Area-Dependent Resistive Switching and Interfacial Dynamics in GCMO-Based Memristors
Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide This study explores the area-dependent resistive switching (RS) characteristics of Gd 0.2 Ca 0.8 MnO 3 (GCMO)-based memristors with aluminum (Al) and gold (Au) electrodes, emphasizing their potential for neuromorphic computing applications. Using a combination of electrical measurements and X-ray photoelectron spectroscopy (XPS), we demonstrate that the high-resistance (HRS) and low-resistance (LRS) states exhibit predictable scaling with device area, with HRS resistances ranging from 10 7 to 10 8 Ω and LRS from 10 5 to 10 7 Ω, supporting the hypothesis of interface-type RS. XPS depth profiling revealed notable differences in AlO x interfacial layer composition between HRS and LRS, with a higher oxide content and a widened interfacial region in HRS. Additionally, the multistate RS capability of up to ten distinct levels was achieved by modulating applied voltages, highlighting GCMO’s suitability as a material for synaptic weight storage in artificial neural networks. Our findings underscore GCMO’s promise for energy-efficient, scalable memristor-based systems.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Ferroelectric and Negative Capacitance Devices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Wihuri Physical Laboratory, Department of Physics and Astronomy
University of Turku
Materials Research Laboratory, Department of Physics and Astronomy
Facultad de Ciencias
University of Salamanca
Funding
Turun yliopiston tutkijakoulu · H2020 Marie Sklodowska-Curie Actions · Jenny ja Antti Wihurin Rahasto · Research Council of Finland · Suomen Kulttuurirahasto
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