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Desai T, Goud RSP, Dongale TD, Gurnani C. Evaluation of Nanostructured NiS 2 Thin Films from a Single-Source Precursor for Flexible Memristive Devices. ACS OMEGA 2023; 8:48873-48883. [PMID: 38162788 PMCID: PMC10753740 DOI: 10.1021/acsomega.3c06331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/18/2023] [Accepted: 11/08/2023] [Indexed: 01/03/2024]
Abstract
Herein, we report the first demonstration of a single-step, in situ growth of NiS2 nanostructures from a single-source precursor onto a flexible substrate as a versatile platform for an effective nonvolatile memristor. The low temperature, solution-processed deposition of NiS2 thin films exhibits a wide band gap range, spherical-flower-like morphology with high surface area and porosity, and negligible surface roughness. Moreover, the fabricated Au/NiS2/ITO/PET memristor device reveals reproducible bipolar resistive switching (RS) at low operational voltages under both flat and bending conditions. The flexible device shows stable RS behavior for multiple cycles with a good memory window (∼102) and data retention of up to 104 s. The switching of a device between a high-resistance state and a low-resistance state is attributed to the filamentary conduction based on sulfur ion migration and sulfur vacancies and plays a key role in the outstanding memristive performance of the device. Consequently, this work provides a simple, scalable, solution-processed route to fabricate a flexible device with potential applications in next-generation neuromorphic computing and wearable electronics.
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Affiliation(s)
- Trishala
R. Desai
- Department
of Chemistry, Ecole Centrale School of Engineering, Mahindra University, Hyderabad 500043, India
| | - R. Sai Prasad Goud
- Centre
for Advanced Studies in Electronic Sciences and Technology, University of Hyderabad, Hyderabad 500046, India
| | - Tukaram D. Dongale
- Computational
Electronics and Nanoscience Research Laboratory, School of Nanoscience
and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Chitra Gurnani
- Department
of Chemistry, Ecole Centrale School of Engineering, Mahindra University, Hyderabad 500043, India
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Wu Z, Li Z, Lin X, Shan X, Chen G, Yang C, Zhao X, Sun Z, Hu K, Wang F, Ren T, Song Z, Zhang K. Diverse long-term potentiation and depression based on multilevel LiSiO xmemristor for neuromorphic computing. NANOTECHNOLOGY 2023; 34:475201. [PMID: 37586343 DOI: 10.1088/1361-6528/acf0c8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 08/15/2023] [Indexed: 08/18/2023]
Abstract
Memristor-based neuromorphic computing is expected to overcome the bottleneck of von Neumann architecture. An artificial synaptic device with continuous conductance variation is essential for implementing bioinspired neuromorphic systems. In this work, a memristor based on Pt/LiSiOx/TiN structure is developed to emulate an artificial synapse, which shows non-volatile multilevel resistance state memory behavior. Moreover, the high nonlinearity caused by abrupt changes in the set process is optimized by adjusting the initial resistance. 100 levels of continuously modulated conductance states are achieved and the nonlinearity factors are reduced to 1.31. The significant improvement is attributed to the decrease in the Schottky barrier height and the evolution of the conductive filaments. Finally, due to the improved linearity of the long-term potentiation/long-term depression behaviors in LiSiOxmemristor, a robust recognition rate (∼94.58%) is achieved for pattern recognition with the modified National Institute of Standards and Technology handwriting database. The Pt/LiSiOx/TiN memristor shows significant potential in high-performance multilevel data storage and neuromorphic computing systems.
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Affiliation(s)
- Zeyu Wu
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Zewen Li
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Xin Lin
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Xin Shan
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Gang Chen
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Chen Yang
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Xuanyu Zhao
- School of Microelectronics, Fudan University, Shanghai 200433, People's Republic of China
| | - Zheng Sun
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Kai Hu
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Fang Wang
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
| | - Tianling Ren
- Beijing National Research Center for Information Science and Technology, Institute of Microelectronics, Tsinghua University, Beijing 100084, People's Republic of China
| | - Zhitang Song
- Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, People's Republic of China
| | - Kailiang Zhang
- School of Integrated Circuit Science and Engineering, Tianjin Key Laboratory of Film Electronic and Communication Devices, Tianjin University of Technology, Tianjin 300384, People's Republic of China
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Dong X, Wei W, Sun H, Li S, Chen J, Chen J, Zhang X, Zhao Y, Li Y. Neotype kuramite optoelectronic memristor for bio-synaptic plasticity simulations. J Chem Phys 2023; 158:2889009. [PMID: 37154283 DOI: 10.1063/5.0151205] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 04/12/2023] [Indexed: 05/10/2023] Open
Abstract
Memristive devices with both electrically and optically induced synaptic dynamic behaviors will be crucial to the accomplishment of brain-inspired neuromorphic computing systems, in which the resistive materials and device architectures are two of the most important cornerstones, but still under challenge. Herein, kuramite Cu3SnS4 is newly introduced into poly-methacrylate as the switching medium to construct memristive devices, and the expected high-performance bio-mimicry of diverse optoelectronic synaptic plasticity is demonstrated. In addition to the excellent basic performances, such as stable bipolar resistive switching with On/Off ratio of ∼486, Set/Reset voltage of ∼-0.88/+0.96 V, and good retention feature of up to 104 s, the new designs of memristors possess not only the multi-level controllable resistive-switching memory property but also the capability of mimicking optoelectronic synaptic plasticity, including electrically and visible/near-infrared light-induced excitatory postsynaptic currents, short-/long-term memory, spike-timing-dependent plasticity, long-term plasticity/depression, short-term plasticity, paired-pulse facilitation, and "learning-forgetting-learning" behavior as well. Predictably, as a new class of switching medium material, such proposed kuramite-based artificial optoelectronic synaptic device has great potential to be applied to construct neuromorphic architectures in simulating human brain functions.
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Affiliation(s)
- Xiaofei Dong
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Wenbin Wei
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Hao Sun
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Siyuan Li
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Jianbiao Chen
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Jiangtao Chen
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Xuqiang Zhang
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Yun Zhao
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
| | - Yan Li
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou 730070, China
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Mao S, Sun B, Zhou G, Qin J, Yang Y, Rao Z, Liu M, Ke C, Zhao Y. A magnetic field controlled memristor towards the design of an implantable detector. J Colloid Interface Sci 2023; 643:38-46. [PMID: 37044012 DOI: 10.1016/j.jcis.2023.04.027] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 03/30/2023] [Accepted: 04/05/2023] [Indexed: 04/14/2023]
Abstract
Memristors, which combine the behaviors of memory and resistive switching (RS), have a wide application prospect in information processing and artificial neural networks. The RS memory behaviors of memristors are primarily determined by the functional layer materials, device structure, and working conditions. Herein, a CuMnO2 nanomaterial with the manganese copper ore structure was prepared on a Ti substrate by hydrothermal method, and a memristor with the Ag/CuMnO2/Ti sandwich structure was developed. The RS memory behavior of the as-prepared memristor can be regulated through a low magnetic field (MF), and thus the resistance value of device shows a multi-level resistance states. Compared with other regulation factors, the MF can remotely adjust and control the RS characteristics of memristor, which is a non-invasive and non-destructive regulatory means. The MF regulated memristor can not only be used for multi-level high-density information storage, but also it can protect the health of special populations by identifying the MF intensity of the surrounding environment. When the device is operated in an MF environment, the change of resistance value of the device in both high resistance state (HRS) and low resistance state (LRS) is mainly attributed to the influence of Loren magnetic force on conductive ions.
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Affiliation(s)
- Shuangsuo Mao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Bai Sun
- Frontier Institute of Science and Technology (FIST), Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China.
| | - Guangdong Zhou
- College of Artificial Intelligence, Brain-inspired Computing & Intelligent Control of Chongqing Key Lab, Southwest University, Chongqing 400715, China
| | - Jiajia Qin
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Yusheng Yang
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Zhaowei Rao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Mingnan Liu
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China
| | - Chuan Ke
- Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
| | - Yong Zhao
- Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering, College of Physics and Energy, Fujian Normal University, Fuzhou, Fujian 350117, China; Key Laboratory of Magnetic Suspension Technology and Maglev Vehicle, Ministry of Education, Southwest Jiaotong University, Chengdu, Sichuan 610031, China.
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