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Origin of large variations of current on/off ratio and switching voltage in atomically thin memristors: an exascale ab initio transport study

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Abstract

Nonvolatile resistive switching in two-dimensional monolayers opens a new avenue for high-density memory/computing devices. However, questions remain as to why the current on/off ratio and switching voltage vary significantly among different devices. Here, we simulate electronic transport of large systems consisting of a h-BN monolayer sandwiched by gold electrodes, enabled by an implementation of the nonequilibrium Green’s function method in the exascale density functional theory (DFT) code: Real-space MultiGrid. Systematic calculations reveal that the wide range of on/off ratios is due to variations in interface distances between the electrode and h-BN that significantly modulate their wavefunction overlap. In addition, DFT calculations demonstrate that the energy barrier of a gold atom dissociating from the electrode to h-BN increases dramatically with the interface distance, thereby explaining the strong dependence of the switching voltage on distance. Our work demonstrates the significance of interface distance in governing the current on/off ratio and switching voltage.

Original languageEnglish
Article number95
Journalnpj 2D Materials and Applications
Volume9
Issue number1
DOIs
StatePublished - Dec 2025

Funding

This research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility at Oak Ridge National Laboratory. The calculations used resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 using NERSC award BES-ERCAP0031261. We also used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725. The Frontier resources were provided through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. D.A. acknowledges the support of the Office of Naval Research (ONR) award #N00014-24-1-2080 and the National Science Foundation (NSF) award #2422934.

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