From Memory Traces to Surface Chemistry: Decoding REDOX Reactions

TL;DR

This paper introduces planar resistive switching devices that analyze complex REDOX reaction patterns on surfaces, enhancing sensor capabilities beyond traditional models through advanced pattern recognition algorithms.

Contribution

It presents a novel planar device architecture and a systematic analysis of surface REDOX reactions, moving beyond the traditional Butler-Volmer model for better sensor insights.

Findings

Demonstrated complex switching patterns in Na-doped ZnO devices

Revealed intricate surface REDOX reaction dynamics

Enabled advanced pattern recognition for sensor analysis

Abstract

Gas and moisture sensing devices leveraging the resistive switching effect in transition metal oxide memristors promise to revolutionize next-generation, nano-scaled, cost-effective, and environmentally sustainable sensor solutions. These sensors encode readouts in resistance state changes based on gas concentration, yet their nonlinear current-voltage characteristics offer richer dynamics, capturing detailed information about REDOX reactions and surface kinetics. Traditional vertical devices fail to fully exploit this complexity. This study demonstrates planar resistive switching devices, moving beyond the Butler-Volmer model. A systematic investigation of the electrochemical processes in Na-doped ZnO with lateral planar contacts reveals intricate patterns resulting from REDOX reactions on the device surface. When combined with advanced algorithms for pattern recognition, allow the analysis of complex switching patterns, including crossings, loop directions, and resistance values, providing unprecedented insights for next-generation complex sensors.