Chiral 2D metal halide perovskites (MHPs) are among the most promising materials for future technologies that exploit the spin of electrons in spin-based optoelectronics, or spintronics, but getting them to perform consistently has proven difficult. Now scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a data-driven approach that identifies and models key synthesis parameters to optimize their performance.