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Ghafoor F, Kim H, Ghafoor B, Rehman S, Asghar Khan M, Aziz J, Rabeel M, Faheem Maqsood M, Dastgeer G, Lee MJ, Farooq Khan M, Kim DK. Interface engineering in ZnO/CdO hybrid nanocomposites to enhanced resistive switching memory for neuromorphic computing. J Colloid Interface Sci 2024; 659:1-10. [PMID: 38157721 DOI: 10.1016/j.jcis.2023.12.084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 11/29/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024]
Abstract
Resistive random-access memory (RRAMs) has attracted significant interest for their potential applications in embedded storage and neuromorphic computing. Materials based on metal chalcogenides have emerged as promising candidates for the fulfilment of these requirements. Due to its ability to manipulate electronic states and control trap states through controlled compositional dynamics, metal chalcogenide RRAM has excellent non-volatile resistive memory properties. In the present we have synthesized ZnO-CdO hybrid nanocomposite by using hydrothermal method as an active layer. The Ag/C15ZO/Pt hybrid nanocomposite structure memristors showed electrical properties similar to biological synapses. The device exhibited remarkably stable resistive switching properties that have a low SET/RESET (0.41/-0.2) voltage, a high RON/OFF ratio of approximately 105, a high retention stability, excellent endurance reliability up to 104 cycles and multilevel device storage performance by controlling the compliance current. Furthermore, they exhibited an impressive performance in terms of emulating biological synaptic functions, which include long-term potentiation (LTP), long-term depression (LTD), and paired-pulse facilitation (PPF), via the continuous modulation of conductance. The hybrid nanocomposite memristors notably achieved an impressive recognition accuracy of up to 92.6 % for handwritten digit recognition under artificial neural network (ANN). This study shows that hybrid-nanocomposite memristor performance could lead to efficient future neuromorphic architectures.
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Affiliation(s)
- Faisal Ghafoor
- Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea
| | - Honggyun Kim
- Department of Semiconductor Systems Engineering, Sejong University, Seoul 05006, Republic of Korea
| | - Bilal Ghafoor
- PPGE3M, Federal University of Rio Grande do Sul, Porto Alegre /RS, Brazil
| | - Shania Rehman
- Department of Semiconductor Systems Engineering, Sejong University, Seoul 05006, Republic of Korea
| | | | - Jamal Aziz
- Chair of Smart Sensor Systems, University of Wuppertal, Wuppertal, Germany
| | - Muhammad Rabeel
- Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea
| | - Muhammad Faheem Maqsood
- Department of Nanotechnology and Advanced Materials Engineering, Sejong University, 05006 Seoul, Republic of Korea
| | - Ghulam Dastgeer
- Department of Physics and Astronomy, Sejong University, Seoul 05006, Korea
| | - Myoung-Jae Lee
- Institute of Conversion Daegu Gyeongbuk Institute of Science and Technology (DGIST)., Daegu 42988, Republic of Korea.
| | - Muhammad Farooq Khan
- Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea.
| | - Deok-Kee Kim
- Department of Electrical Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Republic of Korea; Department of Semiconductor Systems Engineering, Sejong University, Seoul 05006, Republic of Korea.
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Yang M, Zhao X, Tang Q, Cui N, Wang Z, Tong Y, Liu Y. Stretchable and conformable synapse memristors for wearable and implantable electronics. NANOSCALE 2018; 10:18135-18144. [PMID: 30152837 DOI: 10.1039/c8nr05336g] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Stretchable and conformable synapse memristors that can emulate the behaviour of the biological neural system and well adhere onto the curved surfaces simultaneously are desirable for the development of imperceptible wearable and implantable neuromorphic computing systems. Previous synapse memristors have been mainly limited to rigid substrates. Herein, a stretchable and conformable memristor with fundamental synaptic functions including potentiation/depression characteristics, long/short-term plasticity (STP and LTP), "learning-forgetting-relearning" behaviour, and spike-rate-dependent and spike-amplitude-dependent plasticity is demonstrated based on highly elastic Ag nanoparticle-doped thermoplastic polyurethanes (TPU : Ag NPs) and polydimethylsiloxane (PDMS). The memristor can be well operated even at 60% strain and can be well conformed onto the curved surfaces. The formed conductive filament (CF) obtained from the movement of Ag nanoparticle clusters under the locally enhanced electric field gives rise to resistance switching of our memristor. These results indicate a feasible strategy to realize stretchable and conformable synaptic devices for the development of new-generation artificial intelligence computers.
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Affiliation(s)
- Mihua Yang
- Key Laboratory of UV Light Emitting Materials and Technology under Ministry of Education, Northeast Normal University, Changchun 130024, P. R. China.
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Choi J, Han JS, Hong K, Kim SY, Jang HW. Organic-Inorganic Hybrid Halide Perovskites for Memories, Transistors, and Artificial Synapses. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2018; 30:e1704002. [PMID: 29847692 DOI: 10.1002/adma.201704002] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 10/29/2017] [Indexed: 05/25/2023]
Abstract
Fascinating characteristics of halide perovskites (HPs), which cannot be seen in conventional semiconductors and metal oxides, have boosted the application of HPs in electronic devices beyond optoelectronics such as solar cells, photodetectors, and light-emitting diodes. Here, recent advances in HP-based memory and logic devices such as resistive-switching memories (i.e., resistive random access memory (RRAM) or memristors), transistors, and artificial synapses are reviewed, focusing on inherently exotic properties of HPs: i) tunable bandgap, ii) facile majority carrier control, iii) fast ion migration, and iv) superflexibility. Various fabrication techniques of HP thin films from solution-based methods to vacuum processes are introduced. Up-to-date work in the field, emphasizing the compositional flexibility of HPs, suggest that HPs are promising candidates for next-generation electronic devices. Taking advantages of their unique electrical properties, low-cost and low-temperature synthesis, and compositional and mechanical flexibility, HPs have enormous potential to provide a new platform for future electronic devices and explosively intensive studies will pave the way in finding new HP materials beyond conventional silicon-based semiconductors to keep up with "More-than-Moore" times.
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Affiliation(s)
- Jaeho Choi
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Ji Su Han
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Kootak Hong
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
| | - Soo Young Kim
- School of Chemical Engineering and Materials Science, Chung-Ang University, Seoul, 06974, Republic of Korea
| | - Ho Won Jang
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Seoul National University, Seoul, 08826, Republic of Korea
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