检索结果-南通市图书馆

精炼及浇注温度对K417G镍基高温合金组织及持久性能的影响

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

铸造 2021年第12期70卷 1417-1422页

作者：刘子禹仉凤江荀淑玲谢君舒德龙侯桂臣于金江周亦胄贵阳航发精密铸造有限公司贵州贵阳550014 中国科学院金属研究所辽宁沈阳110016

采用不同精炼及浇注温度制备K417G镍基高温合金,通过对合金的组织形貌进行观察分析,以及测试合金在760℃/645 MPa下的持久性能,研究了精炼温度、浇注温度等铸造工艺参数对K417G镍基高温合金组织及持久性能的影响。结果表明,提高精炼温... 详细信息

采用不同精炼及浇注温度制备K417G镍基高温合金,通过对合金的组织形貌进行观察分析,以及测试合金在760℃/645 MPa下的持久性能,研究了精炼温度、浇注温度等铸造工艺参数对K417G镍基高温合金组织及持久性能的影响。结果表明,提高精炼温度可降低铸态合金组织中的碳化物尺寸,并使碳化物分布更加均匀;降低浇注温度可降低合金的晶粒尺寸、枝晶间距以及碳化物尺寸,并使合金的共晶组织由γ'共晶转变为(γ+γ')共晶。合金在760℃/645 MPa拉伸持久期间的主要断裂机制为裂纹在枝晶间区域内的MC碳化物处萌生,并沿正应力方向扩展,导致合金发生持久断裂。其中,采用1500℃精炼,1450℃浇注的合金中碳化物尺寸较小且弥散分布是其具有较高持久寿命的主要原因。

关键词： K417G 精炼及浇注温度铸态组织持久性能

维普期刊数据库

Recent advances of metal vacancies in energy and environmental catalysis:Synthesis,characterization,and roles

在线全文

学校读者我要写书评

暂无评论

Green Energy & Environment 2025年第1期10卷 84-108页

作者： long Sun shunzheng Zhao Sirui Gao Ronghui Zhu Yiran Tan Xiaolong Tang Honghong Yi School of Energy and Environmental Engineering University of Science and Technology BeijingBeijing100083China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants Beijing100083China

With the ongoing depletion of fossil fuels,energy and environmental issues have become increasingly critical,necessitating the search for effective ***,being one of the hallmarks of modern industry,offers a promising avenue for ***,the question of how to significantly enhance the performance of catalysts has gradually drawn the attention of *** engineering,a commonly employed and effective approach to improve catalyst activity,has become a significant research focus in the catalysis field in recent *** vacancies have received extensive attention due to their simple ***,exploration of metal vacancies has remained stagnant for a considerable period,resulting in a scarcity of comprehensive reviews on this ***,based on the latest research findings,this paper summarizes and consolidates the construction strategies for metal vacancies,characterization techniques,and their roles in typical energy and environmental catalytic ***,it outlines potential challenges in the future,aiming to provide valuable references for researchers interested in investigating metal vacancies.

关键词： Metal vacancies Catalysis Construction strategies Characterization techniques Roles

维普期刊数据库

When Software Security Meets Large Language Models:A Survey

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 317-334页

作者： Xiaogang Zhu Wei Zhou Qing-long Han Wanlun Ma Sheng Wen Yang Xiang IEEE the School of Computer and Mathematical Sciences the University of Adelaide the School of Science Computing and Engineering Technologies Swinburne University of Technology

Software security poses substantial risks to our society because software has become part of our life. Numerous techniques have been proposed to resolve or mitigate the impact of software security issues. Among them, software testing and analysis are two of the critical methods, which significantly benefit from the advancements in deep learning technologies. Due to the successful use of deep learning in software security, recently,researchers have explored the potential of using large language models(LLMs) in this area. In this paper, we systematically review the results focusing on LLMs in software security. We analyze the topics of fuzzing, unit test, program repair, bug reproduction, data-driven bug detection, and bug triage. We deconstruct these techniques into several stages and analyze how LLMs can be used in the stages. We also discuss the future directions of using LLMs in software security, including the future directions for the existing use of LLMs and extensions from conventional deep learning research.

关键词： Large language models (LLMs) software analysis software security software testing

Simultaneous immobilization of multiple heavy metal(loid)s in contaminated water and alkaline soil inoculated Fe/Mn oxidizing bacterium

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 Environmental Sciences 2025年第1期147卷 370-381页

作者： Yi Wu Shengli Wang Jun Xu Fei Zang Song long Yining Wu Yuqing Wang Zhongren Nan Technology Research Center for Pollution Control and Remediation of Northwest Soil and Groundwater College of Earth and Environmental SciencesLanzhou UniversityLanzhou 730000China State Key Laboratory of Grassland Agro-ecosystems College of Pastoral Agriculture Science and TechnologyLanzhou UniversityLanzhou 730000China

Two strains of Fe/Mn oxidizing bacteria tolerant to high concentrations of multiple heavy metal(loid)s and efficient decontamination for them were *** surface of the bio-Fe/Mn oxides produced by the oxidation of Fe(II)and Mn(II)by Pseudomonas taiwanensis(marked as P4)and Pseudomonas plecoglossicida(marked as G1)contains rich reactive oxygen functional groups,which play critical roles in the removal efficiency and immobilization of heavymetal(loid)s in co-contamination *** isolated strains P4 and G1 can growwell in the following environments:pH 5-9,NaCl 0-4%,and temperature 20-30℃.The removal efficiencies of Fe,Pb,As,Zn,Cd,Cu,and Mn are effective after inoculation of the strains P4 and G1 in the simulated water system(the initial concentrations of heavy metal(loid)were 1 mg/L),approximately reaching 96%,92%,85%,67%,70%,54%and 15%,*** exchangeable and carbonate bound As,Cd,Pb and Cu are more inclined to convert to the Fe-Mn oxide bound fractions in P4 and G1 treated soil,thereby reducing the phytoavailability and bioaccessible of heavy metal(loid)*** research provides alternatives method to treat water and soil containing high concentrations of multi-heavy metal(loid)s.

关键词： Bio-Fe/Mn oxides Pseudomonas Heavy metal(loid)s Removal and immobilization

Research on the balance optimization algorithm of image recognition accuracy and speed based on autocollimator measurement

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optoelectronics Letters 2025年第2期21卷 121-128页

作者： LI Renpu MA long CUI Jiwen GUO Junqi Andrei KULIKOV WEN Dandan Chongqing Engineering Research Center of Intelligent Sensing Technology and Microsystem Chongqing University of Post and TelecommunicationsChongqing 400065China School of Instrumentation Science and Engineering Harbin Institute of TechnologyHarbin 150080China Higher School of Engineering and Technology ITMO UniversitySaint Petersburg 197101Russia

The autocollimator is an important device for achieving precise,small-angle,non-contact *** primarily obtains angular parameters of a plane target mirror indirectly by detecting the position of the imaging *** is limited report on the core algorithmic techniques in current commercial products and recent scientific *** paper addresses the performance requirements of coordinate reading accuracy and operational speed in autocollimator image *** proposes a cross-image center recognition scheme based on the Hough transform and another based on Zernike moments and the least squares *** experimental evaluation of the accuracy and speed of both schemes,the optimal image recognition scheme balancing measurement accuracy and speed for the autocollimator is *** these,the center recognition method based on Zernike moments and the least squares method offers higher measurement accuracy and stability,while the Hough transform-based method provides faster measurement speed.

关键词： image optimization recognition

维普期刊数据库

MixerKT:A Knowledge Tracing Model Based on Pure MLP Architecture

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2025年第1期82卷 485-498页

作者： Jun Wang Mingjie Wang Zijie Li Ken Chen Jiatian Mei shu Zhang Key Laboratory of Education Informatization for Nationalities Ministry of EducationYunnan Normal UniversityKunming650000China Yunnan Key Laboratory of Smart Education Yunnan Normal UniversityKunming650000China

In the field of intelligent education,the integration of artificial intelligence,especially deep learning technologies,has garnered significant *** tracing(KT)plays a pivotal role in this field by predicting students’future performance through the analysis of historical interaction data,thereby assisting educators in evaluating knowledgemastery and tailoring instructional *** knowledge tracingmethods,largely based on Recurrent Neural Networks(RNNs)and Transformer models,primarily focus on capturing long-term interaction patterns in sequential ***,these models may neglect crucial short-term dynamics and other relevant *** paper introduces a novel approach to knowledge tracing by leveraging a pure Multilayer Perceptron(MLP)*** proposeMixerKT,a knowledge tracing model based on theHyperMixer framework,which uniquely integrates global and localMixer feature *** architecture enables more effective extraction of both long-terminteraction trends and recent learning behaviors,addressing limitations in currentmodels thatmay overlook these key *** evaluations on twowidely-used datasets,ASSIS Tments2009 and Algebra2005,demonstrate that MixerKT consistently outperforms several state-of-the-art models,including DKT,SAKT,and Separated Self-Attentive Neural Knowledge Tracing(SAINT).Specifically,MixerKT achieves higher prediction accuracy,highlighting its effectiveness in capturing the nuances of learners’knowledge *** results indicate that our model provides a more comprehensive representation of student learning patterns,enhancing the ability to predict future performance with greater precision.

关键词： Knowledge tracing multilayer perceptron channel mixer sequence mixer

Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions

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 Environmental Sciences 2025年第3期149卷 68-78页

作者： Qiang Zhang Xin Li long Yu Lingxiao Wang Zhiqing Wen Pengchen Su Zhenli Sun Suhua Wang School of Environmental Science and Engineering Guangdong University of Petrochemical TechnologyMaoming 525000China MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China

The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient *** this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous *** proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/***,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/*** fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data ***,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model ***,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride *** results demonstrate that the developed model excels in terms of accuracy and *** groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.

关键词： Machine learning Aluminum ion detection Fluorine ion detection Fluorescence probe K-means model

Phase-transfer-shuttle generated in situ enables novel SN1-type fluorination of sulfonium ylide with hydrofluoric acid

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年第2期68卷 641-648页

作者： Yisa Xiao Rui Wang Zhaoxuan Xu Qunchao Zhao Renyi Pang Tao Dong long Lu Qilong Shen Key Laboratory of Fluorine and Nitrogen Chemistry and Advanced Materials Shanghai Institute of Organic ChemistryUniversity of Chinese Academy SciencesChinese Academy of SciencesShanghai 200032China

The development of a nucleophilic fluorination protocol using hydrofluoric acid as the fluoride source represents a long-sought goal in the field of organofluorine *** report herein the realization of such a reaction that employed alkyl-substituted sulfonium ylides as the *** key to the success of the protocol was attributed to two factors:First,as a Brϕnsted base,the ylide was able to be protonated by HFaq,thus serving as a phase-transfer shuttle generated in situ to bring F−from aqueous phase to the organic phase promoting desolvation of fluoride ***,after protonation,a sulfonium salt,a good leaving group,was generated and subsequent attacked by the fluoride to afford the alkyl *** investigation indicates that the reaction occurs via an SN1 *** of the nature of the cationic intermediate in the reaction,two attractive rearrangement-fluorination approaches including 1,2-aryl migration fluorination and ring-expansion fluorination were disclosed.

关键词： SN1 fluorination hydrofluoric acid sulfonium ylide cation rearrangement

designing the counter pressure casting gating system for a large thin-walled cabin by machine learning

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

China Foundry 2025年

作者： Xiao-long Zhang Hua Hou Xiao-long Pei Zhi-qiang Duan Yu-hong Zhao School of Materials Science and Engineering Collaborative Innovation Center of Ministry of Education and Shanxi Province for High-performance Al/Mg Alloy Materials North University of China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Institute of Materials Intelligent Technology Liaoning Academy of Materials

The design of casting gating system directly determines the solidification sequence, defect severity,and overall quality of the casting. A novel machine learning strategy was developed to design the counter pressure casting gating system of a large thin-walled cabin casting. A high-quality dataset was established through orthogonal experiments combined with design criteria for the gating system. Spearman's correlation analysis was used to select high-quality features. The gating system dimensions were predicted using a gated recurrent unit(GRU) recurrent neural network and an elastic network model. Using EasyCast and ProCAST casting software, a comparative analysis of the flow field, temperature field, and solidification field can be conducted to demonstrate the achievement of steady filling and top-down sequential solidification. Compared to the empirical formula method, this method eliminates trial-and-error iterations, reduces porosity, reduces casting defect volume from 11.23 cubic centimeters to 2.23 cubic centimeters, eliminates internal casting defects through the incorporation of an internally cooled iron, fulfilling the goal of intelligent gating system design.

关键词：