aebrahim

My research focuses on using machine learning to improve simulations of materials, particularly perovskites like CsPbI₃ and CsSnI₃, which are important for solar cells. I work on developing machine learning models to create more accurate interatomic potentials for molecular dynamics simulations, which help us understand how these materials behave under different conditions like temperature and pressure. My work also involves using advanced computational methods, like density functional theory (DFT) and ab initio molecular dynamics, to generate data that feeds into these models. Ultimately, I aim to make safer, lead-free perovskites for sustainable energy applications and better predict their properties and phase behavior.