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Fabrication of carbon nanotube neuromorphic thin film transistor arrays and their applications for flexible olfactory-visual multisensory synergy recognition

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International Journal of Extreme Manufacturing 2025年第1期7卷 555-565页

作者： Nianzi Sui Kaixiang Kang Min Li Dan Zhang Benxiang Li Shuangshuang Shao Hua Wang Jianwen Zhao School of Nano-Tech and Nano-Bionics University of Science and Technology of ChinaNo.398 Ruoshui RoadSuzhou Industrial ParkSuzhouJiangsu Province 215123People’s Republic of China Key Laboratory of Semiconductor Display Materials and Chips Division of Nanodevices and Related NanomaterialsSuzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesNo.398 Ruoshui RoadSuzhou Industrial ParkSuzhouJiangsu Province 215123People’s Republic of China School of the Environment and Safety Engineering Jiangsu UniversityZhenjiang212013 JiangsuPeople’s Republic of China Key Laboratory of Interface Science and Engineering in Advanced Materials of Ministry of Education Taiyuan University of TechnologyNO.79Yingze West Main StreetTaiyuanShanxi Province 030024People’s Republic of China

Artificial multisensory devices play a key role in human-computer interaction in the field of artificial intelligence(AI).In this work,we have designed and constructed a novel olfactory-visual bimodal neuromorphic carbon nanotube thin film transistor(TFT)arrays for artificial olfactory-visual multisensory synergy recognition with a very low power consumption of 25 aJ for a single pulse,employing semiconducting single-walled carbon nanotubes(sc-SWCNTs)as channel materials and gas sensitive materials,and poly[[4,8-bis[5-(2-ethylhexyl)-2-thienyl]benzo[1,2-b:4,5-b0]dithiophene-2,6-diyl]-2,5-thiophenediyl-[5,7-bis(2-ethylhexyl)-4,8-dioxo-4H,8H-benzo[1,2-c:4,5-c0]dithio-phene-1,3-diyl]](PBDB-T)as the photosensitive *** is noted that it is the first time to realize the simulation of olfactory and visual senses(from 280 nm to 650 nm)with the wide operating temperature range(0-150℃)in a single SWCNT TFT device and successfully simulate the recovery of olfactory senses after COVID-19 by olfactory-visual ***,our SWCNT neuromorphic TFT devices with a high IOn/IOff ratio(up to 10^(6))at a low operating voltage(−2 to 0.5 V)can mimic not only the basic biological synaptic functions of olfaction and vision(such as paired-pulse facilitation,short-term plasticity,and long-term plasticity),but also optical wireless communication by Morse *** proposed multisensory,broadband light-responsive,low-power synaptic devices provide great potential for developing AI robots to face complex external environments.

关键词： carbon nanotube photosensitive polymers neuromorphic transistors olfactory-visual multisensory synergy recognition

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Semi-supervised dual-constraint centroid contrastive prototypical network for flip chip defect detection under limited labeled data

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Engineering Applications of Artificial Intelligence 2025年 156卷

作者： Lou, Yunxia Su, Lei Gu, Jiefei Zhao, Xinwei Li, Ke Pecht, Michael Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology School of Intelligent Manufacturing Jiangnan University Wuxi214122 China Center for Advanced Life Cycle Engineering University of Maryland College ParkMD20742 United States

Flip chips are widely used in electronic systems for defense, aerospace, and other applications where packaging reliability is critical. However, flip chip defect samples present a variety of defect types and few samples with labels in actual industrial applications. The paucity of labeled defect samples indicates that the existing data volume cannot be matched with deep learning detection models. Therefore, flip chip intelligent defect detection faces the problems of poor model adaptability and weak generalization performance. As a solution to these problems, a semi-supervised dual-constraint centroid contrastive prototypical network (SSDCPN) for flip chip defect detection under limited labeled data is proposed in this paper. First, a prototype-based supervised contrastive learning strategy is developed to construct the contrastive prototypical network, which increases the inter-class sparsity and intra-class compactness of features to acquire more discriminative features. Then, to address the susceptibility of the support set prototypes to outliers, dual constraints are imposed on the support set prototypes to calibrate and refine the prototypes. Finally, a pseudo-labeled sample selection mechanism based on epistemic uncertainty and entropy is proposed to obtain rich semi-supervised information to guide the model training. The mechanism can select high-confidence pseudo-labeled samples that can complement the training samples to further strengthen the generalization performance of the model. Defect detection experiments on flip chip vibration signals indicate that the present method is superior to other methods in the case of limited labeled samples. © 2025

关键词： Semi-supervised learning

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Electromagnetic Duality Symmetry-Protected Dirac-Like Cones

arXiv

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arXiv 2025年

作者： Yang, Muxuan Yan, Dongyang Gao, Lei Liu, Wei Lai, Yun Xu, Yadong Hang, Zhi Hong Luo, Jie School of Physical Science and Technology Collaborative Innovation Center of Suzhou Nano Science and Technology Jiangsu Key Laboratory of Frontier Material Physics and Devices Soochow University Suzhou215006 China Key Laboratory of Biophotonics Suzhou215104 China College for Advanced Interdisciplinary Studies National University of Defense Technology Hunan Changsha410073 China National Laboratory of Solid State Microstructures School of Physics Collaborative Innovation Center of Advanced Microstructures Jiangsu Physical Science Research Center Nanjing University Nanjing210093 China

Dirac-like cones, featuring conical linear dispersions intersecting with flat bands, typically arise from accidental degeneracy of multiple modes that requires precise tuning of material and structural parameters, inherently limiting their robustness and applications. In this work, by introducing electromagnetic duality symmetry into photonic crystals, we demonstrate the emergence of intrinsically robust deterministic Dirac-like cones. We show that such symmetry (achieved through either self-dual particles or non-self-dual particle clusters with duality-glide symmetry) enforces double degeneracies for band structures of photonic crystals. Furthermore, by harnessing the joint duality-structural symmetry, multiple deterministic Dirac-like cones exhibiting exceptional resilience to lattice size variations can be obtained. Our introduction of an extra symmetry into photonic crystals establishes a profound connection between duality symmetry and Dirac physics, providing a robust platform for advanced photonic band engineering. Copyright © 2025, The Authors. All rights reserved.

关键词： Photonic crystals

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Stacked NiCoSe clusters decorated cross-shaped star-like MOF-derived NiCo2O4 heterojunction for hybrid supercapacitors

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Journal of Energy Storage 2025年 125卷

作者： Wang, Dan Zhu, Mengkang Wang, Jibiao Chen, Yanli Chen, Yukai Wang, Wenchang Mitsuzaki, Naotoshi Jia, Shuyong Chen, Zhidong Jiangsu Key Laboratory of Advanced Catalytic Materials and Technology Advanced Catalysis and Green Manufacturing Collaborative Innovation Center School of Petrochemical Engineering Changzhou University Jiangsu Changzhou213164 China Electrolytic Copper Foil Engineering Technology Center of Changzhou University Jiangsu Changzhou213164 China Qualtec Co. Ltd Osaka590-0906 Japan Co. Ltd Jiangsu Changzhou213166 China

In view of the inadequate energy density of hybrid supercapacitors, developing high-performance heterojunction electrodes is a promising strategy to solve this problem. However, the precise design and synthesis of heterojunction structure remains a challenge. In this work, a stacked NiCoSe clusters decorated cross-shaped star-like MOF-derived NiCo2O4 heterojunction (MOF-NiCo2O4@NiCoSe) was well-defined designed. The abundant heterogeneous interfaces and unique structure provide a large reactive area and structural stability during charge and discharge, thus facilitating the electrochemical reaction kinetics and boosting the electrochemical properties of electrode. Impressively, the obtained MOF-NiCo2O4@NiCoSe exhibits an excellent specific capacitance of 1266 F g−1 at 1 A g−1, outstanding multiplicative performance (91.6 % at 10 A g−1) and favorable cycling stability. In addition, the assembled device equipped with MOF-NiCo2O4@NiCoSe cathode exhibits uplifting electrochemical features in terms of a maximum energy density of 52.0 Wh kg−1 at a power density of 800.0 W kg−1 along with a high capacitance retention after 10,000 cycles. © 2025 Elsevier Ltd

关键词： Crystallization kinetics

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Bioinspired structural laminates with superior ice-repellence and damage resistance for aviation applications

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Chemical Engineering Journal 2025年 515卷

作者： Shi, Mingdi Pan, You Cao, Haixiao Guo, Yongxin Sun, Xue Fu, Yuan Wu, Yihang Luo, Yufei Lu, Yangyu Wu, Zhenting Jiang, Liang Li, Bo Niu, Shichao Han, Zhiwu School of Automation Wuxi University Jiangsu Wuxi214105 China Jilin University Jilin Changchun130022 China State Key Laboratory of Tribology in Advanced Equipment Tsinghua University Beijing100084 China State Key Laboratory of Lunar and Planetary Sciences Macau University of Science and Technology Macau999078 China

Carbon fiber laminate (CFL) is extensively utilized in airfoil, aero-engine blade, aircraft skin, and other domains due to its superior fatigue and corrosion resistance compared to metallic materials. However, conventional CFL is constrained by inadequate damage resistance and insufficient ice-repellent capabilities. Herein, bionic carbon fiber laminates (BCFLs) are designed and prepared by a combination of thermoforming and micro-nano spraying techniques. The BCFLs consist of a nonlinear helical carbon fiber prepreg (inspired by lobster claws) and a micro-nano coating (inspired by lotus leaves), exhibiting exceptional damage resistance and ice-repellent properties. Specifically, comprehensive mechanical tests are conducted. Notably, the tensile strength of BCFLs reaches 647.2 MPa, an increase of 60.4 % compared to conventional structural laminates (403.5 MPa). The three-dimensional Hashin failure criterion is employed for finite element simulation. The simulation results indicate that the predicted strength values for the three laminate types align with the experimental results within an acceptable error range ( © 2025 Elsevier B.V.

关键词： Corrosion resistant coatings

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Enhancing the mechanical properties of carbonated CS through coupled carbonation-hydration: Synergistic effects of fiber growth and gel filling

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Construction and Building Materials 2025年 482卷

作者： Wei, Chengbo Tan, Ning Pang, Fangjie Zhu, Ruijian Wang, Zengmei State Key Laboratory of Engineering Materials for Major Infrastructure Jiangsu Key Lab. of Construction Materials School of Materials Science and Engineering Southeast University Nanjing211189 China School of Materials Science and Engineering Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology Nanjing Institute of Technology Nanjing211167 China

The carbonation of α-CS (CaSiO₃) rapidly enhances its mechanical properties and sequesters CO₂, making it a promising ultra-low calcium CO₂-sequestering binder (LC-CSB). This study investigates the impact of varying amounts of β-C2S (β-Ca₂SiO₄) and C4A3S̅ (4CaO·3Al₂O₃·SO₃) on the mechanical properties and microstructure of α-CS during CO₂ curing and hydration. Mechanical properties, including compressive and flexural strengths, were measured, and the carbonation products and microstructural changes were analyzed using X-ray diffraction (XRD), thermogravimetric-differential scanning calorimetry (TG-DSC), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and Fourier-transform infrared spectroscopy (FT-IR).The results indicate that after 24 hours of carbonation, α-CS reacted with CO₂ to form calcite, while the addition of β-C2S and C4A3S̅ promoted the formation of aragonite whiskers and AFm (monosulfoaluminate), creating a more complex microstructure. After 28 days of standard hydration, AFm transformed into AFt (ettringite), significantly enhancing both compressive and flexural strengths. Specifically, samples containing 2 % and 5 % C4A3S̅ achieved compressive strengths of 126.17 MPa and 79.35 MPa, and flexural strengths of 9.07 MPa and 12.40 MPa, respectively, representing increases of 47.96 % and 102.25 % compared to the control samples. The improvement in strength is primarily attributed to the synergistic effects of carbonation and hydration. The formation of in-situ grown aragonite whiskers and interwoven AFt fibers during the carbonation-hydration coupling process provided a three-dimensional network structure that enhanced toughness and reduced porosity. Additionally, the hydration products of β-C₂S, particularly C-S-H gel, played a critical role in pore filling, further supporting the long-term development of mechanical properties. © 2025 Elsevier Ltd

关键词： Fourier transform infrared spectroscopy

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Obstacle-Avoidance Motion Planning Method of Manipulator Based on Deep Reinforcement Learning

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Unmanned Systems 2025年

作者： Liu, Yiyang Wu, Defan Fu, Yukai Bai, Hongfei Deng, Chao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210023 China

In recent years, driven by the rapid advancement of industrial automation and intelligent manufacturing, the demand for manipulators to perform tasks in complex environments has significantly increased. Traditional motion planning methods face challenges of computational complexity and lack of adaptability when handling robots with redundant degrees of freedom. To address these issues, this paper proposes a novel obstacle avoidance motion planning method for manipulators based on deep reinforcement learning (DRL), which is especially important when unmanned systems operate in a GPS-free environment. The primary contributions are twofold: (i) we propose an innovative algorithm, termed PPO-HER, which incorporates hindsight experience replay (HER) into proximal policy optimization (PPO) during training, effectively leveraging failed experiences to enhance policy learning efficiency;(ii) an adaptive action exploration strategy is designed to accelerate training convergence and avoid local optima. Experimental results demonstrate that the PPO-HER algorithm and the adaptive action exploration strategy perform exceptionally well across three environments of varying difficulty, significantly improving network training speed and success rates, shortening planned paths, and enhancing autonomous obstacle avoidance capabilities. These findings provide new ideas for target location and tracking of unmanned systems, and lay the foundation for future learning and data-driven approaches in complex environments. © World Scientific Publishing Company.

关键词： Deep reinforcement learning

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EDA: Enhanced Domain-Adversarial Training for Anatomical Landmark Detection

EDA: Enhanced Domain-Adversarial Training for Anatomical Lan...

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IEEE International Symposium on Biomedical Imaging

作者： Fan Yang S. Kevin Zhou School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui China Center for Medical Imaging Robotics Analytic Computing & Learning (MIRACLE) Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou Jiangsu China Key Laboratory of Precision and Intelligent Chemistry USTC Hefei Anhui China Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Manually annotating anatomical landmarks in medical images requires experienced clinicians and is a labor-intensive process. However, recent AI-assisted methods for landmark detection often rely on the training and test data originating from the same domain. This work introduces a novel unsupervised domain adaptation (UDA) framework aimed at anatomical landmark detection from a medical image, designed to bridge the gap between a source domain with labels and an unlabeled target domain. Specifically, we have developed a new Domain-Adversarial Network that incorporates skip connections to transfer and fuse high-resolution feature maps. Additionally, we proposed Dynamic Gaussian Learning, which allows the model to escape from local error regions. We carry out experiments on landmark detection for both head and chest, and the results demonstrate that our method achieves state-of-the-art performances in each experiment.

关键词： Training Measurement Adaptation models Three-dimensional displays Smoothing methods Head Kernel Biomedical imaging

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Charge and spin instabilities in superconducting La3Ni2O7

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Physical Review B 2025年第1期111卷 014515-014515页

作者： Xuejiao Chen Peiheng Jiang Jie Li Zhicheng Zhong Yi Lu National Laboratory of Solid State Microstructures and Department of Physics Nanjing University Nanjing 210093 China Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo 315201 China School of Photoelectric Engineering Changzhou Institute of Technology Changzhou Jiangsu 213002 China School of Physics MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Xi'an Jiaotong University Xi'an 710049 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China

Motivated by the recent discovery of superconductivity in La3Ni2O7 under high pressure, we explore its potential charge and spin instabilities through combined model analysis and first-principles calculations. Taking into account the small charge-transfer nature of high valence nickel, a fully correlated two-cluster model identifies a lattice-coupled charge instability characterized by substantial short-range fluctuations of oxygen holes. This periodicity-two instability is corroborated by density functional theory plus U calculations that also reveal a strong tendency towards concurrent antiferromagnetic ordering. The charge, spin, and associated lattice instabilities are significantly suppressed with increasing external pressure, contributing to the emergence of superconductivity in pressurized La3Ni2O7. Carrier doping and chemical substitution at the La site is found to effectively suppress these instabilities, suggesting a viable strategy to stabilize a superconducting phase under ambient pressure.

关键词： Charge transfer

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Low-Ir-Content Ir0.10Mn0.90O2 Solid Solution for Highly Active Oxygen Evolution in Acid Media

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Small 2025年第21期21卷 e2412096页

作者： Hu, Hongyan Liu, Shilong Sun, Hongfei Sun, Wenli Tang, Jike Wei, Lingzhi Chen, Xiaowei Chen, Qianwang Lin, Yichao Tian, Ziqi Su, Jianwei Anhui University Hefei230601 China Zhejiang Key Laboratory of Advanced Fuel Cells and Electrolyzers Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China School of Material Science and Engineering Key Laboratory for Ecological-Environment Materials of Jiangsu Province Yancheng Institute of Technology Yancheng224051 China Hefei National Laboratory for Physical Science at Microscale Department of Materials Science & Engineering University of Science and Technology of China Hefei230026 China

Iridium (Ir)-based materials are the most widely used oxygen evolution reaction (OER) electrocatalysts in proton exchange membrane water electrolysis (PEMWE). However, their commercial application suffers from high cost and insufficient activity. To optimize the atom utilization efficiency of Ir, the aim is to engineer and develop a rutile-structured solid solution catalyst with minimal Ir content, which is identified through a phase boundary. Here, Ir0.10Mn0.90O2 represents the lowest Ir content in the desired IrO2-MnO2 solid solution. The Ir0.10Mn0.90O2 catalyst exhibits outstanding OER performance in acidic electrolytes, reaching a remarkable mass activity of 1135 A g−1Ir at an overpotential of 300 mV, which is ≈50 times higher than that of a commercial IrO2 catalyst. Additionally, it demonstrates excellent stability at a current density of 200 mA cm−2 over 120 h during PEMWE operations. Density functional theory (DFT) calculations indicate that the hydroxylation process can be efficiently promoted by the electron-withdrawing on Ir sites in Ir0.10Mn0.90O2, contributing to the enhancement of OER activity. © 2025 Wiley-VCH GmbH.

关键词： Hydroxylation

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