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.

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.

ASU is home to researchers at the forefront of material science, pushing boundaries with innovative techniques. These methods are not only advancing the understanding of matter but also driving the ...

The integration of self-driving laboratories and advanced automation software is revolutionising the fields of chemistry and materials science. By harnessing the power of robotics, artificial ...

From creating lightweight yet durable prosthetics to designing new types of solar panels and batteries, materials engineers combine their expertise in physics, chemistry, biology, and engineering to ...

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.

Princeton Engineering researchers are combining their expertise in chemical engineering, materials and computation to design crystalline materials that can be used to mitigate pollution or make ...

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