The Toyota Research Institute, aka TRI, will work with research entities, universities and companies on new materials science research, investing approximately $35 million over the next four years using artificial intelligence to help accelerate the design and discovery of advanced new materials.
Initially, the program aims to help revolutionize materials science and identify new materials for batteries and fuel cell catalysts that can power future zero-emissions and carbon-neutral vehicles.
Early research projects include collaborations with Stanford University, the Massachusetts Institute of Technology, the University of Michigan, the University at Buffalo, the University of Connecticut and the U.K.-based materials science company Ilika. TRI is also in ongoing discussions with additional research partners.
New materials research – it’s claimed – will merge advanced computational materials modeling, new sources of experimental data, machine learning and artificial intelligence to reduce the time for new materials development from a period that has historically been measured in decades.
Research programs will follow parallel paths, trying to identify new materials for use in future energy systems as well as to develop tools and processes that can accelerate the design and development of new materials more broadly.
TRI will partner on projects for:
- The development of new models and new materials for batteries and fuel cells;
- Broader programs to pursue novel uses of machine learning, artificial intelligence and materials informatics approaches for the design and development new materials; and,
- New automated materials discovery systems that integrate simulation, machine learning, artificial intelligence and/or robotics.
Accelerating materials science discovery represents one of four core focus areas for TRI, which was launched in 2015 to also enhance auto safety with automated technologies, increase access to mobility for those who otherwise cannot drive and help translate outdoor mobility technology into products for indoor mobility.