Grant: Alliance Grants

A3MD - as a partnership between University of Toronto, McMaster University, TOTAL, Microsoft, and LG - will use artificial intelligence (AI) and high-throughput experimentation to accelerate the rate at which new materials are discovered by a minimum factor of 100x relative to conventional approaches. Materials discovery-here defined as the identification and experimental realization of new materials with desired properties for high-performance technologies-is expensive and time-consuming, with typical lab-to-market timelines near or exceeding 20 years. We will address this by accelerating different stages of the materials discovery pipeline: computational screening of properties of materials, synthesis of materials, and evaluation of materials; and we will accelerate the learning rate from each experiment toward achieving target properties. Our efforts will focus on new materials for electrocatalysis and ultraviolet light emission, two technologies that present multi-billion-dollar untapped economic benefits for Canada. By project outcome, we will deliver 1) the generalized methodology (algorithms, processes, and tools) for >100x acceleration of materials discovery, and demonstrate the value of this by achieving: 2) CO2 reducing catalysts with >75% faradaic efficiency for methane, 3) oxygen evolution catalysts with < 200 mV overpotential, and 4) ultraviolet light-emitting diodes with external quantum efficiency >20%.