Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...

Physics-informed machine learning connects atomic structure with ion transport and electrolyte stability, accelerating better sodium- and lithium-ion batteries.

Artificial intelligence startup HeyDonto AI Technology today announced that it has established DFT Labs, a research ...

Analytical chemists have been using machine learning long before ChatGPT made headlines. Now, as generative AI enters the ...

For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National Laboratory (LLNL) scientists are tackling that challenge in many ways, but ...

This review examines how microscopy and computational analysis can identify defects in self-assembled nanosphere structures ...

What if the Higgs boson found in 2012 is not alone but is the only sibling we have encountered so far? Scientists at CERN discovered the particle that year, and it was a major discovery because it ...

Summary: A study demonstrates that learning in neural networks is driven primarily by adjusting the strength of existing ...

From AI majors to traditional STEM degrees, here's what you should study if you want to work in artificial intelligence and set yourself up for a future-proof career.

How does the brain learn? Does it acquire new knowledge by creating new neural pathways or by strengthening existing ...

Researchers found that leading AI tools for protein structure prediction can produce scientifically implausible results while ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics.