Tungsten's superior performance in extreme environments makes it a leading candidate for plasma-facing components (PFCs) in ...

A new study shows that combining machine learning with advanced material engineering can significantly improve the ...

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 ...

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 ...

Hydrogen storage is limited by high pressure or cold tanks. Metal hydrides offer efficiency. A large curated database reveals key atomic traits to guide design. (Nanowerk News) Hydrogen fuels ...

Two-dimensional (2D) materials have shown extraordinary potential in electrocatalytic reactions due to their unique structural and electronic properties. In a new review published in AI Mater., first ...

A team of researchers has used machine learning to design a new stainless steel alloy built specifically for 3D printing, one ...

More aggressive feature scaling and increasingly complex transistor structures are driving a steady increase in process complexity, increasing the risk that a specified pattern may not be ...

As AI's integration in the process of designing and improving industrial infrastructure progresses, governance needs to ...

With additive manufacturing, used to build this heat exchanger, one key is to do prototyping for the part and then see whether additive or subtractive manufacturing is the better choice of manufacture ...