A new review in the Journal of Materials Science maps how machine learning, from graph neural networks to large language models, is accelerating the design of high-entropy alloy catalysts across vast ...

A first-of-its-kind systematic review of 190 studies finds that HASM, Euclidean-enhanced machine learning, and Bayesian ...

High-entropy alloys (HEAs), characterized by complex multielement compositions, offer broad opportunities to tune mechanical, corrosion, thermal, wetting, and functional properties, while their vast ...

Until yesterday, I was on a road trip with five university friends, renting an Alphard and driving around the Kushiro Marsh, ...

Entropy now offers a shortcut to assessing quantum error correction where previously only complex computation existed. This ...

Magnetic tunnel junction hardware random number generators hit new performance frontier: UT Austin research in Journal of ...

Could reliable quantum hypothesis tests previously be guaranteed only for relatively simple systems? This work extends the ...

One of the most important qualities of a strong magnet is its ability to keep its magnetization aligned in a preferred ...

Text analysis textbooks, Kaggle tutorials, and commercial NLP tools—every 'preprocessing guide' recommends it first: 'Remove ...

Google Cloud's CISO, and other experts talk about agentic cybersecurity technologies real-time capabilities, and 2027 CISO ...

Explore how an ai investing think tank blends machine learning and economic history to build resilient quantitative models and capture institutional alpha.

Metals and alloys are materials that are typically hard, malleable, and have good electrical and thermal conductivity. Alloys are made by melting two or more elements together, at least one of them a ...