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.
You may like 'Thermodynamic computing' could slash energy use of AI image generation by a factor of ten billion, study claims Chinese researchers hail breakthrough in DRAM-like cells, which could be used in embedded or 3D stacked memory Bill Gates-backed silicon photonics startup develops optical transistors 10,000x smaller than current tech Most existing HfO2-based memristors rely on filamentary resistive switching, where conductive paths grow and rupture inside the oxide. These filaments exhibit stochastic behavior, resulting in poor device-to-device and cycle-to-cycle uniformity that limits computational accuracy.
The Cambridge team took a different approach by adding strontium and titanium to hafnium oxide and depositing the film in a two-step process, thereby creating a p-type Hf(Sr,Ti)O2 layer that self-assembles a p-n heterointerface with an underlying n-type titanium oxynitride layer. Resistance changes occur by shifting the energy barrier height at this interface rather than by growing or breaking filaments.
"Filamentary devices suffer from random behavior," Bakhit said in a Cambridge press release announcing the work. "But because our devices switch at the interface, they show outstanding uniformity from cycle to cycle and from device to device."
The devices demonstrated switching currents at or below 10 -8 amps, retention exceeding 10 5 seconds, and endurance beyond 50,000 pulse-switching cycles. Using identical 1.0 V spikes comparable to biological neural signaling, the researchers achieved a conductance-modulation range exceeding 50 times across hundreds of distinct levels without saturation.
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