Unraveling precipitation evolution and strengthening function of the Al-Zn-Mg-Cu alloys with various Zn contents: Multiple experiments and integrated internal-state-variable modeling

doi:10.1016/j.jmst.2021.12.008

Abstract

Abstract:

Zn content is one of the most concerned factors in the development of next generation ultra-strength Al-Zn-Mg-Cu alloys owing to its essential role in precipitation strengthening. In the present work, the underlying functions of Zn content in precipitation evolution and strengthening function of Al-Zn-Mg-Cu alloys were systematically investigated by combining multiple experiments and an integrated internal-state-variable model. The experimental results indicated that the increased Zn content in Al-Zn-Mg-Cu alloys would promote the development of precipitates and enhance aging hardening. The diffusion flux of soluble Zn and the coordination of Mg atom controlled the crystallographic microstructures evolution during precipitates nucleation, growth and transition processes. By integrating precipitation development with electrical resistivity and hardness evolutions, an improved internal-state-variable physical model was then developed for the aging responses of Al-Zn-Mg-Cu alloys. The unified model considered the intrinsic characteristics of precipitates such as crystallographic orientation, morphology, component, and distribution. The specific improvements were to balance the combined functions of Zn element and Mg element and consider the plate-like morphology and directed growth as indicated by experiments. This model was also adaptive to heat-treatment variables and chemical compositions, and owned the notable advantages to simultaneously rationalize the observed microstructural characteristics, mechanical and electrical properties following artificial aging of Al-Zn-Mg-Cu alloys. In addition, a preliminary model framework between electrical resistivity and hardness for Al-Zn-Mg-Cu alloys was established.

Key words: Al-Zn-Mg-Cu alloys, Precipitation, Strengthening, In situ electrical resistivity, Modeling

Jie Tang, Mingcai Liu, Guowei Bo, Fulin Jiang, Chunhui Luo, Jie Teng, Dingfa Fu, Hui Zhang. Unraveling precipitation evolution and strengthening function of the Al-Zn-Mg-Cu alloys with various Zn contents: Multiple experiments and integrated internal-state-variable modeling[J]. J. Mater. Sci. Technol., 2022, 116: 130-150.

Figures/Tables 20

Table 1. Main chemical compositions of the employed Al-Zn-Mg-Cu alloys (wt.%).

Alloys	Zn	Mg	Cu	Fe	Si	Al
6.25% alloy	6.25	2.06	2.12	0.16	0.043	Bal.
7.93% alloy	7.93	2.02	2.03	0.13	0.047	Bal.
10.11% alloy	10.11	2.04	2.11	0.16	0.047	Bal.

Fig. 1. Schematic illustration of the heat treatment procedure and sketch of in-situ electrical resistivity measurement. (As seen in the sketch, the Al wires at both ends of the sample introduce a constant current I. By monitoring the variation of voltage U between the two Al wires on the inside sides, the resistance R for the sample could be obtained. Then the electrical resistivity would be recorded in-situ.).

Fig. 2. (a-c) The calculated equilibrium phase fractions for the studied Al-Zn-Mg-Cu alloys by Thermo-Calc software; (d, e) in-situ electrical resistivity and corresponding derivative evolutions and (f) micro-hardness variations during non-isothermal heat treatments.

Fig. 3. TEM micrographs with corresponding SAD patterns ([110]Al zone axis) of the Al-Zn-Mg-Cu alloys during non-isothermal heat treatments at: (a-c) 120 °C; (d-f) 160 °C. High-resolution SAD patterns in both [110]Al projections and [100]Al projections are shown in Fig. S1 in Supplementary Information.

Fig. 4. The in-situ electrical resistivity and corresponding derivative evolutions for the studied Al-Zn-Mg-Cu alloys at different isothermal artificial aging temperatures: (a) 80 °C; (b) 120 °C; (c) 160 °C; (d) 200 °C. The abbreviation of “SS” refers to the solid solution treated alloys.

Fig. 5. Micro-hardness evolutions of the studied Al-Zn-Mg-Cu alloys at different isothermal aging temperatures: (a) 80 °C; (b) 120 °C; (c) 160 °C; (d) 200 °C.

Fig. 6. TEM micrographs with corresponding SAD patterns of the studied Al-Zn-Mg-Cu alloys during isothermal artificial aging at 120 °C for different time: (a-c) 150 min; (d-f) 24 h. High-resolution SAD patterns in both [110]Al projections and [100]Al projections are shown in Fig. S2 in Supplementary Information.

Fig. 7. TEM micrographs with corresponding SAD patterns of the studied Al-Zn-Mg-Cu alloys during isothermal artificial aging at 160 °C and 200 °C for different time: (a-c) aged at 160 °C, 4 h for three studied alloys; (d) aged at 160 °C, 24 h for 7.93% alloy; (e) aged at 200 °C, 100 s for 7.93% alloy; (f) aged at 200 °C, 24 h for 7.93% alloy. High-resolution SAD patterns in both [110]Al projections and [100]Al projections are shown in Fig. S3 in Supplementary Information.

Fig. 8. Statistic results of plate-like precipitates in the studied alloys based on TEM observations: (a) diameter; (b) thickness.

Fig. 9. STEM micrographs and corresponding EDS mappings for 6.25% alloy and 10.11% alloy aging at 120 °C for different holding time: (a-d) 6.25% alloy, 100 s; (e-h) 10.11% alloy, 100 s; (i-l) 6.25% alloy, 150 min; (m-p) 10.11% alloy, 150 min. The analysed elements are labelled in the lower left corner of EDS mappings. The statistical results of average element concentration (at.%) of matrix and precipitates are marked in the pictures respectively.

Fig. 10. (a-h) HAADF-STEM micrographs and corresponding fast Fourier transform (FFT) diffractograms of 6.25% alloy and 10.11% alloy aged at 120 °C for different time (The aging conditions are marked in the graph); (i) schematic atomic stacking model showing the evolution of plate-like precipitates.

Table 2. Categories of the precipitates in the studied alloys under different aging conditions. The collected results from published works are also summarized [[17], [18], [19],29,30,38,58,59].

Alloys	Aging conditions	Subsistent precipitates
6.25% alloy	120 °C-24 h	GPII + η'
Al-5.6Zn-2.5Mg-1.6Cu alloy (wt.%) [58]	120 °C-24 h	GPII + η'
Al-6.08Zn-2.5Mg-1.93Cu alloy (wt.%) [29]	120 °C-24 h	GPII
Al-6.22Zn-2.46Mg-2.13Cu-0.15Zr alloy (wt.%) [30]	120 °C-24 h	GPII
Al-6.56Zn-2.25Mg-2.1Cu-0.12Zr alloy (wt.%) [19]	120 °C-24 h	η'
7.93% alloy	120 °C-24 h	GPII + η'
Al-3.56Zn-2.36Mg-0.9Cu-0.04Zr alloy (at.%) [18]	120 °C-24 h	η'
Al-7.76Zn-1.94Mg-2.35Cu-0.12Zr alloy (wt.%) [38]	120 °C-24 h	η' + η
Al-7.8Zn-1.6Mg-1.8Cu-0.14Zr alloy (wt.%) [59]	120 °C-24 h	η'
10.11% alloy	120 °C-24 h	GPII + η'
Al-9.78Zn-2.04Mg-1.76Cu-0.11Zr alloy (wt.%) [17]	120 °C-24 h	η'
6.25% alloy	160 °C-0 s	GPII + η'
7.93% alloy	160 °C-0 s	GPII + η'
10.11% alloy	160 °C-0 s	GPII + η'

Fig. 11. Growth rate contour map of solid solution concentration versus precipitates radius of the studied alloys at different aging temperatures: (a-d) 120 °C; (e-h) 160 °C. The represented alloys and growth controlling elements are marked in the image.

Table 3. Physical meaning and values of different internal parameters for GPII zone, η' precipitate and η precipitate used in the integrated model.

Precipitates	Shape	Habit plane	Composition	A	l	V_p	σ_s	α_plate
GPII zone	Plate-like	{111}_Al	MgZn₂	1.72	1.5 nm	2.1 × 10^-5 m³/mol [62,66]	0.11 J/m²	≈0.45
η'	Plate-like	{111}_Al	MgZn₂	> 3	1.5 nm		0.2 J/m² [40]	≈0.11
η	Rod-like or Spherical	-	Mg₃₃Zn₄₂Al₁₂Cu₁₃	-	-		0.4 J/m² [62,66]	≈0.05

Table 4. The quantitative density (N) of the precipitate nucleus formed at the aging temperatures of 120, 160 and 200 °C.

Alloys	120 °C	160 °C	200 °C
6.25% alloy	1.05 × 10²⁴	6.27 × 10²³	1.48 × 10²²
7.93% alloy	1.10 × 10²⁴	6.67 × 10²³	1.55 × 10²²
10.11% alloy	1.15 × 10²⁴	6.91 × 10²³	1.97 × 10²²

Fig. 12. The modeling results of precipitation characteristics and Δρ of the studied Al-Zn-Mg-Cu alloys during the aging process at 120 °C: (a, b) the comparison between predicted Δρ and mean precipitate size evolutions with experimental results; (c) the calculated evolutions of solutes Zn, Mg concentration remaining in the matrix; (d-f) the simulation of precipitate size distribution based on experimental statistics; (g-i) the simulation of precipitate size distribution based on a designed stew distribution.

Fig. 13. The modeling precipitation characteristics and Δρ of the studied Al-Zn-Mg-Cu alloys during the aging process at 160 °C: (a, b) the comparison between the predicted Δρ and mean precipitate size evolutions with experimental results; (c) the calculated evolutions of solutes Zn, Mg concentration remaining in the matrix; (d-f) the simulation of precipitate size distribution based on experimental statistics; (g-i) the simulation of precipitate size distribution based on a designed stew distribution.

Fig. 14. The modeling precipitation characteristics and Δρ of the studied Al-Zn-Mg-Cu alloys during the aging process at 200 °C: (a, b) the comparison between the predicted mean precipitates radius and Δρ evolutions with experimental results; (c) the modeling evolutions of solutes Zn, Mg and Cu concentration remaining in the matrix; (d) the predicated precipitates density evolutions. The separate growth and coarsening periods for precipitation are marked in the figure.

Fig. 15. (a-c) The modelled contribution of solid solution atoms σs and precipitates σp on yield strength at the aging temperature of 120 °C, 160 °C and 200 °C, respectively; (d-f) comparison of experimental and predicted hardness in the studied alloys at 120 °C, 160 °C and 200 °C.

Fig. 16. (a) Summary of the present integrated model which couples microstructures simulation and performance simulation; plots of Δρ vs. microhardness of the studied alloys during artificial aging treatments: (b) experimental results, (c) modeling results.

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