The study about the resistive switching based on graphene/NiO interfaces
Source abstract
Abstract
Six different interfaces namely, armchair Graphene (aGNR), zigzag Graphene (zGNR), and surface defect zigzag Graphene (zGNR1) nanoribbons with uni- and bi-laminar <001>-oriented NiO were studied. First, the Mulliken mean and difference populations, the interface energy, and the interface adhesion energy were calculated by the Cambridge sequential total energy package (CASTEP). The aGNR/NiO interface showed higher interface adhesion energy and Mulliken population mean as compared to the other interface structures (i.e., aGNR/NiO was more compact than the rest of interfaces). Moreover, the lowest interface energy and Mulliken difference population values along with the negligible aberration state clearly revealed aGNR/NiO to be the best interface among those studied herein. Subsequently, the current–voltage (I–V) curves indicate the aGNR/NiO/aGNR device presents memory effect while tracing the path back in the current data, but not switching between positive and negative voltages due to the device unipolar behavior. The mechanism of resistive switching is demonstrated by performing density functional tight binding and much more (DFTB+) dynamics.
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Research context
OpenAlex topics: Advanced Memory and Neural Computing · Graphene research and applications · Advancements in Battery Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Electronics and Information Engineering, Anhui University 1 , Hefei, Anhui 230601, China
School of Electronics and Information Engineering, Hefei Normal University 2 , Hefei, Anhui 230601, China
Funding
Nature Science Foundation of the Higher Education Institutions of Anhui Province, China · Research Foundation of Education Bureau of Anhui Province, China · National Natural Science Foundation of China
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