Physics-based material parameters extraction from perovskite experiments via Bayesian optimization

arXiv:2402.11101v1 Announce Type: cross
Abstract: The ability to extract material parameters from quantitative experimental analysis is essential for rational design and theory advancement. However, the difficulty of this analysis increases significantly with the complexity of the theoretical model and the number of material parameters. Here we use Bayesian optimization to develop an analysis platform that can extract up to 8 fundamental material parameters of an organometallic perovskite semiconductor from a transient photoluminescence experiment, based on a complex full physics model …

abstract advancement analysis arxiv bayesian complexity cond-mat.mtrl-sci cs.ce cs.lg design experimental extract extraction material optimization parameters physics quantitative theory type via