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 ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
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 ...
Researchers at the Indian Institute of Science (IISc), with collaborators at University College London, have developed ...
MIT researchers have designed a printable aluminum alloy that’s five times stronger than cast aluminum and holds up at ...
Machine learning (ML) enables the accurate and efficient computation of fundamental electronic properties of binary and ternary oxide surfaces, as shown by scientists. Their ML-based model could be ...
(a) The workflow contains three parts: ML model selection to calculate the expected improvement (EI) values of the target properties for a given alloy; the non-dominated sorting genetic algorithm ...
A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
Programmable material systems are emerging architectural structures but the co-design of structure, material, and external stimuli present grand challenges. A team with Northwestern Engineering’s Wei ...
Scientists have used artificial intelligence (AI) to design never-before-seen nanomaterials with the strength of carbon steel and the lightness of styrofoam. The new nanomaterials, made using machine ...
By applying machine learning techniques, engineers at MIT have created a new method for 3D printing metal alloys that produce ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback