New Cambridge human brain-inspired chip could slash AI energy use — new type of memristor has roughly a million times lower switching current than conventional devices

Researchers at the University of Cambridge published a paper in Science Advances earlier this month describing a new type of hafnium oxide memristor. The highlight of the new technology is that it operates at switching currents roughly a million times lower than conventional oxide-based devices.

The team, led by Dr. Babak Bakhit from Cambridge's Department of Materials Science and Metallurgy, engineered a multicomponent thin film that forms an internal p-n junction, enabling the device to switch states smoothly at currents below 10 nanoamps while producing hundreds of distinct conductance levels.

Memristors are two-terminal devices that can store and process data in the same physical location, eliminating the energy-intensive data shuttling between separate memory and processing units in conventional computer architectures. Neuromorphic systems built from memristors could reduce computing power consumption by more than 70%, according to the paper.

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