Literature DB >> 30896171

Vertical MoS2 Double-Layer Memristor with Electrochemical Metallization as an Atomic-Scale Synapse with Switching Thresholds Approaching 100 mV.

Renjing Xu1, Houk Jang1, Min-Hyun Lee2, Dovran Amanov1, Yeonchoo Cho2, Haeryong Kim2, Seongjun Park2, Hyeon-Jin Shin2, Donhee Ham1.   

Abstract

Atomically thin two-dimensional (2D) materials-such as transition metal dichalcogenide (TMD) monolayers and hexagonal boron nitride (hBN)-and their van der Waals layered preparations have been actively researched to build electronic devices such as field-effect transistors, junction diodes, tunneling devices, and, more recently, memristors. Two-dimensional material memristors built in lateral form, with horizontal placement of electrodes and the 2D material layers, have provided an intriguing window into the motions of ions along the atomically thin layers. On the other hand, 2D material memristors built in vertical form with top and bottom electrodes sandwiching 2D material layers may provide opportunities to explore the extreme of the memristive performance with the atomic-scale interelectrode distance. In particular, they may help push the switching voltages to a lower limit, which is an important pursuit in memristor research in general, given their roles in neuromorphic computing. In fact, recently Akinwande et al. performed a pioneering work to demonstrate a vertical memristor that sandwiches a single MoS2 monolayer between two inert Au electrodes, but it could neither attain switching voltages below 1 V nor control the switching polarity, obtaining both unipolar and bipolar switching devices. Here, we report a vertical memristor that sandwiches two MoS2 monolayers between an active Cu top electrode and an inert Au bottom electrode. Cu ions diffuse through the MoS2 double layers to form atomic-scale filaments. The atomic-scale thickness, combined with the electrochemical metallization, lowers switching voltages down to 0.1-0.2 V, on par with the state of the art. Furthermore, our memristor achieves consistent bipolar and analogue switching, and thus exhibits the synapse-like learning behavior such as the spike-timing dependent plasticity (STDP), the very first STDP demonstration among all 2D-material-based vertical memristors. The demonstrated STDP with low switching voltages is promising not only for low-power neuromorphic computing, but also from the point of view that the voltage range approaches the biological action potentials, opening up a possibility for direct interfacing with mammalian neuronal networks.

Entities:  

Keywords:  Memristor; analogue neural network; neuromorphic computing; resistive memory; spike-timing dependent plasticity; transition metal dichalcogenide; two-dimensional materials

Year:  2019        PMID: 30896171     DOI: 10.1021/acs.nanolett.8b05140

Source DB:  PubMed          Journal:  Nano Lett        ISSN: 1530-6984            Impact factor:   11.189


  13 in total

1.  Cluster-type analogue memristor by engineering redox dynamics for high-performance neuromorphic computing.

Authors:  Jaehyun Kang; Taeyoon Kim; Suman Hu; Jaewook Kim; Joon Young Kwak; Jongkil Park; Jong Keuk Park; Inho Kim; Suyoun Lee; Sangbum Kim; YeonJoo Jeong
Journal:  Nat Commun       Date:  2022-07-12       Impact factor: 17.694

2.  Analog-digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion.

Authors:  Shania Rehman; Muhammad Farooq Khan; Hee-Dong Kim; Sungho Kim
Journal:  Nat Commun       Date:  2022-05-19       Impact factor: 17.694

3.  Ultralow Power Wearable Heterosynapse with Photoelectric Synergistic Modulation.

Authors:  Tian-Yu Wang; Jia-Lin Meng; Zhen-Yu He; Lin Chen; Hao Zhu; Qing-Qing Sun; Shi-Jin Ding; Peng Zhou; David Wei Zhang
Journal:  Adv Sci (Weinh)       Date:  2020-03-16       Impact factor: 16.806

4.  Robust Memristor Networks for Neuromorphic Computation Applications.

Authors:  Dániel Hajtó; Ádám Rák; György Cserey
Journal:  Materials (Basel)       Date:  2019-10-31       Impact factor: 3.623

Review 5.  Memristive Devices Based on Two-Dimensional Transition Metal Chalcogenides for Neuromorphic Computing.

Authors:  Ki Chang Kwon; Ji Hyun Baek; Kootak Hong; Soo Young Kim; Ho Won Jang
Journal:  Nanomicro Lett       Date:  2022-02-05

6.  Artificial Neurons and Synapses Based on Al/a-SiNxOy:H/P+-Si Device with Tunable Resistive Switching from Threshold to Memory.

Authors:  Kangmin Leng; Xu Zhu; Zhongyuan Ma; Xinyue Yu; Jun Xu; Ling Xu; Wei Li; Kunji Chen
Journal:  Nanomaterials (Basel)       Date:  2022-01-18       Impact factor: 5.076

7.  Graphene-oxide interface for optoelectronic synapse application.

Authors:  Ricardo Martinez-Martinez; Molla Manjurul Islam; Adithi Krishnaprasad; Tania Roy
Journal:  Sci Rep       Date:  2022-04-07       Impact factor: 4.379

8.  Resistance state evolution under constant electric stress on a MoS2 non-volatile resistive switching device.

Authors:  Xiaohan Wu; Ruijing Ge; Yifu Huang; Deji Akinwande; Jack C Lee
Journal:  RSC Adv       Date:  2020-11-19       Impact factor: 4.036

9.  Epitaxial Growth of Wafer-Scale Molybdenum Disulfide/Graphene Heterostructures by Metal-Organic Vapor-Phase Epitaxy and Their Application in Photodetectors.

Authors:  Anh Tuan Hoang; Ajit K Katiyar; Heechang Shin; Neeraj Mishra; Stiven Forti; Camilla Coletti; Jong-Hyun Ahn
Journal:  ACS Appl Mater Interfaces       Date:  2020-09-17       Impact factor: 9.229

10.  Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system.

Authors:  Changsoon Choi; Juyoung Leem; Minsung Kim; Amir Taqieddin; Chullhee Cho; Kyoung Won Cho; Gil Ju Lee; Hyojin Seung; Hyung Jong Bae; Young Min Song; Taeghwan Hyeon; Narayana R Aluru; SungWoo Nam; Dae-Hyeong Kim
Journal:  Nat Commun       Date:  2020-11-23       Impact factor: 17.694

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