Acceleration of Materials Insertion in the Age of Artificial Intelligence

While concepts around applying artificial intelligence to materials R&D have become commonplace, the road to this ubiquity has been decidedly uneven. Here we explore this evolution from the foundational ideas captured in the Materials Genome Initiative to the implications of autonomous laboratories (self-driving laboratories, SDLs) for the research enterprise. Realizing the promise of SDLs will also require a long, ongoing conversation about standards, as the interoperability of research tools is central to successful SDL implementation. Standards development can take years, and the incentives are often diffuse at best. However, the advent of large language models (LLMs) and associated tools may help to overcome the barriers to interoperability.