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Ammonia pyrolysis oxidation excited by nanosecond pulsed discharge:Global/fluid models hybrid solution

Journal of Energy Chemistry 2025年第1期100卷 385-396页

作者： Mingming Zhang Hanyu Wu Qi Chen Jiaxin Yang Bonan Liu school of Mechanical Electronic and Control Engineering Beijing Jiaotong University China University of Petroleum

The kinetic characteristics of plasma-assisted oxidative pyrolysis of ammonia are studied by using the global/fluid models hybrid solution ***,the stable products of plasma-assisted oxidative pyrolysis of ammonia are *** results show that the consumption of NH3/O2and the production of N2/H2change linearly with the increase of voltage,which indicates the decoupling of nonequilibrium molecular excitation and oxidative pyrolysis of ammonia at low ***,the detailed reaction kinetics mechanism of ammonia oxidative pyrolysis stimulated by a nanosecond pulse voltage at low pressure and room temperature is *** on the reaction path analysis,the simplified mechanism is *** detailed and simplified mechanism simulation results are compared with experimental data to verify the accuracy of the simplified ***,based on the simplified mechanism,the fluid model of ammonia oxidative pyrolysis stimulated by the nanosecond pulse plasma is established to study the pre-sheath/sheath behavior and the resultant consumption and formation of key *** results show that the generation,development,and propagation of the pre-sheath have a great influence on the formation and consumption of *** consumption of NH3by the cathode pre-sheath is greater than that by the anode pre-sheath,but the opposite is true for OH and O（1S）.However,within the sheath,almost all reactions do not ***,by changing the parameters of nanosecond pulse power supply voltage,it is found that the electron number density,electron current density,and applied peak voltages are not the direct reasons for the structural changes of the sheath and ***,the discharge interval has little effect on the sheath structure and gas mixture *** research results of this paper not only help to understand the kinetic promotion of non-equilibrium excitation in the process of oxidative pyrolysis but also help to explore th

关键词： Nanosecond pulsed discharge Ammonia Oxidative pyrolysis Fluid model Global model

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Anomaly monitoring and early warning of electric moped charging device with infrared image

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Optoelectronics Letters 2025年第3期 136-141页

作者： LI Jiamin HAN Bo JIANG Mingshun school of control Science and engineering Shandong University

Potential high-temperature risks exist in heat-prone components of electric moped charging devices, such as sockets,interfaces, and controllers. Traditional detection methods have limitations in terms of real-time performance and monitoring scope. To address this, a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image, then applying an image segmentation algorithm to divide the image.

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Influence of introducing Zr,Ti,Nb and Ce elements on externally solidified crystals and mechanical properties of high-pressure die-casting Al–Si alloy

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 147-153页

作者： Junjie Li Wenbo Yu Zhenyu Sun Weichen Zheng Liangwei Zhang Yanling Xue Wenning Liu Shoumei Xiong Center of Materials Science and engineering School of Mechanical and Electronic Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Traffic&Transportation engineering Central South UniversityChangsha 410075China Shanghai Synchrotron Radiation Facility Shanghai Advanced Research InstituteChinese Academy of SciencesShanghai 201204China school of Materials Science and engineering Tsinghua UniversityBeijing 100084China

High pressure die casting(HPDC)AlSi10Mn Mg alloy castings are widely used in the automobile *** can optimize the mechanical properties of castings through heat treatment,while the release of thermal stress arouses the deformation of large integrated ***,the development of non-heat treatment Al alloys is becoming the hot *** addition,HPDC contains externally solidified crystals(ESCs),which are detrimental to the mechanical properties of *** achieve high strength and toughness of non-heat treatment die-casting Al-Si alloy,we used AlSi9Mn alloy as matrix with the introduction of Zr,Ti,Nb,and *** influences on ESCs and mechanical properties were systematically investigated through three-dimensional reconstruction and thermodynamic *** results reveal that the addition of Ti increased ESCs'size and porosity,while the introduction of Nb refined ESCs and decreased ***,large-sized Al_3(Zr,Ti)phases formed and degraded the mechanical *** introduction of Ce resulted in the poisoning effect and reduced mechanical properties.

关键词： aluminium alloy high-pressure die-casting externally solidified crystals non-heat treatment

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Bandgap characteristics analysis and graded design of a novel metamaterial for flexural wave suppression

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 1-24页

作者： Fan YANG Zhaoyang MA Xingming GUO Shanghai Key Laboratory of Mechanics in Energy engineering Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering ScienceShanghai University Shanghai Institute of Aircraft Mechanics and control

A novel elastic metamaterial is proposed with the aim of achieving lowfrequency broad bandgaps and bandgap regulation. The band structure of the proposed metamaterial is calculated based on the Floquet-Bloch theorem, and the boundary modes of each bandgap are analyzed to understand the effects of each component of the unit cell on the bandgap formation. It is found that the metamaterials with a low elastic modulus of ligaments can generate flexural wave bandgaps below 300 Hz. Multi-frequency vibrations can be suppressed through the selective manipulation of bandgaps. The dual-graded design of metamaterials that can significantly improve the bandgap width is proposed based on parametric studies. A new way that can regulate the bandgap is revealed by studying the graded elastic modulus in the substrate. The results demonstrate that the nonlinear gradient of the elastic modulus in the substrate offers better bandgap performance. Based on these analyses, the proposed elastic metamaterials can pave the way for multi-frequency vibration control, low-frequency bandgap broadening, and bandgap tuning.

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A Novel Self-Supervised Learning Network for Binocular Disparity Estimation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 209-229页

作者： Jiawei Tian Yu Zhou Xiaobing Chen Salman A.AlQahtani Hongrong Chen Bo Yang Siyu Lu Wenfeng Zheng Department of Computer Science and engineering Major in Bio Artificial IntelligenceHanyang UniversityAnsan-si15577Republic of Korea school of Electrical and Computer engineering Louisiana State UniversityBaton RougeLA 70803USA Department of Computer engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11574Saudi Arabia school of Automation University of Electronic Science and Technology of ChinaChengdu610054China

Two-dimensional endoscopic images are susceptible to interferences such as specular reflections and monotonous texture illumination,hindering accurate three-dimensional lesion reconstruction by surgical *** study proposes a novel end-to-end disparity estimation model to address these *** approach combines a Pseudo-Siamese neural network architecture with pyramid dilated convolutions,integrating multi-scale image information to enhance robustness against lighting *** study introduces a Pseudo-Siamese structure-based disparity regression model that simplifies left-right image comparison,improving accuracy and *** model was evaluated using a dataset of stereo endoscopic videos captured by the Da Vinci surgical robot,comprising simulated silicone heart sequences and real heart video *** results demonstrate significant improvement in the network’s resistance to lighting interference without substantially increasing ***,the model exhibited faster convergence during training,contributing to overall performance *** study advances endoscopic image processing accuracy and has potential implications for surgical robot applications in complex environments.

关键词： Parallax estimation parallax regression model self-supervised learning Pseudo-Siamese neural network pyramid dilated convolution binocular disparity estimation

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Identifying the dynamic behaviors in complete reconstruction of Co-based complex precatalysts during electrocatalytic oxygen evolution

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Journal of Energy Chemistry 2025年第1期100卷 226-233页

作者： Jingfang Zhang Danyang Wu Linke Cai Youluan Lu Fanpeng Cheng Lijuan Shi Qun Yi Yao Liu Yi Huang Key Laboratory of Green Chemical engineering Process of Ministry of Education Engineering Research Center of Phosphorus Resources Development and Utilization of Ministry of Education Hubei Key Laboratory of Novel Reactor and Green Chemical Technology School of Chemical Engineering & Pharmacy Wuhan Institute of Technology Key Laboratory of Pesticide & Chemical Biology of Ministry of Education Engineering Research Center of Photoenergy Utilization for Pollution Control and Carbon Reduction of Ministry of Education College of Chemistry Central China Normal University College of Materials Science and engineering Fuzhou University

Transition metal-based nanomaterials have emerged as promising electrocatalysts for oxygen evolution reaction（OER）. Considerable research efforts have shown that self-reconstruction occurs on these nanomaterials under operating conditions of OER process. However, most of them undergo incomplete reconstruction with limited thickness of reconstruction layer, leading to low component utilization and arduous exploration of real catalytic mechanism. Herein, we identify the dynamic behaviors in complete reconstruction of Co-based complexes during OER. The hollow phytic acid（PA） cross-linked CoFe-based complex nanoboxes with porous nanowalls are designed because of their good electrolyte penetration and mass transport ability, in favor of the fast and complete reconstruction. A series of experiment characterizations demonstrate that the reconstruction process includes the fast substitution of PA by OH-to form Co（Fe）(OH)xand subsequent potential-driven oxidation to Co（Fe）OOH. The obtained CoFeOOH delivers a low overpotential of 290 mV at a current density of 10 mA cm-2and a long-term *** experiment results together with theory calculations reveal that the Fe incorporation can result in the electron rearrangement of reconstructed CoFeOOH and optimization of their electronic structure,accounting for the enhanced OER activity. The work provides new insights into complete reconstruction of metal-based complexes during OER and offers guidelines for rational design of high-performance electrocatalysts.

关键词： Complete reconstruction Co-based complex Precatalysts Oxygen evolution reaction

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Buried interface bridging for inverted cesium-formamidinium triiodide perovskite solar cells with long operational stability

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Science China Chemistry 2025年第01期 163-173页

作者： Chenhui Zhang Chunjun Liang Fulin Sun Ting Zhu Xinghai Huang Yuzhu Guo Xinyu Guo Kunyang Ge Dan Li Fangtian You Zhiqun He Key Laboratory of Luminescence and Optical information Ministry of Education Institute of Optoelectronic TechnologyBeijing Jiaotong University Department of Physics School of Physical Science and Engineering Beijing Jiaotong University

In the field of perovskite solar cells(PSCs), the research on defects in the buried interface has been relatively limited due to its non-exposure; however, this interface significantly impacts the performance enhancement of inverted PSCs. This study employs phenylethylammonium chloride(PEACl) molecules as a buffer layer to modify the buried interface of p-i-n structured PSCs,aiming to enhance the uniformity of self-assembled monolayers(SAMs) and facilitate the uniform nucleation and growth of perovskite films on the substrate. Furthermore, the introduction of the PEACl buffer layer effectively passivates defects at the bottom of the perovskite layer and notably enhances the crystal quality of the perovskite film by mitigating residual stress,thereby reducing nonradiative recombination loss. Following these optimizations, the MA-free PSCs treated with PEACl achieve a power conversion efficiency(PCE) of 24.11%, with significant improvements in storage, thermal stability, and operational stability. Particularly noteworthy is the device's performance in an unencapsulated state, whereas after 1,500 hours of continuous light operation stability testing, it retains 97% of its original efficiency. This study not only enriches the systematic understanding of the characteristics of the buried interface in PSCs but also contributes significantly to advancing the commercial production of perovskite photovoltaic technology.

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Near-perfect replication on amorphous alloys through active force modulation based on machine learning/neural network parameter prediction

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 181-191页

作者： Senkuan Meng Zheng Wang Ruisong Zhu Ruijie Liu Jiang Ma Lina Hu Weihua Wang Key Laboratory for Liquid-Solid Structural Evolution and Processing of Materials (Ministry of Education) School of Materials Science and Engineering Shandong University College of Mechatronics and control engineering Shenzhen University Songshan Lake Materials Laboratory Institute of Physics Chinese Academy of Sciences

As a microforming technique, micro/nano-structural replication possesses advantages of high precision and efficiency. With the remarkable superplasticity in the supercooled liquid region, amorphous alloys or metallic glasses(MGs) are regarded as ideal materials for miniature fabrication. However, due to the intrinsic metastable nature of supercooled liquids, the design of imprinting processes for MGs poses a challenge. In the past, process parameters have largely relied on trial-and-error *** this work, a low-frequency active force modulation system is employed to apply a stable, precise, and real-time feedback stress field for imprinting of MG samples. Low-frequency vibrations can facilitate the filling of microstructures on the template surface by reducing the effective viscosity of the supercooled liquid. With the dataset composed of orthogonal experiments, a machine learning strategy based on back-propagation(BP) neural networks was utilized to construct a 3D parameter space for temperature, stress, and time, and to predict the corresponding filling ratio. Furthermore, the optimal combination of imprinting process parameters was identified, and its filling ratio was experimentally validated to reach as high as 0.94. The near-perfect replication of microstructures confirms the superiority of the active force modulation system and the data-driven strategy of machine learning-assisted parameter design. At the same time, this one-step microforming process provides a new approach to addressing the accuracy-cost trade-off dilemma in precision manufacturing.

关键词： metallic glass amorphous alloy microforming imprinting machine learning

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Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho school of Computing Sastra Deemed to be UniversityThanjavur613401India Department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India Department of AI and Software engineering Kangwon National UniversitySamcheok25913Republic of Korea Department of Electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the school of Biomedical engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

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Interpretable Data-Driven Learning With Fast Ultrasonic Detection for Battery Health Estimation

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IEEE/CAA Journal of Automatica Sinica 2025年第1期 267-269页

作者： Kailong Liu Yuhang Liu Qiao Peng Naxin Cui Chenghui Zhang the school of control Science and engineering Shandong University the information Technology Analytics & Operations GroupQueen's University Belfast

Dear Editor,Health management is essential to ensure battery performance and safety, while data-driven learning system is a promising solution to enable efficient state of health(SoH) estimation of lithium-ion(Liion) batteries. However, the time-consuming signal data acquisition and the lack of interpretability of model still hinder its efficient deployment. Motivated by this, this letter proposes a novel and interpretable data-driven learning strategy through combining the benefits of explainable AI and non-destructive ultrasonic detection for battery SoH estimation. Specifically, after equipping battery with advanced ultrasonic sensor to promise fast real-time ultrasonic signal measurement, an interpretable data-driven learning strategy named generalized additive neural decision ensemble(GANDE) is designed to rapidly estimate battery SoH and explain the effects of the involved ultrasonic features of interest.

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