Structure‐Engineered Nanoporous Vanadium Oxide Memristors for Reconfigurable Synapse–Neuron Integration and Synergistic Robotic Motion

Abstract

ABSTRACT Neuromorphic sensory‐to‐motor interfaces require compact devices that can combine nonvolatile synaptic weight storage with volatile neuronal firing, yet these functions typically rely on distinct material and circuit mechanisms. Here, we report a structure‐engineered VO y /nanoporous VO x heterostructure that enables electrically selectable nonvolatile and volatile switching within a vanadium oxide memristor platform. Annealing‐induced interfacial diffusion and oxidation produce an asymmetric stack comprising a crystalline VO y layer that supports threshold insulator‐to‐metal transition dynamics and an oxygen‐vacancy‐rich nanoporous VO x region that promotes filamentary conductance modulation. In a 16 × 16 crossbar array, identically fabricated cells are reconfigured either as artificial synapses exhibiting multilevel retention and analog long‐term potentiation/depression or as artificial neurons producing relaxation‐oscillator spiking and diverse neuronal response features. By pairing two cells as a one‐synapse–one‐neuron unit, the programmed synaptic conductance modulates the neuronal firing frequency and measured current‐spike amplitude, thereby linking analog weight storage with spike‐based signal generation. Using measured device characteristics, a hardware‐informed spiking neural network recognizes rock–paper–scissors images with high accuracy, and its output commands are coupled to a memristive synergistic motor system that drives a robotic hand to generate counter‐gestures. These results suggest that structure‐engineered nanoporous vanadium oxide memristors can serve as reconfigurable building blocks for neuromorphic sensory‐to‐motor interfaces.