Researchers Use Deep Learning to Create New Alloys

Liputan6.com, Jakarta – Supercomputer simulations help researchers find types of alloy metal new, called high-entropy alloys.

The researchers have used the Stampede2 supercomputer from the Texas Advanced Computing Center (TACC) allocated by the Extreme Science and Engineering Discovery Environment (XSEDE). Their research is published in the journal Npj Computational Materials.

This approach can be applied to finding new materials for batteries, catalysts and more without the need for expensive metals such as platinum or cobalt.

“High-entropy alloys represent a completely different design concept. In this case we tried to combine some of the main elements together,” said Wei Chen, co-author of the paper, who is also a professor of materials science and engineering at the Illinois Institute. of Technology.

The term “high entropy” briefly refers to the energy drop obtained from the random mixing of several elements of the same atomic fraction, which can stabilize the new material.

For research deep learning In this case, Chen and colleagues surveyed a large chamber made up of 14 elements and combinations that resulted in high-entropy metal alloys.

They performed high-throughput quantum mechanics calculations, which discovered the stability and elastic properties of alloys, the ability to regain their size and shape from stress, in more than 7,000 high-entropy alloys.

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