From guesswork to guidance: How machine learning speeds dopant design for water-splitting photocatalysts

MLIP calculations successfully identify suitable dopants for a novel photocatalytic material, report researchers from the ...
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 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 ...
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 ...
Nanowerk

Strong as steel, light as foam: Machine learning and nano-3D printing create breakthrough nano-architected materials

(Nanowerk News) Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon ...
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 ...
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 ...
Medicine Buffalo

AI-Guided Material Discovery: Unsupervised Learning and Data Science for Safer, High Performance Material Discovery

Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning. Our lab in the Department of Materials ...
Science Daily

A novel machine learning model for the characterization of material surfaces

Machine learning (ML) enables the accurate and efficient computation of fundamental electronic properties of binary and ternary oxide surfaces, as shown by scientists. Their ML-based model could be ...
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

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 ...