Literature DB >> 24571386

Comprehensive physical model of dynamic resistive switching in an oxide memristor.

Sungho Kim1, ShinHyun Choi, Wei Lu.   

Abstract

Memristors have been proposed for a number of applications from nonvolatile memory to neuromorphic systems. Unlike conventional devices based solely on electron transport, memristors operate on the principle of resistive switching (RS) based on redistribution of ions. To date, a number of experimental and modeling studies have been reported to probe the RS mechanism; however, a complete physical picture that can quantitatively describe the dynamic RS behavior is still missing. Here, we present a quantitative and accurate dynamic switching model that not only fully accounts for the rich RS behaviors in memristors in a unified framework but also provides critical insight for continued device design, optimization, and applications. The proposed model reveals the roles of electric field, temperature, oxygen vacancy concentration gradient, and different material and device parameters on RS and allows accurate predictions of diverse set/reset, analog switching, and complementary RS behaviors using only material-dependent device parameters.

Entities:  

Year:  2014        PMID: 24571386     DOI: 10.1021/nn405827t

Source DB:  PubMed          Journal:  ACS Nano        ISSN: 1936-0851            Impact factor:   15.881


  17 in total

Review 1.  A Collective Study on Modeling and Simulation of Resistive Random Access Memory.

Authors:  Debashis Panda; Paritosh Piyush Sahu; Tseung Yuen Tseng
Journal:  Nanoscale Res Lett       Date:  2018-01-10       Impact factor: 4.703

2.  Local atomic order of the amorphous TaO x thin films in relation to their chemical resistivity.

Authors:  Krystyna Lawniczak-Jablonska; Anna Wolska; Piotr Kuzmiuk; Pawel Rejmak; Kamil Kosiel
Journal:  RSC Adv       Date:  2019-11-04       Impact factor: 4.036

3.  Study of multi-level characteristics for 3D vertical resistive switching memory.

Authors:  Yue Bai; Huaqiang Wu; Riga Wu; Ye Zhang; Ning Deng; Zhiping Yu; He Qian
Journal:  Sci Rep       Date:  2014-07-22       Impact factor: 4.379

4.  Bottom-up synthesis of ordered metal/oxide/metal nanodots on substrates for nanoscale resistive switching memory.

Authors:  Un-Bin Han; Jang-Sik Lee
Journal:  Sci Rep       Date:  2016-05-09       Impact factor: 4.379

5.  Data Clustering using Memristor Networks.

Authors:  Shinhyun Choi; Patrick Sheridan; Wei D Lu
Journal:  Sci Rep       Date:  2015-05-28       Impact factor: 4.379

6.  Compliance-Free, Digital SET and Analog RESET Synaptic Characteristics of Sub-Tantalum Oxide Based Neuromorphic Device.

Authors:  Yawar Abbas; Yu-Rim Jeon; Andrey Sergeevich Sokolov; Sohyeon Kim; Boncheol Ku; Changhwan Choi
Journal:  Sci Rep       Date:  2018-01-19       Impact factor: 4.379

7.  Pavlovian conditioning demonstrated with neuromorphic memristive devices.

Authors:  Zheng-Hua Tan; Xue-Bing Yin; Rui Yang; Shao-Bo Mi; Chun-Lin Jia; Xin Guo
Journal:  Sci Rep       Date:  2017-04-06       Impact factor: 4.379

8.  Sub-10 nm Ta Channel Responsible for Superior Performance of a HfO2 Memristor.

Authors:  Hao Jiang; Lili Han; Peng Lin; Zhongrui Wang; Moon Hyung Jang; Qing Wu; Mark Barnell; J Joshua Yang; Huolin L Xin; Qiangfei Xia
Journal:  Sci Rep       Date:  2016-06-23       Impact factor: 4.379

9.  Stateful characterization of resistive switching TiO2 with electron beam induced currents.

Authors:  Brian D Hoskins; Gina C Adam; Evgheni Strelcov; Nikolai Zhitenev; Andrei Kolmakov; Dmitri B Strukov; Jabez J McClelland
Journal:  Nat Commun       Date:  2017-12-07       Impact factor: 14.919

Review 10.  Wearable Intrinsically Soft, Stretchable, Flexible Devices for Memories and Computing.

Authors:  Krishna Rajan; Erik Garofalo; Alessandro Chiolerio
Journal:  Sensors (Basel)       Date:  2018-01-27       Impact factor: 3.576

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