According to a post by Northwestern University announcing their partnership with Toyota Research Institute (TRI), this collaboration will “help accelerate the discovery, design and development of new materials with the world’s first nanomaterial ‘data factory.’”
This AI-driven methodology goes far beyond the traditional trial and error by exploring vast parameter sets. It collects data and then empowers AI to search the materials genome — the set of all nanoparticle combinations of any of the usable elements in the periodic table — to find the best materials for a given application. While the first application of the data factory will be to discover new catalysts to make fuel cell vehicles more efficient, TRI and Northwestern believe this method of materials discovery will have wide-ranging applications in the future…
TRI and Northwestern developed a machine learning algorithm capable of synthesizing materials at record speeds to sift through Northwestern’s new Megalibraries — a library containing more new inorganic materials than scientists have ever collected and categorized. Together, these concepts form the first nanomaterial data factory — a groundbreaking effort to create and mine large sets of high-quality, complex data.
Chad Mirkin, director of the International Institute for Nanotechnology and the George B. Rathmann Professor of Chemistry at Northwestern states: “This groundbreaking research marks an inflection point in how we discover and develop critical materials…Together with TRI, we’re poised to empower the scientific community to find the best materials that can truly power the clean energy transition.”