October 2022: Matter
Materials Acceleration Platforms (MAPs) autonomously perform AI-guided, high-throughput experiments in the pursuit of materials discovery. Currently, MAPs are developed and operated in isolation by research groups, limiting their utility to their specific domains and groups. Furthermore, since developing a MAP is a time- and resource-intensive process, engineering constraints to their capabilities cannot be avoided. Surpassing these limitations require next-generation MAPs to work in collaboration among research groups, and the adoption of a common framework to plan experimental workflows could achieve this. Herein, we propose a framework to produce evolving experimental workflows that facilitate the interfacing between MAPs and enable collaborators to share knowledge, data, and tools. Through the wide adoption of our framework, we envision a global community of MAPs working together to solve the scientific grand challenges required to solve pressing societal problems.
