Article
Nanoscience & Nanotechnology
Carola Ebenhoch, Lukas Schmidt-Mende
Summary: Memristors have the potential to mimic human memory functionalities and emulate synaptic behaviors, with high endurance and decay lifetimes. The lifetime of signals shows a strong dependency on the frequency and amplitude of stimulation pulses.
ADVANCED ELECTRONIC MATERIALS
(2021)
Article
Nanoscience & Nanotechnology
Renu Kumari, Jnaneswari Gellanki, Somnath S. Kundale, Ruhan E. Ustad, Tukaram D. Dongale, Ying Fu, Hakan Pettersson, Sandeep Kumar
Summary: Computational efficiency is improved using artificial neural network-based computing. This study focuses on the fabrication of a memristive device with a resistive switching layer that can mimic the behavior of a biological synapse. The incorporation of ZnO nanoparticles into the polymer film allows the fabricated memristive devices to exhibit functionalities closely resembling those of biological synapses.
Review
Nanoscience & Nanotechnology
Ki Chang Kwon, Ji Hyun Baek, Kootak Hong, Soo Young Kim, Ho Won Jang
Summary: This article provides a thorough examination of high-performance memristors based on 2D TMCs, including the properties of materials and devices, as well as the challenges and future prospects.
NANO-MICRO LETTERS
(2022)
Article
Chemistry, Physical
Kaihui Chen, Zhen Fan, Jingjing Rao, Wenjie Li, Deming Wang, Changjian Li, Gaokuo Zhong, Ruiqiang Tao, Guo Tian, Minghui Qin, Min Zeng, Xubing Lu, Guofu Zhou, Xingsen Gao, Jun-Ming Liu
Summary: This study demonstrates the feasibility of constructing neuronal and synaptic devices based on SrFeOx material system, achieving nonvolatile and volatile resistive switching behavior by controlling the phase transition between different phases of SrFeOx. Fully memristive SNNs are constructed using SFO-based synapses and neurons and show good performance in unsupervised image recognition.
JOURNAL OF MATERIOMICS
(2022)
Review
Chemistry, Multidisciplinary
Hongyu Bian, Yi Yiing Goh, Yuxia Liu, Haifeng Ling, Linghai Xie, Xiaogang Liu
Summary: The performance of neural synapse networks depends on the characteristics of synaptic learning, requiring the design of reliable multi-functional neural synaptic devices to achieve intelligent functions.
ADVANCED MATERIALS
(2021)
Article
Nanoscience & Nanotechnology
Zhe Wang, He-Ming Huang, Xin Guo
Summary: A Pt/α-MoO3/SrCoO2.5/Nb-SrTiO3 memristive device is developed based on proton migration in the alpha-MoO3/SrCoO2.5 stack, showing multiple resistance states and excellent nonvolatility.
ADVANCED ELECTRONIC MATERIALS
(2021)
Review
Chemistry, Multidisciplinary
Wenxiao Wang, Song Gao, Yaqi Wang, Yang Li, Wenjing Yue, Hongsen Niu, Feifei Yin, Yunjian Guo, Guozhen Shen
Summary: Emerging photonic memristive and memristive-like devices possess high efficiency, low consumption, and versatility, making them highly attractive for constructing novel neuromorphic computing and miniaturized bionic electronic systems. However, due to the ambiguity of the mechanism and the reliability of the material, the development and commercialization of these devices are still limited. Therefore, a detailed and systematic review is needed to promote their further development, understanding the resistive switching mechanisms, evaluating the active materials, and summarizing recent applications.
Article
Physics, Applied
Jianxing Zhang, Hangfei Li, Tao Liu, Shijie Dong, Sheng Xu, Hailian Li, Jie Su
Summary: This study has successfully prepared a (La-0.67, Sr-0.33)MnO3/BaTiO3-based memristor with good forward and reverse memristor function and multilevel resistive tunability. By varying the amplitude and pulse width of the applied voltage, different synaptic simulations were achieved and a high classification accuracy for handwritten digit data was achieved through an artificial neural network. These results provide important reference value for neural devices.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Materials Science, Multidisciplinary
Tong Wang, He-Ming Huang, Xiao-Xue Wang, Xin Guo
Summary: An artificial olfactory inference system based on memristive devices has been developed to classify four gases with 10 different concentrations, achieving a high accuracy of 95%. Three strategies are applied to reduce the extracted features from the reservoir computing system in order to reduce device number and power consumption.
Article
Chemistry, Multidisciplinary
Suk Yeop Chun, Young Geun Song, Ji Eun Kim, Jae Uk Kwon, Keunho Soh, Ju Young Kwon, Chong-Yun Kang, Jung Ho Yoon
Summary: Technologies combining gas sensors and neuromorphic computing have great potential, but conventional gas sensors lack necessary functions for neuromorphic olfactory systems. This study proposes a chemi-memristive gas sensor based on oxygen vacancy dynamics, which enhances redox reactions and induces rapid current changes. The sensor achieves fast responses, short recovery times, and hysteresis. The sensor's advantageous functionality allows for the experimental demonstration of device-level olfactory systems and the conversion of gas stimuli into synaptic weights.
ADVANCED MATERIALS
(2023)
Article
Mathematics, Interdisciplinary Applications
I. A. Surazhevsky, V. A. Demin, A. I. Ilyasov, A. Emelyanov, K. E. Nikiruy, V. V. Rylkov, S. A. Shchanikov, I. A. Bordanov, S. A. Gerasimova, D. Guseinov, N. Malekhonova, D. A. Pavlov, A. Belov, A. N. Mikhaylov, V. B. Kazantsev, D. Valenti, B. Spagnolo, M. Kovalchuk
Summary: The study explores the constructive role of external noise signals in maintaining or even recovering memory traces without direct renewal in a spiking neural network. By fine-tuning the conductance values of memristors, unreliable weights can be generated due to limited retention time of resistive state or variation of switching voltages. The noise-assisted persistence of memory in unreliable neural networks brings potential for building reliable systems closer to reality.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Materials Science, Multidisciplinary
Zhen Li, Bin Zhang, Yu Chen
Summary: Emulating synaptic bionics and plasticity is a crucial step in achieving efficient brain-like artificial neural networks. This study presents a novel approach by introducing a metalloporphyrin into the main chain of a polymer to synthesize a polyfluorene-based conjugated polyelectrolyte. The memristive devices based on this organic polymer material successfully simulated synaptic biomimetic and synaptic plasticity, providing new insights into the design of neurosynaptic biomimetic devices.
ORGANIC ELECTRONICS
(2022)
Review
Automation & Control Systems
Ben Walters, Mohan V. Jacob, Amirali Amirsoleimani, Mostafa Rahimi Azghadi
Summary: As data processing volume increases, the limitations of traditional computers and the need for more efficient computing methods become evident. Neuromorphic computing mimics the brain's low-power and high-speed computations, making it crucial in the era of big data and artificial intelligence. One significant development in this field is the memristor, a device that exhibits neuromorphic tendencies.
ADVANCED INTELLIGENT SYSTEMS
(2023)
Review
Chemistry, Multidisciplinary
Geonyeop Lee, Ji-Hwan Baek, Fan Ren, Stephen J. Pearton, Gwan-Hyoung Lee, Jihyun Kim
Summary: Neuromorphic systems, which mimic neural functionalities of a human brain using artificial synapses and neurons, have advantages of high energy efficiency and fast computing speed. 2D materials, with unique surface properties and excellent crystallinity, have emerged as promising candidates for neuromorphic computing hardware due to uncontrollable defects in bulk material-based devices.
Article
Physics, Applied
Yi Huang, Fatemeh Kiani, Fan Ye, Qiangfei Xia
Summary: Progress in AI hardware and algorithms has led to the development of large machine learning models and various applications in our daily lives. However, current AI, mainly artificial neural networks, still falls short of human brains due to high energy consumption and the inability to generalize knowledge and adapt to changes. Neuromorphic systems built with emerging devices like memristors offer a promising solution to these challenges. This Perspective provides an overview of the progress and challenges in transitioning from memristor devices to neuromorphic systems, and suggests potential directions for implementation based on memristive devices.
APPLIED PHYSICS LETTERS
(2023)
Article
Chemistry, Physical
Xin Guo, Hao Zhang, Yiyuan Yao, Chengming Xiao, Xin Yan, Ke Chen, Junwen Qi, Yujun Zhou, Zhigao Zhu, Xiuyun Sun, Jiansheng Li
Summary: Integrating the merits of the substrate and active sites with the water matrix is crucial for designing novel catalysts for advanced oxidation processes. A sandwich-like hetero-structure catalyst showed excellent decontamination performance under high salinity conditions, degrading bisphenol A with nearly 100% efficiency within 10 minutes and high turnover frequency.
APPLIED CATALYSIS B-ENVIRONMENTAL
(2023)
Article
Engineering, Chemical
Ke Chen, Linhan Ni, Hao Zhang, Li Li, Xin Guo, Junwen Qi, Yujun Zhou, Zhigao Zhu, Xiuyun Sun, Jiansheng Li
Summary: In this study, core-shell ZIF-8@RF nanofillers were incorporated into 6FDA-Durene and Pebax 1657 via a physical blending approach to form MMMs, which showed outstanding performance for CO2/CH4 separation due to enhanced interfacial compatibility, CO2 affinity, and the intrinsic characteristics of porous ZIF-8. The CO2 permeability and CO2/CH4 selectivity of the MMMs increased significantly compared to the pristine membrane, and the presence of RF layer in ZIF-8@RF MMMs further improved the CO2/CH4 selectivity. Importantly, both MMMs maintained their excellent separation performance even in the presence of moisture.
JOURNAL OF MEMBRANE SCIENCE
(2023)
Review
Materials Science, Multidisciplinary
Zhi-Yong Li, Zhuo Li, Jia-Long Fu, Xin Guo
Summary: This review provides an overview of recent advances in polymer electrolytes for solid-state sodium batteries. Polymer electrolytes may be a solution to the safety and stability issues in sodium-ion batteries due to their better safety properties. The review discusses the fundamental properties, ionic conduction mechanisms, and promising applications of polymer electrolytes, as well as emphasizes the pending challenges and effective solutions. It is hoped that this review will promote the commercial applications of polymer electrolytes in energy storage systems.
Article
Chemistry, Multidisciplinary
Xiaoyan Zhou, Zhuo Li, Wanming Li, Xiaogang Li, Jialong Fu, Lu Wei, Hui Yang, Xin Guo
Summary: A cross-linking quasi-solid electrolyte is developed to suppress sodium dendrite growth in sodium metal batteries, resulting in improved cycling stability and discharge capacity.
ADVANCED FUNCTIONAL MATERIALS
(2023)
Article
Multidisciplinary Sciences
Zhuo Li, Rui Yu, Suting Weng, Qinghua Zhang, Xuefeng Wang, Xin Guo
Summary: This article reports a quasi-solid-state polymer electrolyte that can improve interfacial charge transfer and enable stable lithium metal cell operation even at -30 degrees C. The electrolyte exhibits an ionic conductivity of 2.2 x 10(-4) S cm(-1) at -20 degrees C and inhibits the growth of dendrites on the lithium metal electrode, leading to a dual-layered solid electrolyte interphase formation.
NATURE COMMUNICATIONS
(2023)
Review
Chemistry, Multidisciplinary
Zhuo Li, Jialong Fu, Xiaoyan Zhou, Siwei Gui, Lu Wei, Hui Yang, Hong Li, Xin Guo
Summary: Polymer-based solid electrolytes have shown great promise for next-generation batteries due to their good safety, high interfacial compatibility, low cost, and facile processability. However, a mechanistic understanding of the ionic conduction is still lacking, hindering the design and optimization of polymer-based solid electrolytes. This comprehensive review summarizes and evaluates the ionic conduction mechanisms and optimization strategies of various polymer-based solid electrolytes, highlighting challenges and strategies for enhancing the ionic conductivity.
Article
Chemistry, Multidisciplinary
Jialong Fu, Zhuo Li, Xiaoyan Zhou, Zhiyong Li, Xin Guo
Summary: A fluorinated quasi-solid polymer electrolyte is synthesized to stabilize Li metal, effectively suppressing Li dendrites and Li pulverization. The lithium metal battery with the fluorinated quasi-solid polymer electrolyte exhibits stable cycling performance owing to the enriched C-F/LiF solid electrolyte interphase and lithophilic C-F-guided ion plating/stripping and rapid Li+ transportation.
Article
Materials Science, Multidisciplinary
Zhao Li, Cheng-Jia Xie, Xiao-Wei Ren, Qun Zhang, Bao-Jin Ma
Summary: Nanoenzyme-mediated antibacterial strategies are widely used to overcome the limitations of antibiotic therapy. Chitosan-oligosaccharide-modified CuS nanoparticles (PCuS NPs) with positive charges were prepared and exhibited efficient peroxidase-like activity. The PCuS NPs can interact with bacteria through electrostatic attraction, enabling the generation of hydroxyl radicals on the bacterial surface and effectively treating bacterial infections.
Article
Chemistry, Physical
Hang Lu, Sheng Zheng, Lu Wei, Xiaodong Zhang, Xin Guo
Summary: Compared with aqueous single-ion batteries, rechargeable aqueous hybrid ion batteries, especially Li+/Zn(2+) hybrid ion batteries, are gaining attention due to their low cost, high operating voltage, and energy density. However, the decomposition of water and the growth of Zn dendrites limit their working voltage and lifespan. By adding poly(propylene glycol) (PPG) in the electrolyte, detrimental side reactions induced by water reduction and Zn dendrite growth can be successfully suppressed, leading to a highly reversible aqueous hybrid ion battery with high specific capacities and long cycle life.
Article
Computer Science, Information Systems
Jingyang Chen, Zhihao Wang, Tong Wang, Heming Huang, Zheyuan Shao, Zhe Wang, Xin Guo
Summary: This work constructs fully-connected spiking neural networks (SNNs) based on various memristive devices and applies a hardware-compatible spike-timing-dependent plasticity (STDP) learning rule to train the network. Strategies are designed to address overfitting and improve performance when training set is small. The effects of imperfect properties of memristive devices on SNN performance, such as asymmetric weight update, insufficient number of conductance states, and low on/off ratio, are elaborated.
SCIENCE CHINA-INFORMATION SCIENCES
(2023)
Article
Chemistry, Analytical
Renjun Si, Yan Li, Jie Tian, Changshu Tan, Shaofeng Chen, Ming Lei, Xin Guo, Shunping Zhang
Summary: Temperature modulation technology is widely used in metal oxide semiconductor (MOS) gas sensors for enhanced selectivity and sensitivity. However, the high surface activity of MOS sensors can lead to hydroxide formation when exposed to water, negatively affecting their stability. This study found that SnO2 gas sensors demonstrated good stability, while In2O3 gas sensors exhibited poor stability due to the formation of In(OH)3. These findings suggest that temperature modulation can induce the generation of hydroxides, affecting the stability of gas sensitive materials.
SENSORS AND ACTUATORS B-CHEMICAL
(2023)
Review
Multidisciplinary Sciences
Xingzi Xiahou, Sijia Wu, Xin Guo, Huajian Li, Chen Chen, Ming Xu
Summary: This review provides an in-depth analysis of the research progress in low-frequency energy harvesting technologies and explores the factors affecting the performance of mechanical energy harvesters and improvement strategies.
Article
Engineering, Electrical & Electronic
Juan Wen, Zhen-Ye Zhu, Xin Guo
Summary: The human visual system encodes optical information into neural spikes and processes them efficiently. Inspired by this, an artificial neuron using a resistor and a threshold switching memristor can achieve rate coding. An artificial visual neuron is proposed by replacing the resistor with a photo-resistor, enabling depth perception for precise recognition and learning.
NEUROMORPHIC COMPUTING AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Cheng Li, Xiang Zheng, Zhenyu Sun, Luqiang Zhou, Xin Guo, Xin Huang, Bo Yang
Summary: By equipping MEMS accelerometers with a digital closed-loop detection system and electromagnetic force feedback, we have improved the dynamic range and linearity of interferometric accelerometers and successfully detected 0.2 Hz terrestrial microseism.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Chemistry, Physical
Juan Zeng, Hao Chen, Liubing Dong, Lu Wei, Xin Guo
Summary: In this study, a new type of anti-freezing hydrogel electrolyte was proposed by adding zwitterionic proline, which enables high ionic conductivity in hydrogel electrolytes at subzero temperatures. The unique structure of the proline electrolytes leads to strong hydration, ionic interactions, and low self-associations, resulting in excellent performance at low temperatures. The proline hydrogel electrolytes show high ionic conductivity and good low-temperature adaptability, making them suitable for anti-freezing energy storage devices.
JOURNAL OF COLLOID AND INTERFACE SCIENCE
(2023)