记忆电阻器
动力学(音乐)
电阻式触摸屏
材料科学
电阻随机存取存储器
纳米技术
物理
电气工程
工程类
电压
声学
作者
Anni Antola,Johanna Laaksonen,H. Huhtinen,Ilari Angervo,Sari Granroth,Alejandro Schulman,P. Laukkanen,P. Paturi
标识
DOI:10.1021/acsaelm.5c00403
摘要
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.
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