What if scientists could get a taste of discovery as soon as their experiment finishes? Thanks to a new machine learning tool called DONUT, researchers at the U.S. Department of Energy's (DOE) Argonne ...

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.

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 ...

This chapter is divided into two sections. The first section is an overview of the materials-science microgravity research program implemented by the National Aeronautics and Space Administration ...

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.

As artificial intelligence pushes semiconductors and data centers to new physical limits, advances in materials science are becoming essential to sustaining the pace of innovation. Provided bySyensqo ...

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 ...

For decades, parents have warned children to stay away from dangerous objects. In 1950, however, one American company did the ...

This chapter contains descriptions of the broad categories of microgravity materials-science experiments that could yield significant information that is unattainable in a terrestrial gravity field.