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

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful ...

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 ...

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) A feasible route for developing large materials models capable of describing the structure-property relationship of materials. The universal materials model of DeepH accepts an arbitrary material ...

The number of scientific papers is growing so rapidly that scientists are no longer able to keep track of all of them, even ...

A new model measures defects that can be leveraged to improve materials' mechanical strength, heat transfer, and ...

A recent study published in Small highlights how machine learning (ML) is reshaping the search for sustainable energy materials. Researchers introduced OptiMate, a graph attention network designed to ...

Researchers at Monash University have developed an artificial intelligence (AI) model that significantly improves the accuracy of four-dimensional scanning transmission electron microscopy (4D STEM) ...

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