A new wave of physics-informed AI is accelerating the way scientists design and understand advanced materials. By embedding physical laws into machine learning models, researchers can simulate, test, ...

A ripple tells you something happened, but not exactly what. That is the core problem behind a hard class of equations that ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

From the outset, Alsym set a clear objective: to develop a truly non-flammable and high-performance battery chemistry. The physics-informed AI platform enabled this goal-guiding the discovery and ...

See more of our trusted coverage when you search. Prefer Newsweek on Google to see more of our trusted coverage when you search. John Hopfield and Geoffrey Hinton were awarded the 2024 Nobel Prize in ...

Machine learning is becoming an essential part of a physicist’s toolkit. How should new students learn to use it? When Radha Mastandrea started her undergraduate physics program at MIT in 2015, she ...

The study, published in Communications Chemistry, explores the first AI‑powered model that can keep molecular simulations running safely and smoothly, even when molecules are pushed to extreme ...

From mineral exploration to seismic interpretation, AI is reshaping how geoscientists work with complex, multi-source data. Machine learning models, generative AI, and prompt engineering are enabling ...