4.7 Article

Investigation of the microstructure and physical properties of directionally solidified ternary Al-8.8La-1.2Ni alloy

Journal

JOURNAL OF ALLOYS AND COMPOUNDS
Volume 855, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jallcom.2020.157331

Keywords

Directional solidification; Ternary alloys; Microstructure; Microhardness; Tensile strength; Compessive strength

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This paper systematically studied the microstructure evolution, microhardness, and tensile properties of Al-8.8La-1.2Ni ternary alloy under various solidification rates. The results showed that the solidification rate significantly influenced both the microstructure and mechanical properties of the alloy.
This paper systematically studies the microstructure evolution, microhardness and tensile property of Al-8.8La-1.2Ni ternary alloy with directionally solidified under a wide range of solidification rates by Bridgman-type growth apparatus. The directionally solidified microstructure of studied alloy consists aligned dendrites, and eutectics in the region between them. Primary dendrite arm spacing (lambda(1)), secondary dendrite arm spacing (lambda(2)) and microhardness (HV) were measured from both transverse and longitudinal sections of many samples. Also, ultimate tensile strength (sigma(uts)), tensile yield strength (sigma(tys)), ultimate compressive strength (sigma(ucs)) and compressive yield strength (sigma(cys)) of the solidified many samples at room temperature the dependence of solidification rate (V) were carried out. The present results show that the solidification rate can change both microstructure and mechanical properties effectively. According to these results, it has been found that, for increasing values of V, the values of lambda(1) and lambda(2) decrease, the values of HV, sigma(uts), sigma(tys), and sigma(cys), increase. Relationships between microstructural parameters (lambda(1, )lambda(2)) and mechanical properties (HV, sigma(uts), sigma(tys), and sigma(cys)) expressed as function of solidification rate using a linear regression analysis method. (C) 2020 Elsevier B.V. All rights reserved.

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