenide (Cu(In, Ga)Se2 ). Furthermore, we have utilized state-of-the-art data-driven science and machine learning for the development of photovoltaic materials. In this Perspective, we review our results along with a survey of the field.