AI and ML-assisted prediction, design, and optimization of solar cells

With the increase in energy demands and a growing need for a green energy source, solar cells have risen as a competent candidate. Artificial Intelligence (AI) and Machine Learning (ML) techniques are emerging as promising technologies that are assisting in different research areas by contributing to their technological development and increasing operational efficiency. Integrating AI and ML into the process of development of solar cells is a growing research field that can help reduce the limitations of solar cells- their low stability, low power conversion efficiency, and high manufacturing costs. This study discusses the incorporation of and recent developments made by AI and ML-assisted techniques for designing and optimizing solar cells. Selecting optimal materials for solar cells can be done by using ML techniques to predict the properties of materials, such as their optical and electrical properties, I-V performance, water solubility, and stability. Researchers can then analyze these material properties to select suitable materials for solar cell design. AI can further help apply different ML models to to study the effect of different parameters in the designed solar cells. These parameters can then be optimized to increase the performance of solar cells. Hence, incorporating AI and ML can make the process of solar cell design cost, labour, and time effective. This study discuses the recent developments made by researchers in these fronts.