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

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

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 ...

Understanding the properties of different materials is an important step in material design. X-ray absorption spectroscopy (XAS) is an important technique for this, as it reveals detailed insights ...

Despite the excitement surrounding generative AI, the data shows that scientific research is still powered primarily by ...

Penn State researchers created seven new high-entropy oxides by removing oxygen during synthesis, enabling metals that normally destabilize to form rock-salt ceramics. Machine learning helped identify ...

Shanghai, August 21, 2025 — Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and efficient use depends critically on the development ...

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 ...

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, ...

Penn State scientists discovered seven new ceramics by simply removing oxygen—opening a path to materials once beyond reach.

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...