Nanoscale multistate resistive switching in WO3 through scanning probe induced proton evolution

Fan Zhang, Yang Zhang, Linglong Li, Xing Mou, Huining Peng, Shengchun Shen, Meng Wang, Kunhong Xiao, Shuai-Hua Ji, Di Yi, Tianxiang Nan, Jianshi Tang and Pu Yu ()
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Fan Zhang: Tsinghua University
Yang Zhang: Tsinghua University
Linglong Li: Tsinghua University
Xing Mou: Tsinghua University
Huining Peng: Tsinghua University
Shengchun Shen: Tsinghua University
Meng Wang: RIKEN Center for Emergent Matter Science (CEMS)
Kunhong Xiao: Tsinghua University
Shuai-Hua Ji: Tsinghua University
Di Yi: Tsinghua University
Tianxiang Nan: Tsinghua University
Jianshi Tang: Tsinghua University
Pu Yu: Tsinghua University

Nature Communications, 2023, vol. 14, issue 1, 1-8

Abstract: Abstract Multistate resistive switching device emerges as a promising electronic unit for energy-efficient neuromorphic computing. Electric-field induced topotactic phase transition with ionic evolution represents an important pathway for this purpose, which, however, faces significant challenges in device scaling. This work demonstrates a convenient scanning-probe-induced proton evolution within WO3, driving a reversible insulator-to-metal transition (IMT) at nanoscale. Specifically, the Pt-coated scanning probe serves as an efficient hydrogen catalysis probe, leading to a hydrogen spillover across the nano junction between the probe and sample surface. A positively biased voltage drives protons into the sample, while a negative voltage extracts protons out, giving rise to a reversible manipulation on hydrogenation-induced electron doping, accompanied by a dramatic resistive switching. The precise control of the scanning probe offers the opportunity to manipulate the local conductivity at nanoscale, which is further visualized through a printed portrait encoded by local conductivity. Notably, multistate resistive switching is successfully demonstrated via successive set and reset processes. Our work highlights the probe-induced hydrogen evolution as a new direction to engineer memristor at nanoscale.

Date: 2023
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DOI: 10.1038/s41467-023-39687-9

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