检索结果-南通市图书馆

Establishing a new testing protocol of the electrochemical stability window for electric double-layer capacitors

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science china Chemistry 2025年第1期68卷 217-225页

作者： Ruilin Hou Xiaoxi Zhao Tingting Liang Qingyun Dou Shan Xu Xingbin Yan School of Materials Science and Engineering Sun Yat-sen University Laboratory of Clean Energy Chemistry and Materials Lanzhou Institute of Chemical Physics Chinese Academy of Sciences College of Engineering and Applied Sciences Nanjing University center of Industrial Analysis and testing Guangdong Academy of Science

The electrochemical stability window(ESW) is crucial for determining the energy density of electric double-layer capacitors(EDLCs). However, current ESW testing protocols of EDLCs are strongly affected by artificial factors, thereby leading to unreliable result. To solve this problem, we first identify the key shortcomings of the traditional protocols by analyzing their test principles. Subsequently, taking an aqueous carbon-based EDLC as an example, we design a side reaction descriptor to represent the response difference in the charging capacitance to side reactions between the cyclic voltammetry and galvanostatic chargedischarge methods. With the aid of this descriptor, we propose a new ESW testing protocol, which is not only able to completely avoid the adverse influence of subjective factors but also fully consider the operating condition limitations. The protocol can be extended from the single electrode to the full device. This work proposes a more rigorous definition of ESW and provides a reliable protocol for evaluating the ESW of EDLCs.

关键词： electric double-layer capacitors electrochemical stability window testing protocol side reaction descriptor operating limitation

Modification of Maxwell model for conductivity prediction of carbon nanotubes-filled polymer composites with tunneling effect

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 25-36页

作者： Jue ZHU Longyuan LI Ningtao ZHU Zhejiang Provincial Engineering Research center for the Safety of Pressure Vessel and Pipeline Key Laboratory of Impact and Safety Engineering (Ningbo University) Ministry of Education School of Engineering Computing and Mathematics University of Plymouth Xi'an Zhanshi testing & Engineering Co.Ltd.

Carbon nanotubes(CNTs) have garnered great attention in recent years due to their outstanding electrical, thermal, and mechanical properties. The incorporation of small amounts of CNTs in polymers can substantially improve the sensitivity of the polymer's electrical conductivity. This paper presents a modified Maxwell model to evaluate the electrical conductivity of CNTs-filled polymer composites by introducing a transition zone to account for the tunneling effect. In this modified Maxwell model, the CNTs-filled polymer composite is modeled as a three-phase composite, consisting of a matrix(polymer), inclusions(CNTs), and a transition zone(tunneling zone). The effective electrical conductivity(EEC) of the composite is calculated based on the volume fractions and electrical conductivities of the matrix, inclusions, and transition zone. The model's validity is confirmed through the use of available test data, which demonstrates its capability to accurately capture the nonlinear conductivity behavior observed in CNTs-polymer composites. This study offers valuable insights into the design of high-performance conductive polymer nanocomposites, and enhances the understanding of electrical conduction mechanisms in CNT-dispersed polymer composites.

关键词： Nanoclay

Constructing Donor–Acceptor‑Linked COFs Electrolytes to Regulate Electron Density and Accelerate the Li^(+)Migration in Quasi‑Solid‑State Battery

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Nano-Micro Letters 2025年第1期17卷 456-471页

作者： Genfu Zhao Hang Ma Conghui Zhang Yongxin Yang Shuyuan Yu Haiye Zhu Yongjiang Sun Hong Guo School of Materials and Energy International Joint Research Center for Advanced Energy Materials of Yunnan ProvinceYunnan UniversityKunming 650091People’s Republic of China Yunnan Yuntianhua Co. LtdR&D CenterKunming 650228People’s Republic of China Southwest United Graduate School Kunming 650091People’s Republic of China

Regulation the electronic density of solid-state electrolyte by donor–acceptor(D–A)system can achieve highly-selective Li^(+)transportation and conduction in solid-state Li metal *** study reports a high-performance solid-state electrolyte thorough D–A-linked covalent organic frameworks(COFs)based on intramolecular charge transfer *** other reported COFbased solid-state electrolyte,the developed concept with D–A-linked COFs not only achieves electronic modulation to promote highly-selective Li^(+)migration and inhibit Li dendrite,but also offers a crucial opportunity to understand the role of electronic density in solid-state Li metal *** introduced strong electronegativity F-based ligand in COF electrolyte results in highlyselective Li^(+)(transference number 0.83),high ionic conductivity(6.7×10^(-4)S cm^(−1)),excellent cyclic ability(1000 h)in Li metal symmetric cell and high-capacity retention in Li/LiFePO_(4)cell(90.8%for 300 cycles at 5C)than substituted C-and N-based *** is ascribed to outstanding D–A interaction between donor porphyrin and acceptor F atoms,which effectively expedites electron transferring from porphyrin to F-based ligand and enhances Li^(+)***,we anticipate that this work creates insight into the strategy for accelerating Li^(+)conduction in high-performance solid-state Li metal batteries through D–A system.

关键词： Electronic modulation engineering Donor-acceptor-linked covalent organic frameworks Quasi-solid-state Li metal battery

Deep learning-based software engineering: progress,challenges, and opportunities

在线全文

学校读者我要写书评

暂无评论

Science china(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of software Technology Zhejiang University School of software Engineering Sun Yat-sen University School of software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel software Technology Nanjing University School of Computer Science and Engineering Beihang University Institute of Information Engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

Optimization of groove texture profile to improve hydrodynamic lubrication performance:Theory and experiments

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Friction 2020年第1期8卷 83-94页

作者： Wei WANG Yongyong HE Jun ZHAO Junyuan MAO Yutong HU Jianbin LUO State Key Laboratory of Tribology Tsinghua UniversityBeijing 100084China Intelligent&Connected Vehicle testing Department China Software Testing CenterBeijing 100048China

It is well known that groove texture with a careful design can be used to enhance the load‐carrying capacity of oil film under the conditions of hydrodynamic *** this study,a general parametric model was developed,and agenetic algorithm‐sequential quadratic programming hybrid method was adopted to obtain the global‐optimum profile of the groove *** optimized profiles at different rotating speeds are all *** numerical analysis results verified the effect of the *** addition to the numerical optimization,experiments were conducted to validate the superiority of the optimized *** experimental results show that the optimized groove texture can efficiently reduce the coefficient of friction(COF)and the temperature rise of the *** particular,the optimized groove textures can achieve stable ultra‐low COF values(COF<0.01)under certain conditions.

关键词： groove texture hydrodynamic lubrication laser texturing ultra‐low coefficient of friction

Cross-Project software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 1687-1711页

作者： Xin Fan Shuqing Zhang Kaisheng Wu Wei Zheng Yu Ge School of software Nanchang Hangkong UniversityNanchang330063China software testing and Evaluation center Nanchang Hangkong UniversityNanchang330063China

Cross-Project Defect Prediction(CPDP)is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target ***,existing CPDP methods only consider linear correlations between features(indicators)of the source and target *** models are not capable of evaluating non-linear correlations between features when they exist,for example,when there are differences in data distributions between the source and target *** a result,the performance of such CPDP models is *** this paper,this paper proposes a novel CPDP method based on Synthetic Minority Oversampling Technique(SMOTE)and Deep Canonical Correlation Analysis(DCCA),referred to as *** Correlation Analysis(CCA)is employed to address the issue of non-linear correlations between features of the source and target projects.S-DCCA extends CCA by incorporating the MlpNet model for feature extraction from the *** redundant features are then eliminated by maximizing the correlated feature subset using the CCA loss ***,cross-project defect prediction is achieved through the application of the SMOTE data sampling *** Under Curve(AUC)and F1 scores(F1)are used as evaluation *** paper conducted experiments on 27 projects from four public datasets to validate the proposed *** results demonstrate that,on average,our method outperforms all baseline approaches by at least 1.2%in AUC and 5.5%in F1 *** indicates that the proposed method exhibits favorable performance characteristics.

关键词： Cross-project defect prediction deep canonical correlation analysis feature similarity

High-selectivity electroreduction of low-concentration CO2 with large concentration fluctuation

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

Science china Chemistry 2025年

作者： Mengyu Qi Yanbin Ma Chao Zhang Bingwei Li Xueqing Yang Zhaolin Shi Simeng Liu Changhua An Jiqing Jiao Tongbu Lu MOE International Joint Laboratory of Materials Microstructure Analysis and Testing CenterInstitute for New Energy Materials and Low Carbon TechnologiesSchool of Materials Science and EngineeringSchool of Chemistry and Chemical EngineeringTianjin University of Technology Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education) Nankai University

Electrochemical CO2reduction reaction（CO2RR） has been regarded as one of the most promising solutions to achieving “zero carbon emission”. In most of the CO2RR-related studies, high-purity CO2has been employed as the feed gas; however, in practice, CO2is generally emitted in low concentrations, so it is of great significance to realize high-selectivity electroreduction of low-concentration CO2with large concentration fluctuation. In this work, we constructed a dual-active-site catalyst and successfully achieved CO2local enrichment and conversion for low-concentration CO2. Operando experiments reveal that the catalyst has one type of site for activating CO2and one type of site for binding the reaction intermediates. The dual-active-site catalyst displays a selectivity for formic acid consistently above 97% over a broad potential window（from-0.9 to-1.6 V ***）. Even when fed with a low-concentration CO2stream（volume ratio from 50% down to 10%）, the dual-active-site catalyst could display high activity and selectivity（>91%）. In particular, the selectivity is still above 85% when the CO2volume ratio is as low as 5%. This work offers a feasible route for converting low-concentration CO2via a synergistic effect for dual-active-site catalysts.

关键词：

Research on software Structure Analysis Technology and Reliability Evaluation Method of Warship Equipment

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 Donghua University(English Edition) 2018年第5期35卷 430-438页

作者： YAN Ran HAN Xinyu LIU Bojiang TANG Longli china Shipbuilding software Quality&Reliability testing center Beijing 100081China

In view of the current reliability evaluation requirements of warship equipment based on component, this paper comprehensively considered the characteristics of components,and the component identification method, structural decomposition method,component architecture modeling method were studied for warship equipment software. Based on the characteristics of warship equipment component, this paper proposed a formal modeling language based on Petri nets to realize the modeling of component software architecture and laid a foundation for the reliability evaluation method research of warship equipment component.

关键词： warship equipment component software software architecture component identification component modeling reliability evaluation

Practical Strategies to Improve Test Efficiency

在线全文

学校读者我要写书评

暂无评论

Tsinghua Science and Technology 2007年第S1期12卷 250-254页

作者：丁志刚汪泓澄凌良合 Shanghai Development center of software Technology Shanghai Key Laboratory of Computer Software Evaluating and Testing

This paper introduces strategies to detect software bugs in earlier life cycle stage in order to improve test efficiency. Static analysis tool is one of the effective methods to reveal software bugs during software development. Three popular static analysis tools are introduced, two of which, PolySpace and Splint, are compared with each other by analyzing a set of test cases generatedd by the authors. PolySpace can reveal 60% bugs with 100% R/W ratio (ratio of real bugs and total warnings), while Splint reveal 73.3% bugs with 44% R/W ratio. And they are good at finding different categories of bugs. Two strategies are concluded to improve test efficiency, under the guideline that static analysis tools should be used in finding different categories of bugs according to their features. The first one aims at finding bugs as many as possible, while the second concentrates to reduce the average time on bug revelation. Experimental data shows the first strategy can find 100% bugs with 60% R/W ratio, the second one find 80% bugs with 66.7% R/W ratio. Experiment results prove that these two strategies can improve the test efficiency in both fault coverage and testing time.

关键词： static analysis PolySpace splint software bug