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 ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

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 ...

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 developed a machine learning model that accurately predicts which polyimide structures will form liquid crystalline phases, speeding up the design of thermally conductive polymers for ...

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 ...

The Evolving Landscape Of Material Science. It feels like material science is really hitting its stride right now. We’re not ...

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 ...

NASA’s Transformational Tools and Technologies project integrates AI, advanced materials, and computational methods to ...

Advancements in Material Design and Synthesis It feels like every week there’s some new material that’s supposed ...