article content
The first generation of computers used vacuum tubes. The second, transistors and the third, integrated circuits. With each new generation, computers have become faster, smaller and more energy efficient. Now that the world is moving beyond the limits of integrated circuits, what does the fourth generation of computers look like?
The answer could lie in quantum materials capable of achieving neuromorphic or brain-like computing abilities 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, in a hard-fought 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 confidence in the work of Q-MEEN-C,” said Pradeep K. Khosla, Chancellor of UC San Diego. “The center embodies many of our guiding principles of collaboration and cutting-edge research. This achievement not only casts a positive light on the researchers, but also on the Department of Physics and the entire university.”
Q-MEEN-C is a DOE Energy Frontier Research Center (EFRC) – one of more than 40 established to help address some of the most pressing energy technology challenges. Led by UC San Diego, the center is a collaborative effort that brings together researchers from around the world. They all bring unique expertise to a compelling scientific challenge: creating a brain-like computer that uses drastically less power.
“With current technology, the local energy requirement to produce a device that mimics the brain is so great that it is impractical,” said Ivan K. Schuller, director of Q-MEEN-C and distinguished professor of physics. “During the semiconductor revolution, materials science helped designers identify silicon and germanium as ideal materials. It is the same now that we see quantum materials as the key to increasing computational power while reducing local energy consumption.”
Quantum materials are a class of new materials that exhibit more complex quantum mechanical behavior than silicon and whose property spectrum is well suited for more efficient and transformative neuromorphic computing.
