Understanding Volatile Electrical Switching in hBN Nanodevices by Fully Optical Operando Investigation
Source abstract
Abstract
Abstract Memristors based on 2D materials have emerged as promising candidates for use in artificial synaptic devices and energy‐efficient neuromorphic computing. Limited understanding of the fundamental switching mechanisms hinders device optimization and stalls commercialization. Conventional analysis techniques are often destructive, and only offer a static characterization of the device after electrical cycling, providing limited insights into switching dynamics. In this study, an operando approach utilizing plasmon enhancement of optical signals is used to investigate a two‐terminal vertical device based on monolayer hexagonal boron nitride. Real‐time photoluminescence and dark‐field scattering measurements reveal that conductive filaments (CFs) form through the migration of metallic ions from the electrode. The modification of a photoluminescence signal near 620 nm and a redshift of dark‐field scattering indicating a refractive index change of roughly 1 are detected when voltage is applied across the nanodevice. These optical changes are interpreted to show that this CF formation is mediated by point defect structures. This highlights the crucial role of defects in the switching dynamics. This finding resolves the ongoing debate in the literature about the mechanism of CF formation and paves the way for defect engineering as a step‐changing pathway to the optimization of these devices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Semiconductor materials and devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Materials Science and Metallurgy University of Cambridge 27 Charles Babbage Rd Cambridge CB3 0FS UK
Department of Engineering University of Cambridge Cambridge CB2 1PZ UK
Funding
Cambridge Trust · Royal Society · UK Research and Innovation · Engineering and Physical Sciences Research Council
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