Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

When it comes to designing the moving structural elements of high-performance machine tools—such as beams, shafts and spindles, and the assemblies used to hold cutting tools—the need for the machine ...

Imagine having a super-powered lens that uncovers hidden secrets of ultra-thin materials used in our gadgets. Research led by University of Florida engineering professor Megan Butala enables a novel ...

Artificial Intelligence and its related tools, such as machine learning, deep learning, and neural networks, are revolutionizing every field of life. The domain of materials science and engineering is ...

Scientists and institutions dedicate more resources each year to the discovery of novel materials to fuel the world. As natural resources diminish and the demand for higher value and advanced ...

As new machining techniques become more widespread, it can be tempting for shops to try them out and put their promises to the test. It is important to not only learn how to use a new machining ...

How additive manufacturing advanced the development of functionally graded materials. Why compositionally graded materials present a greater challenge to materials engineers. How computational ...

Data driven science. Attendees from government and academia gather at the 10th colloquium by the journal Science and Technology of Advanced Materials at the Japanese Embassy to discuss the future of ...

Researchers have successfully applied machine learning to guide the synthesis of new nanomaterials, eliminating barriers associated with materials discovery. The highly trained algorithm combed ...