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| 1 | 2D Material Chemistry:Graphdiyne-based Biochemical Sensing显示文摘The modern internet-of-things era has witnessed an increasing growth in the demand for advanced sensors to collect precise information.To meet this demand,extensive efforts have been devoted to exploring competent ma terials and designing rational architectures for the fabrication of sensing devices.Graphdiyne represents a promising material due to the attractive electronic.optical and electrochemical properties deriving from its unique molecular structure.In this review,we firstly provide the points of view on the architectures and work principles of the graph divnebased sensing devices with respect to resistive,electrochemical,photoelectrochemical and fluorescent catego ries.Secondly,we present the promising applications on biochemical sensing,such as the detection of DNA,micro-RNA,and glucose.Finally,the challenges and prospects of graphdivne-based biochemical sensing platforms are also discussed,in order to provide a cornerstone for understanding this rapidly developing area. | LI Jiaofu WAN Changjin WANG Cong ZHANG Han CHEN Xiaodong | 2020 | Chemical Research in Chinese Universities2020，36，4： | 2 |
| 2 | A Smarter Pavlovian Dog with Optically Modulated Associative Learning in an Organic Ferroelectric Neuromem显示文摘Associative learning is a critical learning principle uniting discrete ideas and percepts to improve individuals’adaptability.However,enabling high tunability of the association processes as in biological counterparts and thus integration of multiple signals from the environment,ideally in a single device,is challenging.Here,we fabricate an organic ferroelectric neuromem capable of monadically implementing optically modulated associative learning.This approach couples the photogating effect at the interface with ferroelectric polarization switching,enabling highly tunable optical modulation of charge carriers.Our device acts as a smarter Pavlovian dog exhibiting adjustable associative learning with the training cycles tuned from thirteen to two.In particular,we obtain a large output difference(>10^(3)),which is very similar to the all-or-nothing biological sensory/motor neuron spiking with decrementless conduction.As proof-of-concept demonstrations,photoferroelectric coupling-based applications in cryptography and logic gates are achieved in a single device,indicating compatibility with biological and digital data processing. | Mengjiao Pei Changjin Wan Qiong Chang Jianhang Guo Sai Jiang Bowen Zhang Xinran Wang Yi Shi Yun Li | 2022 | Research2022，，1： | 0 |
| 3 | CMOS-compatible neuromorphic devices for neuromorphic perception and computing: a review显示文摘Neuromorphic computing is a brain-inspired computing paradigm that aims to construct efficient,low-power,and adaptive computing systems by emulating the information processing mechanisms of biological neural systems.At the core of neuromorphic computing are neuromorphic devices that mimic the functions and dynamics of neurons and synapses,enabling the hardware implementation of artificial neural networks.Various types of neuromorphic devices have been proposed based on different physical mechanisms such as resistive switching devices and electric-double-layer transistors.These devices have demonstrated a range of neuromorphic functions such as multistate storage,spike-timing-dependent plasticity,dynamic filtering,etc.To achieve high performance neuromorphic computing systems,it is essential to fabricate neuromorphic devices compatible with the complementary metal oxide semiconductor(CMOS)manufacturing process.This improves the device’s reliability and stability and is favorable for achieving neuromorphic chips with higher integration density and low power consumption.This review summarizes CMOS-compatible neuromorphic devices and discusses their emulation of synaptic and neuronal functions as well as their applications in neuromorphic perception and computing.We highlight challenges and opportunities for further development of CMOS-compatible neuromorphic devices and systems. | Yixin Zhu Huiwu Mao Ying Zhu Xiangjing Wang Chuanyu Fu Shuo Ke Changjin Wan Qing Wan | 2023 | International Journal of Extreme Manufacturing2023，5，4： | 0 |
| 4 | IGZO-based neuromorphic transistors with temperature-dependent synaptic plasticity and spiking logics显示文摘Temperature is one of the vital influential factors for all physiological and mental activities.Studying the influence of temperature on the properties of synaptic devices is of great importance for neuromorphic computing and bionic perception.Here,indium-gallium-zinc-oxide(IGZO)based electrical-doublelayer neuromorphic transistors were proposed for the emulation of temperature-dependent synaptic functions.The influence of temperature on the synaptic plasticity,including excitatory postsynaptic current,pairedpulse facilitation,and dynamic filtering was investigated.Interestingly,temperature induced spiking AND to OR logic switching was demonstrated in an IGZO-based neuromorphic transistor with two in-plane gate electrodes.Our results provided an insight into the temperature-induced synaptic functions and spiking logic switching,which is interesting for neuromorphic systems with biological fidelity. | Ying ZHU Yongli HE Chunsheng CHEN Li ZHU Changjin WAN Qing WAN | 2022 | Science China(Information Sciences)2022，65，6： | 0 |
| 5 | A Smarter Pavlovian Dog with Optically Modulated Associative Learning in an Organic Ferroelectric Neuromem显示文摘Associative learning is a critical learning principle uniting discrete ideas and percepts to improve individuals’adaptability.However,enabling high tunability of the association processes as in biological counterparts and thus integration of multiple signals from the environment,ideally in a single device,is challenging.Here,we fabricate an organic ferroelectric neuromem capable of monadically implementing optically modulated associative learning.This approach couples the photogating effect at the interface with ferroelectric polarization switching,enabling highly tunable optical modulation of charge carriers.Our device acts as a smarter Pavlovian dog exhibiting adjustable associative learning with the training cycles tuned from thirteen to two.In particular,we obtain a large output difference(>10^(3)),which is very similar to the all-or-nothing biological sensory/motor neuron spiking with decrementless conduction.As proof-of-concept demonstrations,photoferroelectric coupling-based applications in cryptography and logic gates are achieved in a single device,indicating compatibility with biological and digital data processing. | Mengjiao Pei Changjin Wan Qiong Chang Jianhang Guo Sai Jiang Bowen Zhang Xinran Wang Yi Shi Yun Li | 2021 | Research2021，，1： | 0 |
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