# Ames Lab's DuctGPT discovers rare-earth-free permanent magnets via physics-informed AI

> Researchers at Ames Laboratory have used an AI model called DuctGPT to discover new rare-earth-free permanent magnets, and the interesting part is how it reasons. Rather than pattern-matching against a database of known materials, the model is physics-informed, meaning it works from the underlying chemistry and physics, which lets it propose candidates in chemical territory no one has catalogued yet. In this case it invented new bismuth-manganese composites, and notably it weighed production costs and component sourcing while doing so, not just theoretical performance. That practicality matters because rare-earth magnets sit at the heart of everything from electric motors to wind turbines to defense hardware, and their supply is geopolitically fraught. A viable rare-earth-free alternative would be a genuinely big deal. The broader signal is a shift in how AI is used in science. Instead of serving as a fast analyzer of existing data, a model like this acts more like a reasoning collaborator exploring unknown space. That is the difference between speeding up the search and actually expanding where you can look.

_Section: [Daily AI Updates](https://www.wortins.com/daily-ai) · Source: News Medical · Published Thursday, July 23, 2026_

## Wortins' read

Researchers at Ames Laboratory have used an AI model called DuctGPT to discover new rare-earth-free permanent magnets, and the interesting part is how it reasons. Rather than pattern-matching against a database of known materials, the model is physics-informed, meaning it works from the underlying chemistry and physics, which lets it propose candidates in chemical territory no one has catalogued yet. In this case it invented new bismuth-manganese composites, and notably it weighed production costs and component sourcing while doing so, not just theoretical performance. That practicality matters because rare-earth magnets sit at the heart of everything from electric motors to wind turbines to defense hardware, and their supply is geopolitically fraught. A viable rare-earth-free alternative would be a genuinely big deal. The broader signal is a shift in how AI is used in science. Instead of serving as a fast analyzer of existing data, a model like this acts more like a reasoning collaborator exploring unknown space. That is the difference between speeding up the search and actually expanding where you can look.

## Source

[Read the full story at News Medical](https://www.news-medical.net/news/20260611/AI-breakthrough-accelerates-molecular-simulations-for-drug-discovery.aspx)

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