Reconfigurable perovskite nickelate electronics for artificial intelligence

Reconfigurable devices offer the ability to program electronic circuits on demand. In this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in post-fabricated perovskite NdNiO3 devices that can be simply reconfigured for a specific purpose by single-shot electric pulses. The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks. Description Reconfigurable neuromorphic functions Having all the core functionality required for neuromorphic computing in one type of a device could offer dramatic improvements to emerging computing architectures and brain-inspired hardware for artificial intelligence. Zhang et al. showed that proton-doped perovskite neodymium nickelate (NdNiO3) could be reconfigured at room temperature by simple electrical pulses to generate the different functions of neuron, synapse, resistor, and capacitor (see the Perspective by John). The authors designed a prototype experimental network that not only demonstrated electrical reconfiguration of the device, but also showed that such dynamic networks enabled a better approximation of the dataset for incremental learning scenarios compared with static networks. —YS Hydrogen-doped perovskites can be reconfigured by electrical pulses to take on all essential functions necessary for artificial intelligence hardware.

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