Full-stack inorganic crystal structure discovery and its discontents

Accelerated materials discovery has long been a stated goal of our research community, and organized efforts towards this goal are numerous and well-supported. Furthermore, simulation and machine learning have rapidly become popular methods of rationalizing and predicting material properties. However, the full-stack process of generating new material candidates, predicting their properties, synthesizing them, and identifying the resulting structure and function has not yet reached a widespread inflection point in its efficiency. In this talk, I describe Toyota Research Institute’s (TRI) end-to-end process, enhanced by AI and simulation, in which we have discovered previously unobserved inorganic crystal structures. Synthesis and characterization remain rate-limiting in our process, but preliminary research shows promise in addressing these bottlenecks to realize an accelerated full-stack materials discovery process.