Article
Chemistry, Multidisciplinary
Yitong Chen, Dingwei Li, Huihui Ren, Yingjie Tang, Kun Liang, Yan Wang, Fanfan Li, Chunyan Song, Jiaqi Guan, Zhong Chen, Xingyu Lu, Guangwei Xu, Wenbin Li, Shi Liu, Bowen Zhu
Summary: This work presents the development of a polarized switch synaptic memtransistor based on a two-dimensional ferroelectric semiconductor α-In2Se3, which exhibits high accuracy and synaptic characteristics, providing new opportunities for neuromorphic computing.
Article
Optics
Huan Zhang, Beiju Huang, Zanyun Zhang, Chuantong Cheng, Zan Zhang, Run Chen, Lei Bao, Yiyang Xie
Summary: A photonic synapse based on waveguides and phase-change materials has been designed to achieve multilevel weights by triggering a specific number of phase-change islands, resulting in improved accuracy for recognition tasks.
OPTICS COMMUNICATIONS
(2024)
Article
Chemistry, Multidisciplinary
Qiang Wang, Ren Luo, Yankun Wang, Wencheng Fang, Luyue Jiang, Yangyang Liu, Ruobing Wang, Liyan Dai, Jinyan Zhao, Jinshun Bi, Zenghui Liu, Libo Zhao, Zhuangde Jiang, Zhitang Song, Jutta Schwarzkopf, Thomas Schroeder, Shengli Wu, Zuo-Guang Ye, Wei Ren, Sannian Song, Gang Niu
Summary: The long-term plasticity of bio-synapses is important for information encoding and its emulation in neuromorphic computing. Ga-doped GST PCRAM devices demonstrate excellent long-term synaptic plasticity and high accuracy in image recognition tasks, highlighting their potential for future high-performance neuromorphic computing.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Zhenqiang Guo, Gongjie Liu, Yong Sun, Yinxing Zhang, Jianhui Zhao, Pan Liu, Hong Wang, Zhenyu Zhou, Zhen Zhao, Xiaotong Jia, Jiameng Sun, Yiduo Shao, Xu Han, Zixuan Zhang, Xiaobing Yan
Summary: This research presents a highly stable memristor with self-assembled vertically aligned nanocomposite (VAN) SrTiO3:MgO films, which achieve low set/reset voltage variability and highly linear conductivity variation. This provides a material system and design idea for high-performance neuromorphic computing and logic operation.
Article
Automation & Control Systems
Li-Wei Chen, Wei-Chun Wang, Shao-Han Ko, Chien-Yu Chen, Chih-Ting Hsu, Fu-Ching Chiao, Tse-Wei Chen, Kai-Chiang Wu, Hao-Wu Lin
Summary: The development of artificial synapses inspired by the recognition ability of the central nervous system of living organisms has successfully demonstrated uniform electrical characteristics and stable synaptic functions in perovskite/MoO3/Ag synaptic devices. This research suggests that utilizing such components in neuromorphic computing systems can reduce circuitry complexity and increase recognition accuracy with noisy inputs.
ADVANCED INTELLIGENT SYSTEMS
(2021)
Article
Materials Science, Multidisciplinary
Ghulam Dastgeer, Haider Abbas, Duk Young Kim, Jonghwa Eom, Changhwan Choi
Summary: A nano-sized two-terminal memristor demonstrating volatile threshold switching has been fabricated to emulate biological synaptic functions in neuromorphic computing. The device exhibits a large I-ON/OFF ratio and the experimental realization of synaptic behavior validates a psychological model of human brain learning. Input pulses with different spike-times are used to replicate synaptic functionalities.
PHYSICA STATUS SOLIDI-RAPID RESEARCH LETTERS
(2021)
Article
Chemistry, Multidisciplinary
YiLong Wang, Minghui Cao, Jing Bian, Qiang Li, Jie Su
Summary: In this study, a flexible synaptic memristor with ZnO nanosheets as the intermediate layer is successfully prepared. The device shows excellent switching characteristics and stable retention characteristic. By modulating the conductance, the memristor can simulate various synaptic plasticities. The neuromorphic system built from this memristor achieves high recognition accuracy for handwriting digit and maintains good performance under noise and bending.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Materials Science, Multidisciplinary
Junyao Zhang, Qianqian Shi, Ruizhi Wang, Xuan Zhang, Li Li, Jianhua Zhang, Li Tian, Lize Xiong, Jia Huang
Summary: Research on photonic synaptic transistors based on 2DPs shows that they can successfully emulate common synaptic functions with low energy consumption and spectrum-dependent synaptic behaviors.
Article
Chemistry, Multidisciplinary
Yiqun Liu, Yonghuang Wu, Haojie Han, Yue Wang, Ruixuan Peng, Kai Liu, Di Yi, Ce-Wen Nan, Jing Ma
Summary: This research proposes an optoelectronic synaptic device with a simple structure but multifunctional capabilities, and demonstrates its potential applications in visual perception, processing, and memory. The device can emulate both short-term and long-term memory and simulate light adaptive behavior through optical-electrical cooperative modulation.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Review
Chemistry, Multidisciplinary
Qing Zhang, Tengyu Jin, Xin Ye, Dechao Geng, Wei Chen, Wenping Hu
Summary: Photonic artificial synapses-based neuromorphic computing systems are promising candidates for replacing von Neumann-based systems. Organic field-effect transistors (OFETs) have significant advantages in synaptic emulation, enabling complex photoelectric modulation and simulation of the visual system.
ADVANCED FUNCTIONAL MATERIALS
(2021)
Article
Multidisciplinary Sciences
Chen Zhu, Wen Huang, Wei Li, Xuegong Yu, Xing'ao Li
Summary: Synaptic devices, as key connecting points in neuromorphic computing systems, have been extensively studied in recent years. The development of optoelectronic synaptic devices with optical outputs has gained attraction due to the advantages of optical signals. Colloidal quantum dots (CQDs), potential luminescent materials for information displays, have emerged as appealing candidates for optoelectronic synaptic devices. Furthermore, light-emitting transistors exhibit significant application potential in these synaptic devices. This article discusses light-emitting artificial synapses based on these structures, analyzing and prospecting their mechanisms, performance, and future development in detail.
Article
Nanoscience & Nanotechnology
Pu Guo, Junyao Zhang, Dapeng Liu, Ruizhi Wang, Li Li, Li Tian, Jia Huang
Summary: This study develops solution-processed optoelectronic synaptic transistors (OSTs) that can simulate the visual nociceptor perception functions of the peripheral nervous system (PNS) and the memorizing and computing functions of the central nervous system (CNS). The OSTs demonstrate ultraviolet light selectivity and achieve 1000 conductance states, showing their potential for artificial vision and pattern recognition based on neural networks.
ACS APPLIED MATERIALS & INTERFACES
(2023)
Article
Chemistry, Multidisciplinary
Jingon Jang, Sanggyun Gi, Injune Yeo, Sanghyeon Choi, Seonghoon Jang, Seonggil Ham, Byunggeun Lee, Gunuk Wang
Summary: Realization of memristor-based neuromorphic hardware system is important for energy efficient big data processing and artificial intelligence. Uniform and reliable titanium oxide (TiOx) memristor array devices are fabricated to enable vector-matrix multiplication process in a hardware neural network. A convolutional neural network hardware system using TiOx memristor arrays is designed and implemented, achieving learning rate modulation and fast convergence. This in situ training reduces training iterations and energy consumption while maintaining high classification accuracy.
Article
Engineering, Environmental
Shubin Liu, Yu Cheng, Fang Han, Suna Fan, Yaopeng Zhang
Summary: In this work, a multilevel storage memristor based on graphene oxide/silk fibroin/graphene oxide structure is reported. The memristor exhibits both binary and ternary switching behaviors, and the transition between the two modes can be regulated by the compliance current. The device shows stable, repeatable, and nonvolatile switching behaviors, and has great potential for simulating synaptic plasticity and application in artificial neural networks for digital image recognition, compression, and reconstruction. The highest accuracy of recognition for handwritten digital images using the ternary neural network built by the device reaches 92.3%. This research highlights the promise of graphene oxide/silk fibroin/graphene oxide memristors for improving memory cell density and simplifying the structure of memristor-based storage systems.
CHEMICAL ENGINEERING JOURNAL
(2023)
Review
Chemistry, Multidisciplinary
Tae Joon Park, Sunbin Deng, Sukriti Manna, A. N. M. Nafiul Islam, Haoming Yu, Yifan Yuan, Dillon D. Fong, Alexander A. Chubykin, Abhronil Sengupta, Subramanian K. R. S. Sankaranarayanan, Shriram Ramanathan
Summary: This review discusses the opportunities provided by complex oxides in the fields of brain-inspired computing, robotics, and artificial intelligence. It covers natural intelligence in the nervous system, collective intelligence and learning, as well as recent demonstrations of artificial neurons, synapses, and circuits. The implementation of experimental characteristics into neural networks and algorithm design is also reviewed, with a focus on the importance of microscopic understanding for advancing neuromorphic computing.
ADVANCED MATERIALS
(2023)
Article
Nanoscience & Nanotechnology
Huiwu Mao, Yongli He, Chunsheng Chen, Li Zhu, Yixin Zhu, Ying Zhu, Shuo Ke, Xiangjing Wang, Changjin Wan, Qing Wan
Summary: This research introduces a stacked memristor based on IGZO as a spiking stochastic neuron, showing tunable firing probability and demonstrating eliminated switching variation and small relative deviation in stacked configuration compared to a single memristor.
ADVANCED ELECTRONIC MATERIALS
(2022)
Article
Chemistry, Multidisciplinary
Chunsheng Chen, Yongli He, Huiwu Mao, Li Zhu, Xiangjing Wang, Ying Zhu, Yixin Zhu, Yi Shi, Changjin Wan, Qing Wan
Summary: This study presents a highly bio-realistic photoelectric spiking neuron for visual depth perception. By utilizing memristive spiking encoders and a network of neuromorphic transistors, it imitates the distance-dependent response and eye fatigue of biological visual systems.
ADVANCED MATERIALS
(2022)
Article
Engineering, Electrical & Electronic
Shuo Ke, Chuanyu Fu, Xinhuang Lin, Yixin Zhu, Huiwu Mao, Li Zhu, Xiangjing Wang, Chunsheng Chen, Changjin Wan, Qing Wan
Summary: In this study, amorphous indium gallium zinc oxide transistors were used to mimic light-induced short-term synaptic plasticity and successfully realize BCM learning rules. This is of great significance for the development of photoelectronic neuromorphic systems with sophisticated learning rules.
IEEE TRANSACTIONS ON ELECTRON DEVICES
(2022)
Article
Physics, Applied
Yixin Zhu, Baocheng Peng, Li Zhu, Chunsheng Chen, Xiangjing Wang, Huiwu Mao, Ying Zhu, Chuanyu Fu, Shuo Ke, Changjin Wan, Qing Wan
Summary: In this study, a photoelectric transistor based on indium-gallium-zinc-oxide (IGZO) nanofibers is proposed to achieve tunable photoelectric synaptic plasticity by adjusting the indium composition ratio. The results show that low indium ratio devices can achieve spatiotemporal dynamic logic and low energy consumption, while high indium ratio devices can emulate photoelectric long-term plasticity and high recognition accuracy.
APPLIED PHYSICS LETTERS
(2022)
Article
Physics, Multidisciplinary
Yue Li, Li Zhu, Chunsheng Chen, Ying Zhu, Changjin Wan, Qing Wan
Summary: High-performance amorphous indium-gallium-zinc-oxide thin-film transistors (a-IGZO TFTs) gated by Al2O3/HfO2 stacked dielectric films are investigated. The optimized TFTs with Al2O3 (2.0 nm)/HfO2 (13 nm) stacked gate dielectrics demonstrate the best performance, showing great potential for low-power, high-performance, and large-area display and emerging electronics.
CHINESE PHYSICS LETTERS
(2022)
Article
Physics, Applied
Yang Yang, Hangyuan Cui, Shuo Ke, Mengjiao Pei, Kailu Shi, Changjin Wan, Qing Wan
Summary: Physical reservoir computing (PRC) is a potential low-cost temporal processing platform, utilizing the nonlinear and volatile dynamics of materials. An electric-double-layer (EDL) formed at the interface between a semiconductor and an electrolyte is used to build a high energy-efficiency PRC. In this study, EDL coupled indium-gallium-zinc-oxide (IGZO) artificial synapses are used to implement reservoir computing (RC), which exhibits nonlinearity, fade memory properties, and low power consumption, making it suitable for high energy-efficient RC systems. The results show the potential of using EDL coupling for a lightweight hardware physical reservoir that can underlie a next-generation machine learning platform.
APPLIED PHYSICS LETTERS
(2023)
Article
Physics, Applied
Huiwu Mao, Yixin Zhu, Ying Zhu, Baocheng Peng, Chunsheng Chen, Li Zhu, Shuo Ke, Xiangjing Wang, Changjin Wan, Qing Wan
Summary: In this study, a crossbar array of amorphous indium-gallium-zinc-oxide (a-IGZO)-based threshold switching memristors was designed for high-throughput true random number generators (TRNGs). The stochasticity of the Ag conductive filament in the IGZO memristor and the stochastic sneak paths in the crossbar array are the sources of randomness in the TRNGs. The integration scale of the memristors can be increased to further reduce the average energy consumption of the TRNGs. These IGZO-based TRNGs are of great significance for security applications.
APPLIED PHYSICS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Kailu Shi, Sizhuo Heng, Xiangjing Wang, Siyao Liu, Hangyuan Cui, Chunsheng Chen, Yixin Zhu, Weigao Xu, Changjin Wan, Qing Wan
Summary: In this study, we developed an artificial spiking thermoreceptor based on Ag/TaOX/AlOX/ITO threshold switching memristor, which can encode thermal information into spikes at low power consumption, achieving human-like thermal perception. This provides convenience for low-power and accurate thermography edge detection.
IEEE ELECTRON DEVICE LETTERS
(2022)
Article
Multidisciplinary Sciences
Xiangjing Wang, Chunsheng Chen, Li Zhu, Kailu Shi, Baocheng Peng, Yixin Zhu, Huiwu Mao, Haotian Long, Shuo Ke, Chuanyu Fu, Ying Zhu, Changjin Wan, Qing Wan
Summary: The research proposes a metal oxide-based vertically integrated spiking cone photoreceptor array that can directly convert persistent lights into spike trains with a power consumption of less than 400 picowatts. By using lights with three wavelengths as pseudo-three-primary colors, the device shows better accuracy in discriminating mixed colors. The results have the potential to enable hardware spiking neural networks with biologically plausible visual perception and contribute to the development of dynamic vision sensors.
NATURE COMMUNICATIONS
(2023)
Article
Physics, Applied
Shuo Ke, Feiyu Wang, Chuanyu Fu, Huiwu Mao, Yixin Zhu, Xiangjing Wang, Changjin Wan, Qing Wan
Summary: Fear neural circuits can recognize threatening stimuli and provide early warning. Implementing fear neural circuits through neuromorphic devices can enhance the adaptability and cognition of humanoid robots. We propose an artificial fear neural circuit that successfully emulates fear behaviors.
APPLIED PHYSICS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Biaobiao Ding, Yichen Zhu, Run Li, Guangan Yang, Jie Wu, Li Zhu, Xiang Wan, Zhihao Yu, Chee Leong Tan, Yong Xu, Huabin Sun
Summary: In this study, the interface states of D-A polymer transistors are quantified using the dynamic pumping method, and it is found that the interface state density is insensitive to the measurement pulse condition, staying within the range of 10^12 to 10^13 cm(-2). These findings provide a quantitative analysis of interface states and can serve as effective guidance for optimizing future devices.
IEEE JOURNAL OF THE ELECTRON DEVICES SOCIETY
(2023)
Proceedings Paper
Engineering, Electrical & Electronic
Yixin Zhu, Changjin Wan
Summary: This paper proposes an IGZO nanofiber-based photoelectric synapse, which demonstrates the versatility and potential in mimicking biological synapses and constructing artificial neural networks with 5-bit precision and 15 fJ weight updating energy.
6TH IEEE ELECTRON DEVICES TECHNOLOGY AND MANUFACTURING CONFERENCE (EDTM 2022)
(2022)
Article
Physics, Multidisciplinary
Jiang Zi-Han, Ke Shuo, Zhu Ying, Zhu Yi-Xin, Zhu Li, Wan Chang-Jin, Wan Qing
Summary: This review introduces the research progress of flexible neuromorphic transistors, including device structure, working principle, basic functions, and their applications in the field of bionic perception. The research of flexible neuromorphic transistors has become a recent focus of attention.
ACTA PHYSICA SINICA
(2022)
