Magnetic materials are in high demand. They're essential to the energy storage innovations on which electrification depends ...

This is the case for Koopmans functionals, a promising approach to expand the power of density-functional theory so that it can be used to predict the spectral properties of materials (such as ...

Machine learning technique sharpens prediction of material's mechanical properties Date: March 16, 2020 Source: Nanyang Technological University Summary: Scientists have developed new approaches ...

Produced water composition reveals subsurface structures and provides a basis for scaling tendency prediction. Saudi Aramco developed a machine learning (ML) workflow that classifies produced ...

Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed machine learning-based methods to predict material properties even with limited ...

A new framework uses machine learning to simultaneously predict molecular properties and generate new molecules using only a small amount of data for training.

Machine learning predictions and system updates in real-time Huyen's analysis refers to real-time machine learning models and systems on 2 levels.

To model the properties of such materials, a group of physicists and mathematicians from MIPT and Skoltech updated its Moment Tensor Potentials method for obtaining machine learning interatomic ...