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Maldonado D, Cantudo A, Gómez-Campos FM, Yuan Y, Shen Y, Zheng W, Lanza M, Roldán JB. 3D simulation of conductive nanofilaments in multilayer h-BN memristors via a circuit breaker approach. MATERIALS HORIZONS 2024; 11:949-957. [PMID: 38105726 DOI: 10.1039/d3mh01834b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
A 3D simulation of conductive nanofilaments (CNFs) in multilayer hexagonal-BN memristors is performed. To do so, a simulation tool based on circuit breakers is developed including for the first time a 3D resistive network. The circuit breakers employed can be modeled with two, three and four resistance states; in addition, a series resistance and a module to account for quantum effects, by means of the quantum point contact model, are also included. Finally, to describe real dielectric situations, regions with a high defect density are modeled with a great variety of geometrical shapes to consider their influence in the resistive switching (RS) process. The simulator has been tuned with measurements of h-BN memristive devices, fabricated with chemical-vapour-deposition grown h-BN layers, which were electrically and physically characterized. We show the formation of CNFs that produce filamentary charge conduction in our devices. Moreover, the simulation tool is employed to describe partial filament rupture in reset processes and show the low dependence of the set voltage on the device area, which is seen experimentally.
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Affiliation(s)
- D Maldonado
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias, Avd. Fuentenueva s/n, 18071 Granada, Spain.
| | - A Cantudo
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias, Avd. Fuentenueva s/n, 18071 Granada, Spain.
| | - F M Gómez-Campos
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias, Avd. Fuentenueva s/n, 18071 Granada, Spain.
| | - Yue Yuan
- Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
| | - Yaqing Shen
- Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
| | - Wenwen Zheng
- Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
| | - M Lanza
- Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
| | - J B Roldán
- Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias, Avd. Fuentenueva s/n, 18071 Granada, Spain.
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Noh M, Ju D, Cho S, Kim S. The Enhanced Performance of Neuromorphic Computing Hardware in an ITO/ZnO/HfO x/W Bilayer-Structured Memory Device. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:2856. [PMID: 37947701 PMCID: PMC10648049 DOI: 10.3390/nano13212856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 10/13/2023] [Accepted: 10/25/2023] [Indexed: 11/12/2023]
Abstract
This study discusses the potential application of ITO/ZnO/HfOx/W bilayer-structured memory devices in neuromorphic systems. These devices exhibit uniform resistive switching characteristics and demonstrate favorable endurance (>102) and stable retention (>104 s). Notably, the formation and rupture of filaments at the interface of ZnO and HfOx contribute to a higher ON/OFF ratio and improve cycle uniformity compared to RRAM devices without the HfOx layer. Additionally, the linearity of potentiation and depression responses validates their applicability in neural network pattern recognition, and spike-timing-dependent plasticity (STDP) behavior is observed. These findings collectively suggest that the ITO/ZnO/HfOx/W structure holds the potential to be a viable memory component for integration into neuromorphic systems.
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Affiliation(s)
- Minseo Noh
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea; (M.N.)
| | - Dongyeol Ju
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea; (M.N.)
| | - Seongjae Cho
- Department of Electronic and Electrical Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea; (M.N.)
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Pyo J, Jang J, Ju D, Lee S, Shim W, Kim S. Amorphous BN-Based Synaptic Device with High Performance in Neuromorphic Computing. MATERIALS (BASEL, SWITZERLAND) 2023; 16:6698. [PMID: 37895680 PMCID: PMC10608025 DOI: 10.3390/ma16206698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 10/13/2023] [Accepted: 10/14/2023] [Indexed: 10/29/2023]
Abstract
The von Neumann architecture has faced challenges requiring high-fulfillment levels due to the performance gap between its processor and memory. Among the numerous resistive-switching random-access memories, the properties of hexagonal boron nitride (BN) have been extensively reported, but those of amorphous BN have been insufficiently explored for memory applications. Herein, we fabricated a Pt/BN/TiN device utilizing the resistive switching mechanism to achieve synaptic characteristics in a neuromorphic system. The switching mechanism is investigated based on the I-V curves. Utilizing these characteristics, we optimize the potentiation and depression to mimic the biological synapse. In artificial neural networks, high-recognition rates are achieved using linear conductance updates in a memristor device. The short-term memory characteristics are investigated in depression by controlling the conductance level and time interval.
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Affiliation(s)
- Juyeong Pyo
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
| | - Junwon Jang
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
| | - Dongyeol Ju
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
| | - Subaek Lee
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
| | - Wonbo Shim
- Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
| | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea
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Kundale SS, Kamble GU, Patil PP, Patil SL, Rokade KA, Khot AC, Nirmal KA, Kamat RK, Kim KH, An HM, Dongale TD, Kim TG. Review of Electrochemically Synthesized Resistive Switching Devices: Memory Storage, Neuromorphic Computing, and Sensing Applications. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:1879. [PMID: 37368309 DOI: 10.3390/nano13121879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/09/2023] [Accepted: 06/13/2023] [Indexed: 06/28/2023]
Abstract
Resistive-switching-based memory devices meet most of the requirements for use in next-generation information and communication technology applications, including standalone memory devices, neuromorphic hardware, and embedded sensing devices with on-chip storage, due to their low cost, excellent memory retention, compatibility with 3D integration, in-memory computing capabilities, and ease of fabrication. Electrochemical synthesis is the most widespread technique for the fabrication of state-of-the-art memory devices. The present review article summarizes the electrochemical approaches that have been proposed for the fabrication of switching, memristor, and memristive devices for memory storage, neuromorphic computing, and sensing applications, highlighting their various advantages and performance metrics. We also present the challenges and future research directions for this field in the concluding section.
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Affiliation(s)
- Somnath S Kundale
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Girish U Kamble
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Pradnya P Patil
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Snehal L Patil
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Kasturi A Rokade
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
| | - Atul C Khot
- School of Electrical Engineering, Korea University, Anam-dong, Seoul 02841, Republic of Korea
| | - Kiran A Nirmal
- School of Electrical Engineering, Korea University, Anam-dong, Seoul 02841, Republic of Korea
| | - Rajanish K Kamat
- Department of Electronics, Shivaji University, Kolhapur 416004, India
- Department of Physics, Dr. Homi Bhabha State University, 15, Madam Cama Road, Mumbai 400032, India
| | - Kyeong Heon Kim
- Department of Convergence Electronic Engineering, Gyeongsang National University, Jinjudae-ro 501, Jinju 52828, Republic of Korea
| | - Ho-Myoung An
- Department of Electronics, Osan University, 45, Cheonghak-ro, Osan-si 18119, Republic of Korea
| | - Tukaram D Dongale
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416004, India
- School of Electrical Engineering, Korea University, Anam-dong, Seoul 02841, Republic of Korea
| | - Tae Geun Kim
- School of Electrical Engineering, Korea University, Anam-dong, Seoul 02841, Republic of Korea
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Li K, Ji Q, Liang H, Hua Z, Hang X, Zeng L, Han H. Biomedical application of 2D nanomaterials in neuroscience. J Nanobiotechnology 2023; 21:181. [PMID: 37280681 DOI: 10.1186/s12951-023-01920-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/05/2023] [Indexed: 06/08/2023] Open
Abstract
Two-dimensional (2D) nanomaterials, such as graphene, black phosphorus and transition metal dichalcogenides, have attracted increasing attention in biology and biomedicine. Their high mechanical stiffness, excellent electrical conductivity, optical transparency, and biocompatibility have led to rapid advances. Neuroscience is a complex field with many challenges, such as nervous system is difficult to repair and regenerate, as well as the early diagnosis and treatment of neurological diseases are also challenged. This review mainly focuses on the application of 2D nanomaterials in neuroscience. Firstly, we introduced various types of 2D nanomaterials. Secondly, due to the repairment and regeneration of nerve is an important problem in the field of neuroscience, we summarized the studies of 2D nanomaterials applied in neural repairment and regeneration based on their unique physicochemical properties and excellent biocompatibility. We also discussed the potential of 2D nanomaterial-based synaptic devices to mimic connections among neurons in the human brain due to their low-power switching capabilities and high mobility of charge carriers. In addition, we also reviewed the potential clinical application of various 2D nanomaterials in diagnosing and treating neurodegenerative diseases, neurological system disorders, as well as glioma. Finally, we discussed the challenge and future directions of 2D nanomaterials in neuroscience.
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Affiliation(s)
- Kangchen Li
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China
| | - Qianting Ji
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China
| | - Huanwei Liang
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China
| | - Zixuan Hua
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China
| | - Xinyi Hang
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China
| | - Linghui Zeng
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China.
| | - Haijun Han
- School of Medicine, Institute of Brain and Cognitive Science, Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of Medicine, Hangzhou City University, Hangzhou, 310015, Zhejiang, China.
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Lee D, Kim HD. Effect of Hydrogen Annealing on Performances of BN-Based RRAM. NANOMATERIALS (BASEL, SWITZERLAND) 2023; 13:nano13101665. [PMID: 37242080 DOI: 10.3390/nano13101665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 05/12/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023]
Abstract
BN-based resistive random-access memory (RRAM) has emerged as a potential candidate for non-volatile memory (NVM) in aerospace applications, offering high thermal conductivity, excellent mechanical, and chemical stability, low power consumption, high density, and reliability. However, the presence of defects and trap states in BN-based RRAM can limit its performance and reliability in aerospace applications. As a result, higher set voltages of 1.4 and 1.23 V were obtained for non-annealed and nitrogen-annealed BN-based RRAM, respectively, but lower set voltages of 1.06 V were obtained for hydrogen-annealed BN-based RRAM. In addition, the hydrogen-annealed BN-based RRAM showed an on/off ratio of 100, which is 10 times higher than the non-annealed BN-based RRAM. We observed that the LRS changed to the HRS state before 10,000 s for both the non-annealed and nitrogen-annealed BN-based RRAMs. In contrast, the hydrogen-annealed BN-based RRAM showed excellent retention characteristics, with data retained up to 10,000 s.
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Affiliation(s)
- Doowon Lee
- Department of Semiconductor Systems Engineering, and Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea
| | - Hee-Dong Kim
- Department of Semiconductor Systems Engineering, and Convergence Engineering for Intelligent Drone, Institute of Semiconductor and System IC, Sejong University, 209, Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea
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7
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Wali A, Ravichandran H, Das S. Hardware Trojans based on two-dimensional memtransistors. NANOSCALE HORIZONS 2023; 8:603-615. [PMID: 37021644 DOI: 10.1039/d2nh00568a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Hardware Trojans (HTs) have emerged as a major security threat for integrated circuits (ICs) owing to the involvement of untrustworthy actors in the globally distributed semiconductor supply chain. HTs are intentional malicious modifications, which remain undetectable through simple electrical measurements but can cause catastrophic failure in the functioning of ICs in mission critical applications. In this article, we show how two-dimensional (2D) material based in-memory computing elements such as memtransistors can be used as hardware Trojans. We found that logic gates based on 2D memtransistors can be made to malfunction by exploiting their inherent programming capabilities. While we use 2D memtransistor-based ICs as the testbed for our demonstration, the results are equally applicable to any state-of-the-art and emerging in-memory computing technologies.
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Affiliation(s)
- Akshay Wali
- Electrical Engineering and Computer Science, Penn State University, University Park, PA 16802, USA.
| | | | - Saptarshi Das
- Electrical Engineering and Computer Science, Penn State University, University Park, PA 16802, USA.
- Engineering Science and Mechanics, Penn State University, University Park, PA 16802, USA
- Materials Science and Engineering, Penn State University, University Park, PA 16802, USA
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8
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Shi J, Kang S, Feng J, Fan J, Xue S, Cai G, Zhao JS. Evaluating charge-type of polyelectrolyte as dielectric layer in memristor and synapse emulation. NANOSCALE HORIZONS 2023; 8:509-515. [PMID: 36757200 DOI: 10.1039/d2nh00524g] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Based on credible advantages, organic materials have received more and more attention in memristor and synapse emulation. In particular, an implementation of the ionic pathway as a dielectric layer is essential for organic materials used as building blocks of memristor and artificial synaptic devices. Herein, we describe an evaluation of the use of positive and negative polyelectrolytes as dielectric layers for a memristor with calcium ion (Ca2+) doping. The device based on a negative polyelectrolyte shows the potential to obtain an excellent resistive switching performance and synapse functionality, especially in the transformation behaviours from short-term plasticity (STP) to long-term plasticity (LTP) in both the potentiation and depression processes, which were comparable to the perfomrmance obtained with a positive polyelectrolyte. The mechanism of electrical resistance transition and synaptic function can be attributed to the migration of the doped Ca2+ and the ionic functional groups of polyelectrolyte, which result in the formation and vanishing filament-like Ca2+ flux.
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Affiliation(s)
- Jingzhou Shi
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Shaohui Kang
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Jiang Feng
- Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion, Department of Applied Chemistry, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Jiaming Fan
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Song Xue
- Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion, Department of Applied Chemistry, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Gangri Cai
- Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion, Department of Applied Chemistry, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
| | - Jin Shi Zhao
- Tianjin Key Laboratory of Film Electronic & Communication Devices, School of Integrated Circuit Science and Engineering, Tianjin University of Technology, No. 391, Binshui Xidao, Xiqing District, Tianjin, 300384, PR China.
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9
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Seok H, Son S, Jathar SB, Lee J, Kim T. Synapse-Mimetic Hardware-Implemented Resistive Random-Access Memory for Artificial Neural Network. SENSORS (BASEL, SWITZERLAND) 2023; 23:3118. [PMID: 36991829 PMCID: PMC10058286 DOI: 10.3390/s23063118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/11/2023] [Accepted: 03/13/2023] [Indexed: 06/19/2023]
Abstract
Memristors mimic synaptic functions in advanced electronics and image sensors, thereby enabling brain-inspired neuromorphic computing to overcome the limitations of the von Neumann architecture. As computing operations based on von Neumann hardware rely on continuous memory transport between processing units and memory, fundamental limitations arise in terms of power consumption and integration density. In biological synapses, chemical stimulation induces information transfer from the pre- to the post-neuron. The memristor operates as resistive random-access memory (RRAM) and is incorporated into the hardware for neuromorphic computing. Hardware composed of synaptic memristor arrays is expected to lead to further breakthroughs owing to their biomimetic in-memory processing capabilities, low power consumption, and amenability to integration; these aspects satisfy the upcoming demands of artificial intelligence for higher computational loads. Among the tremendous efforts toward achieving human-brain-like electronics, layered 2D materials have demonstrated significant potential owing to their outstanding electronic and physical properties, facile integration with other materials, and low-power computing. This review discusses the memristive characteristics of various 2D materials (heterostructures, defect-engineered materials, and alloy materials) used in neuromorphic computing for image segregation or pattern recognition. Neuromorphic computing, the most powerful artificial networks for complicated image processing and recognition, represent a breakthrough in artificial intelligence owing to their enhanced performance and lower power consumption compared with von Neumann architectures. A hardware-implemented CNN with weight control based on synaptic memristor arrays is expected to be a promising candidate for future electronics in society, offering a solution based on non-von Neumann hardware. This emerging paradigm changes the computing algorithm using entirely hardware-connected edge computing and deep neural networks.
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Affiliation(s)
- Hyunho Seok
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Shihoon Son
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Sagar Bhaurao Jathar
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Jaewon Lee
- School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
| | - Taesung Kim
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Republic of Korea
- Department of Nano Science and Technology, Sungkyunkwan University, Suwon 16419, Republic of Korea
- School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
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10
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Kaya O, Colombo L, Antidormi A, Lanza M, Roche S. Revealing the improved stability of amorphous boron-nitride upon carbon doping. NANOSCALE HORIZONS 2023; 8:361-367. [PMID: 36625288 DOI: 10.1039/d2nh00520d] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
We report on a large improvement of the thermal stability and mechanical properties of amorphous boron-nitride upon carbon doping. By generating versatile force fields using first-principles and machine learning simulations, we investigate the structural properties of amorphous boron-nitride with varying contents of carbon (from a few percent to 40 at%). We found that for 20 at% of carbon, the sp3/sp2 ratio reaches a maximum with a negligible graphitisation effect, resulting in an improvement of the thermal stability by up to 20% while the bulk Young's modulus increases by about 30%. These results provide a guide to experimentalists and engineers to further tailor the growth conditions of BN-based compounds as non-conductive diffusion barriers and ultralow dielectric coefficient materials for a number of applications including interconnect technology.
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Affiliation(s)
- Onurcan Kaya
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain.
- School of Engineering, RMIT University, Melbourne, Victoria, 3001, Australia
| | - Luigi Colombo
- Department of Materials Science and Engineering, The University of Texas at Dallas, Richardson, TX, 75080, USA
| | - Aleandro Antidormi
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain.
| | - Mario Lanza
- Department of Material Science and Engineering, King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia
| | - Stephan Roche
- Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, Campus UAB, Bellaterra, 08193, Barcelona, Spain.
- ICREA Institucio Catalana de Recerca i Estudis Avancats, 08010 Barcelona, Spain
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11
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Dong X, Li S, Sun H, Jian L, Wei W, Chen J, Zhao Y, Chen J, Zhang X, Li Y. Optoelectronic Memristive Synapse Behavior for the Architecture of Cu 2ZnSnS 4@BiOBr Embedded in Poly(methyl methacrylate). J Phys Chem Lett 2023; 14:1512-1520. [PMID: 36745109 DOI: 10.1021/acs.jpclett.2c03939] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The great potential of artificial optoelectronic devices that are capable of mimicking biosynapse functions in brain-like neuromorphic computing applications has aroused extensive interest, and the architecture design is decisive yet challenging. Herein, a new architecture of p-type Cu2ZnSnS4@BiOBr nanosheets embedded in poly(methyl methacrylate) (PMMA) films (CZTS@BOB-PMMA) is presented acting as a switching layer, which not only shows the bipolar resistive switching features (SET/RESET voltages, ∼ -0.93/+1.35 V; retention, >104 s) and electrical- and near-infrared light-induced synapse plasticity but also demonstrates electrical-driven excitatory postsynaptic current, spiking-time-dependent plasticity, paired pulse facilitation, long-term plasticity, long- and short-term memory, and "learning-forgetting-learning" behaviors. The approach is a rewarding attempt to broaden the research of optoelectric controllable memristive devices for building neuromorphic architectures mimicking human brain functionalities.
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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, Lanzhou730070, China
| | - Siyuan Li
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Hao Sun
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Lijuan Jian
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Wenbin Wei
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Jianbiao Chen
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Yun Zhao
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Jiangtao Chen
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Xuqiang Zhang
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
| | - Yan Li
- Key Laboratory of Atomic and Molecular Physics & Functional Materials of Gansu Province, College of Physics and Electronic Engineering, Northwest Normal University, Lanzhou730070, China
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12
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Nirmal KA, Nhivekar GS, Khot AC, Dongale TD, Kim TG. Unraveling the Effect of the Water Content in the Electrolyte on the Resistive Switching Properties of Self-Assembled One-Dimensional Anodized TiO 2 Nanotubes. J Phys Chem Lett 2022; 13:7870-7880. [PMID: 35979996 DOI: 10.1021/acs.jpclett.2c01075] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The applied potential, time, and water content are crucial factors in the electrochemical anodization process because the growth of one-dimensional nanotubes can be accelerated by enhancing the corrosive effect. We investigated the effect of the water content on the resistive switching (RS) properties of Ti foils by anodizing the foils and varying the water content in an electrolyte (1-10 vol %). By increasing the water content, we facilitated a slow transition from nanopores to nanotubes and realized an increase in the tube wall diameter and tube length. All of the fabricated memristive devices exhibited a reliable and reproducible bipolar resistive switching effect. The optimized device exhibited bipolar RS properties with good dc endurance (104 cycles) and data retention capability (105 s). Our results suggest that as the water content increases to 5 vol %, the RS process improves; further increases in the water content impair the RS process.
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Affiliation(s)
- Kiran A Nirmal
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Ganesh S Nhivekar
- Department of Electronics, Yashavantrao Chavan Institute of Science, Satara 415 001, India
| | - Atul C Khot
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
| | - Tukaram D Dongale
- Computational Electronics and Nanoscience Research Laboratory, School of Nanoscience and Biotechnology, Shivaji University, Kolhapur 416 004, India
| | - Tae Geun Kim
- School of Electrical Engineering, Korea University, Anam-ro 145, Seongbuk-gu, Seoul 02841, Republic of Korea
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Abbas H, Li J, Ang DS. Conductive Bridge Random Access Memory (CBRAM): Challenges and Opportunities for Memory and Neuromorphic Computing Applications. MICROMACHINES 2022; 13:mi13050725. [PMID: 35630191 PMCID: PMC9143014 DOI: 10.3390/mi13050725] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/29/2022] [Accepted: 04/29/2022] [Indexed: 11/16/2022]
Abstract
Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based storage devices and computing systems are approaching their scaling and technical limits, extensive research on emerging technologies is becoming more and more important. Among other emerging technologies, CBRAM offers excellent opportunities for future memory and neuromorphic computing applications. The principles of the CBRAM are explored in depth in this review, including the materials and issues associated with various materials, as well as the basic switching mechanisms. Furthermore, the opportunities that CBRAMs provide for memory and brain-inspired neuromorphic computing applications, as well as the challenges that CBRAMs confront in those applications, are thoroughly discussed. The emulation of biological synapses and neurons using CBRAM devices fabricated with various switching materials and device engineering and material innovation approaches are examined in depth.
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