The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

A physics informed machine learning model predicts thermal conductivity from infrared images in milliseconds, enabling fast, ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Orbital-free approach enables precise, stable, and physically meaningful calculation of molecular energies and electron densities By applying new methods of machine learning in quantum chemistry ...

A particle collision reconstructed using the new CMS machine-learning-based particle-flow (MLPF) algorithm. The HFEM and HFHAD signals come from the ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently ...

In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic rays—particles arriving at high speed from outer space.

New data-driven map uses live weather, water temperature modeling, and machine learning to help prevent fish loss ...

Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...

BANGALORE, India , Feb. 17, 2026 /PRNewswire/ -- According to Valuates Reports, The global market for AI in Biotechnology was valued at USD 1033 Million in the year 2024 and is projected to reach a ...

Princeton Plasma Physics Laboratory plans to launch a new AI project, called STELLAR-AI, to lower costs and heighten efficiency for experiments. The program is anticipated to launch in 2027, and is ...