A machine-learning model trained on fewer than 300 molecules has flagged diatomic pairs with record-high electric dipole ...

Machine learning models trained on molecular quadrupole moments predict electrostatic potentials rapidly, enabling faster ...

Scientists at Harvard have built a miniature device that can twist and tune light in real time. By rotating two stacked photonic crystals and adjusting their spacing with a tiny mechanical system, ...

Large language models lack grounding in physical causality — a gap world models are designed to fill. Here's how three distinct architectural approaches (JEPA, Gaussian splats, and end-to-end ...

A breakthrough deterministic physics kernel delivers molecular, materials, and reaction screening across three ...

Modern-day LLMs are "fiction machines," designed not to be truthful but to make sense. What can we expect from these machines, and what are their limitations?

Researchers join Wellcome Leap’s international effort to better understand early biological influences on neurodevelopment.

A research team has demonstrated how carbon-based diamond–water nanofluids can be strategically engineered to boost heat transfer over complex, wavy ...

Carbon forms the graphite in pencils, the diamonds in jewelry and the molecules that make up every living thing. But under extreme conditions—like the heat and pressure of intense explosions—carbon ...

The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as well?

Accurate spatiotemporal prediction is fundamentally essential for anticipating and managing the dynamic evolutions within global physical, environmental, ...

Google-Tesla MagNet Challenge is an annual competition. It’s designed to accelerate innovation in magnetic modeling using artificial intelligence (AI). This article reviews some of the highlights from ...