Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Isaac Newton may have met his match. For centuries, engineers have relied on physical laws -- developed by Newton and others -- to understand the stresses and strains on the materials they work with.

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of the quantum interactions that take place in materials. In new work, the group ...

For over 100 years, physicists, chemists, and materials scientists have developed extensive theoretical and experimental machinery to predict and characterize the electronic properties of magnetic ...

In a recent study published in Science, researchers from the University of Houston and Rice University found ways to predict band convergence in different materials. They also designed materials using ...

New metal-organic framework (MOF) materials based on gold nanoclusters have the potential to transform nanoelectronics. Four ...

Researchers developed a machine-learning technique that uses an image to estimate the stresses and strains acting on a material. The advance could accelerate engineers' design process by eliminating ...

Humans have been aware of the strange phenomenon of magnetism for over 2,000 years. From ancient Greece through modern times, researchers have steadily improved upon humanity’s fundamental ...