Anni Antola*, Johanna Laaksonen, Hannu Huhtinen, Ilari Angervo, Sari Granroth, Alejandro Schulman, Pekka Laukkanen and Petriina Paturi,
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引用次数: 0
Abstract
This study explores the area-dependent resistive switching (RS) characteristics of Gd0.2Ca0.8MnO3 (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 107 to 108 Ω and LRS from 105 to 107 Ω, supporting the hypothesis of interface-type RS. XPS depth profiling revealed notable differences in AlOx 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.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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