Thursday, September 10, 2026
Science

Physics-aware benchmark reveals why similar materials AI models can predict thermal conductivity differently

Material properties such as sound insulation, resistance to extreme heat and thermal expansion originate from how the zillions of microscopic building blocks (nuclei and electrons) interact at equilibrium and respond to perturbations. Atoms are typically about one ten-billionth of a meter across, so...

Physics-aware benchmark reveals why similar materials AI models can predict thermal conductivity differently
Image: Phys.org
Material properties such as sound insulation, resistance to extreme heat and thermal expansion originate from how the zillions of microscopic building blocks (nuclei and electrons) interact at equilibrium and respond to perturbations. Atoms are typically about one ten-billionth of a meter across, so there can be a lot of parts to keep track of—a task that is complicated at the quantum-mechanical level, where particles are neither here nor there until observed.

Originally published at Phys.org

The Morning Briefing

Subscribe to our Newsletter

Be the first to receive the latest news, market analysis and updates — delivered straight to your inbox.