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Chemically activating biomass into hierarchically porous carbon as an efficient sulfur host for high-performance room temperature Na-S batteries

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Chemical engineering Journal 2025年 510卷

作者： Liu, Jiawang Zhang, Heng Xie, Baojian Cheng, Junquan Song, Tao Bai, Youcun Ma, Ruguang Li, Chang Ming School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China School of Materials Science and Engineering Suzhou University of Science and Technology Suzhou215009 China School of New Energy Materials and Chemistry Leshan Normal University Sichuan Leshan614000 China

Biomass-derived cellulosic carbon materials as loaded sulfur hosts applied to room temperature sodium-sulfur batteries (RT Na-S) have received much attention as attractive alternatives for large-scale energy storage due to their low cost, high regenerative properties and abundant resource reserves. However, labile sodium polysulfides (Na2Sn, 4 ≤ n ≤ 8) and poor reaction kinetics cause difficulties in its practical application. To address these issues, we report hierarchical fibre porous carbon (HFPC), where the multilayered porous network structure of carbon reduces the detrimental effects of volume expansion, and the high specific surface area (2685 m2 g−1) with microporous synergistic adsorption inhibits the shuttling of sodium polysulfides (NaPSs) and stabilizes the electrode structure during the cycling process. The experimental and theoretical results demonstrated that the pore sizes with different size distributions had extremely strong adsorption of NaPSs and fast reaction kinetics toward sulfur reduction. The Na-S batteries tested at room temperature with 55 wt% sulfur content in the cathode maintained a reversible capacity of 330 mAh g−1 at a high current density of 16.75 A g−1, and a reversible capacity of 1042 mAh g−1 at 167.5 mA g−1, at a current density of 3.35 A g−1, the cycling capacity decay rate was only 0.01372% over 5000 cycles. This research holds broad implications for the synthesis of highly porous and electrically conductive carbon materials derived from biomass, encompassing agricultural residues and other biological waste, for diverse applications in energy storage and conversion systems. © 2025 Elsevier B.V.

关键词： Sodium-ion batteries

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Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification

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Results in engineering 2025年 26卷

作者： Subburaj, Brindha M, Rohan Ananthanarayanan, Samhruth Won, Daehan School of Computer Science and Engineering Vellore Institute of Technology Chennai India United States

Continuous and ever-growing threats in the form of bacteria and leaf diseases cause large yearly agricultural losses, rendering crops inedible and seeds infertile. Being a staple contributor to the Indian economy, these losses can cause large problems in other sectors as well. Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. Although these models need large amounts of data to operate, their accuracy and precision far beat traditional machine learning methods. Still, most of these existing models tend to operate on datasets of particular crops. This paper proposes a lightweight model named Plantention, built on the MobileNetV2 encoder with a softmax classifier as a general-purpose classifier for five major crops grown in India, namely Rice, Wheat, Tea, Banana, and Sugarcane. Plantention uses a dual split attention network with residual classifiers to improve the classification of the individual leaf diseases using. Compared to CBAM and soft attention networks that simply accentuate the disease features on the leaf, the dual split attention mechanism utilizes both the leaf features and the leaf disease features by combining them to classify the leaf disease. The experimentation has been performed on five different publicly available datasets. The model performance was assessed using comprehensive performance metrics, and the model achieved an accuracy of 98.34 %, precision of 98.74 %, recall of 99.19 %, and F1 Score of 99.02 %. In addition, the model has around 7.3 million parameters, making it incredibly lightweight and very ready for deployment in low-computing technology. © 2025 The Author(s)

关键词： Deep learning

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Torque Ripple Mitigation Strategy for Bearingless Flux-Reversal Slice Motors Considering Rotor Eccentricity

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IEEE Transactions on Transportation Electrification 2025年

作者： Liu, Jiayun Qu, Ronghai Liu, Zirui Kong, Wubin Li, Dawei Huazhong University of Science and Technology School of Electrical and Electronic Engineering Wuhan430074 China

Bearingless flux-reversal slice motor (BFRSM) is a compact and innovative motor known for its robust rotor design and simplified manufacturing processes. However, inherent design features like the double-salient air-gap and consequent-pole stator teeth cause increased torque ripple, leading to fluctuations in speed and rotor suspension, which ultimately compromise overall performance. Existing literature has not given a comprehensive research on torque ripple mitigation strategy for flux-reversal motors under conditions of rotor eccentricity and suspension currents. To address this issue, this paper presents a torque ripple mitigation strategy based on a comprehensive torque ripple model specific to the BFRSM. As the foundation for the torque model, this paper derives the electromotive force (EMF) model of BFRSM by analyzing the magnetic field of the air-gap, with a double-pole structure under eccentric conditions. Then the torque ripple model corresponding to each order harmonics and reflecting the impact of rotor eccentricity, is derived. Building on this model, the proposed strategy designs compensation harmonic currents with minimal copper loss to reduce torque ripple and enhance the performance of BFRSM. Furthermore, to enhance harmonic current control performance and improve system stability, the impulse invariant method is applied in the digital implementation. Experimental validation on a BFRSM prototype demonstrates the effectiveness of the strategy in mitigating torque ripple under both steady-state and transient operational conditions. The results indicate a 38% reduction in torque ripple under both normal and eccentric conditions. © 2025 IEEE. All rights reserved.

关键词： Suspensions (components)

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Effects of Mn addition on the static and dynamic mechanical performance and fracture behavior of Al–8Si–xMn alloy sheets

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Journal of Materials Research and technology 2025年 36卷 3451-3464页

作者： Guangdong Wang Tian Hua Yinghao Liu Shuying Chen Yiran Zhou Jingyi Cao School of Materials Science and Engineering Liaoning University of Technology Jinzhou 121001 China School of Materials Science and Engineering Northeastern University Shenyang 110819 China Department of Mechanical Engineering Tsinghua University Beijing 100084 China

This study thoroughly investigates the effect of Mn-containing dispersoids on the static and dynamic mechanical performance, as well as the fracture behavior of Al–8Si–( special texture also appearing. The tensile s... 详细信息

This study thoroughly investigates the effect of Mn-containing dispersoids on the static and dynamic mechanical performance, as well as the fracture behavior of Al–8Si–(<0.01∼0.85) Mn alloy sheets, using OM, EBSD, LSCM, SEM/EDS, TEM, tensile tests, and fatigue tests. According to the data, as the Mn concentration increases, the number of Mn-containing dispersoids gradually increases, with their size remaining around 90 nm. Meanwhile, the recrystallization grain size growing from 16 to 29 μm, the texture type transitions from the Goss texture to the Cube texture, and finally, a strong {001} <140> special texture also appearing. The tensile strength of Al–8Si–xMn alloy sheets rises from 162 to 174 MPa, their yield strength rises from 68 to 78 MPa, and their elongation falls from 30 % to 27 %. A yield strength contribution model is established, and when the Mn concentration reaches 0.85 %, the Orowan strengthening contribution reaches its maximum, approximately 18 MPa. The tensile fracture mechanism of alloy sheets is known as ductile fracture. Additionally, the fatigue life of alloy sheets increases while the Mn concentration rises. The alloy sheet reaches its max fatigue life of 9.56 × 10 5 to 2.14 × 10 6 cycles, or around 2 to 4 times longer than the Mn-free alloy sheet, when the Mn concentration reaches 0.85 %. Fatigue crack always initiate at persistent slip bands. Based on the functional connection between fatigue life and Mn concentration, a fatigue life influencing factor I Mn is presented to quantitatively explain the impact of dispersoids amount on the alloy sheets' fatigue life and performance.

关键词： Mn-containing dispersoids Al–Si–Mn alloy sheets Tensile performance Fatigue life Fracture behavior

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DRL-Enabled Computation Offloading for AIGC Services in IIoT-Assisted Edge Computing Networks

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IEEE Internet of Things Journal 2025年第9期12卷 12829-12844页

作者： Zhang, Xingxing Li, Shaobo Tang, Jianhang Zhu, Keyu Zhang, Yang Guizhou University State Key Laboratory of Public Big Data Guiyang550025 China National University of Singapore Department of Electrical and Computer Engineering Queenstown Singapore Guizhou Institute of Technology School of Big Data Guiyang550003 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210016 China

The widespread application of AI-generated content (AIGC) services has driven demand for efficient computational resources, making effective task scheduling and computation offloading in edge computing (EC) environments a critical research topic. However, the high computational requirements and low latency demands of AIGC services, combined with the limitations of EC, present challenges for existing offloading methods, such as unstable decision making in dynamic task environments and resource overloading. Here, we propose a decentralized AIGC task offloading architecture within an IoT-assisted EC network to optimize the quality of AIGC services. In this architecture, we define a multiobjective joint optimization problem for AIGC task offloading, aiming to simultaneously optimize key performance metrics, such as task latency, energy efficiency, and load balancing. To address this problem, we introduce an improved proximal policy optimization (PPO)-based deep reinforcement learning (DRL) algorithm, named TOPPO. By incorporating a policy update step size constraint and a clipping mechanism, TOPPO significantly enhances the stability of the training process and reduces fluctuations during policy updates. Additionally, the algorithm integrates an LSTM model to improve its ability to handle temporal dependencies. Through continuous interaction between the model and the environment, the offloading strategy is iteratively updated to ensure that diverse AIGC tasks are efficiently executed on IoT devices or edge servers. Extensive simulations and performance evaluations demonstrate that the proposed method achieves significant improvements in task latency, energy consumption, and load management during AIGC task processing. © 2014 IEEE.

关键词： Computation offloading

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Measurement of Oil Film Thickness Distribution in Roll Bite during Cold Rolling Using Quantum Dots

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ISIJ International 2025年第1期65卷 50-61页

作者： Shimura, Masahiro Kasai, Daisuke Otsuka, Takayuki Yamashita, Naoki Hirayama, Tomoko Research & Development Process Research Laboratories Nippon Steel Corporation 20-1 Shintomi Futtu-shi Chiba293-8511 Japan Department of Mechanical Engineering and Physics Kyoto Institute of Technology Matsugasakigoshokaidocho Sakyo-ku Kyoto606-8585 Japan Department of Mechanical Engineering and Science Graduate School of Engineering Kyoto University Katsura Nishikyo-ku Kyoto615-8510 Japan

Lubrication is critical to achieve stable rolling during the cold rolling of flat steel products. However, the oil film thickness distribution in the roll bite and its effect on the friction between the work roll and strip has not yet been clarified. This study aims to elucidate the relationship between the oil film thickness distribution and friction by focusing on the rolling oil viscosity and steel grades because they significantly affect the friction between the work roll and the strip. Rolling oil was prepared with quantum dots (QDs) as the fluorescent additive and used in rolling experiments to determine its distribution. Furthermore, cold rolling experiments were conducted using two types of oils with different viscosities and three steel grades: low-carbon steel (LCS), high-strength steel (HSS), and advanced high-strength steel (AHSS) with tensile strengths of 270, 590, and 1 180 MPa, respectively. Subsequently, the oil film thickness distribution on the steel strip surface was visualized by fluorescence microscopy using QDs. The idea that the higher the tensile strength of the steel or the higher the oil viscosity, the wider the rolling oil distribution on the strip surface was demonstrated. The numerical analyses revealed that the rolling oil distribution on the steel sheet surface was wider for AHSS and HSS than that for LCS. The high surface pressure between the roll and the steel plate may have increased the oil leaching area by increasing the oil viscosity. These findings demonstrate that rolling oil permeation from oil pits reduces the friction between the work rolls and the strip. © 2025 The Iron and Steel Institute of Japan.

关键词： Fluorescence microscopy

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Applications of Advanced Optimized Neuro Fuzzy Models for Enhancing Daily Suspended Sediment Load Prediction

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Computer Modeling in engineering & sciences 2025年第4期143卷 1249-1272页

作者： Rana Muhammad Adnan Mo Wang Adil Masood Ozgur Kisi Shamsuddin Shahid Mohammad Zounemat-Kermani College of Architecture and Urban Planning Guangzhou UniversityGuangzhou510006China Center for Global Health Research Saveetha Institute of Medical and Technical SciencesChennai600001India Department of Natural and Applied Sciences TERI School of Advanced StudiesNew Delhi110070India Department of Civil Engineering Lübeck University of Applied ScienceLübeck23562Germany Department of Civil Engineering School of TechnologyIlia State UniversityTbilisi0162Georgia School of Civil Environmental and Architectural EngineeringKorea UniversitySeoul02841Republic of Korea School of Civil Engineering Faculty of EngineeringUniversiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia Department of Civil Engineering Shahid Bahonar University of KermanKerman***Iran

Accurate daily suspended sediment load(SSL)prediction is essential for sustainable water resource management,sediment control,and environmental ***,SSL prediction is highly complex due to its nonlinear and dynamic nature,making traditional empirical models *** study proposes a novel hybrid approach,integrating the Adaptive Neuro-Fuzzy Inference System(ANFIS)with the Gradient-Based Optimizer(GBO),to enhance SSL forecasting *** research compares the performance of ANFIS-GBO with three alternative models:standard ANFIS,ANFIS with Particle Swarm Optimization(ANFIS-PSO),and ANFIS with Grey Wolf Optimization(ANFIS-GWO).Historical SSL and streamflow data from the Bailong River Basin,China,are used to train and validate the *** input selection process is optimized using the Multivariate Adaptive Regression Splines(MARS)*** performance is evaluated using statistical metrics such as Root Mean Square Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),Nash Sutcliffe Efficiency(NSE),and Determination Coefficient(R^(2)).Additionally,visual assessments,including scatter plots,Taylor diagrams,and violin plots,provide further insights into model *** results indicate that including historical SSL data improves predictive accuracy,with ANFIS-GBO outperforming the other ***-GBO achieves the lowest RMSE and MAE and the highest NSE and R^(2),demonstrating its superior learning ability and *** findings highlight the effectiveness of nature-inspired optimization algorithms in enhancing sediment load forecasting and contribute to the advancement of AI-based hydrological *** research should explore the integration of additional environmental and climatic variables to enhance predictive capabilities further.

关键词： Suspended sediment load prediction neuro-fuzzy gradient-based optimizer ANFIS

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A Compact Wideband Circularly Polarized Tapered Slot Antenna with Bent Directors Based on Double-Ridge GWG

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IEEE Antennas and Wireless Propagation Letters 2025年

作者： Quan, Shuanglong Cao, Jianyin Wang, Hao Wang, Yan Nanjing University of Science and Technology School of Electronic and Optical Engineering Nanjing210094 China

In this paper, a wideband circular polarized (CP) antenna based on double ridge gap waveguide (GWG) with end-fire radiation is proposed. The symmetric tapered slots are etched for CP condition. The periodic ridge structures are introduced between the transition ridge and periodic pins to increase the current path. By this means, the appropriate phase differences of orthogonal electric fields are achieved within compact radiation aperture. The bent dipoles are added at the end of the tapered slot to improve the amplitude and phase condition in lower frequency. Additionally, the gradient transitions from the ridge to radiation aperture are adjusted for wide impedance matching performance. To validate the proposed antenna, a 1×4 CP array fed from the double ridge GWG power divider was fabricated and measured. A measured bandwidth of 32.6% (28.2-39.2 GHz) for both S11 © 2002-2011 IEEE.

关键词： Circular polarization

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HA-FGOVD: Highlighting Fine-grained Attributes via Explicit Linear Composition for Open-Vocabulary Object Detection

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IEEE Transactions on Multimedia 2025年

作者： Ma, Yuqi Liu, Mengyin Zhu, Chao Yin, Xu-Cheng University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

Open-vocabulary object detection (OVD) models are considered to be Large Multi-modal Models (LMM), due to their extensive training data and a large number of parameters. Mainstream OVD models prioritize object coarse-grained category rather than focus on their fine-grained attributes, e.g., colors or materials, thus failed to identify objects specified with certain attributes. Despite being pretrained on large-scale image-text pairs with rich attribute information, their latent feature space does not highlight these fine-grained attributes. In this paper, we introduce HA-FGOVD, a universal and explicit method that enhances the attribute-level detection capabilities of frozen OVD models by highlighting fine-grained attributes in explicit linear space. Our approach uses a LLM to extract attribute words in input text as a zero-shot task. Then, token attention masks are adjusted to guide text encoders in extracting both global and attribute-specific features, which are explicitly composited as two vectors in linear space to form a new attribute-highlighted feature for detection tasks. The composition weight scalars can be learned or transferred across different OVD models, showcasing the universality of our method. Experimental results show that HA-FGOVD achieves state-of-the-art performance on the FG-OVD benchmark and demonstrates promising generalization on the OVDEval benchmark, suggesting that our method addresses significant limitations in fine-grained attribute detection and has potential for broader fine-grained detection applications. © 1999-2012 IEEE.

关键词： Coarse-grained modeling

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Analytical solution for the stress fields of a hypocycloidal hole with two radial cracks in an infinite plate

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engineering Fracture Mechanics 2025年 321卷

作者： Bi, Shengfan Cui, Xiaoting Huang, Yong Wang, Hao School of Energy and Power Engineering Nanjing University of Science and Technology Nanjing210094 China

Hole structures are widely utilized in engineering applications. Edge cracks may form around holes during manufacturing or operation, potentially leading to structural failure. This study investigates the problem of unequal radial cracks emanating from a hypocycloid-shaped hole in a two-dimensional isotropic infinite plate. Using the Muskhelishvili approach and conformal mapping, a general solution is derived for cracked deltoid and astroid holes. The analytical theory is validated through finite element simulations, with numerical examples for both single-sided and double-sided radial cracks. The effects of crack length and hypocycloid geometry on the stress intensity factor (SIF) are investigated. Under uniaxial tension, an increase in crack length raises the SIF for both the corresponding and opposite crack tips. Due to geometric differences at the crack initiation location, cracks emanating from the cusps of a deltoid hole exhibit reduced sensitivity of SIF to crack length compared to cracks emanating from smoother hole edges. © 2025

关键词： Conformal mapping

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