# Skoltech reports active-learning method for large composite-material simulations

_Monday, August 24, 2026 at 5:20 PM EDT · Science, AI · Latest · Tier 2 — Notable_

![Skoltech reports active-learning method for large composite-material simulations — Primary](https://scx2.b-cdn.net/gfx/news/hires/2026/metal-ceramics-under-a.jpg)

Researchers at Skoltech reported a machine-learning approach for modeling heterogeneous materials that uses active learning on local chemical configurations. The method identifies unreliable energy predictions during a simulation, sends selected fragments for density-functional-theory calculations, then adds them to training data and retrains the potential. In a WC-Co composite case study, the researchers said it handled systems containing tens of thousands of atoms with accuracy comparable to direct DFT calculations and described brittle-to-ductile behavior as cobalt content increased.

## Sources

- [Phys.org - latest science and technology news stories](https://phys.org/news/2026-08-metal-ceramics-ai-approach-mechanical.html)

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Retrieved: 2026-08-25T01:01:58.719Z
Publisher: Tech & Business (techandbusiness.org)