Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Tech Xplore on MSN
With machine learning, researchers embrace the atomic-scale complexity of batteries
For grid-scale energy storage and national energy resilience, the U.S. needs better batteries. Lawrence Livermore National ...
Understanding the influence of quasiperiodicity on magnetic fluctuations could ultimately enable the design of materials with ...
Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in fusion reactors, but the ultra-high heat can damage its microscopic ...
The name “Magneto” surfaced during a discussion about using artificial intelligence to discover crystal structures for stronger permanent magnets. In Marvel Comics, Magneto can control every form of ...
Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...
Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...
Image courtesy by QUE.com For decades, the search for room-temperature superconductors has been one of physics' most ...
More than 20 faculty members and several students from across academic disciplines attended a two-day training workshop on June 4–5 to learn how AI machine-learning skills can assist with their ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results