Graph deep learning models, which incorporate a natural inductive bias for atomic structures, are of immense interest in materials science and chemistry. Here, we introduce the Materials Graph Library ...

An international team of researchers has developed a new method for parameterizing machine-learning interatomic potentials (MLIP) to simulate magnetic materials, making the prediction of their ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

A fundamental challenge in teaching a subject like materials science is that students need to absorb and rapidly connect concepts that link materials behavior at the engineering scale with molecular ...

Materials language processing (MLP) can facilitate materials science research by automating the extraction of structured data from research papers. Despite the existence of deep learning models for ...

MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...

Amorphous materials such as glass are solids whose internal structure lacks a repeating pattern. Their molecules are arranged ...

Materials are a necessity for all engineering applications. Materials science and engineering seeks to understand the fundamental physical origins of material behavior in order to optimize properties ...

The Materials Science and Engineering PhD program at CU Boulder will provide you a thorough, interdisciplinary education in materials science and engineering and the fundamental physics, engineering, ...

Recycling-focused technology firm says its Scrap Science app offers affordable metals identification and workforce training tools. Beyond materials identification, employers can use the Scrap Science ...