Revealing the evolution of order in materials microstructures using multi-modal computer vision
Year: 2025
Type: article
Abstract: The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La 1− x Sr x FeO 3 . We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision.
Source: npj Computational Materials
Authors: Arman Ter-Petrosyan, Michael Holden, Jenna A. Bilbrey, Sarah Akers, Christina Doty, Kayla H. Yano, Le Wang, Rajendra Paudel, Eric Lang, Khalid Hattar, Ryan B. Comes, Yingge Du, Bethany E. Matthews, Steven R. Spurgeon
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,490
Funders: National Science Foundation, U.S. Department of Energy, Battelle, Center for Integrated Nanotechnologies, Office of Science, Division of Materials Research, Biological and Environmental Research, Laboratory Directed Research and Development, National Renewable Energy Laboratory, Sandia National Laboratories, Los Alamos National Laboratory, Pacific Northwest National Laboratory
Awards: G1017065088, G11630931, G125460123, G1279347439, G138090931, G14908310, G1527848044, G1554626710, G1843378252, CAREER: Topological Phenomena in 4d and 5d Complex Oxide Interfaces and Superlattices Grown by Hybrid Molecular Beam Epitaxy, G2270264153, G2356915424, G2644915645, G280414146, G288067973, G2988778103, G3850071954, G3883580859, G391136020, G413247060, G440252240, G472303462, G4785159920, G5061342813, G5082106324, G5269527469, Exploration of Electronic and Catalytic Behavior in Epitaxial Complex Oxide Films and Nanocomposites, G5361327416, G5435665298, G5726405315, G5985666050, G6259200350, G6338696783, G680142904, G7002074430, G7021897321, G70659677, G70797072, G7977574923, G821644656, G834333836, G847654844, G851502033, G872931124, G944719100
OpenAlex ID: W4416468963