Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

research laboratory to study “bad bubbles” that cause defects in metal alloys used to produce engine turbine blades and semiconductor crystals that are crucial components in electronic devices.

In a recent webinar organized by the National Academy of Engineering in connection with its forthcoming Fall ...

Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

This familiar phenomenon has puzzled researchers for centuries, but experiments are finally making sense of its unruly ...

We are entering a new era in science — the fourth paradigm, according to Kristin Persson, a professor in materials science at the University of California in Berkeley, United States. The first ...

Researchers have found an efficient way to identify 'topological' materials, whose surfaces can have different electrical or functional properties than their interiors. The approach should make it ...

Materials are a necessity for all engineering applications. Materials science and engineering seeks to understand the fundamental physical origins of material behavior in order to optimize properties ...

The Materials Science Laboratory is primarily used by the Mechanical Engineering students to support relevant courses and research activities. The Material Science laboratory consists of equipment ...