# Ultra‐Low Operating Voltage Memristors Based on Plating/Stripping Reactions

## TL;DR

This paper introduces a new type of memristor with ultra-low voltage operation and stable switching, inspired by biological processes and suitable for energy-efficient computing.

## Contribution

The development of a plating/stripping memristor with sub-millivolt switching and bio-inspired dynamics for neuromorphic computing.

## Key findings

- The Zn/DEGE/Cu PSM operates at sub-millivolt levels with stable low and high resistance states.
- The PSM system achieves 89.3% classification accuracy in pattern recognition tasks using reservoir computing.
- The DEGE electrolyte enables corrosion resistance and dendrite-free operation.

## Abstract

Current memristor technologies remain limited by instability, high operating voltage, and low switching ratio, primarily due to stochastic filament formation and defect migration. Here, a fundamentally different electrochemical mechanism is proposed through the development of a plating/stripping memristor (PSM) featuring stable, low‐voltage, and bio‐inspired conductance switching. Constructed with Zn/Cu electrodes and a deep eutectic gel electrolyte (DEGE), the PSM accurately emulates spike‐rate‐dependent plasticity and long‐term synaptic dynamics. The DEGE matrix offers a corrosion‐resistant, dendrite‐free, and ionically homogeneous environment, facilitating gradual and programmable conductance evolution. Remarkably, the Zn/DEGE/Cu PSM exhibits switching behavior with a low‐resistance state centered at 15.3 µV and dual high‐resistance states at –10.0 mV and +11.1 mV, governed by electrochemical equilibrium, highlighting its sub‐millivolt‐level operation and energy‐efficient switching characteristics. Furthermore, the Zn/DEGE/Cu PSMs are integrated into a reservoir computing framework using 4‐bit pulse‐encoded conductance states. When applied to pattern recognition tasks, the DEGE‐based PSM system demonstrates a reliable classification accuracy of 89.3%, driven by device‐derived temporal dynamics. Overall, this study establishes a new materials and mechanistic foundation for energy‐efficient neuromorphic computing, bridging electrochemical reactions with biologically plausible information processing.

A plating/stripping memristor exhibits mV‐level redox switching, high endurance, and ultralow‐voltage operation. The system supports gradual conductance evolution and enables 4‐bit pulse‐coded reservoir computing, offering a physically interpretable platform for neuromorphic processing based on interfacial electrochemical kinetics.