Research authored by partners from the Bottle Consortium and published in Nature Communications this month aims to challenge ...

In the quest for stronger, more resilient buildings and infrastructure, engineers are turning to innovative solutions, such as concrete-filled steel tube columns (CFST) strengthened with carbon ...

A newly developed machine learning model makes reliable strength predictions in carbon fiber-reinforced steel columns, according to a news release by Seoul National University of Science & Technology.

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

To address these challenges, Associate Professor Takuya Taniguchi from the Center for Data Science and Ryo Fukasawa from Graduate School of Advanced Science and Engineering at Waseda University, Japan ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

This schematic illustrates the MALIO software, a machine learning structure analysis tool designed to analyze and distinguish the local structures of BP I and BP II liquid crystal phases. By ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...