检索结果-南通市图书馆

Journal of Energy Chemistry 2025年第2期101卷 156-162页

作者： Zhengru Yang Jia Hui Wangxi Fan Pengcheng Liu Chunyong Zhang Shuang Dong Zhou Yang department of Chemistry and Chemical engineering & Jiangsu Key Laboratory of Clean Energy Storage and Conversion Jiangsu University of Technology engineering technology and Materials Research Center China Academy of Transportation Sciences School of Chemical engineering and Materials Changzhou Institute of Technology

It is very appealing that 5-hydroxymethylfurfural（HMF） is electrocatalytical oxidized as 2,5-furandicarboxylic acid（FDCA） linking to non-classical cathodic hydrogen（H2） ***,the electrocatalysts for electrocatalytic HMF oxidative reaction（e-HMFOR） have been facing low Faradaic efficiency（FE） and high water splitting ***,we propose a strategy of the NiSeO3@（CoSeO3）4heterojunction by constructing a Co-Ni paired site,where the Co site is in charge of adsorbing for HMF while the electrons are transferred to the Ni site,thus giving the NiSeO3@（CoSeO3）4heterojunction superior electrocata lytic performances for e-HMFOR and water *** optimizing conditions,the NiSeO3@（CoSeO3）4heterojunction has high conversion of 99.7%,high selectivity of 99.9%,and high FE of 98.4% at 1.3 V,as well as low cell voltage of 1.31 V at 10 mA cm-2in 1 M KOH+0.1 M *** study offers a potential insight for e-HMFOR to high value-added FDCA coupling water splitting to produce H2in an economical manner.

关键词： Co-Ni paired site e-HMFOR FDCA Heterojunction Hydrogen evolution

Robust-optimal control of electromagnetic levitation system with matched and unmatched uncertainties:experimental validation

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Control Theory and technology 2025年第1期23卷 28-48页

作者： Amit Pandey Dipak M.Adhyaru department of Electronics and Instrumentation engineering Institute of TechnologyNirma UniversityAhmedabadGujarat382481India

The electromagnetic levitation system(EMLS)serves as the most important part of any magnetic levitation ***,its characteristics are defined by its highly nonlinear dynamics and ***,the uncertainties in the dynamics of an electromagnetic levitation system make the controller design more ***,it is necessary to design a robust control law that will ensure the system’s stability in the presence of these *** this framework,the dynamics of an electromagnetic levitation system are addressed in terms of matched and unmatched *** robust control problem is translated into the optimal control problem,where the uncertainties of the electromagnetic levitation system are directly reflected in the cost *** optimal control method is used to solve the robust control *** solution to the optimal control problem for the electromagnetic levitation system is indeed a solution to the robust control problem of the electromagnetic levitation system under matched and unmatched *** simulation and experimental results demonstrate the performance of the designed control *** performance indices such as integral absolute error(IAE),integral square error(ISE),integral time absolute error(ITAE),and integral time square error(ITSE)are compared for both uncertainties to showcase the robustness of the designed control scheme.

关键词： Nonlinear system Robust control Optimal control HJB equation Lyapunov stability Electromagnetic levitation system

Direct ink writing of nickel oxide-based thin films for room temperature gas detection

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Semiconductors 2025年第1期46卷 245-258页

作者： Neha Thakur Hari Murthy Sudha Arumugam Neethu Thomas Aarju Mathew Koshy Parasuraman Swaminathan department of Electronics and Communication engineering School of Engineering and TechnologyCHRIST UniversityKumbalagoduBengaluruKarnataka560074India department of Metallurgical and Materials engineering Indian Institute of Technology MadrasChennaiTamil Nadu600036India

The rapid industrial growth and increasing population have led to significant pollution and deterioration of the natural atmospheric *** atmospheric pollutants include NO_(2)and CO_(2).Hence,it is imperative to develop NO_(2)and CO_(2)sensors for ambient conditions,that can be used in indoor air quality monitoring,breath analysis,food spoilage detection,*** the present study,two thin film nanocomposite(nickel oxide-graphene and nickel oxide-silver nanowires)gas sensors are fabricated using direct ink *** nano-composites are investigated for their structural,optical,and electrical *** the nano-composite is deposited on the interdigitated electrode(IDE)pattern to form NO_(2)and CO_(2)*** deposited films are then exposed to NO_(2)and CO_(2)gases separately and their response and recovery times are determined using a custom-built gas sensing *** oxide-graphene provides a good response time and recovery time of 10 and 9 s,respectively for NO_(2),due to the higher electron affinity of graphene towards NO_(2).Nickel oxide-silver nanowire nano-composite is suited for CO_(2)gas because silver is an excellent electrocatalyst for CO_(2)by giving response and recovery times of 11 s *** is the first report showcasing NiO nano-composites for NO_(2)and CO_(2)sensing at room temperature.

关键词： nickel oxide graphene silver nanowires NO_(2) CO_(2) gas sensor

维普期刊数据库

Electrochemical sensor for dopamine detection based on multiwalled carbon nanotube/molybdenum disulfide quantum dots with machine learning integration and anti-interference capability

在线全文

学校读者我要写书评

暂无评论

Tungsten 2025年第1期7卷 137-151页

作者： Geethukrishnan Onkar Apte Kiran Kumar Tadi Energy Electrodics and Electrocatalysis (EEE) Lab Department of Chemistry School of Advanced Sciences Vellore Institute of Technology School of Computer Science and engineering Vellore Institute of Technology

The precise detection and measurement of dopamine（DA）,a crucial neurotransmitter in the human body,plays a significant role in diagnosing,preventing,and treating neurological diseases associated with its levels.A highly sensitive DA electrochemical sensor was constructed by combining molybdenum disulfide quantum dots（MSQDs） with multiwalled carbon nanotubes（MWCNTs）.The MSQDs were synthesized using the shear exfoliation *** sensors consist of MSQDs with Mo-S edge catalytic centers for the DA redox reaction,and MWCNTs amplify the sensor *** linearity of the sensor for the detection of DA was tested in the presence of ascorbic acid(AA,50 μmol·L-1) and uric acid(UA,200 μmol·L-1),and exhibited linearity from 2 to 966 μmol·L-1of DA with 0.097 μA(mol·L-1)-1sensitivity and a low limit of detection of0.6 μmol·L-1（the ratio between signal and noise,S/N=3）.Moreover,the sensitivity and selectivity of the sensor were also studied using *** is no increase in amperometric current after adding the most potentially interfering *** sensor was successfully applied to recover DA in human blood sera ***,machine learning algorithms were operated to aid in the near-precise detection of DA in the heterogeneous mixture containing AA and *** algorithms facilitate the identification and quantification of DA amidst coexisting interferents,including AA,that are commonly present in biological matrices.

关键词： Biosensor Complex mixture Dopamine Machine learning MoS2 Multiwalled carbon nanotubes

Semantic Segmentation of Lumbar Vertebrae Using Meijering U-Net(MU-Net)on Spine Magnetic Resonance Images

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 733-757页

作者： Lakshmi S V V Shiloah Elizabeth Darmanayagam Sunil Retmin Raj Cyril department of Computer Science and engineering College of Engineering GuindyAnna UniversityChennai600025India department of Information technology Madras Institute of TechnologyAnna UniversityChrompetChennai600044India

Lower back pain is one of the most common medical problems in the world and it is experienced by a huge percentage of people *** to its ability to produce a detailed view of the soft tissues,including the spinal cord,nerves,intervertebral discs,and vertebrae,Magnetic Resonance Imaging is thought to be the most effective method for imaging the *** semantic segmentation of vertebrae plays a major role in the diagnostic process of lumbar *** is difficult to semantically partition the vertebrae in Magnetic Resonance Images from the surrounding variety of tissues,including muscles,ligaments,and intervertebral discs.U-Net is a powerful deep-learning architecture to handle the challenges of medical image analysis tasks and achieves high segmentation *** work proposes a modified U-Net architecture namely MU-Net,consisting of the Meijering convolutional layer that incorporates the Meijering filter to perform the semantic segmentation of lumbar vertebrae L1 to L5 and sacral vertebra ***-colour mask images were generated and used as ground truth for training the *** work has been carried out on 1312 images expanded from T1-weighted mid-sagittal MRI images of 515 patients in the Lumbar Spine MRI Dataset publicly available from Mendeley *** proposed MU-Net model for the semantic segmentation of the lumbar vertebrae gives better performance with 98.79%of pixel accuracy(PA),98.66%of dice similarity coefficient(DSC),97.36%of Jaccard coefficient,and 92.55%mean Intersection over Union(mean IoU)metrics using the mentioned dataset.

关键词： Computer aided diagnosis(CAD) magnetic resonance imaging(MRI) semantic segmentation lumbar vertebrae deep learning U-Net model

Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Modeling in engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj department of Mechanical engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India department of Mechanical engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India department of Mechanical engineering Gharda Institute of TechnologyLavelMaharashtra415708India department of Electrical and Electronics engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

Physics-informed battery degradation prediction:Forecasting charging curves using one-cycle data

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第2期101卷 825-836页

作者： Aihua Tang Yuchen Xu Jinpeng Tian Xing Shu Quanqing Yu Key Laboratory of Advanced Manufacturing technology for Automobile Parts Ministry of Education Chongqing University of Technology department of Electrical and Electronic engineering and Research Centre for Grid Modernization The Hong Kong Polytechnic University School of Automotive engineering Harbin Institute of Technology

Accurately predicting battery degradation is crucial for battery system ***,due to the complexities of aging mechanisms and limitations of historical data,comprehensively indicating battery degradation solely through maximum capacity loss assessment is *** machine learning offers promising solutions,it often overlooks domain knowledge,resulting in reduced accu racy,increased computational burden and decreased ***,this study proposes a method to predict the voltage-capacity（V-Q） curve during battery degradation with limited historical *** process is achieved through two physically interpretable components:a lightweight interpretable physical model and a physics-informed neural *** components incorporate domain knowledge into machine learning to improve V-Q curve prediction performance and enhance *** validation was conducted on 52 batteries of different types under different testing *** proposed method can accurately predict future *** for hundreds of cycles using only one-present-cycle V-Q curve,with root mean square error and mean absolute error basically less than 0.035 Ah and R2basically less than 98.5%.This means that incremental capacity curves can be extracted from the predicted results for a more comprehensive and accurate battery degradation ***,the method can flexibly adjust prediction length and density to cater to the practical needs of long-cycle prediction and data *** study provides a viable method for rapid degradation prediction and is expected to be generalized to in-vehicle implementations.

关键词： Degradation prediction Lightweight interpretable physical model Lithium-ion battery Physics-informed neural network Voltage-capacity curve

Comprehensive review of advances in machine-learning-driven optimization and characterization of perovskite materials for photovoltaic devices

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第2期101卷 298-323页

作者： Bonghyun Jo Wenning Chen Hyun Suk Jung School of Advanced Materials Science and engineering Sungkyunkwan University SKKU institute of Energy Science and technology (SIEST) Sungkyunkwan University department of Future Energy engineering Sungkyunkwan University

Perovskite solar cells(PSCs) have developed rapidly,positioning them as potential candidates for nextgeneration renewable energy ***,conventional trial-and-error approaches and the vast compositional parameter space continue to pose challenges in the pursuit of exceptional performance and high stability of perovskite-based *** increasing demand for novel materials in optoelectronic devices and establishment of substantial databases has enabled data-driven machinelearning(ML) approaches to swiftly advance in the materials *** review succinctly outlines the fundamental ML procedures,techniques,and recent breakthroughs,particularly in predicting the physical characteristics of perovskite ***,it highlights research endeavors aimed at optimizing and screening materials to enhance the efficiency and stability of ***,this review highlights recent efforts in using characterization data for ML,exploring their correlations with material properties and device performance,which are actively being researched,but they have yet to receive significant ***,we provide future perspectives,such as leveraging Large Language Models(LLMs) and text-mining,to expedite the discovery of novel perovskite materials and expand their utilization across various optoelectronic fields.

关键词： Characterization Data-driven machine learning Perovskite materials Perovskite solar cell

Uncovering fantastic synergistic lithium adsorption with manganese-titanium based composite nanospheres:Mild synthesis and molecular dynamics simulation insights

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2025年第2期101卷 52-67页

作者： Yameng Wang Zi-Yu Liu Yubei Su Yu Liu Aoqun Liu Xiaoye Zhang Yugang Huang Liyun Zhang Haisheng Chen Wancheng Zhu department of Chemical engineering Qufu Normal University institute of engineering Thermophysics Chinese Academy of Sciences State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical Technology

In light of the burgeoning energy technology sector and the ever-growing demand for lithium across diverse industrial domains,conventional lithium extraction methods have been proven inadequate due to their limited production capacity and high operational *** work introduces a novel approach to the manganese-titanium based composite HMTO（Mn:Ti=1:4） lithium ion-sieve（LIS） nanospheres,employing lithium acetate dihydrate,manganese carbonate and titanium dioxide P25 as the primary *** nanospheres exhibit relatively uniform spherical morphology,narrow size distribution,small average particle size（ca.55 nm）,large specific surface area(43.58 m2g-1) and high surface O2-content（59.01%）.When utilized as the adsorbents for Li+ions,the HMTO（Mn:Ti=1:4） LIS demonstrates a fast adsorption rate,approaching equilibrium within 6.0 h with an equilibrium adsorption capacity（qe）of 79.5 mg g-1and a maximum adsorption capacity（qm） of 87.26 mg g-1(initial concentration CO:1.8 g L-1).In addition,the HMTO（Mn:Ti=1:4） also delivers a high lithium extraction from the simulated high magnesium-lithium molar ratio salt lake brine（Mg:Li=103）,achieving a qeof 33.85 mg g-1along with a remarkable selectivity(αMgLi=2192.76).Particularly,the HMTO（Mn:Ti=1:4） LIS showcases a satisfactory recycling adsorption *** adsorption capacity remains at a high level,even that determined after the 5th cycle(55.45 mg g-1) surpasses that of the most recently reported ***,the fantastic synergistic lithium adsorption mechanism is deliberately uncovered by leveraging the ion exchange principles and molecular dynamics（MD） simulations.

关键词： Adsorption performance Ion exchange Lithium ion-sieves Manganese titanium composite Salt lake brine lithium extraction

The dynamic effects of solar eclipses of October 25,2022,and October 14,2023,on GPS-derived total electron content

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Geodesy and Geodynamics 2025年第1期16卷 75-86页

作者： Vishal Chauhan Vishakha Rakesh Singh Shishupal Singh Vikram Singh Om Prakash Singh department of Physics Graphic Era Hill University department of Petroleum engineering Graphic Era (Deemed to be University) department of Physics St.John's College department of Applied Sciences & Humanities Institute of Engineering & Technology

This study analyzes total electron content(TEC) variations during two solar eclipse events that occurred on October 25, 2022, and October 14, 2023. The solar eclipse of October 25, 2022, was a partial solar eclipse, while the eclipse of October 14, 2023, was an annular solar eclipse. For this study, the data of eight International GNSS Service(IGS) stations from different eclipse coverage zones are used to analyze TEC variations. It is found that the stations located in the maximum eclipse cover zone exhibited notable decreases in TEC values. The minimum variation of about 11.76% in TEC values is observed at the station situating in about 20 percent eclipse cover zone, while it varies from 22% to 38% at the stations falling in about 60 percent eclipse cover zone. The highest variation in TEC values of about 44% is found at the stations in about 80 percent eclipse cover zone. The time of occurrence of maximum depletion in TEC values at each station is in line with their longitudinal sequence. Atmospheric gravity waves(AGWs) are also observed by performing wavelet analysis on TEC data. The global TEC maps visualize and confirm observed TEC variations, providing spatial and temporal insights into the ionospheric response. This analysis highlights the influence of station location and eclipse coverage on the magnitude and spatial distribution of TEC variations.

关键词： Solar eclipse Ionosphere GPS TEC AGW

维普期刊数据库