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High-throughput screening of CO_(2) cycloaddition MOF catalyst with an explainable machine learning model

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Green Energy & Environment 2025年第1期10卷 132-138页

作者： Xuefeng Bai Yi li Yabo Xie Qiancheng Chen Xin Zhang Jian-Rong li Beijing Key Laboratory for Green Catalysis and Separation and Department of Chemical Engineering College of Materials Science&EngineeringBeijing University of TechnologyBeijing100124China

The high porosity and tunable chemical functionality of metal-organic frameworks(MOFs)make it a promising catalyst design ***-throughput screening of catalytic performance is feasible since the large MOF structure database is *** this study,we report a machine learning model for high-throughput screening of MOF catalysts for the CO_(2) cycloaddition *** descriptors for model training were judiciously chosen according to the reaction mechanism,which leads to high accuracy up to 97%for the 75%quantile of the training set as the classification *** feature contribution was further evaluated with SHAP and PDP analysis to provide a certain physical understanding.12,415 hypothetical MOF structures and 100 reported MOFs were evaluated under 100℃ and 1 bar within one day using the model,and 239 potentially efficient catalysts were *** them,MOF-76(Y)achieved the top performance experimentally among reported MOFs,in good agreement with the prediction.

关键词： Metal-organic frameworks High-throughput screening Machine learning Explainable model CO_(2)cycloaddition

Leading-edge flow separation control over an airfoil using a symmetrical dielectric barrier discharge plasma actuator

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Chinese Journal of Aeronautics 2019年第5期32卷 1190-1203页

作者： Xin ZHANG Huaxing li Yong HUANG Kun TANG wanbo WANG School of Aeronautics Northwestern Polytechnical University Low Speed Aerodynamics Institute China Aerodynamics Research and Development Center

In order to promote an in-depth understanding of the mechanism of leading-edge flow separation control over an airfoil using a symmetrical Dielectric Barrier Discharge(DBD) plasma actuator excited by a steady-mode excitation, an experimental investigation of an SC(2)-0714 supercritical airfoil with a symmetrical DBD plasma actuator was performed in a closed chamber and a low-speed wind tunnel. The plasma actuator was mounted at the leading edge of the ***-resolved Particle Image Velocimetry(PIV) results of the near-wall region in quiescent air suggested that the symmetrical DBD plasma actuator could induce some coherent structures in the separated shear layer, and these structures were linked to a dominant frequency of f0= 39 Hz when the peak-to-peak voltage of the plasma actuator was 9.8 kV. In addition, an analysis of flow structures without and with plasma actuation around the upper side of the airfoil at an angle of attack of18° for a wind speed of 3 m/s(Reynolds number Re = 20000) indicated that the dynamic process of leading-edge flow separation control over an airfoil could be divided into three stages. Initially, this plasma actuator could reinforce the shedding vortices in the separated shear layer. Then, these vortical structures could deflect the separated flow towards the wall by promoting the mixing between the outside flow with a high kinetic energy and the flow near the surface. After that, the plasma actuator induced a series of rolling vortices in the vicinity of the suction side of the airfoil, and these vortical structures could transfer momentum from the leading edge of the airfoil to the separated region, resulting in a reattachment of the separated flow around the airfoil.

关键词： Airfoil Dielectric Barrier Discharge(DBD) Flow control Particle Image Velocimetry(PIV) Plasma actuator

A Hybrid Approach for Pavement Crack Detection Using Mask R-CNN and Vision Transformer Model

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Computers, Materials & Continua 2025年第1期82卷 561-577页

作者： Shorouq Alshawabkeh li Wu Daojun Dong Yao Cheng liping li Faculty of Engineering China University of GeosciencesWuhan430074China

Detecting pavement cracks is critical for road safety and infrastructure *** methods,relying on manual inspection and basic image processing,are time-consuming and prone to *** deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental *** study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement *** evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and *** findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and F1-Score across both ***,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and *** high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.

关键词： Pavement crack segmentation transportation deep learning vision transformer Mask R-CNN image segmentation

Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

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Nano-Micro Letters 2025年第2期17卷 432-446页

作者： Hao Yin Yanting li Zhiying Tian Qichao li Chenhui Jiang Enfu liang Yiping Guo State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China Beijing Vacuum Electronics Research Institute Beijing 100015People’s Republic of China Fundamental Science On Vibration Shock and Noise LaboratoryState Key Laboratory of Mechanical System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240People’s Republic of China

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing ***,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also ***,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic *** as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse *** ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate ***,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%*** structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

关键词： Flexible piezoelectric filaments Anisotropic Ultra-high sensitivity Structural health detection Texture recognition

Optimization Strategies of Na_(3)V_(2)(PO_(4))_(3) Cathode Materials for Sodium‑Ion Batteries

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Nano-Micro Letters 2025年第2期17卷 204-251页

作者： Jiawen Hu Xinwei li Qianqian liang li Xu Changsheng Ding Yu liu Yanfeng Gao School of Materials Science and Engineering Shanghai UniversityShanghai 200444People’s Republic of China Shanghai Institute of Ceramics Chinese Academy of SciencesShanghai 200050People’s Republic of China

Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural ***,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in ***,it is of significance to boost the sodium storage performance of NVP cathode *** to now,many methods have been developed to optimize the electrochemical performance of NVP cathode *** this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology *** foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so ***,the challenges and prospects of high-performance NVP cathode material are also put *** is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in SIBs.

关键词： Sodium-ion batteries Na_(3)V_(2)(PO_(4))_(3) Cathode materials Electrochemical performance Optimization strategies

Sex-dependent alterations in extracellular vesicles linking chronic spinal cord injury to brain neuroinflammation and neurodegeneration

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Neural Regeneration Research 2025年第2期20卷 483-484页

作者： Yun li Junfang Wu Department of Anesthesiology&Shock Trauma and Anesthesiology Research(STAR)CenterUniversity of Maryland School of MedicineBaltimoreMDUSA

Traumatic spinal cord injury(SCI)is a devastating exogenous injury with long-lasting consequences and a leading cause of death and disability *** in assistive technology,rehabilitative interventions,and the ability to identify and intervene in secondary conditions have significantly increased the long-term survival rate of SCI patients,with some people even living well into their seventh or eighth *** survival changes have led neurotrauma researchers to examine how SCI interacts with brain *** health and epidemiological data showed that patients with long-term SCI can have a lower life expectancy and quality of life,along with a higher risk of comorbidities and complications.

关键词： alterations inflammation injury

Joint Feature Encoding and Task Alignment Mechanism for Emotion-Cause Pair Extraction

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Computers, Materials & Continua 2025年第1期82卷 1069-1086页

作者： Shi li Didi Sun College of Computer and Control Engineering Northeast Forestry UniversityHarbin150040China

With the rapid expansion of social media,analyzing emotions and their causes in texts has gained significant ***-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text,facilitating a deeper understanding of expressed sentiments and their underlying *** comprehension is crucial for making informed strategic decisions in various business and societal ***,recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneouslymodel extracted features and their interactions,or inconsistencies in label prediction between emotion-cause pair extraction and independent assistant tasks like emotion and cause *** address these issues,this study proposes an emotion-cause pair extraction methodology that incorporates joint feature encoding and task alignment *** model consists of two primary components:First,joint feature encoding simultaneously generates features for emotion-cause pairs and clauses,enhancing feature interactions between emotion clauses,cause clauses,and emotion-cause ***,the task alignment technique is applied to reduce the labeling distance between emotion-cause pair extraction and the two assistant tasks,capturing deep semantic information interactions among *** proposed method is evaluated on a Chinese benchmark corpus using 10-fold cross-validation,assessing key performance metrics such as precision,recall,and F1 *** results demonstrate that the model achieves an F1 score of 76.05%,surpassing the state-of-the-art by 1.03%.The proposed model exhibits significant improvements in emotion-cause pair extraction(ECPE)and cause extraction(CE)compared to existing methods,validating its *** research introduces a novel approach based on joint feature encoding and task alignment mechanisms,contributing to advancements in emotion-c

关键词： Emotion-cause pair extraction interactive information enhancement joint feature encoding label consistency task alignment mechanisms

Impact of Bubbles on Mechanical Performances in a Borosilicate Glass

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 25-29页

作者： li Chengxing li Dongfeng MA Shilong QIAO Ang ZHENG Qingshuang China Helicopter Research and Development Institute Jingdezhen 333001China State Key Laboratory of Silicate Materials for Ar-chitectures Wuhan University of TechnologyWuhan 430070China

To analyze the impact of bubbles on the mechanical behavior of glasses,by controlling the refining time,we prepared three borosilicate glasses with the same composition and different *** the analysis software integrated within the optical microscope,the diameter and number of the bubbles on the surface of three borosilicate glasses were *** the hardness and crack initiation resistance(CR),we built the relationship between the porosity and the mechanical performance of these borosilicate glasses.

关键词： bubbles oxide glass hardness creak initiation resistance

Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo li Institute of Biomechanics and Medical Engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation Engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics