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Experimental Validation of Switching Dependence of Nanoscale Y2O3 Memristors on Electrode Symmetry via Physical Electrothermal Modeling Experimental Validation of Switching Dependence of Nanoscale Y2O3 Memristors on Electrode Symmetry via Physical Electrothermal Modeling AITranslate

Indian Institute of Technology Indore; University of Edinburgh; Indian Institute of Technology Indore; Indian Institute of Technology Indore; Gyeongsang National University; Gyeongsang National University; Shinshu University; RMIT University
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Publisher: ACS
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Abstract AITranslate

In this work, the impact of symmetric and asymmetric electrodes on the resistive switching (RS) behavior of the nanoscale Y2O3-based memristor is investigated with experiments. In addition, the extracted switching parameters are validated with systemic modeling. Memristor growth is deployed by utilizing a dual ion beam sputtering (DIBS) system, and simulation is carried out in a semiconductor physics-based tool, i.e., COMSOL Multiphysics with a defined MATLAB script. The performed simulation work is based on the minimum free energy of the used materials at an applied certain voltage. The simulated results exhibit a stable pinched hysteresis loop in the RS responses either in symmetric or asymmetric electrode combinations with an efficient ON/OFF current ratio and show a close match with the experimental results. Moreover, the simulated devices show synaptic plasticity functionalities in terms of potentiation and depression processes with an almost ideal linearity factor for both electrode combinations similar to the realistic experimental data. Therefore, the present work efficiently depicts the suitability of the electrode material with the Y2O3 switching layer to enhance electrical performance to integrate into the artificial synapse and neuromorphic computations.

KeyWords AITranslate

electrode variation linearity factor Y2O3 memristor synaptic behavior
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Basic Information:

DOI:https://doi.org/10.1021/acsaelm.3c00598

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Citation Information:

In this work, the impact of symmetric and asymmetric electrodes on the resistive switching (RS) behavior of the nanoscale Y2O3-based memristor is investigated with experiments. In addition, the extracted switching parameters are validated with systemic modeling. Memristor growth is deployed by utilizing a dual ion beam sputtering (DIBS) system, and simulation is carried out in a semiconductor physics-based tool, i.e., COMSOL Multiphysics with a defined MATLAB script. The performed simulation work is based on the minimum free energy of the used materials at an applied certain voltage. The simulated results exhibit a stable pinched hysteresis loop in the RS responses either in symmetric or asymmetric electrode combinations with an efficient ON/OFF current ratio and show a close match with the experimental results. Moreover, the simulated devices show synaptic plasticity functionalities in terms of potentiation and depression processes with an almost ideal linearity factor for both electrode combinations similar to the realistic experimental data. Therefore, the present work efficiently depicts the suitability of the electrode material with the Y2O3 switching layer to enhance electrical performance to integrate into the artificial synapse and neuromorphic computations.

quote

GB/T 7714-2015 [1] Mohit Kumar Gautam, Sanjay Kumar, Sumit Chaudhary, et al. ACS Applied Electronic Materials, 2023(5). DOI:10.1021/acsaelm.3c00598.
MLA [1] Mohit Kumar Gautam, et al., ACS Applied Electronic Materials, no. 5, 2023, https://doi.org/10.1021/acsaelm.3c00598.
APA [1] Mohit Kumar Gautam, Sanjay Kumar, Sumit Chaudhary, Lokesh Kumar Hindoliya, Dhananjay D. Kumbhar, Jun Hong Park, Myo Than Htay, & Shaibal Mukherjee. (2023). ACS Applied Electronic Materials(5). https://doi.org/10.1021/acsaelm.3c00598
IEEE [1] Mohit Kumar Gautam, Sanjay Kumar, Sumit Chaudhary, Lokesh Kumar Hindoliya, Dhananjay D. Kumbhar, Jun Hong Park, Myo Than Htay, and Shaibal Mukherjee, ACS Applied Electronic Materials, no. 5, 2023, doi: 10.1021/acsaelm.3c00598. keywords: {electrode variation linearity factor Y2O3 memristor synaptic behavior}