  Antisolvent crystallization methods are frequently used to fabricate
high-quality perovskite thin films, to produce sizable single crystals, and to
synthesize nanoparticles at room temperature. However, a systematic exploration
of the effect of specific antisolvents on the intrinsic stability of
multicomponent metal halide perovskites has yet to be demonstrated. Here, we
develop a high-throughput experimental workflow that incorporates chemical
robotic synthesis, automated characterization, and machine learning techniques
to explore how the choice of antisolvent affects the intrinsic stability of
binary perovskite systems in ambient conditions over time. Different
combinations of the endmembers, MAPbI3, MAPbBr3, FAPbI3, FAPbBr3, CsPbI3, and
CsPbBr3, are used to synthesize 15 combinatorial libraries, each with 96 unique
combinations. In total, roughly 1100 different compositions are synthesized.
Each library is fabricated twice using two different antisolvents: toluene and
chloroform. Once synthesized, photoluminescence spectroscopy is automatically
performed every 5 minutes for approximately 6 hours. Non-negative Matrix
Factorization (NMF) is then utilized to map the time- and
compositional-dependent optoelectronic properties. Through the utilization of
this workflow for each library, we demonstrate that the selection of
antisolvent is critical to the stability of metal halide perovskites in ambient
conditions. We explore possible dynamical processes, such as halide
segregation, responsible for either the stability or eventual degradation as
caused by the choice of antisolvent. Overall, this high-throughput study
demonstrates the vital role that antisolvents play in the synthesis of
high-quality multicomponent metal halide perovskite systems.
