Soft-AE: Lowering the Barrier for High-Throughput Characterization and Autonomous Experimentation in Conductive Polymers

Development of selective, robust, and efficient conducting polymers for separations and energy applications requires navigating a many-dimensional design space of molecular design (e.g., moiety, architecture, ion selectivity), processing trajectory, and operating conditions. To help accelerate the mapping of structure-property-function relationships in soft charge-transporting materials, we present Soft-AE, a high-throughput, multimodal characterization platform assembled with a combination of budget open-source and custom-prototyped hardware. We showcase high-throughput, humidity-controlled electrical and ionic conductivity measurements, with developing capabilities for probing polymer and nanocomposite formulation spaces. We further demonstrate proof-of-concept, autonomous Bayesian optimization campaigns of electrical conductivity in drop-casted aqueous polymer-nanoparticle composites. In demonstrating this system, we envision a path towards more accessible soft-matter instrumentation for greater accessibility and aggregate impact in polymer science.