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He Y, Zhu Y, Wan Q. Oxide Ionic Neuro-Transistors for Bio-inspired Computing. NANOMATERIALS (BASEL, SWITZERLAND) 2024; 14:584. [PMID: 38607119 PMCID: PMC11013937 DOI: 10.3390/nano14070584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/24/2024] [Accepted: 03/25/2024] [Indexed: 04/13/2024]
Abstract
Current computing systems rely on Boolean logic and von Neumann architecture, where computing cells are based on high-speed electron-conducting complementary metal-oxide-semiconductor (CMOS) transistors. In contrast, ions play an essential role in biological neural computing. Compared with CMOS units, the synapse/neuron computing speed is much lower, but the human brain performs much better in many tasks such as pattern recognition and decision-making. Recently, ionic dynamics in oxide electrolyte-gated transistors have attracted increasing attention in the field of neuromorphic computing, which is more similar to the computing modality in the biological brain. In this review article, we start with the introduction of some ionic processes in biological brain computing. Then, electrolyte-gated ionic transistors, especially oxide ionic transistors, are briefly introduced. Later, we review the state-of-the-art progress in oxide electrolyte-gated transistors for ionic neuromorphic computing including dynamic synaptic plasticity emulation, spatiotemporal information processing, and artificial sensory neuron function implementation. Finally, we will address the current challenges and offer recommendations along with potential research directions.
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Affiliation(s)
- Yongli He
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
| | - Yixin Zhu
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
| | - Qing Wan
- Yongjiang Laboratory (Y-LAB), Ningbo 315202, China; (Y.H.); (Y.Z.)
- National Laboratory of Solid-State Microstructures, Collaborative Innovation Center of Advanced Microstructures, School of Electronic Science and Engineering, Nanjing University, Nanjing 210093, China
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Yoo H, Lee IS, Jung S, Rho SM, Kang BH, Kim HJ. A Review of Phototransistors Using Metal Oxide Semiconductors: Research Progress and Future Directions. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2021; 33:e2006091. [PMID: 34048086 DOI: 10.1002/adma.202006091] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 10/15/2020] [Indexed: 06/12/2023]
Abstract
Metal oxide thin-film transistors have been continuously researched and mass-produced in the display industry. However, their phototransistors are still in their infancy. In particular, utilizing metal oxide semiconductors as phototransistors is difficult because of the limited light absorption wavelength range and persistent photocurrent (PPC) phenomenon. Numerous studies have attempted to improve the detectable light wavelength range and the PPC phenomenon. Here, recent studies on metal oxide phototransistors are reviewed, which have improved the range of light wavelengths and the PPC phenomenon by introducing an absorption layer of oxide or non-oxide hybrid structure. The materials of the absorption layer applied to absorb long-wavelength light are classified into oxides, chalcogenides, organic materials, perovskites, and nanodots. Finally, next-generation convergence studies combined with other research fields are introduced and future research directions are detailed.
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Affiliation(s)
- Hyukjoon Yoo
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - I Sak Lee
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Sujin Jung
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Sung Min Rho
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Byung Ha Kang
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
| | - Hyun Jae Kim
- School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea
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John RA, Tiwari N, Patdillah MIB, Kulkarni MR, Tiwari N, Basu J, Bose SK, Ankit, Yu CJ, Nirmal A, Vishwanath SK, Bartolozzi C, Basu A, Mathews N. Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics. Nat Commun 2020; 11:4030. [PMID: 32788588 PMCID: PMC7424569 DOI: 10.1038/s41467-020-17870-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 07/17/2020] [Indexed: 01/25/2023] Open
Abstract
Sensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphery to central processors, at the cost of wiring, latency, fault tolerance and robustness. We envision a decentralized approach where intelligence is embedded in the sensing nodes, using a unique neuromorphic methodology to extract relevant information in robotic skins. Here we specifically address pain perception and the association of nociception with tactile perception to trigger the escape reflex in a sensorized robotic arm. The proposed system comprises self-healable materials and memtransistors as enabling technologies for the implementation of neuromorphic nociceptors, spiking local associative learning and communication. Configuring memtransistors as gated-threshold and -memristive switches, the demonstrated system features in-memory edge computing with minimal hardware circuitry and wiring, and enhanced fault tolerance and robustness.
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Affiliation(s)
- Rohit Abraham John
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Naveen Tiwari
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | | | - Mohit Rameshchandra Kulkarni
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Nidhi Tiwari
- Energy Research Institute @ NTU (ERI@N), Nanyang Technological University, Singapore, 637553, Singapore
| | - Joydeep Basu
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Sumon Kumar Bose
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Ankit
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Chan Jun Yu
- School of Mechanical and Aerospace Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Amoolya Nirmal
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Sujaya Kumar Vishwanath
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore
| | - Chiara Bartolozzi
- Event-Driven Perception for Robotics, Italian Institute of Technology, via San Quirico 19D, 16163, Genova, Italy
| | - Arindam Basu
- School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
| | - Nripan Mathews
- School of Materials Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore.
- Energy Research Institute @ NTU (ERI@N), Nanyang Technological University, Singapore, 637553, Singapore.
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Wang Y, Liao Q, She D, Lv Z, Gong Y, Ding G, Ye W, Chen J, Xiong Z, Wang G, Zhou Y, Han ST. Modulation of Binary Neuroplasticity in a Heterojunction-Based Ambipolar Transistor. ACS APPLIED MATERIALS & INTERFACES 2020; 12:15370-15379. [PMID: 32153180 DOI: 10.1021/acsami.0c00635] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl}(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.
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Affiliation(s)
- Yan Wang
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Qiufan Liao
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Donghong She
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Ziyu Lv
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Yue Gong
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Guanglong Ding
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Wenbin Ye
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Jinrui Chen
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Ziyu Xiong
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Guoping Wang
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Ye Zhou
- Institute for Advanced Study, Shenzhen University, Shenzhen 518060, People's Republic of China
| | - Su-Ting Han
- Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518060, People's Republic of China
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