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

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 ...

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 ...

For his research in machine learning-based electron density prediction, Michigan Tech researcher Susanta Ghosh has been recognized with one of the National Science Foundation's highest honors. The NSF ...

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 ...

Jason Rivas is researching materials at the atomic level to improve reliability and resistance of electronics to space radiation. A PhD student in materials science and engineering at the University ...

Overview and trends of intelligent photonics in emerging technologies. Diffractive and metasurface neural networks for intelligent, versatile processing of free-space information. FAYETTEVILLE, GA, ...

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

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

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 ...