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Geotechnical Frontiers 2025: Soil Characterization and Improvement

作者： Rahmani, Fereshteh Espinoza, Wilson F. Material Science Engineering and Commercialization Program Texas State Univ. San MarcosTX United States Material Science Engineering and Commercialization Program Dept. of Engineering Technology Texas State Univ. San MarcosTX United States

ISBN: (数字)9780784486016

Shale, a complex sedimentary rock, exhibits heterogeneous mechanical behavior influenced by its mineral composition and microstructure. Nanoindentation scratch tests offer a promising method to probe the local mechanical properties and understand shale’s response to applied stress at the nanoscale. In this study, shale samples were prepared and subjected to nanoindentation scratch tests, with a systematic approach adopted to analyze critical load, scratch depth, and coefficient of friction (COF) in both parallel and perpendicular orientations to their bedding planes. The results highlight the impact of shale’s anisotropic nature on its mechanical properties. The parallel direction showed 50.18% and 13.37% greater critical loads than the perpendicular direction under scratching forces of 150 and 300 µN. Similarly, a scratch depth analysis reveals a 60.90% reduction of scratch penetration in the parallel direction, attributed to cohesive forces and grain alignment. The coefficient of friction, which fluctuates with lateral displacement, reflects the heterogeneity of shale’s mineral composition and the varying interaction between the indenter and different shale minerals. The obtained average adhesion work in the parallel orientation showed 34.95% more surface energy compared to the perpendicular orientation in the tested shales. These findings demonstrate that microstructural features directly influence fracture propagation and mechanical behavior. The insights gained from this study can be utilized to optimize hydraulic fracturing and drilling operations, and to ensure improved resource extraction efficiency and structural stability. This research evaluates factors that affect the nanostructure and the mechanical properties of shale obtained through indentation techniques. © ASCE.

关键词： Nanoindentation

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Atmospheric clearing of solid-particle debris using femtosecond filaments

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Physical Review Applied 2024年第1期22卷 014075-014075页

作者： Kyle S. Latty Kyle C. Hartig Nuclear Engineering Program Department of Materials Science and Engineering

Through nonlinear self-focusing, femtosecond pulses can propagate several kilometers beyond diffraction limits, forming an ionization channel in air known as a laser filaments. It has been demonstrated that in the wake of the filament, aerosols can be effectively cleared to improve the transmission of subsequent laser pulses or secondary light sources, pertinent to applications in atmospheric sensing. However, the current understanding of aerosol clearing is founded on interactions with droplets to simulate fogs and clouds and thus does not extend to solid particles or atmospheric debris. Using optical trapping, we isolate both graphite and silica microparticles and directly measure the subsequent displacement caused by the filament using time-resolved shadowgraphy. The shock wave from the filament is demonstrated to propel particles away from the filament, directly contributing to atmospheric debris clearing. Particles exposed to the laser light in either the intense filament core or the surrounding energy reservoir are axially displaced along the beam path. It is found that the optomechanical properties of the particle largely influence the axial displacement induced by laser exposure through mechanisms such as radiation pressure, mass ejection from ablation or optical damage, and particle deagglomeration.

关键词： Atmospheric science Light-matter interaction Microparticles Self-focusing Shock waves & discontinuities in plasma Aerosols Femtosecond laser irradiation Optical tweezers

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Compact Model Build Upon Dynamic Weighting Artificial Neural Network Approach for Complementary Field Effect Transistors

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IEEE Transactions on Electron Devices 2024年第1期71卷 246-253页

作者： Butola, Rajat Li, Yiming Kola, Sekhar Reddy National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SPICE simulations for cost-effectiveness. This methodology is developed for gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field effect transistor (CFET), a potential candidate for future CMOS technology due to its innate properties. The critical process variation (PV) sources that severely degrade the CFET performance are estimated using DW-ANN. It reduces the computation cost and predicts the effects of PV sources with less than 1% error. Furthermore, a compact DW-ANN-based Verilog-A model has been developed that captures the dc as well as transient behavior accurately for circuit-level analysis. CFET-based circuits such as inverter, 6T-static random access memory (SRAM), and ring oscillator (RO) are characterized and implemented using DW-ANN-based CM. The overall average error of the model is reported as less than 2%. Therefore, the proposed device and circuit modeling approach provides a feasible solution for the rapid compact modeling of new emerging devices with good convergence and high accuracy. © 1963-2012 IEEE.

关键词： Neural networks

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Collective wetting transitions of submerged gas-entrapping microtextured surfaces

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Droplet 2024年第3期3卷 102-106页

作者： Sankara Arunachalam Himanshu Mishra Environmental Science and Engineering Program Biological and Environmental Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)ThuwalKingdom of Saudi Arabia Water Desalination and Reuse Center King Abdullah University of Science and Technology(KAUST)ThuwalKingdom of Saudi Arabia

Numerous natural and industrial processes entail the spontaneous entrapment of gas/air as rough/patterned surfaces are submerged under *** the wetting transitions ensue,the gas diffuses into the water leading to the fully water-filled ***,the standard models forwetting do not accountfor the microtexture’s topography on collective wetting *** other words,it is not clear whether the lifetime of n cavities arranged in a one-dimensional(I-D)line or a two-dimensional(II-D)(circular or square)lattice would be the same or not as a single 0-D *** response,we tracked the time-dependentfates of gas pockets trapped in I-D and II-D lattices and compared them with wetting transitions in commensurate 0-D ***,the collective wetting transitions in the I-D and the II-D arrays had a directionality such thatthe gas from the outermost cavities was lostthe first,while the innermost gotfilled by water the *** essence,microtexture’s spatial organization afforded shielding to the loss of the gas from the innermost cavities,which we probed as a function of the microtexture’s pitch,surface density,dimensionality,and hydrostatic *** findings advance our knowledge of wetting transitions in microtextures and inspiring surface textures to protect electronic devices against liquid ingression.

关键词： topography transitions submerged

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Verification of Impedance Matching Using Input/Output Current Equalization Control in Wireless Power Transfer Systems with Active Rectifier

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IEEJ Transactions on Industry Applications 2025年第4期145卷 261-271页

作者： Kobayashi, Seiya Maekawa, Sari Electrical Engineering Program Graduate School of Science and Technology Meiji University 1-1-1 Higashimita Tama-ku Kanagawa Kawasaki214-8571 Japan

The efficiency of a wireless power transfer system changes with the load. To solve this problem, an impedance matching method has been developed. Conventional methods control the equivalent load to the optimal value using circuit parameters and the detected load voltage and current. However, they require estimating the mutual inductance M in case of misalignment or an airgap change. M-estimation has some issues such as a limited operating range. In this study, we developed a high-efficiency operation method that can respond to a change in M without its estimation by controlling the currents in the coils to equalize them. We confirmed that the developed method enables highly efficient operation without M-estimation despite misalignment. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Inductive power transmission

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Ethane integration project—a study for Egyptian NGLs plants and their economics

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Journal of engineering and Applied science 2024年第1期71卷 169页

作者： Elzohairy, Hamdy R. Ahmed, Tamer S. El-Marsafy, Sahar M. Chemical Engineering Department Faculty of Engineering Cairo University Giza12613 Egypt New Cairo Egypt Environmental Engineering Program Zewail City of Science and Technology 6th of October City Giza12578 Egypt

For Egypt, ethane is a vital chemical precursor, with the potential to significantly attract financial resources and drive economic growth. Enhancing its added value necessitates efficient recovery of ethane before it enters the national grid without processing. This research investigates the technical and economic feasibility of integrating natural gas liquids (NGLs) from three Egyptian NGLs plants—South Western Desert NGLs (SWD NGLs), North Western Desert NGLs (NWD NGLs), and East Mediterranean NGLs (EMD NGLs)—to improve ethane recovery from natural gas fields. The study focuses on revamping these NGLs plants using various NGLs recovery techniques, conducting a comprehensive comparison to identify the most effective methods for processing rich feed gas. Detailed design of the NGLs recovery processes was developed using HYSYS V.14 simulation software and supplementary calculation sheets. The design criteria encompass both technical and economic parameters to ensure a holistic approach in meeting project requirements. Results indicate a significant increase in ethane recovery: 16% for SWD NGLs, 10% for NWD NGLs (A, B, C), and 85% for EMD NGLs. This improvement will boost ethane feedstock for petrochemical companies from 2000 ton/day to 3500 ton/day, enabling increased polyethylene production. Economic analysis for the base case shows an expected internal rate of return (IRR) of 26%, a net present value (NPV) of USD 73 million, and a payback period of approximately 3 years. Sensitivity analysis on product prices, feed gas prices, and total capital investment confirms the project’s economic viability, with all cases showing feasibility (IRR ≥ 15%) except when product prices fall below USD 225/ton for propane, USD 215/ton for liquefied petroleum gas (LPG), and USD 25/bbl for condensate. This study highlights the potential for enhanced ethane recovery, offering substantial economic benefits and supporting the growth of Egypt’s petrochemical industry. © The Author(s) 202

关键词： Ethane

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Design of an Automatic Price Tag System for Web-Based Retail Business 9

Design of an Automatic Price Tag System for Web-Based Retail...

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9th International Conference on Information Management and Technology, ICIMTech 2024

作者： Liawatimena, Suryadiputra Gunawan, Devina Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Computer Science Deparment BINUS Graduate Program Master of Computer Science Jakarta11480 Indonesia Bina Nusantara University Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Jakarta11480 Indonesia

ISBN: (纸本)9798350390025

Modern retail businesses face a significant challenge with the inefficiency of manually changing price labels on shelves. This manual process not only consumes valuable time and resources but also increases the likelihood of errors, leading to potential inaccuracies in pricing and a less streamlined shopping experience for customers. The proposed solution is the implementation of an Electronic Shelf Label (ESL) system that automatically displays the prices of goods on retail business shelves. This system connects a website (front end and back end) to e-paper via a Wi-Fi network and microcontroller, allowing retail business owners to update prices more easily. Additionally, buyers can search for desired items through the website. The results are the time to send data from the website to the e-paper, namely, to know the performance of the e-paper used. The average time required from 10 attempts to send data from the website to the e-paper is 20.935 seconds. Since the data is connected to the server and will be updated automatically, using this system will be more efficient than manually changing the price label, although it takes time to transfer data from the website to the e-paper. © 2024 IEEE.

关键词： Sales

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Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection

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Neural Computing and Applications 2025年第6期37卷 4567-4583页

作者： Sayem, Faizul Rakib Islam, Md. Sakib Bin Naznine, Mansura Nashbat, Mohammad Hasan-Zia, Mazhar Kunju, Ali K Ansaruddin Khandakar, Amith Ashraf, Azad Majid, Molla Ehsanul Kashem, Saad Bin Abul Chowdhury, Muhammad E. H. Department of Electrical and Electronic Engineering University of Dhaka Dhaka Bangladesh Department of Biomedical Engineering Military Institute of Science and Technology Dhaka Bangladesh Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Chemical Engineering Department University of Doha for Science and Technology Doha Qatar Department of Electrical Engineering Qatar University Doha2713 Qatar Computer Applications Department Academic Bridge Program Qatar Foundation Doha Qatar Department of Computing Science AFG College With the University of Aberdeen Doha Qatar

Given the severity of waste pollution as a major environmental concern, intelligent and sustainable waste management is becoming increasingly crucial in both developed and developing countries. The material composition and volume of urban solid waste are key considerations in processing, managing, and utilizing city waste. Deep learning technologies have emerged as viable solutions to address waste management issues by reducing labor costs and automating complex tasks. However, the limited number of trash image categories and the inadequacy of existing datasets have constrained the proper evaluation of machine learning model performance across a large number of waste classes. In this paper, we present robust waste image classification and object detection studies using deep learning models, utilizing 28 distinct recyclable categories of waste images comprising a total of 10,406 images. For the waste classification task, we proposed a novel dual-stream network that outperformed several state-of-the-art models, achieving an overall classification accuracy of 83.11%. Additionally, we introduced the GELAN-E (generalized efficient layer aggregation network) model for waste object detection tasks, obtaining a mean average precision (mAP50) of 63%, surpassing other state-of-the-art detection models. These advancements demonstrate significant progress in the field of intelligent waste management, paving the way for more efficient and effective solutions. © The Author(s) 2024.

关键词： Deep learning for waste management Intelligent waste management Object detection in waste management Sustainable waste processing Urban solid waste Waste image classification

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A ShuffleNet Architecture-Based Multi-Layer Feature Scaling and Fusion Approach for Underwater Net Cage Damage Detection in Aquaculture

A ShuffleNet Architecture-Based Multi-Layer Feature Scaling ...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Huang, Xiang-Rui Chen, Yi-Cheng Chen, Liang-Bi Hu, Wu-Chih National Penghu University of Science and Technology Master Program in Electrical Engineering and Computer Science Department of Electrical Engineering Penghu Taiwan National Penghu University of Science and Technology Department of Computer Science and Information Engineering Penghu Taiwan

ISBN: (纸本)9798331530839

In offshore aquaculture operations, personnel equipped with diving gear are often necessary to inspect the underwater net cages for damage, particularly on the sea floor. This manual inspection process is time-consuming and complex. To overcome this problem, this paper proposes a computer vision solution for identifying damage in underwater net cages to address the inefficiencies and challenges of traditional manual inspections. The proposed scheme utilizes a high-performance multi-branch computational architecture designed based on ShuffleNet architecture to detect net cage damage more efficiently. Experimental results demonstrate that this work performs well on the ImageNet ILSVRC-2010 dataset and achieves an accuracy of 88.54% in underwater net damage detection. © 2024 IEEE.

关键词： Aquaculture

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Electrocatalysis for sustainable nitrogen management: materials innovation for sensing, removal and upcycling technologies

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science China Chemistry 2025年第6期 2322-2342页

作者： Mei Yi Hongmei Li Minghao Xie Panpan Li Zhaoyu Jin Guihua Yu Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China College of Materials Science and Engineering and College of Chemistry Sichuan University Materials Science and Engineering Program and Walker Department of Mechanical Engineering The University of Texas at Austin

The global nitrogen cycle holds immense importance due to its crucial role in supporting life, supplying vital nutrients for plant growth, preserving environmental balance, and enabling the proper functioning of ecosystems. However, human activities frequently disrupt this cycle, leading to the accumulation of nitrates and nitrites in water bodies. This accumulation causes environmental pollution and health risks. Traditional methods for treating nitrogen pollution, including biological, physical, and chemical approaches, have inherent limitations. In recent years, electrocatalysis has emerged as a promising and sustainable approach for nitrogen management. This technology offers superior efficiency, high selectivity, and environmental *** not only enables accurate detection of nitrogen pollutants in the environment but also facilitates their conversion into harmless nitrogen gas. Moreover, recent advancements have focused on the upcycling of nitrogen pollutants into valuable compounds,such as ammonia and urea. In this comprehensive review, we showcase the applications of electrocatalysis in sustainable nitrogen management. Specifically, we highlight its use in the sensing, removal, and upcycling of major nitrogen pollutants,including nitrate（NO3-）, nitrite（NO2-）, and nitric oxide（NO）. We discuss the use of catalysts, such as Pd alloys, Cu-based, and Fe-based materials, in electrochemical sensing and catalysis. Additionally, we explore recent advancements in the conversion of nitrogen pollutants into valuable compounds like ammonia and urea. The review also addresses current challenges and future opportunities in the field, including innovations in sensor and catalyst design, as well as large-scale treatment strategies. We anticipate that these perspectives will provide profound insights for effective nitrogen pollution control and sustainable utilization of nitrogen resources.

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