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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 182-187页

作者： ÇELİK Erçevik ATA ESENER Pınar ÖZTÜRK Esra AKSÖZ Sezen Nevşehir HacıBektaşVeli University Department of Physics50300NevşehirTurkey Erciyes University Graduate School of Natural and Applied Sciences38039KayseriTurkey Kocaeli University Department of Physics41380KocaeliTurkey

Ag-In intermetallic Alloys were produced by using vacuum arc furnace. Differential Scanning Calorimetry(DSC) and Energy Dispersive X-Ray Spectrometry(EDX) were used to determine the thermal properties and chemical composition of the phases respectively. Microhardness values of Ag-In intermetallics were calculated with Vickers hardness measurement method. According to the experimental results, Ag-34 wt%In intermetallic system generated the best results of energy saving and storage compared to other intermetallic systems. Also from the microhardness results, it was observed that intermetallic Alloys were harder than pure silver and Ag-26 wt%In system had the highest microhardness value with 143.45 kg/mm^(2).

关键词： thermal properties microstructure characterization microhardness Alloys material characterization

Recent developments in high-pressure die-cast magnesium Alloys for automotive and future applications

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Journal of Magnesium and Alloys 2023年第1期11卷 78-87页

作者： Gerry Gang Wang J.P.Weiler Meridian Lightweight Technologies StrathroyOntario N7G 4H6Canada

The use of magnesium alloy high pressure die cast(HPDC)components for structural applications,especially in the automotive and transportation industries,where weight reduction is of a great concern,is increasing.As new applications are developing and existing applications are becoming more complex,there is a need for improved properties from magnesium HPDC Alloys.This paper reviews the recent developments in HPDC magnesium Alloys for transportation applications.Compared to the conventional HPDC magnesium Alloys,i.e.AZ91D,AM50A/AM60B and AE44,these new Alloys have one or more of the following properties:higher strength,higher ductility,superior high-temperature properties or higher thermal conductivities.In this work,characteristics which are important in product manufacturing or product performance will be evaluated and discussed,including die castability of powertrain component or thin-walled structural component,mechanical properties at elevated temperatures and ductility.Results indicate that these Alloys have great potentials to be added to the current magnesium HPDC alloy family and being used in actual automotive and other transport applications.

关键词： Alloys alloy ductility

Abnormal grain growth induced byδ→γphase transformation in Fe-based shape memory Alloys

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Journal of Materials Science & Technology 2024年第5期172卷 196-201页

作者： Huabei Peng Liqiu Yong Gaixia Wang Jiazhen Yan Bing Xu Yuhua Wen School of Mechanical Engineering Sichuan UniversityChengdu 610065China Science and Technology on Reactor Fuel and Materials Laboratory Nuclear Power Institute of ChinaChengdu 610041China

Grain boundaries,including low-angle,high-angle,and coinci-dence boundaries,are intrinsic interfaces in polycrystalline materi-als.During heat-treatment at sufficiently high temperatures,grain boundary migration occurs because the grain boundaries are ther-modynamically unstable.Consequently,grain growth occurs due to a decrease in grain boundary area after heat-treatment[1].In general,there are two types of grain growth:normal grain growth,where grains grow uniformly,and abnormal grain growth,where one or a few grains selectively grow and engulf surround-ing smaller grains,leading to the formation of large grains,some-times several millimeters or greater in size[2].The classical tech-nique to achieve abnormal grain growth is the strain-annealing method,which involves subjecting the material to a small strain followed by annealing[3,4].This method has been reported to ob-tain single-crystal wires or plates[1].Additionally,abnormal grain growth can be achieved by plastic straining at high temperatures,resulting in the fabrication of large grains or single crystals[5].However,the above methods are not applicable to components with complicated shapes due to the inevitable deformation pro-cess.Recently,Omori et al.developed a simply method of abnor-mal grain growth to fabricate ultra-large grains,even single crys-tals,in Cu-Al-Mn[1],Fe-Mn-Al-Ni[2],and Fe-Mn-Al-Ni-Cr[6]al-loys.This method involves applying cyclic heat treatment between a high temperature BCC single-phase region and a low tempera-ture BCC+FCC two-phase region[1,2,6-12].Note that the cyclic heat treatment resulted in the formation of BCC sub-grain struc-tures responsible for abnormal grain growth[1,2,6-12].In addition,Yang et al.reported that abnormal grain growth occurred at above 900℃,and large-grains,even single crystals,were obtained only through annealing cast Cu-based polycrystalline Alloys contained coherent nano-particles[13,14].Notably,the cyclic heat treatment and annealing cast Alloys are deformation-free and much simpler than the strain-anne

关键词： grain Alloys deformation

Entropy engineering in CaZn_(2)Sb_(2)-YbMg_(2)Sb_(2)Zintl Alloys for enhanced thermoelectric performance

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Rare Metals 2022年第9期41卷 2998-3004页

作者： Ke-Jia Liu Zong-Wei Zhang Chen Chen Li-Hua Wei Huo-Lun He Jun Mao Qian Zhang School of Materials Science and Engineering and Institute of Materials Genome&Big DataHarbin Institute of TechnologyShenzhen518055China Department of Mechanical Engineering The University of Hong KongHong Kong999077China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin150001China

The significant atomic disorder induced by entropy engineering can effectively suppress lattice thermal conductivity and improve thermoelectric performance.The variety of compositions of Zintl phases offers a wide range of possibilities for entropy engineering.Herein we successfully prepared a five-component solid solution(CaZn_(2)Sb_(2))_(0.5)(YbMg_(2)Sb_(2))_(0.5) with a configurational entropy of~1.40R,whereR is the gas constant.As a result,the room-temperature lattice thermal conductivity was only~0.68 W·m^(-1)·K^(-1),which is lower than that of all AM_(2)Sb_(2) Zintl phases.

关键词： Alloys entropy performance

Solid solution strengthening of high-entropy Alloys from first-principles study

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Journal of Materials Science & Technology 2022年第26期121卷 105-116页

作者： H.L.Zhang D.D.Cai X.Sun H.Huang S.Lu Y.Z.Wang Q.M.Hu L.Vitos X.D.Ding State Key Laboratory for Mechanical Behavior of Materials Frontier Institute of Science and TechnologyXi’an Jiaotong UniversityXi’an 710049China Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research College of StomatologyXi’an Jiaotong UniversityXi’an 710049China Department of Materials Science and Engineering The Ohio State University2041 College RoadColumbusOH 43210United States Institute of Metal Research Chinese Academy of SciencesShenyang 110016China Science and Technology on Surface Physics and Chemistry Laboratory Jiangyou 621908China Applied Materials Physics Department of Materials Science and EngineeringRoyal Institute of TechnologyStockholm SE-10044Sweden

Solid solution strengthening(SSS)is one kind of strengthening mechanisms and plays an important role in alloy design,in particular for single-phase Alloys including high-entropy Alloys(HEAs).The classical Labusch–Nabarro model and its expansions are most widely applicable to treating SSS of solid solution Alloys including both conventional Alloys(CAs)and HEAs.In this study,the SSS effects in a series of Febased CAs and HEAs are investigated by using the classical Labusch–Nabarro model and its expansions.The size misfit and shear modulus misfit parameters are derived from first-principles calculations.Based on available experimental data in combination with empirical SSS model,we propose fitting constants(i.e.,the ratio between experimental hardness and predicted SSS effect)for these two families of Alloys.The predicted host/alloy family-dependent fitting constants can be used to estimate the hardness of these SSS Alloys.General agreement between predicted and measured hardness values is satisfactory for both CAs and HEAs,implying that the proposed approach is reliable and successful.

关键词： Alloys Solid solution strengthening Hardness Size misfit parameter Shear modulus misfit parameter First-principles calculations

Recent progress in the machine learning-assisted rational design of Alloys

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International Journal of Minerals,Metallurgy and Materials 2022年第4期29卷 635-644页

作者： Huadong Fu Hongtao Zhang Changsheng Wang Wei Yong Jianxin Xie Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory for Advanced Materials Processing(MOE) University of Science and Technology BeijingBeijing 100083China Beijing Laboratory of Metallic Materials and Processing for Modern Transportation University of Science and Technology BeijingBeijing 100083China

Alloys designed with the traditional trial and error method have encountered several problems,such as long trial cycles and high costs.The rapid development of big data and artificial intelligence provides a new path for the efficient development of metallic materials,that is,machine learning-assisted design.In this paper,the basic strategy for the machine learning-assisted rational design of Alloys was introduced.Research progress in the property-oriented reversal design of alloy composition,the screening design of alloy composition based on models established using element physical and chemical features or microstructure factors,and the optimal design of alloy composition and process parameters based on iterative feedback optimization was reviewed.Results showed the great advantages of machine learning,including high efficiency and low cost.Future development trends for the machine learning-assisted rational design of Alloys were also discussed.Interpretable modeling,integrated modeling,high-throughput combination,multi-objective optimization,and innovative platform building were suggested as fields of great interest.

关键词： machine learning data mining rational design Alloys

Development of Ti_(0.85)Zr_(0.17)(Cr-Mn-V)_(1.3)Fe_(0.7)-based Laves phase Alloys for thermal hydrogen compression at mild operating temperatures

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Rare Metals 2022年第8期41卷 2588-2594页

作者： Zi-Ming Cao Pan-Pan Zhou Xue-Zhang Xiao Liu-Jun Zhan Zhi-Fei Jiang Shu-Mao Wang Li-Jun Jiang Li-Xin Chen State Key Laboratory of Silicon Materials School of Materials Science and EngineeringZhejiang UniversityHangzhou310027China Department of Materials Science and Engineering The University of ManchesterManchesterM139PLUK Institute of Energy Materials and Technology General Research Institute for Non-ferrous MetalsBeijing100088China Key Laboratory of Advanced Materials and Applications for Batteries of Zhejiang Province Hangzhou310013China

Metal hydride with proper hydrogen storage properties is the key component of hydride thermal hydrogen compressor.In this work,Ti_(0.85)Zr_(0.17)(Cr-Mn-V)_(1.3)Fe_(0.7)-based Alloys were developed to achieve thermal hydrogen compression at mild operating temperatures of water bath.The results indicate the single C 14-type Laves phase as well as homogeneously distributed elements of all Alloys.With increased Mn content in Ti_(0.85)Zr_(0.17)Cr_(1.2-x)Mn_xFe_(0.7)V_(0.1)(x=0,0.1,0.2,0.3)Alloys.

关键词： Alloys hydrogen Laves

Predicting elastic properties of hard-coating Alloys using ab-initio and machine learning methods

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npj Computational Materials 2022年第1期8卷 139-148页

作者： H.Levämäki F.Tasnádi D.G.Sangiovanni L.J.S.Johnson R.Armiento I.A.Abrikosov Department of Physics Chemistry and BiologyLinköping UniversitySE-58183LinköpingSweden Sandvik Coromant S-12680StockholmSweden Materials Modeling and Development Laboratory National University of Science and Technology‘MISIS’119049MoscowRussia

Accelerated design of hard-coating materials requires state-of-the-art computational tools,which include data-driven techniques,building databases,and training machine learning models.We develop a heavily automated high-throughput workflow to build a database of industrially relevant hard-coating materials,such as binary and ternary nitrides.We use the high-throughput toolkit to automate the density functional theory calculation workflow.We present results,including elastic constants that are a key parameter determining mechanical properties of hard-coatings,for X_(1−x)Y_(x)N ternary nitrides,where X,Y∈{Al,Ti,Zr,Hf}and fraction x=0,1/4,1/2,3/4,1.We also explore ways for machine learning to support and complement the designed databases.We find that the crystal graph convolutional neural network trained on ordered lattices has sufficient accuracy for the disordered nitrides,suggesting that existing databases provide important data for predicting mechanical properties of qualitatively different types of materials,in our case disordered hard-coating Alloys.

关键词： coating Alloys ternary

Phase classification of multi-principal element Alloys via interpretable machine learning

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npj Computational Materials 2022年第1期8卷 206-217页

作者： Kyungtae Lee Mukil V.Ayyasamy Paige Delsa Timothy Q.Hartnett Prasanna V.Balachandran Department of Materials Science and Engineering University of VirginiaCharlottesvilleVA22904USA Department of Physics University of RichmondRichmondVA23173USA Department of Mechanical and Aerospace Engineering University of VirginiaCharlottesvilleVA22904USA

There is intense interest in uncovering design rules that govern the formation of various structural phases as a function of chemical composition in multi-principal element Alloys (MPEAs).In this paper,we develop a machine learning (ML) approach built on the foundations of ensemble learning,post hoc model interpretability of black-box models,and clustering analysis to establish a quantitative relationship between the chemical composition and experimentally observed phases of MPEAs.The originality of our work stems from performing instance-level (or local) variable attribution analysis of ML predictions based on the breakdown method,and then identifying similar instances based on k-means clustering analysis of the breakdown results.We also complement the breakdown analysis with Ceteris Paribus profiles that showcase how the model response changes as a function of a single variable,when the values of all other variables are fixed.Results from local model interpretability analysis uncover key insights into variables that govern the formation of each phase.Our developed approach is generic,model-agnostic,and valuable to explain the insights learned by the black-box models.An interactive web application is developed to facilitate model sharing and accelerate the design of MPEAs with targeted properties.

关键词： Alloys element instance

First-principle prediction of structural and mechanical properties in NbMoTaWRe_(x) refractory high-entropy Alloys with experimental validation

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Rare Metals 2022年第10期41卷 3343-3350页

作者： Jin-Yong Mo Yi-Xing Wan Zhi-Bin Zhang Xin Wang Xiao-Qing Li Bao-Long Shen Xiu-Bing Liang School of Chemistry and Chemical Engineering China University of Mining and TechnologyXuzhou221116China Defense Innovation Institute Academy of Military ScienceBeijing100071China Department of Materials Science and Engineering KTH Royal Institute of Technology10044StockholmSweden School of Materials Science and Engineering Jiangsu Key Laboratory for Advanced Metallic MaterialsSoutheast UniversityNanjing211189China

In this work,the effect of Re alloying on the phase composition,crystal structure,and mechanical properties of NbMoTaWRe_(x) (x=0,0.27,0.57,0.92,1.33) refractory high-entropy Alloys (RHEAs) were systematically investigated by combining the calculation of phase diagram(CALPHAD),first-principle calculations and experiment.The theoretical predictions showed good consistency with the experimental results.As the increase in Re content,the theoretical results showed that all considered Alloys have a single body-centered cubic (bcc) structure and the lattice constant and ductility were decreased,while the elastic moduli and hardness were improved.To avoid extreme brittleness,a strategic suggestion was given for the design of Re-containing RHEAs in the future.

关键词： Alloys alloying entropy