With the expansion of automation in labs and the development of new machine learning tools to guide optimization processes, recent years have seen a boom of materials acceleration platforms (MAPs) in material science , . High-throughput experimental (HTE) platforms now enable rapid synthesis procedures , with inline material characterization , . Parallelization of workflows facilitates batch sampling, making experimentation even faster. Many examples of closed-loop optimization on HTE platforms can be found in the literature. For example, Wagner et al. developed the AMANDA platform to produce and characterize solution-processed thin-film devices for organic photovoltaic applications. Other MAPs have been implemented for the discovery of metal halide perovskite alloys , polymer composites for photovoltaics , and metal nanoparticles - .