# Ames Laboratory Discovers Rare-Earth-Free Permanent Magnets Using AI

> Researchers at Ames National Laboratory are using physics-trained AI to hunt for permanent magnets that contain no rare earth elements, a supply chain dominated by a handful of countries. Rather than the usual trial and error, their workflow pairs fundamental physics models with high-throughput simulations to predict promising magnet compositions, including candidates outside the range of existing data. The distinction from typical machine learning is important. Because the models are grounded in physical laws, they can extrapolate to materials no one has made yet, instead of just interpolating from a training set. That makes them a genuine discovery tool rather than a pattern matcher. The effort feeds into the Department of Energy's Genesis Mission on critical materials, and the stakes are practical: rare-earth-free magnets would ease reliance on foreign sources for everything from electric motors to wind turbines. It is a concrete example of AI accelerating hard materials science.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: Ames Laboratory · Published Tuesday, July 14, 2026_

## Wortins' read

Researchers at Ames National Laboratory are using physics-trained AI to hunt for permanent magnets that contain no rare earth elements, a supply chain dominated by a handful of countries. Rather than the usual trial and error, their workflow pairs fundamental physics models with high-throughput simulations to predict promising magnet compositions, including candidates outside the range of existing data. The distinction from typical machine learning is important. Because the models are grounded in physical laws, they can extrapolate to materials no one has made yet, instead of just interpolating from a training set. That makes them a genuine discovery tool rather than a pattern matcher. The effort feeds into the Department of Energy's Genesis Mission on critical materials, and the stakes are practical: rare-earth-free magnets would ease reliance on foreign sources for everything from electric motors to wind turbines. It is a concrete example of AI accelerating hard materials science.

## Source

[Read the full story at Ames Laboratory](https://www.ameslab.gov/news/ames-lab-scientist-provides-ai-driven-roadmap-for-future-permanent-magnet-design)

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