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

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 ...

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

Immuto CEO Faraz Choudhury spoke with Pharmaceutical Executive about his company’s work with focusing on Surface Protein Conformations (SPCs) for target discovery. According to him, traditional target ...

For Lucas Farnung, there is no question more fascinating than how a single fertilized egg develops into a fully-functioning human. As a structural biologist, he is studying this process on the ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

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 ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

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 ...