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Achieving ultrahigh strength and ductility via high-density nanoprecipitates triggering multiple deformation mechanisms in a dual-aging high-entropy alloy with precold deformation

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材料科学技术（英文版） 2025年第2期205卷 27-41页

作者： Liyuan Liu Yang Zhang Zhongwu Zhang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China State Key Laboratory of Metal Materials for Marine Equipment and Application Anshan 114009China

How to achieve high-entropy alloys(HEAs)with ultrahigh strength and ductility is a challenging *** strengthening is one of the methods to significantly enhance strength,but unfortunately,ductility will be *** overcome the strength-ductility trade-off,the strategy of this study is to induce the formation of high-density nanoprecipitates through dual aging(DA),triggering multiple deformation mechanisms,to obtain HEAs with ultrahigh strength and ***,the effect of precold deforma-tion on precipitation behavior was studied using Ni35(CoFe)55V5Nb5(at.％)HEAas the *** results reveal that the activation energy of recrystallization is 112.2 kJ/*** the precold-deformation amount increases from 15％to 65％,the activation energy of precipitation gradually decreases from 178.8 to 159.7 kJ/*** precipitation time shortens,the size of the nanoprecipitate decreases,and the den-sity ***,the thermal treatment parameters were optimized,and the DA process was customized based on the effect of precold deformation on precipitation ***-density L12 nano-precipitates(～3.21 × 1025 m-3)were induced in the 65％precold-deformed HEA,which led to the si-multaneous formation of twins and stacking fault(SF)networks during *** yield strength(YS),ultimate tensile strength,and ductility of the DA-HEA are～2.0 GPa,～2.2 GPa,and～12.3％,*** with the solid solution HEA,the YS of the DA-HEA increased by 1,657 MPa,possessing an astonishing increase of～440％.The high YS stems from the precipitation strengthening contributed by the L12 nanoprecipitates and the dislocation strengthening contributed by precold *** synergistically enhanced ductility stems from the high strain-hardening ability under the dual support of twinning-induced plasticity and SF-induced plasticity.

关键词： High-entropy alloy Precold deformation Precipitation behavior Ultrahigh strength Deformation mechanism

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Deep Insight of Design,Mechanism,and Cancer Theranostic Strategy of Nanozymes

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Nano-Micro Letters 2024年第2期16卷 165-217页

作者： Lu Yang Shuming Dong Shili Gai Dan Yang He Ding Lili Feng Guixin Yang Ziaur Rehman Piaoping Yang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001People’s Republic of China Yantai Research Institute Harbin Engineering UniversityYantai 264000People’s Republic of China Key Laboratory of Green Chemical Engineering and Technology of Heilongjiang Province College of Material Science and Chemical EngineeringHarbin University of Science and TechnologyHarbin 150040People’s Republic of China Department of Chemistry Quaid-i-Azam UniversityIslamabad 45320Pakistan

Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction conditions,good stability,and suitable for large-scale ***,with the cross fusion of nanomedicine and nanocatalysis,nanozyme-based theranostic strategies attract great attention,since the enzymatic reactions can be triggered in the tumor microenvironment to achieve good curative effect with substrate specificity and low side ***,various nanozymes have been developed and used for tumor *** this review,more than 270 research articles are discussed systematically to present progress in the past five ***,the discovery and development of nanozymes are ***,classification and catalytic mechanism of nanozymes are ***,activity prediction and rational design of nanozymes are focused by highlighting the methods of density functional theory,machine learning,biomimetic and chemical ***,synergistic theranostic strategy of nanozymes are ***,current challenges and future prospects of nanozymes used for tumor theranostic are outlined,including selectivity,biosafety,repeatability and stability,in-depth catalytic mechanism,predicting and evaluating activities.

关键词： Nanozymes Classification Prediction and design Catalytic mechanism Tumor theranostics

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The highest melting point material:Searched by Bayesian global optimization with deep potential molecular dynamics

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Journal of Advanced Ceramics 2023年第4期12卷 803-814页

作者： Yinan Wang Bo Wen Xingjian Jiao Ya Li Lei Chen Yujin Wang Fu-Zhi Dai Artificial Intelligence for Science Institute Beijing 100084China Science and Technology on Advanced Functional Composite Laboratory Aerospace Research Institute of Materials&Processing TechnologyBeijing 100076China College of Computer Science and Technology Heilongjiang Institute of TechnologyHarbin 150001China Institute for Advanced Ceramics School of Materials Science and EngineeringHarbin Institute of TechnologyHarbin 150001China Key Laboratory of Advanced Structural-Functional Integration Materials&Green Manufacturing Technology Harbin Institute of TechnologyHarbin 150001China DP Technology Bejing 100080China

The interest in refractory materials is increasing rapidly in recent decades due to the development of hypersonic ***,the substance that has the highest melting point(Tm)keeps a secret,since precise measurements in extreme conditions are overwhelmingly *** the present work,an accurate deep potential(DP)model of a Hf-Ta-C-N system was first trained,and then applied to search for the highest melting point material by molecular dynamics(MD)simulation and Bayesian global optimization(BGO).The predicted melting points agree well with the experiments and confirm that carbon site vacancies can enhance the melting point of rock-saltstructure *** solid solution with N is verified as another new and more effective melting point enhancing approach for HfC,while a conventional routing of the solid solution with Ta(e.g.,HfTa_(4)C_(5))is not suggested to result in a maximum melting *** highest melting point(~4236 K)is achieved with the composition of HfCo.638No.271,which is~80 K higher than the highest value in a Hf-C binary *** mechanism of the N addition is believed to be unstable C-N and N-N bonds in liquid phase,which reduces liquid phase entropy and renders the liquid phase less *** improved melting point and less gas generation during oxidation by the addition of N provide a new routing to modify thermal protection materials for the hypersonic vehicles.

关键词： melting point(T_(m)) carbides carbonitrides deep potential(DP) Bayesiannglobal optimization(BGO)

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A Digital Twin and Consensus Empowered Cooperative Control Framework for Platoon-Based Autonomous Driving

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清华大学学报自然科学版（英文版） 2025年第3期30卷 1096-1111页

作者： Jiayu Cao Supeng Leng Kai Xiong Xiaosha Chen School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 518110China College of Computer Science and Technology and also with College of Data Science Taiyuan University of TechnologyTaiyuan 030024China

Platoon-based autonomous driving is indispensable for traffic automation,but it confronts substantial constraints in rugged terrains with unreliable links and scarce communication *** paper proposes a novel hierarchical Digital Twin(DT)and consensus empowered cooperative control framework for safe driving in harsh ***,leveraging intra-platoon information exchange,one platoon-level DT is constructed on the leader and multiple vehicle-level DTs are distributed among platoon *** leader first makes critical platoon-driving decisions based on the platoon-level ***,considering the impact of unreliable links on the platoon-level DT accuracy and the consequent risk of unsafe decision-making,a distributed consensus scheme is proposed to negotiate critical decisions *** successful negotiation,vehicles proceed to execute critical decisions,relying on their vehicle-level ***,a Space-Air-Ground-Integrated-Network(SAGIN)enabled information exchange is utilized to update the platoon-level DT for subsequent safe decision-making in scenarios with unreliable links,no roadside units,and obstructed ***,based on this framework,an adaptive platooning scheme is designed to minimize total delay and ensure driving *** results indicate that our proposed scheme improves driving safety by 21.1％and reduces total delay by 24.2％in harsh areas compared with existing approaches.

关键词： platoon autonomous driving distributed consensus digital twin space-air-ground integrated network

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Effects of Blending Ratio on Combustion and NO Emission Characteristics during Co-Firing of Semi-Char and Lignite in a 350 kW Pulverized Coal-Fired Furnace

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Journal of Thermal science 2023年第3期32卷 1292-1305页

作者： YAN Yonghong PENG Zhengkang SUN Liutao CHEN Dengke SUN Rui College of Electrical and Power Engineering Taiyuan University of TechnologyTaiyuan 030024China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China

The influence of the blending ratio of pyrolyzed semi-char(SC)on the ignition,NO emission and burnout characteristics of lignite co-fired with SC was investigated in a 350 kW fuel-rich/lean combustion *** flame temperature and concentrations of gaseous species including O_(2),CO,and NO,were measured in *** results indicated that the ignition characteristics of the blended fuel worsened with increasing SC blending ratio,such as an elongated ignition standoff *** addition of SC to lignite delayed the appearance of a stable flame boundary,and the stable combustion zone moved down,but the final combustion stability was gradually strengthened in the later combustion *** emission concentration at the primary combustion zone(PCZ)outlet was the lowest at 472.6 mg/m^(3)@6%O_(2)when the SC blending ratio was 25%.The combustion zone and reducing zone areas in PCZ were defined to evaluate the NO reduction characteristics,and quantitative analysis using a multiple linear regression model showed that heterogeneous reduction was more important than homogeneous reduction in lowering NO *** Raman spectrum of the char sample indicated that the addition of lignite promoted the formation of small aromatic rings in the early ignition stage,corresponding to a higher char *** burnout ratio of pure lignite was maximal and was decreased by increasing the SC blending ***,considering the ignition standoff distance,NO emission,and burnout ratio,the optimum SC blending ratio was estimated to be 25%.

关键词： co-firing blending ratio ignition characteristics NO emission burnout ratio

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A Survey of the Application of Neural Networks to Event Extraction

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Tsinghua science and technology 2025年第2期30卷 748-768页

作者： Jianye Xie Yulan Zhang Huaizhen Kou Xiaoran Zhao Zhikang Feng Lekang Song Weiyi Zhong College of Computer Science and Technology China University of Petroleum(East China)Qingdao 266000China Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261000China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210000China School of Computer Science Qufu Normal UniversityRizhao 276800China

Event extraction is an important part of natural language information extraction,and it’s widely employed in other natural language processing tasks including question answering and machine reading ***,there is a lack of recent comprehensive survey papers on event *** the past few years,numerous high-quality and innovative event extraction methods have been proposed,making it necessary to consolidate these new developments with previous work in order to provide a clear overview for researchers and serve as a reference for future *** addition,event detection is a fundamental sub-task in event extraction,previous survey papers have often overlooked the related work on event ***,this paper aims to bridge these gaps by presenting a comprehensive survey of event extraction,including recent advancements and an analysis of previous research on event *** resources for event extraction are first introduced in this research,and then the numerous neural network models currently employed in event extraction tasks are divided into four types:word sequence-based methods,graph-based neural network methods,external knowledge-based approaches,and prompt-based *** compare and contrast them in depth,pointing out the flaws and difficulties with existing ***,we discuss the future of event extraction development.

关键词： event extraction natural language processing event extraction methods graph neural network prompt-based learning

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Advanced Machine Learning Approaches for Breast Cancer Detection with Neutrosophic Sets

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Neutrosophic Sets and Systems 2025年 81卷 273-284页

作者： Elbehiery, Hussam Fathi, Hanaa Eassa, Mohamed Abdelhafeez, Ahmed Abdellah, Mohamed Refaat Mahmoud, Hadeer Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt College of Information Technology Amman Arab University Amman Jordan Applied Science Research Center Applied Science Private University Amman Jordan The Department of Computer Science College of Information Technology Misr University for Science and Technology Cairo Egypt Department of Artificial Intelligence Faculty of Computers and Artificial Intelligence Modern University for Technology & Information Cairo Egypt

Breast Cancer (BC) remains a significant health challenge for women and is one of the leading causes of mortality worldwide. Accurate diagnosis is critical for successful therapy and increased survival rates. Recent advances in medical imaging and computational technologies have enabled more precise methods of detecting and evaluating breast cancer. Accurate analysis and diagnosis utilizing medical imaging have developed as essential research topics, providing important help in clinical decision-making for various illnesses, including breast cancer. Machine learning (ML) can accurately predict breast cancer. But the breast cancer data has vague and uncertainty information. So, the neutrosophic sets (NSs) are used in this study to deal with uncertainty data. We convert the original dataset into neutrosophic data with three components such as truth, indeterminacy, and falsity values. Then we applied four ML models with N-data such as logistic regression, gradient boosting (GB), k-nearest neighbor (KNN), and support vector machines (SVM), to improve diagnostic accuracy. Then we compared the ML models with and without using N-data. The results show the logistic regression has higher accuracy with 98.6% with the N-data and 95.80% without N-data. So, the NSs can improve the accuracy of ML models. © 2025, university of New Mexico. All rights reserved.

关键词： Lung cancer

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Facile fabrication of graphene/g-C_(3)N_(4) for electromagnetic wave absorption

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Nano Research 2024年第3期17卷 1687-1698页

作者： Qiang Su Yunfei He Dongdong Liu Daguang Li Long Xia Xiaoxiao Huang Bo Zhong School of Materials Science and Engineering Harbin Institute of Technology WeihaiWeihai 264209China Weihai Yunshan Technology Co. Ltd.Weihai 264200China State Key Laboratory on Integrated Optoelectronics College of Electronic Science&EngineeringJilin UniversityChangchun 130012China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China

With the development of the miniaturization of electronic equipment and lightweight weapon equipment,there are new requirements for electromagnetic wave absorption material(EMWAM).EMWAM has outstanding electromagnetic wave absorption properties and lightweight characteristics become an important direction of *** this study,graphene/g-C_(3)N_(4)(GGCN)EMWAM was first synthesized in situ by simple heat treatment,in which the g-C_(3)N_(4) had a porous structure and dispersed on the surface of *** impedance matching of the GGCN was well adjusted by decreasing the dielectric constant and attenuation constant due to the g-C_(3)N_(4) semiconductor property and the graphite-like *** EMW loss mechanism of GGCN was also analyzed by simulating GGCN’s electric field mode distribution and resistance loss power *** analysis result shows that the distribution of g-C_(3)N_(4) among GGCN sheets can produce more polarization effects and relaxation effects by increasing the lamellar ***,the polarization loss of GGCN could be increased successfully by porous g-C_(3)N_(4).Ultimately,the EMW absorption property of GGCN is optimized significantly,and GGCN exhibits excellent EMW absorption *** the thickness is 2 mm,the effective absorption bandwidth(EAB)can reach 4.6 GHz,and when the thickness is 4.5 mm,the minimum reflection loss(RLmin)at 4.56 GHz can reach-34.69 ***,the practical application of EMWAM was studied by radar cross-section(RCS)simulation,showing that GGCN has a good application prospect.

关键词： graphene/g-C_(3)N_(4) impedance matching simulation analysis dielectric loss excellent electromagnetic wave absorption

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A Novel Reliable and Trust Objective Function for RPL-Based IoT Routing Protocol

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computers, Materials & Continua 2025年第2期82卷 3467-3497页

作者： Mariam A.Alotaibi Sami S.Alwakeel Aasem N.Alyahya Department of Computer Engineering College of Computer ScienceKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science and Information Technology Shaqra UniversityShaqra11961Saudi Arabia

The Internet of Things (IoT) integrates diverse devices into the Internet infrastructure, including sensors, meters, and wearable devices. Designing efficient IoT networks with these heterogeneous devices requires the selection of appropriate routing protocols, which is crucial for maintaining high Quality of Service (QoS). The Internet Engineering Task Force’s Routing Over Low Power and Lossy Networks (IETF ROLL) working group developed the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) to meet these needs. While the initial RPL standard focused on single-metric route selection, ongoing research explores enhancing RPL by incorporating multiple routing metrics and developing new Objective Functions (OFs). This paper introduces a novel Objective Function (OF), the Reliable and Secure Objective Function (RSOF), designed to enhance the reliability and trustworthiness of parent selection at both the node and link levels within IoT and RPL routing protocols. The RSOF employs an adaptive parent node selection mechanism that incorporates multiple metrics, including Residual Energy (RE), Expected Transmission Count (ETX), Extended RPL Node Trustworthiness (ERNT), and a novel metric that measures node failure rate (NFR). In this mechanism, nodes with a high NFR are excluded from the parent selection process to improve network reliability and stability. The proposed RSOF was evaluated using random and grid topologies in the Cooja Simulator, with tests conducted across small, medium, and large-scale networks to examine the impact of varying node densities. The simulation results indicate a significant improvement in network performance, particularly in terms of average latency, packet acknowledgment ratio (PAR), packet delivery ratio (PDR), and Control Message Overhead (CMO), compared to the standard Minimum Rank with Hysteresis Objective Function (MRHOF).

关键词： IoT LLNs RPL objective function OF MRHOF OF0 routing metrics reliability trustworthiness

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Resource Allocation in UAV-Assisted Mobile Edge Computing Systems 12

Resource Allocation in UAV-Assisted Mobile Edge Computing Sy...

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12th IEEE International Conference on computer science and Network technology, ICCSNT 2024

作者： Han, Xiao Wang, Huiqiang Wang, Chengbo Harbin Engineering University Computer Science and Technology Harbin China

ISBN: (纸本)9798350350791

In a crowdsensing system, effective transmission of sensing data is an important step in improving task distribution efficiency. In real-life scenarios, when resources are limited or geographic conditions are harsh, Unmanned Aerial Vehicles (UAV) can often be used for data transmission. This paper proposes a group intelligence sensing task distribution method under dynamic topology conditions to solve the problems of unreachable links or high network overhead caused by the dynamic topology of UAVs. This method uses the Markov model to model the data transmission process, and on this basis proposes an improved task distribution method based on topology awareness to achieve efficient task forwarding. The final experimental results show that compared with the traditional self-organizing network data transmission scheme for opportunistic networks, the scheme proposed in this paper can better solve the problems of routing voids and blind paths, and effectively improve the network lifetime while realizing a lower end-To-end delay, with better transmission performance. © 2024 IEEE.

关键词： Markov processes

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