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.
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 ...
Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures using machine learning-based simulations. This information is crucial in ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...
Morning Overview on MSN
Machine learning is turbocharging cheap lithium-ion battery design
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 ...
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