About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Presentation Title |
3rd Wave AI to Accelerate Materials Discovery |
Author(s) |
Andrew Detor, Kareem Aggour, Aida Amroussia, Scott Weaver, Abha Moitra, Alfredo Gabaldon, Paul Cuddihy, Sharad Dixit |
On-Site Speaker (Planned) |
Andrew Detor |
Abstract Scope |
With the widespread availability of open-source tools and commercial platforms, machine learning is changing the way new materials are developed; but a revolution in materials discovery remains elusive. We posit that “3rd wave AI” techniques allowing for the modeling of different forms of knowledge and the abstraction of concepts for reasoning and contextual adaptation will be necessary to make significant advancements in machine-assisted material discovery. We present recent progress at GE Research toward our vision to capture factual materials data in a knowledge graph augmented with analytical models and experiential knowledge codified from domain experts. By fusing these forms of knowledge together, we are enabling (i) reasoning with uncertainty for question-answering, and (ii) inferencing to propose novel materials outside the boundaries of the original dataset. A proof-of-concept is demonstrated through a case study involving the optimization of a physical vapor-deposited coating for power generation steam path applications. |
Proceedings Inclusion? |
Undecided |