This article discusses the bottleneck in property characterization faced by high-throughput materials synthesis methods and proposes automated characterization tools that leverage adaptive computer vision to significantly accelerate the process. The tools include a generalizable composition mapping tool and two scalable autocharacterization algorithms, which have been demonstrated on the formamidinium and methylammonium mixed-cation perovskite system.
