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CREEP DEFORMATION OF INTERMETALLIC ALLOYS

Gerhard Sauthoff(Max-Planck-Institut fur Eisenforschung GmbH. , D-40074 Dusseldorf , Germany)

金属学报(英文版)

Intermetallics for structural applications at high temperatures must show a sufficient high temperature strength which is controlled by creep processes. In the first section the creep behaviour of single-phase intermetallic alloys is overviewed with respect to stress and temperature dependence and effects of composition and microstructure. It is shown in particular that creep deformation is controlled by diffusion. The second section refers to multiphase intermetallic alloys, and both particulate and non-particulate alloys are regarded. Data are presented for single-phase and multiphase alloys based on B2 phases and lesscommon phases and the consequences of diffusion control for alloy design are discussed.

关键词: :creep , null , null , null , null

Sputtering Rates of Alloys in Glow Discharge

Jianshi REN and Gongshu ZHANG (Institute of Metal Research , Chinese Academy of Science , Shenyang , 110015 , China)Zhenshu WANG and Jinwei ZHAO (Shanghai University of Technology Shanghai , 200072 , China)

材料科学技术(英文)

The sputtering rates of alloys were investigated under constant Ar pressure and voltage supplied.The alloys studied in this work range from binary intermetallic alloys to ternary and quaternary alloys. It is revealed that the sputtering rates of alloy targets under steady states are where q is the sputtering rates of alloys, Ci the weight percentage of i-th component in the alloy,and qi0 the sputtering rate of pure metal of i-th component.

关键词:

STUDY ON PROPERTY PREDICTION FOR SEALING ALLOYS

Z.N. Xia , S.G. Lai , Y.Z.Sun and Y.W. Lu(Department of Materials Science and Engineering , Tsinghua University , Beijing 100084 , ChinaManuscript received 4 March 1996)

金属学报(英文版)

This paper describes a model of property prediction for alloys using the mapping function and self-learning ability of artificial neural network. By learning from experimental data, the neural network induces the relationship between composition, processing and properties of alloys, and predicts the properties with given composition and processing parameters of new alloys.The verification of sealing alloys demonstrates that the artificial neural network is an effective method for materials design and properties prediction.

关键词: :property prediction , null , null

Hafnium in Aluminum Alloys: A Review

Zhi-Hong Jia , Hui-Lan Huang , Xue-Li Wang , Yuan Xing , Qing Liu

金属学报(英文版) doi:10.1007/s40195-016-0379-0

Lots of the available literatures on hafnium in aluminum alloys are reviewed. The new binary Al-Hf phase diagram is simply assessed. Two ternary phase diagrams including Al-Hf-Zr and Al-Hf-Sc are accounted for, with emphasis on the aluminum rich part of the diagrams. The relationship between different structure Al3Hf and several different formation mechanisms including the probable phase transformation mechanisms is described. The continuous Al3Hf phase particles can serve as a grain refiner in the Al melt and a precipitate for controlling the grain structure of the alloy and a strengthening precipitate. A series of effects of Fe, Si, Zr, Sc and Li addition on the behavior of Al3Hf and Al alloys are given. Moreover, the effects of Hf on the microstructure and properties of Al alloys, such as hardness and creep, are reviewed. Finally, some views of Hf-containing Al alloys are summarized.

关键词:

Al-Hf , Phase , diagram , Al3Hf , precipitate , Microstructure , Properties

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