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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期34卷 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of Engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL Department of Mechanical Engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University Department of Civil Engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

关键词： Al2O3 concentration CI engine Dairy Scum Methyl Ester Biodiesel

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Laser assisted phase transformation of carbon-based transition metal oxide electrode for high-performance supercapacitor application

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Science China Chemistry 2025年

作者： Mingzhen Xiu Jianghong Zhang Yu Lu Xun Cao Kang Huang Siyu Zhu Bowei Zhang Yu Liang Chunwang Zhao Junsheng Wu Yizhong Huang School of Materials Science and Engineering Nanyang Technological University Energy Research institute Interdisciplinary Graduate Programme Nanyang Technological University institute of Sustainability for Chemicals Energy and Environment Agency for Science Technology and ResearchSingapore institute of Advanced Materials and Technology University of Science and Technology Beijing School of Materials Science and Technology Shenyang University of Chemical Technology School of Materials Science and Hydrogen Energy Foshan University

Transitional metal oxides have a wide range of applications due to their superior *** enhanced performance of metal oxide relies on their desirable oxidation states,which is challenging to achieve and requires complex *** study demonstrates a facile strategy enabling rapid phase transformation of transition metal *** approach involves synthesis of a tetragonal Mn3O4/carbon cloth composite using the liquid plasma discharge deposition （LPDD） technique,followed by laser irradiation with the presence of ethylene glycol under an N2gas *** resulting face-centered cubic MnO/carbon cloth electrode exhibits an excellent capacitance of 1,125 F g-1at 2 A g-1,with remarkable capacitance retention of 95%after10,000 *** approach can be extended to other transition metals including Co,Cu,Cr,Fe,Ni,and *** simulations reveal the significance of ethylene glycol and the underlying mechanism associated with the phase transformation of transition metal *** present study offers a powerful technique for the phase transformation of transition metal oxide which can guide the development of new electrode materials with enhanced electrochemical properties for high-performance energy storage applications.

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Collagen peptide fractions from tilapia(Oreochromis aureus Steindachner,1864)scales:Chemical characterization and biological activity

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Food Bioscience 2023年第3期53卷 1512-1522页

作者： Karen Lilián Hernández-Ruiz Jaime López-Cervantes Dalia Isabel Sánchez-Machado Olga Nydia Campas-Baypoli Angie AraíQuintero-Guerrero Maria de Lourdes Grijalva-Delgado Andrés Francisco Chávez-Almanza technological institute of sonora Ciudad ObregonMX-85000SonoraMexico

This research project was focused on the isolation of compounds from natural sources and their chemical characterization and biological activity were *** is a popular fish and large amounts of byproducts are generated from its *** the abundance of this waste and its low value-added uses,collagen can be recovered at low *** has low toxicity,good compatibility,biodegradability,and functional properties in ***,industrial byproducts could be considered as a valuable source for the re-covery of collagen and the isolation of collagen *** this work,fish scales were used to isolate hydrolyzed collagen using *** fractions of collagen peptides were separated:F1(5-10 kDa peptides)and F2(<5 kDa peptides)through molecular weight cut-offs to evaluate the biological activity *** functional groups of native collagen were identified by Fourier transform infrared(FTIR)*** most abundant total amino acids were glycine,hydroxyproline,and proline,while the pre-dominant free amino acids were glycine,tyrosine,and *** the evaluation of antioxidant activity and capacity,F1 presented the highest antioxidant content and required the least amount of sample to inhibit 50%of the ABTS and DPPH radicals(IC50).An antimicrobial effect against Escherichia coli of clinical origin was observed,although the fraction had no effect on Staphylococcus ***,hydrolyzed collagen is a valuable resource for the production of peptides with bioactive properties to be used in various applications.

关键词： Fish scales Hydrolyzed collagen Collagen peptides Biological properties

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Metal-organic frameworks (MOFs) in aqueous batteries (ABs):unlocking potential through innovative materials design

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Science China Chemistry 2025年

作者： Bo Han Erhai Hu Bei-Er Jia Ziyang Liu Shuen Tso Afriyanti Sumboja Ivandini T.Anggraningrum Anne Zulfia Syahrial Qingyu Yan SCARCE Laboratory Energy Research Institute NTU (ERIN) Nanyang Technological University School of Materials Science and Engineering Nanyang Technological University Material Science and Engineering Research Group Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Department of Chemistry University of Indonesia Metallurgical & Materials Engineering Department Fakultas Teknik Universitas Indonesia

Metal-organic frameworks (MOFs) represent a revolutionary class of materials in the field of energy storage,particularly for aqueous batteries (ABs).Distinguished by their large surface area,tuneable porosity,and adaptable chemical activity,MOFs offer significant advantages over conventional materials in battery *** article provides a thorough analysis of the crucial role that MOFs play in improving the efficiency of *** includes a concise review of the current research progress,emphasizing the fundamental processes by which MOFs enhance electrochemical ***,the review examines the synthesis and design strategies for the structure of MOFs to maximize ion transport,improve conductivity,and enhance *** structural advantages,chemical versatility,stability,durability and functionalization potential of MOFs are comprehensively ***,we explore the distinct advantages of MOFs in overcoming common challenges encountered in ABs,such as declining capacity,inadequate cycling stability,and limited energy *** paper also highlights the future research directions needed to fully harness their *** goal is to develop a fundamental understanding and stimulate further progress in the use of MOFs for advanced energy storage solutions.

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Dynamic modeling of a three-dimensional braided composite thin plate considering braiding directions

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 123-138页

作者： Chentong GAO Huiyu SUN Jianping GU W.M.HUANG College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics School of Mechanical and Aerospace Engineering Nanyang Technological University Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology School of Materials Science and EngineeringNanjing Institute of Technology

Currently, there are a limited number of dynamic models available for braided composite plates with large overall motions, despite the incorporation of three-dimensional(3D) braided composites into rotating blade components. In this paper, a dynamic model of 3D 4-directional braided composite thin plates considering braiding directions is established. Based on Kirchhoff's plate assumptions, the displacement variables of the plate are expressed. By incorporating the braiding directions into the constitutive equation of the braided composites, the dynamic model of the plate considering braiding directions is obtained. The effects of the speeds, braiding directions, and braided angles on the responses of the plate with fixed-axis rotation and translational motion, respectively, are investigated. This paper presents a dynamic theory for calculating the deformation of 3D braided composite structures undergoing both translational and rotational motions. It also provides a simulation method for investigating the dynamic behavior of non-isotropic material plates in various applications.

关键词： Constitutive equations

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AsyCo: an asymmetric dual-task co-training model for partial-label learning

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Science China(Information Sciences) 2025年

作者： Beibei LI Yiyuan ZHENG Beihong JIN Tao XIANG Haobo WANG Lei FENG College of Computer Science Chongqing University State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences School of Software Technology Zhejiang University School of Computer Science and Engineering Nanyang Technological University

Partial-label learning (PLL) is a typical problem of weakly supervised learning, where each training instance is annotated with a set of candidate labels. Self-training PLL models achieve state-of-the-art performance but suffer from error accumulation problems caused by mistakenly disambiguated instances. Although co-training can alleviate this issue by training two networks simultaneously and allowing them to interact with each other, most existing co-training methods train two structurally identical networks with the same task, i.e., are symmetric, rendering it insufficient for them to correct each other due to their similar limitations. Therefore, in this paper, we propose an asymmetric dual-task co-training PLL model called AsyCo,which forces its two networks, i.e., a disambiguation network and an auxiliary network, to learn from different views explicitly by optimizing distinct tasks. Specifically, the disambiguation network is trained with a self-training PLL task to learn label confidence, while the auxiliary network is trained in a supervised learning paradigm to learn from the noisy pairwise similarity labels that are constructed according to the learned label confidence. Finally, the error accumulation problem is mitigated via information distillation and confidence refinement. Extensive experiments on both uniform and instance-dependent partially labeled datasets demonstrate the effectiveness of AsyCo.

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Short-term Photovoltaic Power Prediction Based on Feature Optimization and Hybrid Improved Grey Wolf Algorithm-optimized BiLSTM Network

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Dianwang Jishu/Power System Technology 2025年第1期49卷 209-222页

作者： Zhao, Ruyi Wang, Xiaohui Zheng, Bihuang Li, Daoxing Gao, Yi Guo, Pengtian China Electric Power Research institute Haidian District Beijing 100192 China Economic and technological Research institute State Grid Tianjin Electric Power Company Hedong District Tianjin 300171 China

To address the challenges posed by strong noise interference in photovoltaic (PV) sequences and the issues of low accuracy and poor generalization of a single model in PV power prediction, we propose a short-term PV power prediction method. This method uses feature optimization and a hybrid improved Grey Wolf algorithm to optimize the BiLSTM network. Firstly, the mutual information algorithm is employed for variable selection in input data to eliminate redundant variables. Subsequently, the Complementary Ensemble Empirical Mode Decomposition and an improved wavelet threshold algorithm are applied to the selected data for feature reconstruction to reduce noise interference in the data and optimize input variable features. Finally, the standard Grey Wolf Optimizer algorithm underwent hybrid optimization by integrating improved Tent chaotic mapping, nonlinear decreasing factors, dynamic weight strategies, and the differential evolution algorithm. This process aimed to ascertain the optimal hyperparameter combination for the BiLSTM network. The attention mechanism was also employed to extract key temporal information from the data, developing a novel short-term photovoltaic power prediction model. Simulation experiments demonstrate that, compared to the least squares support vector machine, long short-term memory network, and bidirectional long short-term memory neural network, the proposed model achieves an average reduction of 12.45%, 7.95%, and 5.37% in root mean square error under various weather conditions such as sunny, cloudy, overcast, and rainy, showcasing excellent predictive performance, good generalization ability, and promising engineering application value. © 2025 Power System Technology Press. All rights reserved.

关键词： Mean square error

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NHC-mediated photocatalytic para-selective C–H acylation of aryl alcohols: regioselectivity control via remote radical spiro cyclization

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Science China Chemistry 2025年

作者： Tinglei Zhang Lala Wang Xiaolin Peng Tianhui Liao Dongmei Chen Ting Tu Donghan Liu Ziye Cheng Shiqing Huang Shi-Chao Ren Xinglong Zhang Yonggui Robin Chi State Key Laboratory of Green Pesticide Key Laboratory of Green Pesticide and Agricultural Bioengineering Ministry of Education Guizhou University Qiannan Medical College for Nationalities School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Department of Chemistry The Chinese University of Hong Kong institute of High Performance Computing Agency for Science Technology and Research

Friedel-Crafts reaction and transition-metal catalysis represent primary methodologies for arene acylation; however, suffer from certain limitations, such as electronic effect-dependent reactivity, regioselectivity issues, the necessity of directing group, and relatively exceptionally limited exploration in meta-and para-acylations. N-heterocyclic carbene(NHC) catalysis has recently emerged as a promising alternative strategy for arene acylation, offering distinct regioselectivity profiles that are challenging to achieve through known methods. Herein, an NHC-mediated photo-catalytic para-selective C–H acylation of aryl alcohols is disclosed. The reaction employs a remote radical-induced temporary spiro cyclization strategy, proceeding via tandem radical dearomatization, radical acylation, rearomatization processes. Combined experimental and computational mechanistic studies support the proposed reaction pathway and observe an exclusive para-selectivity regardless of the nature of the substituents on the substrates. Despite the less satisfactory yields, the current method exhibits non-electronic nature-based reactivity and regioselectivity, enabling quick access to acylated arenes that are difficult or impossible for reported methods.

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Recent Advances in Artificial Sensory Neurons:Biological Fundamentals,Devices,Applications,and Challenges

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Nano-Micro Letters 2025年第3期17卷 168-216页

作者： Shuai Zhong Lirou Su Mingkun Xu Desmond Loke Bin Yu Yishu Zhang Rong Zhao Guangdong institute of Intelligence Science and Technology HengqinZhuhai 519031People’s Republic of China College of Integrated Circuits Zhejiang UniversityHangzhou 3112000People’s Republic of China ZJU-Hangzhou Global Scientific and technological Innovation Center Hangzhou 310027People’s Republic of China Department of Science Mathematics and TechnologySingapore University of Technology and DesignSingapore 487372Singapore Department of Precision Instruments Tsinghua UniversityBeijing 100084People’s Republic of China Center for Brain‑Inspired Computing Research Tsinghua UniversityBeijing 100084People’s Republic of China IDG/McGovern institute for Brain Research Tsinghua UniversityBeijing 100084People’s Republic of China

Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power *** fully leverage its advantages,convertingthe external analog signals to spikes is an essential *** including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area *** efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory *** can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory *** review summarizesand benchmarks the recent progress of artificial sensory *** starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial ***,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also ***,we highlight the challenges and perspectives for the future development of artificial sensory neurons.

关键词： Artificial intelligence Emerging devices Artificial sensory neurons Spiking neural networks Neuromorphic sensing

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Negative PO3-implanted bionic ion transport channels for promoting Li-S battery

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Science China Chemistry 2025年

作者： Wenhuan Huang Shun Wang Xuehan Hou Yanan Zhang Xingxing Zhang Yaoxiao Zhao Xilang Jin Huabin Zhang Fei Wang Jian Zhang Key Laboratory of Chemical Additives for China National Light Industry College of Chemistry and Chemical EngineeringShaanxi University of Science and Technology School of Materials and Chemical Engineering Xi'an Technological University Chemistry Program Physical Science and Engineering Division King Abdullah University of Science and Technology State Key Laboratory of Structural Chemistry Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences

Lithium-sulfur （Li-S） battery,as a promising next-generation high-energy-density battery,suffers from lithium polysulfides（LPSs） shuttle and Li dendrites *** crystalline framework-based membranes as separator can effectively absorb and restrain LPSs but without precise structural design principal exploration and mechanism ***,bio-inspired 1D oriented lithium-ion transport channels with molecular negatively charged PO3（-1） have been developed in hybrid tetrazole frameworks for promoting the transmission of Li+*** theoretical calculations and in situ spectroscopy demonstrated the higher binding energy and inhibited diffusion of LPSs in *** assembled PP@PO3Janus separator in Li-S coin cell delivered a high initial capacity of 1410.9 mAh g-1at 0.1 C and a low attenuation rate of 0.038%per cycle over 500 cycles at 5 ***,the high capacities of 862,542 and 409 mAh g-1based on high-sulfur-loading cathodes of 2.6,3.8 and 5.0 mg cm-2at0.5 C were achieved,***,the punch battery of PO3@PP separator with S-cathode of 1.2 mg cm-2has been developed for demonstrating its potentials commercial application,which displays impressive capacity of 873.4 mAh g-1with the retention of～78.9%over 50 cycles.

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