Ab initio modeling of lead-free perovskite-derived 2D Cs₃Bi₂I₉

In recent years, organic-inorganic mixed halide perovskites have been of utmost importance for renewable energy and information technology due to their remarkable properties. But the toxicity of lead and instability of the organic component has limited the potential applications of such materials. The environmentally friendly Pb-free all inorganic two-dimensional (2D) perovskite derived material of the family of Cs₃Bi₂I₉ (CBI) are promising to overcome these limitations.  In this work, we have been modeling 2D CBI using Density Functional Theory to study its electronic structure, elastic and mechanical stability, and Raman spectrum. We also propose to use high-throughput computational approaches assisted by materials informatics, machine learning (ML) models, and first-principles computational modelling to develop a comprehensive understanding of the emerging properties, such as mechanical, optoelectronic, and transport properties of 2D CBI family. The mechanical stability (temperature-dependent) will be studied using the ElasTool toolkit, which is highly efficient for predicting the mechanical properties of materials. Using high-throughput computational modelling and ML models, we will screen the CBI family to determine those with interesting properties for further study using first-principle techniques.