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 ...

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 ...

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 ...

Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...

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 ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

Researchers in Sweden have developed a machine-learning approach that embeds the laws of physics directly into neural ...