Inventing Cheap Catalysts by Modeling Atomic Interactions using Graph Neural Nets. How ML can help save the world from catastrophe.
Computational-chemist - the new breed of scientist In today's rapidly evolving tech landscape, a new breed of scientist/engineer is emerging: the computational chemist, along with their counterpart in biology and physics. Their mission? To harness the power of Machine Learning (ML) to expedite the discovery of revolutionary new compounds. These compounds may serve as catalysts in planetary-scale CO2 removal machines, or as key components in ground-breaking battery chemistry that might someday allow commercial airliners to go electric! Alternatively, they could form the basis for innovative drugs or vaccines in the fight against plague and disease. In this post, I discuss how Graph Neural Nets (GNNs) can be used to accelerate the discovery of new materials critical for fighting climate change. At the recent CVPR conference , the premier gathering for scientists and engineers in Computer Vision and Machine Learning, we were told by Larry Zitnick , the co-architect of the celebrated M...