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 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.

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.

Self-driving laboratories (SDLs) — research systems that combine robotics, AI, and autonomous experimentation — are transforming discoveries of new and better materials. Capable of running and ...

Scientists have developed an AI-based method that helps gather data more efficiently in the search for new materials, allowing researchers to navigate complex design challenges with greater precision ...

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.

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 ...

Materials science explores the structure and properties of materials — semiconductors, metals, ceramics, polymers, composites and more — to understand and improve their performance. From smartphone ...

This collection of lessons, videos and resources is designed for teachers, students and their families, exploring the science of materials from everyday applications to groundbreaking innovations.

The microgravity environment (10-6 g) of space provides a unique opportunity to further our understanding of various materials phenomena involving the molten, fluidic, and gaseous states by reducing ...