Effect of magnesium on microstructure and properties of Cu-Cr alloy

Zhao, Zhanshan; Xiao, Zhu; Zhou, Li; Ma, Muzhi; Dai, Jie

doi:10.1016/j.jallcom.2018.04.159

Cited by 98 publications

(20 citation statements)

References 22 publications

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“…The predicted and experimental values for these alloys are compared in Table 1. Cu-2.93Ni-0.9Si-0.13Mg-0.53Zn alloy is a commercialized product and Cu-2.20Ni-0.42Si-0.08Mg-0.30Zn alloy is made and measured in our own lab and the rest four alloys [26][27][28] are reported very recently. These data are not included in our database.…”

Section: Construction and Analysis Of Two Bp Nn Modelsmentioning

confidence: 99%

A property-oriented design strategy for high performance copper alloys via machine learning

et al. 2019

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Traditional strategies for designing new materials with targeted property including methods such as trial and error, and experiences of domain experts, are time and cost consuming. In the present study, we propose a machine learning design system involving three features of machine learning modeling, compositional design and property prediction, which can accelerate the discovery of new materials. We demonstrate better efficiency of on a rapid compositional design of high-performance copper alloys with a targeted ultimate tensile strength of 600-950 MPa and an electrical conductivity of 50.0% international annealed copper standard. There exists a good consistency between the predicted and measured values for three alloys from literatures and two newly made alloys with designed compositions. Our results provide a new recipe to realize the property-oriented compositional design for highperformance complex alloys via machine learning.

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Section: Construction and Analysis Of Two Bp Nn Modelsmentioning

confidence: 99%

A property-oriented design strategy for high performance copper alloys via machine learning

et al. 2019

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“…However, their strength and conductivity are decreased by the substantial solid solubility of Fe atoms in the Cu matrix at high temperatures, and the slow precipitation speed at low temperatures [7,8]. Their properties may be improved by multi-component alloying [8][9][10][11][12][13]. Wang et al [14], Song et al [15], and Xie et al [16] investigated the influence of Ag.…”

Section: Introductionmentioning

confidence: 99%

Microstructure and Strengthening Model of Cu–Fe In-Situ Composites

Liu

Sheng

et al. 2020

Materials

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The tensile strength evolution and strengthening mechanism of Cu–Fe in-situ composites were investigated using both experiments and theoretical analysis. Experimentally, the tensile strength evolution of the in-situ composites with a cold deformation strain was studied using the model alloys Cu–11Fe, Cu–14Fe, and Cu–17Fe, and the effect of the strain on the matrix of the in-situ composites was studied using the model alloys Cu–3Fe and Cu–4.3Fe. The tensile strength was related to the microstructure and to the theoretical strengthening mechanisms. Based on these experimental data and theoretical insights, a mathematical model was established for the dependence of the tensile strength on the cold deformation strain. For low cold deformation strains, the strengthening mechanism was mainly work hardening, solid solution, and precipitation strengthening. Tensile strength can be estimated using an improved rule of mixtures. For high cold deformation strains, the strengthening mechanism was mainly filament strengthening. Tensile strength can be estimated using an improved Hall–Petch relation.

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“…It is the focus of R&D efforts in various countries to meet the demand for high-performance copper alloys in high-tech fields such as electricity, metallurgy, aerospace, and atomic energy. So far, the aging-precipitation behavior of the Cu-Cr alloy, and the effect of related elements on the microstructure and properties of the alloy were systematically studied by many scholars, and some research results were obtained [15][16][17][18][19]. However, because the Cr element is easy to oxidize and segregate in a nonvacuum environment, casting by means of traditional vacuum smelting cannot meet the demand for large-length, uniform-performance strip products.…”

Section: Introductionmentioning

confidence: 99%

Relationship between Microstructure and Properties of Cu–Cr–Ag Alloy

Peng

Xie

et al. 2020

Materials

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The microstructure evolution and properties of a Cu–Cr–Ag alloy during continuous extrusion and an aging process were studied by Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM). Owing to strong shear deformation that happened during continuous extrusion with working temperatures of 450 to 480 °C, a larger number of fine grains were obtained. Both face-centered cubic (FCC) and body-centered cubic (BCC) precipitates simultaneously existed in the matrix when aged for 450 °C for 2 h, and the Cr phases with BCC structure had an N–W relationship with the matrix. After continuous extrusion, 60% cold deformation, 875 °C × 1 h solid solution treatment, 60% cold deformation, 450 °C × 2 h aging treatment, and 70% cold deformation, the Cu–Cr–Ag alloy acquired excellent comprehensive properties: tensile strength of 494.4 MPa, yield strength of 487.6 MPa, and electrical conductivity of 91.4% IACS.

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Effect of magnesium on microstructure and properties of Cu-Cr alloy

Cited by 98 publications

References 22 publications

A property-oriented design strategy for high performance copper alloys via machine learning

A property-oriented design strategy for high performance copper alloys via machine learning

Microstructure and Strengthening Model of Cu–Fe In-Situ Composites

Relationship between Microstructure and Properties of Cu–Cr–Ag Alloy

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