journal article·2023-02

Precipitation behavior and microstructural evolution during thermo-mechanical processing of precipitation hardened Cu-Hf based alloys

Yihui Jiang, Xingde Zhang, Pengtao Cai, Pengtao Li, Fei Cao, Fan Gao, Shuhua Liang

Acta Materialia· Volume 245
Publisher page

Abstract

A recently found precipitation hardened Cu-Hf alloy is a promising candidate for the fabrication of novel high strength and high electrical conductivity materials. However, the precipitation behavior and microstructural evolution during thermo-mechanical processing remain poorly recognized. The present paper focuses on the crystallography, thermodynamics and kinetics of precipitation process during isothermal aging and the interaction between nano-precipitates and nano-twins during liquid nitrogen temperature (LNT) rolling in Cu-Hf alloys. The isothermal aging precipitation procedure of Cu-Hf alloys was identified as supersaturated FCC-Cu → coherent Cu 5Hf phase → incoherent Cu 51Hf 14 phase. The coherent Cu 5Hf is oriented with respect to the Cu matrix: ( 1 1 1 ) Cu / / ( 3 1 1 ) C u 5 Hf , [ 0 − 1 1 ] Cu / / [ 0 − 1 1 ] C u 5 Hf . According to thermodynamic assessment and kinetic analysis, the formation of intermediate Cu 5 Hf phase is due to the lower accommodation energy and interfacial free energy of coherent nano-precipitates, and the change of the growth mode results in shape change in nano-precipitates. Based on molecular dynamics simulations, the significant improvement in the twinning ability of Cu-Hf alloys by the pre-existing nano-precipitates leads to the formation of plenty of nano-twin bundles during LNT-rolling. Finally, a new type of Cu-Hf based alloys with an excellent combination of high strength, high electrical conductivity, as well as high heat-resistance were fabricated by routine process.
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Research context

OpenAlex topics: Microstructure and mechanical properties · Aluminum Alloys Composites Properties · Aluminum Alloy Microstructure Properties

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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