In data science we trust: Machine learning for stable halide perovskites

Abstract

The exploration of the compositional space of halide perovskites is prohibitively costly using traditional experimental research strategies. Sun and colleagues demonstrated a physics-informed, machine-learning-guided, experimental approach that overturns this limitation enabling a rapid and efficient maximization of stability in mixed-cation perovskites.