Exploring the vast and veiled chemical spaces via synthesis is essential in solid-state materials. However, navigating uncharted chemical spaces can be a daunting task, particularly when a material has complex structural features. Metal halides represent one such space, where the coexistence of perovskites and their derivatives has restricted the exploration of this fascinating family. Here, we meticulously collect inorganic halide perovskite derivatives and systematically explore them via a combination of high-throughput density functional theory calculations and machine learning. We chart the chemical spaces by listing stable compositions on the periodic table and yield informatics on electrical properties and thermal stability. Guided by these predictions, we showcase the successful synthesis of new Cs3LuCl6, as well as its implementation into white-light-emitting diodes. Our exploration can inspire the design of inorganic metal halides, thereby paving the way for envisioning their practical applications across various fields.
This research was supported by National Research Foundation of Korea (RS-2023-00209910). We gratefully acknowledge support from the Ministry of Science and ICT (NRF-2020M3H4A3081867) and from the Samsung Research Funding & Incubation Center of Samsung Electronics under Project Number SRFC-TC2103-04.