AI Approach Accelerates Speed of Predicting the Thermal Properties of Materials
Estimates show that roughly 70% of energy generated around the globe is wasted. Experts believe that more efficient systems to generate power could be designed if researchers were able to forecast how heat passes through insulators and semiconductors. This is hard to do at the moment, however, because it is challenging to model the thermal properties of different materials. The issue stems from subatomic particles that carry heat, known as phonons. A group of MIT researchers have designed a new framework based on machine-learning, which can forecast phonon dispersion relation about 1,000 times faster than other methods based on artificial…