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学者姓名：陈惠鹏
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Memristor-based physical reservoir computing holds significant potential for efficiently processing complex spatiotemporal data, which is crucial for advancing artificial intelligence. However, owing to the single physical node mapping characteristic of traditional memristor reservoir computing, it inevitably induces high repeatability of eigenvalues to a certain extent and significantly limits the efficiency and performance of memristor-based reservoir computing for complex tasks. Hence, this work firstly reports an artificial light-emitting synaptic (LES) device with dual photoelectric output for reservoir computing, and a reservoir system with mixed physical nodes is proposed. The system effectively transforms the input signal into two eigenvalue outputs using a mixed physical node reservoir comprising distinct physical quantities, namely optical output with nonlinear optical effects and electrical output with memory characteristics. Unlike previously reported memristor-based reservoir systems, which pursue rich reservoir states in one physical dimension, our mixed physical node reservoir system can obtain reservoir states in two physical dimensions with one input without increasing the number and types of devices. The recognition rate of the artificial light-emitting synaptic reservoir system can achieve 97.22% in MNIST recognition. Furthermore, the recognition task of multichannel images can be realized through the nonlinear mapping of the photoelectric dual reservoir, resulting in a recognition accuracy of 99.25%. The mixed physical node reservoir computing proposed in this work is promising for implementing the development of photoelectric mixed neural networks and material-algorithm collaborative design. © The Author(s) 2024.
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| GB/T 7714 | Lian, M. , Gao, C. , Lin, Z. et al. Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output [J]. | Light: Science and Applications , 2024 , 13 (1) . |
| MLA | Lian, M. et al. "Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output" . | Light: Science and Applications 13 . 1 (2024) . |
| APA | Lian, M. , Gao, C. , Lin, Z. , Shan, L. , Chen, C. , Zou, Y. et al. Towards mixed physical node reservoir computing: light-emitting synaptic reservoir system with dual photoelectric output . | Light: Science and Applications , 2024 , 13 (1) . |
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The visual perception system is the most important part of the human body to perceive and receive information about the external environment, in which the visual neuron is the basic unit of the visual perception system to achieve the function. As an important part of the bionic neuromimetic perception system, the artificial bionic visual neural system is diligently striving to surmount the computational bottlenecks inherent in the traditional von Neumann architecture. However, structural redundancy and information transmission loss remain a challenge for artificial visual perception systems based on sensor-artificial neuron connections. Here, we propose an artificial bionic visual neuron of sense-storage-computing monolithic type, integrating a light-absorbing layer based on chalcogenide quantum dots and conjugated polymers on top of tantalum oxide artificial neural components, which has good optoelectronic synergistic integration capability. The proposed artificial visual neurons exhibit typical bipolar switching characteristics and integral ignition performance, while showing threshold change behaviour for photomodulation. The unique optoelectronic co-integration ability of the artificial visual neurons can provide assistance for constructing more efficient and low-power artificial visual perception systems, which has a broad application prospect. © 2024 IEEE.
Keyword ：
artificial neurons artificial neurons optoelectronical optoelectronical visual perception visual perception
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| GB/T 7714 | Qin, C. , Lin, J. , Chen, H. . An Optoelectronically Modulated Artificial Bionic Visual Neuron [未知]. |
| MLA | Qin, C. et al. "An Optoelectronically Modulated Artificial Bionic Visual Neuron" [未知]. |
| APA | Qin, C. , Lin, J. , Chen, H. . An Optoelectronically Modulated Artificial Bionic Visual Neuron [未知]. |
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Artificial neural systems demonstrate outstanding performance by processing sensory data and realtime contexts in parallel, far surpassing conventional von Neumann computers in terms of energy efficiency. This property has sparked widespread interest within the field of artificial intelligence. In recent years, research on electric-double-layer synaptic transistors has attracted much attention due to their similarity in ionic motion modulation to that of biological synapses, thereby demonstrating a wealth of potential application scenarios. In this paper, we demonstrate a solid-state electrolyte-gated transistor that uses TaOx with a unique ionic composition as the insulating layer and transparent indium tin oxide (ITO) as the semiconductor layer to prepare artificial synaptic thin-film transistors (TFTs) with signal transmission and self-learning properties. The devices exhibit significant memory holding, memory bank voltage exceeds 6V at operating voltages below 10V. The shift of oxygen Void Sites in the insulating layer in synaptic transistor, entrained by electrical forces created from input signals, plays a crucial role in simulating synaptic behavior. In addition, the device successfully simulates the enhancement and inhibition of synaptic weights, such as excitatory postsynaptic current (EPSC), inhibitory response (IPSC), paired pulse facilitation (PPF), and long-term potentiation (LTP). © 2024 IEEE.
Keyword ：
electric double layer electric double layer synaptic transistor synaptic transistor synaptic weight tenability synaptic weight tenability
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| GB/T 7714 | Ren, Z. , Qin, C. , Chen, H. . A Weight-Tunable Oxide Synaptic Transistor [未知]. |
| MLA | Ren, Z. et al. "A Weight-Tunable Oxide Synaptic Transistor" [未知]. |
| APA | Ren, Z. , Qin, C. , Chen, H. . A Weight-Tunable Oxide Synaptic Transistor [未知]. |
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大学物理作为理工科的课程,其教学内容不仅涉及自然科学知识,更蕴含着丰富的思政教育资源.该门课程具备的知识广度、深度和时间跨度,使其与描述世界普遍规律的马克思主义哲学原理天然契合.通过在大学物理课程中实施唯物论、辩证法、认识论和唯物史观的四维融入,不仅可以培养学生形成正确的世界观、人生观和价值观,还可以培养践行社会主义核心价值观.对此,本文通过分析大学物理课程与马克思主义哲学原理天然契合的依据,在此基础上研究大学物理课程融入马克思主义哲学原理的教学实践及教学方法,以期促进学生提升物理学习水平的同时,提升思想政治水平.
Keyword ：
大学物理 大学物理 实施研究 实施研究 课程思政 课程思政
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| GB/T 7714 | 陈惠鹏 , 陈绍敏 . 大学物理教学中实施课程思政的研究 [J]. | 国家通用语言文字教学与研究 , 2024 , (11) : 1-3 . |
| MLA | 陈惠鹏 et al. "大学物理教学中实施课程思政的研究" . | 国家通用语言文字教学与研究 11 (2024) : 1-3 . |
| APA | 陈惠鹏 , 陈绍敏 . 大学物理教学中实施课程思政的研究 . | 国家通用语言文字教学与研究 , 2024 , (11) , 1-3 . |
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For convolution neural networks, increasing the performance of hardware computer systems is crucial in the era of big data. Benefiting from the neuromorphic devices, producing the convolutional calculation at the crossbar array circuit has become a promising approach for high-performance hardware computer systems. However, as computation scales, this hardware system faces the challenge of low resource utilization efficiency and low power efficiency. Here, a novel pixel-level strategy, leveraging the dynamic change of electron concentration as the process of convolution calculation, is proposed for high-performance hardware computer systems. Compared with the crossbar array circuit-based strategy, instead of at least four devices, raised the power efficiency to 413% and decreased the training epochs to 38%. This work presents a novel physics-based approach that enables highly efficient convolutional calculation, improves power efficiency, speeds up convergency, and paves the way for building complex convolution neural networks with large-scale convolutional computation capabilities.
Keyword ：
carrier dynamics carrier dynamics convolution calculation convolution calculation neuromorphic devices neuromorphic devices organic optoelectronic transistor organic optoelectronic transistor trapped effect trapped effect
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| GB/T 7714 | Zhang, Xianghong , Liu, Di , Wu, Jianxin et al. Pixel-Level Hardware Strategy for Large-Scale Convolution Calculation in Neuromorphic Devices [J]. | ADVANCED FUNCTIONAL MATERIALS , 2024 . |
| MLA | Zhang, Xianghong et al. "Pixel-Level Hardware Strategy for Large-Scale Convolution Calculation in Neuromorphic Devices" . | ADVANCED FUNCTIONAL MATERIALS (2024) . |
| APA | Zhang, Xianghong , Liu, Di , Wu, Jianxin , Cheng, Enping , Qin, Congyao , Gao, Changsong et al. Pixel-Level Hardware Strategy for Large-Scale Convolution Calculation in Neuromorphic Devices . | ADVANCED FUNCTIONAL MATERIALS , 2024 . |
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Inspired by human sense organs, AI is advancing toward multimodal perception, with display technology evolving into intelligent human-computer interaction tools. However, hardware networks with multimodal responses connected by different devices bring problems such as delayed information transfer and inefficiency. Thus, an innovative three-mode photosensitive synaptic LED (PSSL) is first proposed by adding a photosensitive layer indacenodithiophene-benzothiadiazole (IDTBT) to the quantum-dot light-emitting diode (QLED), switched by changing the bias voltage. The self-powered PSSL has a photoresponse range from 310 nm to 808 nm (ultraviolet-near-infrared, UV-NIR). The device exhibits a bipolar response under red and UV light at 1 V. When the voltage reaches the turn-on voltage, the PSSL device turns into a neuromorphic LED, exhibiting conductivity enhancement under red-light irradiation and suppression under UV-light irradiation. As a result, the PSSLs are expected to be applied in the field of optical encryption communication and in neuromorphic display.
Keyword ：
bipolar bipolar convolution convolution neuromorphiclight-emitting neuromorphiclight-emitting optical encryption communication optical encryption communication Self-power photodetection Self-power photodetection
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| GB/T 7714 | Zhao, Wenxiao , Lin, Zexi , Zhang, Liyan et al. Bioinspired Three-Mode Photosensitive Synaptic LED for Optical Information Processing [J]. | NANO LETTERS , 2024 , 24 (44) : 14109-14117 . |
| MLA | Zhao, Wenxiao et al. "Bioinspired Three-Mode Photosensitive Synaptic LED for Optical Information Processing" . | NANO LETTERS 24 . 44 (2024) : 14109-14117 . |
| APA | Zhao, Wenxiao , Lin, Zexi , Zhang, Liyan , Lin, Xing , Wang, Jiawei , Xu, Sheng et al. Bioinspired Three-Mode Photosensitive Synaptic LED for Optical Information Processing . | NANO LETTERS , 2024 , 24 (44) , 14109-14117 . |
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Faced with a huge amount of information, the brain relies on attention mechanisms to highly select information for efficient processing. The degree of processing capacity required for information in different scenarios also varies, and the brain relies on attention to significantly enhance or weaken its ability to process information. However, many studies on attention only focus on the behavioral differences between attention and no attention, without further research on the degree of regulation of attention. The application scenarios of artificial vision systems are so complex that we need to regulate the degree of attention to cope with different information processing intensities. In this work, we demonstrated an optoelectronic synaptic transistor based on the mixture of PDVT-10 and MXene-TiO2, and for the first time imitated the mechanism of attention regulation signals at the biological level. Based on the attention mechanism, for slow-moving objects, we enhance the ability of data processing to prevent data loss caused by undersampling, and for fast-moving objects, we weaken the ability of data processing to prevent data redundancy caused by oversampling. In addition, our device array determines the location of moving targets and sends them to the YOLO network for dynamic target detection. Our research results show that the device realizes a hierarchical response to adapt to objects with different motion speeds, which expands the application scenarios of optoelectronic synapses. Faced with a huge amount of information, the brain relies on attention mechanisms to highly select information for efficient processing.
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| GB/T 7714 | Qin, Ningpu , Ren, Zexuan , Fan, Yuyang et al. MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses [J]. | JOURNAL OF MATERIALS CHEMISTRY C , 2024 , 12 (20) : 7197-7205 . |
| MLA | Qin, Ningpu et al. "MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses" . | JOURNAL OF MATERIALS CHEMISTRY C 12 . 20 (2024) : 7197-7205 . |
| APA | Qin, Ningpu , Ren, Zexuan , Fan, Yuyang , Qin, Congyao , Liu, Changfei , Peng, Wenhong et al. MXene-based optoelectronic synaptic transistors utilize attentional mechanisms to achieve hierarchical responses . | JOURNAL OF MATERIALS CHEMISTRY C , 2024 , 12 (20) , 7197-7205 . |
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Efficient in-sensor computing necessitates linear, bidirectional, and centrosymmetric photoresponse weight updates; however, the realization of these attributes poses a persistent challenge, with most photosensor devices achieving linear analog weight updates while falling short of accomplishing bidirectional and centrosymmetric characteristics. Here, the development of a quantum dot (QD)-based bulk heterojunction synaptic transistor (QBST) with multi-factor modulation through surface ligand engineering of blend QDs is reported. By controlling the charge transmission between QDs and the semiconductor, the QBST device enables tunable fading memory, which transforms linear weight updates in short-chain devices into linear, bidirectional, and unprecedented centrosymmetric optical synaptic responses in long-chain devices. Moreover, through the synergy of chemical and electric factors, the convolutional kernel of QBSTs-based convolutional neural network realizes enhanced recognition for complex noisy fashion-costume images, achieving an impressive 90.3% accuracy in the long-chain device, highlighting the efficiency of centrosymmetric weight updates. The results demonstrate that surface ligand engineering offers a promising approach for customizable synaptic modulation, facilitating energy- and time-efficient in-sensor computing. By modulating the ligand chain length of perovskite QDs, bulk heterojunction synaptic transistors can achieve multi-factor optical synaptic modulation, enabling tunable fading memory. Notably, the optical synaptic weight transforms linear weight updates in short-chain devices into linear, bidirectional, and unprecedented centrosymmetric optical synaptic responses in long-chain devices, showcasing their tremendous potential in high-accuracy in-sensor computing applications. image
Keyword ：
bulk heterojunction bulk heterojunction in-sensor computing in-sensor computing multi-factor modulation multi-factor modulation organic synaptic transistor organic synaptic transistor quantum dot ligand engineering quantum dot ligand engineering
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| GB/T 7714 | Li, Enlong , Wang, Xiumei , Yu, Xipeng et al. Multi-Factor Modulated Organic Bulk Heterojunction Synaptic Transistor Enabled by Ligand Engineering for Centrosymmetric In-Sensor Computing [J]. | ADVANCED FUNCTIONAL MATERIALS , 2024 , 34 (26) . |
| MLA | Li, Enlong et al. "Multi-Factor Modulated Organic Bulk Heterojunction Synaptic Transistor Enabled by Ligand Engineering for Centrosymmetric In-Sensor Computing" . | ADVANCED FUNCTIONAL MATERIALS 34 . 26 (2024) . |
| APA | Li, Enlong , Wang, Xiumei , Yu, Xipeng , Yu, Rengjian , Li, Wenwu , Guo, Tailiang et al. Multi-Factor Modulated Organic Bulk Heterojunction Synaptic Transistor Enabled by Ligand Engineering for Centrosymmetric In-Sensor Computing . | ADVANCED FUNCTIONAL MATERIALS , 2024 , 34 (26) . |
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The flexible organic phototransistors (OPTs) are crucial for next-generation wearable systems for applications where large mechanical deformation is involved. However, most of the reported OPTs utilizing the field-effect transistor (FET) architecture suffer from undesired mechanical flexibility and limited performance due to their interfacial charge transport and inherently low transconductance; moreover, their pi-conjugated semiconductor polymers that serve as channels lack specific healing sites, making it difficult to intrinsically heal themselves. Herein, a more flexible and high-performance OPT with enhanced interfacial charge transport via novel volumetric channel and strong healing capability is developed for the first time. This OPT utilizes an organic electrochemical transistor architecture that consists of intrinsically healing conducting polymer/hydrogel composite films with three-dimensional volumetric channels. Such devices not only efficiently restore their mechanical and electrical performance in 100 ms after undergoing severe damage but also exhibit excellent mechanical flexibility without obviously degraded performance. More importantly, the self-healing OPTs exhibit high performance with a responsivity as high as 1.01 x 10(5) A W-1, detectivity of 1.75 x 10(12) Jones, and high external quantum efficiency of 3.03 x 104%, higher than those of the majority of the reported FET-based OPTs. All of these results indicate that these novel and intrinsically self-healing OPTs with volumetric channels are ideal for use in next-generation wearable devices.
Keyword ：
electrochemical transistor electrochemical transistor flexibility flexibility healing healing interface interface phototransistor phototransistor volumetric channel volumetric channel
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| GB/T 7714 | Yan, Yujie , Zhu, Xiaoting , Zhang, Guocheng et al. Intrinsically healing conducting polymer/hydrogel nanocomposite films and their novel volumetric channel for high-performance, flexible, and healable organic phototransistors [J]. | SCIENCE CHINA-MATERIALS , 2024 , 67 (5) : 1491-1499 . |
| MLA | Yan, Yujie et al. "Intrinsically healing conducting polymer/hydrogel nanocomposite films and their novel volumetric channel for high-performance, flexible, and healable organic phototransistors" . | SCIENCE CHINA-MATERIALS 67 . 5 (2024) : 1491-1499 . |
| APA | Yan, Yujie , Zhu, Xiaoting , Zhang, Guocheng , Wang, Xiumei , Han, Xiao , Li, Weizhou et al. Intrinsically healing conducting polymer/hydrogel nanocomposite films and their novel volumetric channel for high-performance, flexible, and healable organic phototransistors . | SCIENCE CHINA-MATERIALS , 2024 , 67 (5) , 1491-1499 . |
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Photoelectric synaptic transistors integrate optical sensing and synaptic functions into a single device, which has significant advantages in neuromorphic computing for visual information, recognition, memory, and processing. However, the weight updating of existing photoelectric synapses is predominantly based on separate utilization of light and electrical stimuli to regulate synaptic excitation and inhibition. This approach significantly restricts the processing speed and application scenarios of devices. In this work, we propose bipolar synaptic organic/inorganic heterojunction transistor (BSOIHT) that can effectively simulate bidirectional (excitatory/inhibitory) synaptic behavior under light stimulation. Furthermore, by changing the position of electrode contacts and the metals of source and drain electrodes, carrier injection of the transistor is significantly improved with reduced synaptic event power consumption down to 2.4 fJ. Moreover, the BSOIHTs are adopted to build the neuromorphic vision system, which effectively facilitates image preprocessing and substantially enhances the recognition accuracy from 44.93% to 87.01%. This paper provides new avenues for the construction of energy-efficient artificial vision systems.
Keyword ：
artificial vision system artificial vision system bipolar heterojunction transistor bipolar heterojunction transistor low energy consumption low energy consumption photoelectric synaptic transistor photoelectric synaptic transistor
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| GB/T 7714 | Liu, Changfei , Gao, Changsong , Huang, Weilong et al. Bipolar synaptic organic/inorganic heterojunction transistor with complementary light modulation and low power consumption for energy-efficient artificial vision systems [J]. | SCIENCE CHINA-MATERIALS , 2024 . |
| MLA | Liu, Changfei et al. "Bipolar synaptic organic/inorganic heterojunction transistor with complementary light modulation and low power consumption for energy-efficient artificial vision systems" . | SCIENCE CHINA-MATERIALS (2024) . |
| APA | Liu, Changfei , Gao, Changsong , Huang, Weilong , Lian, Minrui , Xu, Chenhui , Chen, Huipeng et al. Bipolar synaptic organic/inorganic heterojunction transistor with complementary light modulation and low power consumption for energy-efficient artificial vision systems . | SCIENCE CHINA-MATERIALS , 2024 . |
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