This Collection supports and amplifies research related to SDG3, SDG9 and SDG10. Physics-Informed Machine Learning (PI-ML) combines principles from physics- and biology-based modeling with data-driven ...

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 ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at temperatures as high as ...

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 ...

One of the key steps in developing new materials is “property identification,” which has long relied on massive amounts of experimental data and expensive equipment, limiting research efficiency. A ...

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 ...

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 ...