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Sun S, Zhang M, Bian J, Xu T, Su J. In 2O 3/ZnO heterojunction thin film transistor for high recognition accuracy neuromorphic computing and optoelectronic artificial synapses. NANOTECHNOLOGY 2024; 35:365602. [PMID: 38861958 DOI: 10.1088/1361-6528/ad5685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 06/11/2024] [Indexed: 06/13/2024]
Abstract
Solid electrolyte-gated transistors exhibit improved chemical stability and can fulfill the requirements of microelectronic packaging. Typically, metal oxide semiconductors are employed as channel materials. However, the extrinsic electron transport properties of these oxides, which are often prone to defects, pose limitations on the overall electrical performance. Achieving excellent repeatability and stability of transistors through the solution process remains a challenging task. In this study, we propose the utilization of a solution-based method to fabricate an In2O3/ZnO heterojunction structure, enabling the development of efficient multifunctional optoelectronic devices. The heterojunction's upper and lower interfaces induce energy band bending, resulting in the accumulation of a large number of electrons and a significant enhancement in transistor mobility. To mimic synaptic plasticity responses to electrical and optical stimuli, we utilize Li+-doped high-k ZrOxthin films as a solid electrolyte in the device. Notably, the heterojunction transistor-based convolutional neural network achieves a high accuracy rate of 93% in recognizing handwritten digits. Moreover, our research involves the simulation of a typical sensory neuron, specifically a nociceptor, within our synaptic transistor. This research offers a novel avenue for the advancement of cost-effective three-terminal thin-film transistors tailored for neuromorphic applications.
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Affiliation(s)
- Shangheng Sun
- School of Physics Science, Qingdao University, Qingdao 266071, People's Republic of China
| | - Minghao Zhang
- School of Physics Science, Qingdao University, Qingdao 266071, People's Republic of China
| | - Jing Bian
- School of Electronic and Information Engineering, Qingdao University, Qingdao 266071, People's Republic of China
| | - Ting Xu
- School of Electronic and Information Engineering, Qingdao University, Qingdao 266071, People's Republic of China
| | - Jie Su
- School of Physics Science, Qingdao University, Qingdao 266071, People's Republic of China
- School of Electronic and Information Engineering, Qingdao University, Qingdao 266071, People's Republic of China
- National Laboratory of Solid State Microstructures, Physics Department, Nanjing University, Nanjing 210093, People's Republic of China
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2
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Song HW, Moon D, Won Y, Cha YK, Yoo J, Park TH, Oh JH. A pattern recognition artificial olfactory system based on human olfactory receptors and organic synaptic devices. SCIENCE ADVANCES 2024; 10:eadl2882. [PMID: 38781346 PMCID: PMC11114221 DOI: 10.1126/sciadv.adl2882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Accepted: 04/18/2024] [Indexed: 05/25/2024]
Abstract
Neuromorphic sensors, designed to emulate natural sensory systems, hold the promise of revolutionizing data extraction by facilitating rapid and energy-efficient analysis of extensive datasets. However, a challenge lies in accurately distinguishing specific analytes within mixtures of chemically similar compounds using existing neuromorphic chemical sensors. In this study, we present an artificial olfactory system (AOS), developed through the integration of human olfactory receptors (hORs) and artificial synapses. This AOS is engineered by interfacing an hOR-functionalized extended gate with an organic synaptic device. The AOS generates distinct patterns for odorants and mixtures thereof, at the molecular chain length level, attributed to specific hOR-odorant binding affinities. This approach enables precise pattern recognition via training and inference simulations. These findings establish a foundation for the development of high-performance sensor platforms and artificial sensory systems, which are ideal for applications in wearable and implantable devices.
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Affiliation(s)
- Hyun Woo Song
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
| | - Dongseok Moon
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
| | - Yousang Won
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
| | - Yeon Kyung Cha
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea
- Korea Institute of Science and Technology (KIST), Seoul 02792, Republic of Korea
| | - Jin Yoo
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
| | - Tai Hyun Park
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
- Interdisciplinary Program in Bioengineering, Seoul National University, Seoul 08826, Republic of Korea
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Joon Hak Oh
- School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of Korea
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Wu X, Chen S, Jiang L, Wang X, Qiu L, Zheng L. Highly Sensitive, Low-Energy-Consumption Biomimetic Olfactory Synaptic Transistors Based on the Aggregation of the Semiconductor Films. ACS Sens 2024; 9:2673-2683. [PMID: 38688032 DOI: 10.1021/acssensors.4c00616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/02/2024]
Abstract
Artificial olfactory synaptic devices with low energy consumption and low detection limits are important for the further development of neuromorphic computing and intelligent robotics. In this work, an ultralow energy consumption and low detection limit imitation olfactory synaptic device based on organic field-effect transistors (OFETs) was prepared. The aggregation state of poly(diketopyrrolopyrrole-selenophene) (PTDPP) semiconductor films is modulated by adding unfavorable solvents and annealing treatments to obtain excellent charge transfer and gas synaptic properties. The regulated OFET device can execute basic biological synaptic functions, including excitatory postsynaptic currents (EPSCs), paired-pulse facilitation (PPF), and the transition from short-term to long-term plasticity, at an ultralow operating voltage of -0.0005 V. The ultralow energy consumption during the biomimetic simulation is in the range of 8.94-88 fJ per spike. Noteworthily, the gas detection limit of the device is as low as 50 ppb, well below normal human NO2 gas perception limits (100-1000 ppb). Additionally, high-pass filtering, Pavlovian conditioned reflexes, and decoding of "Morse code" were simulated. Finally, a grid-free conformal device with outstanding flexibility and stability was fabricated. In conclusion, the control of semiconductor thin-film aggregation provides effective guidance for preparing low-energy-consumption, highly sensitive olfactory nerve-mimicking devices and promoting the development of wearable electronics.
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Affiliation(s)
- Xiaocheng Wu
- National Engineering Lab of Special Display Technology, State Key Lab of Advanced Display Technology, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, P. R. China
- Intelligent Interconnected Systems Laboratory of Anhui, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei 230009, P. R. China
| | - Siyu Chen
- National Engineering Lab of Special Display Technology, State Key Lab of Advanced Display Technology, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, P. R. China
- Intelligent Interconnected Systems Laboratory of Anhui, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei 230009, P. R. China
| | - Longlong Jiang
- National Engineering Lab of Special Display Technology, State Key Lab of Advanced Display Technology, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, P. R. China
- Intelligent Interconnected Systems Laboratory of Anhui, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei 230009, P. R. China
| | - Xiaohong Wang
- National Engineering Lab of Special Display Technology, State Key Lab of Advanced Display Technology, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, P. R. China
- Intelligent Interconnected Systems Laboratory of Anhui, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei 230009, P. R. China
| | - Longzhen Qiu
- National Engineering Lab of Special Display Technology, State Key Lab of Advanced Display Technology, Academy of Optoelectronic Technology, Hefei University of Technology, Hefei 230009, P. R. China
- Intelligent Interconnected Systems Laboratory of Anhui, Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, School of Instrument Science and Optoelectronic Engineering, Hefei University of Technology, Hefei 230009, P. R. China
| | - Lei Zheng
- School of Food and Biological Engineering, Hefei University of Technology, Hefei 230009, China
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Bag A, Ghosh G, Sultan MJ, Chouhdry HH, Hong SJ, Trung TQ, Kang GY, Lee NE. Bio-Inspired Sensory Receptors for Artificial-Intelligence Perception. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024:e2403150. [PMID: 38699932 DOI: 10.1002/adma.202403150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/16/2024] [Indexed: 05/05/2024]
Abstract
In the era of artificial intelligence (AI), there is a growing interest in replicating human sensory perception. Selective and sensitive bio-inspired sensory receptors with synaptic plasticity have recently gained significant attention in developing energy-efficient AI perception. Various bio-inspired sensory receptors and their applications in AI perception are reviewed here. The critical challenges for the future development of bio-inspired sensory receptors are outlined, emphasizing the need for innovative solutions to overcome hurdles in sensor design, integration, and scalability. AI perception can revolutionize various fields, including human-machine interaction, autonomous systems, medical diagnostics, environmental monitoring, industrial optimization, and assistive technologies. As advancements in bio-inspired sensing continue to accelerate, the promise of creating more intelligent and adaptive AI systems becomes increasingly attainable, marking a significant step forward in the evolution of human-like sensory perception.
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Affiliation(s)
- Atanu Bag
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Research Centre for Advanced Materials Technology, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Gargi Ghosh
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - M Junaid Sultan
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Hamna Haq Chouhdry
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Seok Ju Hong
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Tran Quang Trung
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Geun-Young Kang
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
| | - Nae-Eung Lee
- School of Advanced Materials Science & Engineering, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Research Centre for Advanced Materials Technology, Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- SKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
- Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Institute of Quantum Biophysics (IQB) and Biomedical Institute for Convergence at SKKU (BICS), Sungkyunkwan University, Suwon, Gyeonggi-do, 16419, Republic of Korea
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5
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Kim S, Ju D, Kim S. Implementation of Artificial Synapse Using IGZO-Based Resistive Switching Device. MATERIALS (BASEL, SWITZERLAND) 2024; 17:481. [PMID: 38276419 PMCID: PMC10817334 DOI: 10.3390/ma17020481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/12/2024] [Accepted: 01/17/2024] [Indexed: 01/27/2024]
Abstract
In this study, we present the resistive switching characteristics and the emulation of a biological synapse using the ITO/IGZO/TaN device. The device demonstrates efficient energy consumption, featuring low current resistive switching with minimal set and reset voltages. Furthermore, we establish that the device exhibits typical bipolar resistive switching with the coexistence of non-volatile and volatile memory properties by controlling the compliance during resistive switching phenomena. Utilizing the IGZO-based RRAM device with an appropriate pulse scheme, we emulate a biological synapse based on its electrical properties. Our assessments include potentiation and depression, a pattern recognition system based on neural networks, paired-pulse facilitation, excitatory post-synaptic current, and spike-amplitude dependent plasticity. These assessments confirm the device's effective emulation of a biological synapse, incorporating both volatile and non-volatile functions. Furthermore, through spike-rate dependent plasticity and spike-timing dependent plasticity of the Hebbian learning rules, high-order synapse imitation was done.
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Affiliation(s)
| | | | - Sungjun Kim
- Division of Electronics and Electrical Engineering, Dongguk University, Seoul 04620, Republic of Korea (D.J.)
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Chun SY, Song YG, Kim JE, Kwon JU, Soh K, Kwon JY, Kang CY, Yoon JH. An Artificial Olfactory System Based on a Chemi-Memristive Device. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2302219. [PMID: 37116944 DOI: 10.1002/adma.202302219] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 04/18/2023] [Indexed: 06/19/2023]
Abstract
Technologies based on the fusion of gas sensors and neuromorphic computing to mimic the olfactory system have immense potential. However, the implementation of neuromorphic olfactory systems remains in a state of infancy because conventional gas sensors lack the necessary functions. Therefore, this study proposes a hysteretic "chemi-memristive gas sensor" based on oxygen vacancy chemi-memristive dynamics that differ from that of conventional gas sensors. After the memristive switching operation, the redox reaction with the external gas molecules is enhanced, resulting in the generation and elimination of oxygen vacancies that induce rapid current changes. In addition, the pre-generated oxygen vacancies enhance the post-sensing properties. Therefore, fast responses, short recovery times, and hysteretic gas response are achieved by the proposed sensor at room temperature. Based on the advantageous functionality of the sensor, device-level olfactory systems that can monitor the history of input gas stimuli are experimentally demonstrated as a potential application. Moreover, analog conductance modulation induced by oxidizing and reducing gases enables the conversion of external gas stimuli into synaptic weights and hence the realization of typical synaptic functionalities without an additional device or circuit. The proposed chemi-memristive device represents an advance in the bioinspired technology adopted in creating artificial intelligence systems.
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Affiliation(s)
- Suk Yeop Chun
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02841, Republic of Korea
| | - Young Geun Song
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
| | - Ji Eun Kim
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Jae Uk Kwon
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Keunho Soh
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
- Department of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea
| | - Ju Young Kwon
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
| | - Chong-Yun Kang
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02841, Republic of Korea
| | - Jung Ho Yoon
- Electronic Materials Research Center, Korea Institute of Science and Technology (KIST), Seoul, 02791, Republic of Korea
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Rehman S, Khan MA, Kim H, Patil H, Aziz J, Kadam KD, Rehman MA, Rabeel M, Hao A, Khan K, Kim S, Eom J, Kim DK, Khan MF. Optically Reconfigurable Complementary Logic Gates Enabled by Bipolar Photoresponse in Gallium Selenide Memtransistor. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023:e2205383. [PMID: 37076923 DOI: 10.1002/advs.202205383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Revised: 03/01/2023] [Indexed: 05/03/2023]
Abstract
To avoid the complexity of the circuit for in-memory computing, simultaneous execution of multiple logic gates (OR, AND, NOR, and NAND) and memory behavior are demonstrated in a single device of oxygen plasma-treated gallium selenide (GaSe) memtransistor. Resistive switching behavior with RON /ROFF ratio in the range of 104 to 106 is obtained depending on the channel length (150 to 1600 nm). Oxygen plasma treatment on GaSe film created shallow and deep-level defect states, which exhibit carriers trapping/de-trapping, that lead to negative and positive photoconductance at positive and negative gate voltages, respectively. This distinguishing feature of gate-dependent transition of negative to positive photoconductance encourages the execution of four logic gates in the single memory device, which is elusive in conventional memtransistor. Additionally, it is feasible to reversibly switch between two logic gates by just adjusting the gate voltages, e.g., NAND/NOR and AND/NAND. All logic gates presented high stability. Additionally, memtransistor array (1×8) is fabricated and programmed into binary bits representing ASCII (American Standard Code for Information Interchange) code for the uppercase letter "N". This facile device configuration can provide the functionality of both logic and memory devices for emerging neuromorphic computing.
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Affiliation(s)
- Shania Rehman
- Department of Semiconductor System Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Muhammad Asghar Khan
- Department of Physics & Astronomy and Graphene Research Institute, Sejong University, Seoul, 05006, Republic of Korea
| | - Honggyun Kim
- Department of Semiconductor System Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Harshada Patil
- Department of Electrical Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Jamal Aziz
- Department of Electrical Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Kalyani D Kadam
- Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul, 05006, South Korea
| | - Malik Abdul Rehman
- Department of Chemical Engineering, New Uzbekistan University, Tashkent, 100007, Uzbekistan
| | - Muhammad Rabeel
- Department of Electrical Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Aize Hao
- State Key Laboratory of Chemistry and Utilization of Carbon-Based Energy Resources, College of Chemistry, Xinjiang University, Urumqi, Xinjiang, 830017, P. R. China
| | - Karim Khan
- School of Mechanical Engineering, Dongguan University of Technology, Dongguan, 523808, P. R. China
| | - Sungho Kim
- Department of Semiconductor System Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Jonghwa Eom
- Department of Physics & Astronomy and Graphene Research Institute, Sejong University, Seoul, 05006, Republic of Korea
| | - Deok-Kee Kim
- Department of Semiconductor System Engineering, Sejong University, Seoul, 05006, Republic of Korea
- Department of Convergence Engineering for Intelligent Drone, Sejong University, Seoul, 05006, South Korea
| | - Muhammad Farooq Khan
- Department of Electrical Engineering, Sejong University, Seoul, 05006, Republic of Korea
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A flexible artificial chemosensory neuronal synapse based on chemoreceptive ionogel-gated electrochemical transistor. Nat Commun 2023; 14:821. [PMID: 36788242 PMCID: PMC9929093 DOI: 10.1038/s41467-023-36480-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 02/01/2023] [Indexed: 02/16/2023] Open
Abstract
The human olfactory system comprises olfactory receptor neurons, projection neurons, and interneurons that perform remarkably sophisticated functions, including sensing, filtration, memorization, and forgetting of chemical stimuli for perception. Developing an artificial olfactory system that can mimic these functions has proved to be challenging. Herein, inspired by the neuronal network inside the glomerulus of the olfactory bulb, we present an artificial chemosensory neuronal synapse that can sense chemical stimuli and mimic the functions of excitatory and inhibitory neurotransmitter release in the synapses between olfactory receptor neurons, projection neurons, and interneurons. The proposed device is based on a flexible organic electrochemical transistor gated by the potential generated by the interaction of gas molecules with ions in a chemoreceptive ionogel. The combined use of a chemoreceptive ionogel and an organic semiconductor channel allows for a long retentive memory in response to chemical stimuli. Long-term memorization of the excitatory chemical stimulus can be also erased by applying an inhibitory electrical stimulus due to ion dynamics in the chemoresponsive ionogel gate electrolyte. Applying a simple device design, we were able to mimic the excitatory and inhibitory synaptic functions of chemical synapses in the olfactory system, which can further advance the development of artificial neuronal systems for biomimetic chemosensory applications.
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