The integration of machine learning with traditional alloy design methods has allowed researchers to rapidly identify and optimize compositions that were previously unimaginable.

The method, which relies on machine learning, accurately predicted the energy, mechanical and magnetic characteristics of the alloy of iron and aluminum.

Nuclear energy is widely recognized as one of the most promising clean energy sources for the future, but its safe and ...

A new scientific machine learning framework developed by Professors Horacio D. Espinosa, Sridhar Krishnaswamy, and collaborators accurately predicts and inversely designs the mechanical behavior of ...

Carbon nanostructures could become easier to design and synthesize thanks to a machine learning method that predicts how they grow on metal surfaces.

Samsung’s method depends on Cadence’s Cerebrus, an AI-driven chip design automation tool that allows the designer to specify primitives, such as switching power and power leakage, depending on the ...