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CSI papers published: Artificial intelligence for materials discovery

13 Aug 2019, 11:40 UTC
CSI papers published: Artificial intelligence for materials discovery

Artificial intelligence for materials discovery by CSI members Carla Gomes, Bart Selman and colleague; email: cpg5@cornell.edu

Continued progress in artificial intelligence (AI) and associated demonstrations of superhuman performance have raised the expectation that AI can revolutionize scientific discovery in general and materials science specifically. We illustrate the success of machine learning (ML) algorithms in tasks ranging from machine vision to game playing and describe how existing algorithms can also be impactful in materials science, while noting key limitations for accelerating materials discovery. Issues of data scarcity and the combinatorial nature of materials spaces, which limit application of ML techniques in materials science, can be overcome by exploiting the rich scientific knowledge from physics and chemistry using additional AI techniques such as reasoning, planning, and knowledge representation. The integration of these techniques in materials-intelligent systems will enable AI governance of the scientific method and autonomous scientific discovery.

Carla Gomes, Computer Science & Information Science

Bart Selman, Computer Science

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