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Speeding Up Material Discovery


The algorithm simplifies computational required for material discovery and speeds up the process by about 10,000 times, compared to existing algorithms.

A new algorithm uses the chemical elements in a crystal to predict its material properties.

Credit: Second Bay Studioes/SEAS

Researchers at Harvard University's John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed an algorithm for discovering and optimizing new thermoelectric materials within months by tackling quantum mechanical equations without experimental input.

"Our goal was to find a new material that satisfies all the important properties for thermoelectric conversion while at the same time being stable and cheap," says SEAS professor Boris Kozinsky.

The algorithm predicts the electronic transport properties of a material based solely on the chemical elements of its crystal structure, while accelerating the computational approach for electron-phonon scattering by about 10,000-fold, compared to existing algorithms.

"We did in 15 months of computation and experimentation what took 15 years for previous materials to be optimized," Kozinsky says.

"What's really exciting is that we're probably not fully understanding the extent of the simplification yet. We could potentially make this method even faster and cheaper."

From John A. Paulson School of Engineering and Applied Sciences
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