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用于神经形态计算的氧化铈基忆阻器的最新进展。

Recent Advances in Cerium Oxide-Based Memristors for Neuromorphic Computing.

作者信息

Ali Sarfraz, Ullah Muhammad Abaid, Raza Ali, Iqbal Muhammad Waqas, Khan Muhammad Farooq, Rasheed Maria, Ismail Muhammad, Kim Sungjun

机构信息

Department of Physics, Riphah International University, Lahore Campus, 13-KM Raiwand Road, Lahore 54000, Pakistan.

Department of Physics, University of Okara, Okara 56300, Pakistan.

出版信息

Nanomaterials (Basel). 2023 Aug 28;13(17):2443. doi: 10.3390/nano13172443.

DOI:10.3390/nano13172443
PMID:37686950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10489950/
Abstract

This review article attempts to provide a comprehensive review of the recent progress in cerium oxide (CeO)-based resistive random-access memories (RRAMs). CeO is considered the most promising candidate because of its multiple oxidation states (Ce and Ce), remarkable resistive-switching (RS) uniformity in DC mode, gradual resistance transition, cycling endurance, long data-retention period, and utilization of the RS mechanism as a dielectric layer, thereby exhibiting potential for neuromorphic computing. In this context, a detailed study of the filamentary mechanisms and their types is required. Accordingly, extensive studies on unipolar, bipolar, and threshold memristive behaviors are reviewed in this work. Furthermore, electrode-based (both symmetric and asymmetric) engineering is focused for the memristor's structures such as single-layer, bilayer (as an oxygen barrier layer), and doped switching-layer-based memristors have been proved to be unique CeO-based synaptic devices. Hence, neuromorphic applications comprising spike-based learning processes, potentiation and depression characteristics, potentiation motion and synaptic weight decay process, short-term plasticity, and long-term plasticity are intensively studied. More recently, because learning based on Pavlov's dog experiment has been adopted as an advanced synoptic study, it is one of the primary topics of this review. Finally, CeO-based memristors are considered promising compared to previously reported memristors for advanced synaptic study in the future, particularly by utilizing high-dielectric-constant oxide memristors.

摘要

这篇综述文章试图全面回顾基于氧化铈（CeO）的电阻式随机存取存储器（RRAM）的最新进展。由于其多种氧化态（Ce³⁺和Ce⁴⁺）、在直流模式下显著的电阻开关（RS）均匀性、逐渐的电阻转变、循环耐久性、长数据保留期以及将RS机制用作介电层，CeO被认为是最有前途的候选材料，从而展现出在神经形态计算方面的潜力。在此背景下，需要对丝状机制及其类型进行详细研究。因此，本文综述了关于单极、双极和阈值忆阻行为的广泛研究。此外，基于电极的（对称和不对称）工程被聚焦于忆阻器的结构，例如单层、双层（作为氧阻挡层）以及基于掺杂开关层的忆阻器已被证明是独特的基于CeO的突触器件。因此，对包括基于尖峰的学习过程、增强和抑制特性、增强运动和突触权重衰减过程、短期可塑性和长期可塑性在内的神经形态应用进行了深入研究。最近，由于基于巴甫洛夫的狗实验的学习已被用作一种先进的突触研究，它是本综述的主要主题之一。最后，与先前报道的忆阻器相比，基于CeO的忆阻器在未来的先进突触研究中被认为具有前景，特别是通过利用高介电常数氧化物忆阻器。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e76/10489950/4da189a3152d/nanomaterials-13-02443-g020.jpg
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