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Frontiers in high entropy alloys and high entropy functional materials

Rare Metals 2024年第10期43卷 4639-4776页

作者： Wen-Tao Zhang Wen Huang Fu-Jie yu Qi zhao Xin-Dong Zhu Tao Feng Yao Jiang Xiao-Ming Li Xue-Fei Miao He Zhu Si Lan Xue-Qian Wang Bao-Long Shen Zhe Jia Feng-Qi Zhang Wei Wang Qi Liu Yang Ren Xun-Li Wang Xiao-Ya Cui Xiao-Yang Wang Ya-Nan Chen Bing-Bing Fan Meng-Ru Li Qi-Long Gao Jia-Ming Guo Zeng-Bao Jiao Zhi-Min Guo yu-ping zhao Qian yu Rui Huang Ling-Kun Zhang Yi-ping Lu Xu-Bo Li Huai-Jun Lin Yan Ma Wei-Ming Yang Zhi-Hua Shen Hai-Yan He Yong-Gang Sun Yong-Jiang Huang De-Zhuang Wang Qing-Feng Liu Fei-Yang Wang Hui Liu Hong-Hui Wu Li-Qiang Wang Yang Lu Nan Wang Tian-Li Wang Wei-Bing Liao Yi-Han Wang yuan Wu yu-Zhen Yin Jie Pan Yi Zhang Qing Wang Jian-Yang Zhang Tao Yang Yasir Sohail Jin-yu Zhang Hua Ji Qiang Li Wei-Di Liu Zhi-Gang Chen Xiong-Jun Liu Wen Ma Liang Mao Zhen-Duo Wu School of Materials Science and Engineering Nanjing University of Science and Technology Jiangsu Key Laboratory for Advanced Metallic Materials School of Materials Science and Engineering Southeast University Department of Physics City University of Hong Kong School of Materials Science and Engineering Tianjin University School of Physics and Microelectronics Zhengzhou University Department of Mechanical Engineering Research Institute for Advanced Manufacturing The Hong Kong Polytechnic University Center of Electron Microscopy and State Key Laboratory of Silicon Materials School of Materials Science and Engineering Zhejiang University Key Laboratory of Solidification Control and Digital Preparation Technology (Liaoning Province) School of Materials Science and Engineering Dalian University of Technology Institute of Advanced Wear & Corrosion Resistance and Functional Materials Jinan University School of Mechanics and Civil Engineering China University of Mining and Technology School of Physical Sciences Great Bay University School of Materials Science andEngineering Harbin Institute of Technology State Key Laboratory of Materials-Oriented Chemical Engineering College of Chemical Engineering Nanjing Tech University Beijing Advanced Innovation Center for Materials Genome Engineering Research Institute for Carbon Neutrality University of Science and Technology Beijing Department of Mechanical Engineering The University of Hong Kong School of Computing Macquarie University Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Physics and Optoelectronic Engineering Shenzhen University State Key Laboratory for Advanced Metals and Materials University of Science and Technology Beijing State Key Laboratory of Materials Processing and Die & Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Institute of materials Shanghai University Department of Materials Science and Engineering C

Owing to their exceptional properties, high-entropy alloys(HEAs) and high-entropy materials have emerged as promising research areas and shown diverse applications. Here,the recent advances in the field are comprehensively reviewed,organized into five sections. The first section introduces the background of HEAs, covering their definition, significance,application prospects, basic properties, design principles, and microstructure. The subsequent section focuses on cutting-edge high-entropy structural materials, highlighting developments such as nanostructured alloys, grain boundary engineering,eutectic systems, cryogenic alloys, thin films, micro-nano-lattice structures, additive manufacturing, high entropy metallic glasses, nano-precipitate strengthened alloys, composition modulation, alloy fibers, and refractory systems. In the following section, the emphasis shifts to functional materials, exploring HEAs as catalysts, magneto-caloric materials, corrosion-resistant alloys, radiation-resistant alloys, hydrogen storage systems, and materials for biomedicine. Additionally, the review encompasses functional high-entropy materials outside the realm of alloys, including thermoelectric, quantum dots, nanooxide catalysts, energy storage materials, negative thermal expansion ceramics,and high-entropy wave absorption materials. The paper concludes with an outlook, discussing future directions and potential growth areas in the field. Through this comprehensive review,researchers, engineers, and scientists may gain valuable insights into the recent progress and opportunities for further exploration in the exciting domains of high-entropy alloys and functional materials.

关键词： Cutting-edge structural materials Cutting-edgefunctional materials High entropy alloys

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Targeting CD47-SIRPα axis for Hodgkin and non-Hodgkin lymphoma immunotherapy

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Genes & Diseases 2024年第1期11卷 205-217页

作者： Pengcheng zhao Longyan Xie Lei yu ping Wang School of Life Sciences and Medicine Shandong University of TechnologyZiboShandong 255000China Tongji University Cancer Center Shanghai Tenth People's HospitalSchool of MedicineTongji UniversityShanghai 200092China

The interaction between cluster of differentiation 47(CD47)and signal regulatory proteinα(SiRPa)protects healthy cells from macrophage attack,which is crucial for maintain-ing immune *** of CD47 occurs widely across various tumor cell types and transmits the"don't eat me"signal to macrophages to avoid phagocytosis through binding to *** of the CD47-SIRPa axis is therefore a promising approach for cancer *** is the most common hematological malignancy and is an area of unmet clin-ical *** review mainly described the current strategies targeting the CD47-SIRPa axis,including antibodies,SiRPaFc fusion proteins,small molecule inhibitors,and peptides both in preclinical studies and clinical trials with Hodgkin lymphoma and non-Hodgkin lymphoma.

关键词： Cancer treatment CD47-SIRPαaxis Hodgkin lymphoma Immunotherapy Non-Hodgkin lymphoma

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Phase-field study of spinodal decomposition under effect of grain boundary

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Chinese Physics B 2021年第8期30卷 524-528页

作者： Ying-yuan Deng Can Guo Jin-Cheng Wang Qian Liu yu-ping zhao Qing Yang School of Materials Science and Engineering Xi'an University of TechnologyXi'an 710048China State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi'an 710072China

Grain boundary directed spinodal decomposition has a substantial effect on the microstructure evolution and properties of polycrystalline *** morphological selection mechanism of spinodal decomposition at grain boundaries is a major challenge to reveal,and remains elusive so *** this work,the effect of grain boundaries on spinodal decomposition is investigated by using the phase-field *** simulation results indicate that the spinodal morphology at the grain boundary is anisotropic bicontinuous microstructures different from the isotropic continuous microstructures of spinodal decomposition in the bulk ***,at grain boundaries with higher energy,the decomposed phases are alternatingα/βlayers that are parallel to the grain *** the contrary,alternatingα/βlayers are perpendicular to the grain boundary.

关键词： spinodal decomposition grain boundary phase-field method pattern formation

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Understanding Human and Machine Interaction from Decision Perspective: An Empirical Study Based on the Game of Go

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Journal of Systems Science & Complexity 2024年第2期37卷 647-667页

作者： zhao ping LI Xuerong WANG Shouyang Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100190China

The authors aim to interpret human and AI interactions from the decision *** authors decompose the interaction analysis into the following main components in the context of interactions:Individual behavior patterns,interaction relationships,and comprehensive *** authors interpret intertemporal decisions from a physical perspective and employ cross-discipline concepts and methodologies to extract the behavior characteristics of players in the empirical case *** the individual behavior patterns,the authors find that human players prefer short-term periods to AI in *** interaction relationship analysis reveals a dynamic relationship between possible short-term co-movement and nearly counter-movement in the long *** authors apply principal component analysis to descriptive indicators and discover a regular decision *** main behavior pattern of players in the game of Go is switching between careful and daring *** differences in the decision hierarchies imply a discrepancy of patience between humans and AI.

关键词： Coherence analysis decision hierarchy machine behaviour multitaper spectral analysis

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Super-high bed sintering for iron ores:behaviors,causes and solutions of horizontal segregation on strand

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Journal of Iron and Steel Research International 2024年第7期31卷 1590-1596页

作者： Liang-ping Xu Hui-bo Liu Zhong-lin Dong Qiang Zhong yu-chao zhao Guang-hui Li School of Minerals Processing and Bioengineering Central South UniversityChangsha 410083HunanChina

Horizontal segregation has been a constraint to the development and application of super-high bed *** eliminate the horizontal segregation of super-high bed sintering,several typical sintering machines were sampled and analyzed,and theoretical calculation was made to compare the bed depth and their differences in different areas within the mixture ***,solutions were proposed and applied to a 265 m^(2) sintering *** results showed that the horizontal seg-regation of the 265 m^(2) sintering machine was dominated by particles larger than 8 mm with horizontal segregation degree of 0.48,while 360 and 550 m^(2) sintering machines were affected by 5-8 mm and 1-3 mm particles with horizontal segregation degree of 0.27 and 0.31,*** analysis indicated the different segregation distribution results from the matching of the bed depth of each area within the mixture ***,the horizontal segregation degree not larger than 0.06 was achieved by optimizing the time parameters and the division of three zones on the 265 m^(2) sintering machine.

关键词： Super-high bed sintering Horizontal segregation Feeder Particle distribution Agglomeration

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Latest insights into the global epidemiological features,screening,early diagnosis and prognosis prediction of esophageal squamous cell carcinoma

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World Journal of Gastroenterology 2024年第20期30卷 2638-2656页

作者： Yi-Xin zhao He-ping zhao Meng-Yao zhao Yan yu Xi Qi Ji-Han Wang Jing Lv Department of Clinical Laboratory Honghui HospitalXi’an Jiaotong UniversityXi’an 710054Shaanxi ProvinceChina Institute of Medical Research Northwestern Polytechnical UniversityXi’an 710072Shaanxi ProvinceChina

As a highly invasive carcinoma,esophageal cancer(EC)was the eighth most prevalent malignancy and the sixth leading cause of cancer-related death worldwide in *** squamous cell carcinoma(ESCC)is the major histological subtype of EC,and its incidence and mortality rates are decreasing *** to the lack of specific early symptoms,ESCC patients are usually diagnosed with advanced-stage disease with a poor prognosis,and the incidence and mortality rates are still high in many countries,especially in ***,enormous challenges still exist in the management of ESCC,and novel strategies are urgently needed to further decrease the incidence and mortality rates of *** the key molecular mechanisms underlying ESCC pathogenesis have not been fully elucidated,certain promising biomarkers are being investigated to facilitate clinical *** the advent and advancement of highthroughput technologies,such as genomics,proteomics and metabolomics,valuable biomarkers with high sensitivity,specificity and stability could be identified for ***,we aimed to determine the epidemiological features of ESCC in different regions of the world,especially in China,and focused on novel molecular biomarkers associated with ESCC screening,early diagnosis and prognosis prediction.

关键词： Esophageal squamous cell carcinoma Epidemiology Diagnosis Genomics Proteomics Metabolomics

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Understanding microstructure-property relationships of HPDC Al-Si alloy based on machine learning and crystal plasticity simulation

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Advances in Manufacturing 2024年第3期12卷 497-511页

作者： Qiang-Qiang Zhai zhao Liu ping Zhu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China National Engineering Research Center of Automotive Power and Intelligent Control Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China School of Design Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

Al-Si alloys manufactured via high-pressure die casting(HPDC)are suitable for a wide range of ***,the heterogeneous microstructure and unpredictable pore distribution of Al-Si high-pressure die castings result in significant variations in the mechanical properties,thus leading to a complicated microstructure-property relationship that is difficult to ***,a computational framework incorporating machine learning and crystal plasticity method is *** framework aims to provide a systematic and comprehensive understanding of this relationship and enable the rapid prediction of macroscopic mechanical properties based on the ***,we select eight variables that can effectively characterize the microstructural features and then obtain their statistical ***,based on 160 samples obtained via the Latin hypercube sampling method,representative volume elements are constructed,and the crystal plasticity fast Fourier transformation method is executed to obtain the macroscopic mechanical ***,the yield strength,elastic modulus,strength coefficient,and strain-hardening exponent are used to characterize the stress-strain curve,and Gaussian process regression models and microstructural variables are ***,sensitivity and univariate analyses based on these machine-learning models are performed to obtain insights into the microstructure-property relationships of the HPDC Al-Si *** results show that the Gaussian process regression models exhibit high accuracy(R2 greater than 0.84),thus confirming the viability of the proposed *** results of sensitivity analysis indicate that the pore size exerts the most significant effect on the mechanical ***,the proposed framework can not only be transferred to other alloys but also be employed for material design.

关键词： High-pressure die casting(HPDC) Machine learning Crystal plasticity Aluminum alloys

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CMAGAN:classifier-aided minority augmentation generative adversarial networks for industrial imbalanced data and its application to fault prediction

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Advances in Manufacturing 2024年第3期12卷 603-618页

作者： Wen-Jie Wang zhao Liu ping Zhu School of Mechanical Engineering Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China National Engineering Research Center of Automotive Power and Intelligent Control Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China School of Design Shanghai Jiao Tong UniversityShanghai200240People’s Republic of China

Class imbalance is a common characteristic of industrial data that adversely affects industrial data mining because it leads to the biased training of machine learning *** address this issue,the augmentation of samples in minority classes based on generative adversarial networks(GANs)has been demonstrated as an effective *** study proposes a novel GAN-based minority class augmentation approach named classifier-aided minority augmentation generative adversarial network(CMAGAN).In the CMAGAN framework,an outlier elimination strategy is first applied to each class to minimize the negative impacts of ***,a newly designed boundary-strengthening learning GAN(BSLGAN)is employed to generate additional samples for minority *** incorporating a supplementary classifier and innovative training mechanisms,the BSLGAN focuses on learning the distribution of samples near classification ***,it can fully capture the characteristics of the target class and generate highly realistic samples with clear ***,the new samples are filtered based on the Mahalanobis distance to ensure that they are within the desired *** evaluate the effectiveness of the proposed approach,CMAGAN was used to solve the class imbalance problem in eight real-world fault-prediction *** performance of CMAGAN was compared with that of seven other algorithms,including state-of-the-art GAN-based methods,and the results indicated that CMAGAN could provide higher-quality augmented results.

关键词： Class imbalance Minority class augmentation Generative adversarial network(GAN) Boundary strengthening learning(BSL) Fault prediction

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Features and formulae of sediment incipient motion in vegetated flow environment

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Journal of Hydrodynamics 2024年第2期36卷 331-339页

作者： yu-xuan Xu Wei-jie Wang Shi-bao Zhang Han-qing zhao Xue-kai Chen Hai-ping Zhang School of Water Conservancy North China University of Water Resources and Electric PowerZhengzhou450045China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower ResearchBeijing100038China China Three Gorges Corporation Wuhan430010China

Aquatic vegetation is a vital component of natural river ecosystems,playing a crucial role in maintaining ecological balance,providing habitat and improving water ***,the presence of vegetation results in increased resistance in vegetated channels compared with non-vegetated channels,rendering traditional sediment movement predictions inadequate for the ***,the concept of a vegetation influence factor,denoted by CDah,has been proposed by previous researchers to represent the effect of vegetation on sediment movement in *** this study,we focus on exploring the vegetation resistance coefficient(CD)among the vegetation influence factors,evaluating two different calculation methods for vegetation resistance coefficient,and presenting two expressions through genetic algorithm analysis to predict the incipient flow velocity of sediment in vegetated *** predicted values from the new formulae show excellent agreement with measured data,highlighting the high accuracy of the proposed methods in predicting the incipient flow velocity of *** results provide a solid theoretical basis for understanding the influence of aquatic vegetation on sediment particle movement.

关键词： Vegetation flow vegetation resistance coefficient genetic algorithm sediment initiation

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Contrasting strategies of optimizing carrier concentration in bulk InSe for enhanced thermoelectric performance

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Rare Metals 2024年第9期43卷 4425-4432页

作者： Hao-Nan Shi Shu-Lin Bai yu-ping Wang Li-Zhong Su Qian Cao Cheng Chang Li-Dong zhao School of Materials Science and Engineering Beihang UniversityBeijing 100191China School of Materials Science and Engineering Taiyuan University of Science and TechnologyTaiyuan 030024China Huabei Cooling Device Co.Ltd. Hebei 065400China

Indium selenide(InSe),as a wide-bandgap semiconductor,has received extensive attention in the flexible electronics field in recent years due to its exceptional plasticity and promising thermoelectric ***,the low carrier concentration severely limits its thermoelectric performance *** this work,we conducted contrasting strategies that can be employed to increase the carrier concentration of InSe,including bandgap narrowing and heterovalent ***,the carrier concentration initially increases as a result of the reduced bandgap upon Te alloying and then slightly decreases due to the weak electronegativity of *** Br doping realizes high carrier concentration by pushing the Fermi level into the conduction bands and activating the multiple *** the other hand,both Te and Br obviously suppress the thermal conductivity due to the point defect *** contrast,Br doping realizes a higher thermoelectric performance with a maximum ZT of~0.13 at 773 K benefiting from the better optimization of carrier *** work elucidates the strategies for enhancing carrier concentration at anion sites and demonstrates the high efficiency of halogen doping in ***,the carrier concentration of InSe is promising to be further optimized,and future work should focus on employing approaches such as cation doping or secondphase compositing.

关键词： Thermoelectric InSe Carrier concentration Bandgap Heterovalent doping

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