Abstract

Summary Silicon circuitry has dominated the semiconductor industry for decades but is constrained in its power efficiency by the Fermi-Dirac distribution of electron energies. Electron-correlated transition metal oxides exhibiting metal-to-insulator transitions (MITs) are excellent candidates for energy-efficient computation, which can further emulate the spiking behavior of biological neural circuitry. We demonstrate that β′-CuxV2O5 exhibits a pronounced nonlinear response to applied temperature, voltage, and current, and the response can be modulated as a function of Cu stoichiometry. We show that polaron oscillation, coupled to the real-space shuttling of Cu ions across two adjacent sites, underpins the MIT of this material. These results reveal the interplay between crystal structure distortions and electron correlation in underpinning the metal-insulator transition of a strongly correlated system. The utilization of coupled cation diffusion and polaron oscillation further demonstrates a means of using ionic vectors to obtain highly nonlinear conductance switching as required for neuromorphic computing.

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