New physics-based machine-learning method speeds search for 2D quantum materials

Researchers at The University of Manchester have developed a new computational approach to help identify two-dimensional ...

Machine learning unlocks a new class of magnetic materials

Understanding the influence of quasiperiodicity on magnetic fluctuations could ultimately enable the design of materials with ...
Nature

Machine learning for materials discovery and optimization

This Collection supports and amplifies research related to SDG 9 - Industry, Innovation & Infrastructure. Discovering new materials with customizable and optimized properties, driven either by ...
Phys.org

Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Science Daily

Novel machine learning model can predict material failure before it happens

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...
AZOM

Machine Learning Approaches for Accelerated Materials Discovery

Artificial Intelligence and its related tools, such as machine learning, deep learning, and neural networks, are revolutionizing every field of life. The domain of materials science and engineering is ...
Semiconductor Engineering

Machine Learning Tools Accelerate Materials Discovery

Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...
AZOM

OptiMate: Accelerating Sustainable Material Discovery with Machine Learning

A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...
Science Daily

Novel machine learning-based cluster analysis method that leverages target material property

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study ...
Labroots

Machine Learning for Materials Discovery

How can artificial intelligence (AI) machine learning models be used to identify new materials? This is what a recent study published in Nature hopes to address as a team of researchers investigated ...