Feature engineering of material structure for AI-based materials knowledge systems

This article introduces systematically the foundational concepts undergirding the recently formulated AI (artificial intelligence)-based materials knowledge system (AI-MKS) framework. More specifically, these concepts deal with features engineering the heterogeneous material internal structure to obtain low-dimensional representations that can then be combined with machine learning models to establish low computational cost surrogate models for capturing the process–structure–property linkages over a hierarchy of material structure/lengths scales.

Journal of Applied Physics 128, 041103 (2020); https://doi.org/10.1063/5.0011258

Leave a Reply

Your email address will not be published. Required fields are marked *