A better way to model the behavior of metal alloys
MIT researchers' approach captures subtle atomic patterns, improving predictions of material properties. MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal alloys and other complex materials will behave. Zach Winn | MIT News Publication Date : June 19, 2026 Press Inquiries Press Contact : Abby Abazorius Email: abbya@mit.
Key Takeaways
- edu MIT News Office Media Download ↓ Download Image Caption : MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal alloys and other complex materials will behave.
This figure compares a random sampling approach to the researchers' new motif-based sampling.
- At the center of the approach are machine-learning models that make simulations of materials faster and more accurate.
The researchers improved those models by building training datasets that capture the diversity of atomic environments in chemically disordered materials.
- That's what makes this exciting.
" Joining Freitas on the paper are first author Killian Sheriff PhD '26; MIT PhD students Daniel Xiao and Yifan Cao; and University of Sheffield Senior Lecturer Lewis R.
- Over the last two decades, machine learning has become the most accurate way to build those models.
- Credits : Credit: Courtesy of the researchers *Terms of Use: Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license .
MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal alloys and other complex materials will behave. MIT researchers' approach captures subtle atomic patterns, improving predictions of material properties. Zach Winn | MIT News Publication Date : June 19, 2026 Press Inquiries Press Contact : Abby Abazorius Email: abbya@mit.
edu MIT News Office Media Download ↓ Download Image Caption : MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal alloys and other complex materials will behave. This figure compares a random sampling approach to the researchers' new motif-based sampling. Credits : Credit: Courtesy of the researchers *Terms of Use: Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license .
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