Physicists Receive $12.6M From Department of Energy to Continue Exploring Next-Generation Computing


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The first generation of computers used vacuum tubes. The second, transistors and the third, integrated circuits. Each new generation allowed computers to be faster, smaller and more energy efficient. Now, as the world stretches beyond the limits of integrated circuits, what does the fourth generation of computing look like?

The answer may lie with quantum materials that are able to achieve neuromorphic, or brain-like, computing capabilities with low energy consumption. Since 2018, Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C) — led by the University of California San Diego — has been at the forefront of this research. Now, through a highly competitive process, the Department of Energy (DOE) has announced $12.6 million in renewed funding for the center.

“This additional round of funding is a testament to the Department of Energy’s faith in the work Q-MEEN-C is doing,” stated UC San Diego Chancellor Pradeep K. Khosla. “The center embodies many of our guiding principles of collaboration and leading-edge research. This achievement not only reflects positively on the researchers, but also the Department of Physics and the entire university.”

Q-MEEN-C is a DOE Energy Frontier Research Center (EFRC) — one of more than 40 created to help tackle the world’s most pressing energy technology challenges. The center, led by UC San Diego, is a collaborative effort that brings together researchers from around the globe. They each bring unique expertise to a compelling scientific challenge: creating a brain-like computer with drastically lower energy requirements.

“With current technology, to make a device that mimics the brain, the local energy requirement is so large that it’s not practical,” stated Q-MEEN-C Director and Distinguished Professor of Physics Ivan K. Schuller. “During the semiconductor revolution, materials science helped developers identify silicon and germanium as ideal materials. It is the same now, where we see quantum materials as the key to increasing computational power while also decreasing local energy consumption.”

Quantum materials are a class of new materials that display more complex quantum mechanical behavior than silicon, and whose range of properties are exquisitely suited for more efficient and transformative neuromorphic computing.

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