Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
AZOM

Harnessing AI and Machine Learning for Advanced Materials Testing

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...
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 ...
Nature

Machine Learning Applications in Microstructure Design and Material Properties

The integration of machine learning techniques into microstructure design and the prediction of material properties has ushered in a transformative era for materials science. By leveraging advanced ...
Phys.org

High-precision analysis of 2D materials microstructures achieved using electron microscopy and machine learning

A research team led by NIMS has, for the first time, produced nanoscale images of two key features in an ultra-thin material: twist domains (areas where one atomic layer is slightly rotated relative ...
AZOM

Enhancing Materials Research with XRM Microscopy and Deep Learning Reconstruction

Thought LeadersDr. Nikhil Gupta & Dr. Kaushik YanamandraProf. of Mechanical and Aerospace Engineering & Applications Development EngineerNew York University & ZEISS Microscopy In this interview, ...
Michigan Technological University

Researchers Apply Machine Learning and AI in Search of Less Costly Electronic Structure Method

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 ...
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 ...
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 ...