AI Institute: Planning: Novel Neural Architectures for 4D Materials Science

Grants and Contracts Details


The main theme of our proposed project is to build novel material-specific learning architectures based on multi-scale "4D-microstructure" (in contrast to 3D-microstructure) representation space to discover the multi-scale material mechanisms for predictive material modeling and material design. The impact of the proposed project goes far beyond establishing high-fidelity predictive models for the specific material system of interest (i.e., corrosion crack evolution in metallic alloys). It inspires one to re-think the utility of machine learning in materials science: from knowledge-agnostic feature learning to reasoning mechanisms adaptive to domain-specific knowledge. The methodologies and frameworks for constructing novel physics-based learning models developed in this project can be readily applied to a variety of heterogeneous material systems.
Effective start/end date9/1/208/31/23


  • Arizona State University: $30,000.00


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