Effect of Solution Heat Treatment on the Microstructure and Microhardness of 7050 Aluminum Alloy

Abstract

Today, 7xxx aluminum alloys are widely used in aerospace and other fields due to their excellent properties such as low density, high specific strength, and good processing performance. The heat treatment process of 7xxx aluminum alloy is crucial in controlling the strengthening phases and grain size, which is a significant way to enhance the alloy’s performance. In this study, solution heat treatment tests of 7050 aluminum alloys were carried out at different temperatures, ranging from 440 °C to 470 °C, with a holding time ranging from 0.5 h to 8 h, using a DIL 805A thermomechanical test machine. The microstructural evolution during the solution heat treatment was characterized using an optical microscope (OM), a scanning electron microscope (SEM), and a transmission electron microscope (TEM). The effects of the solution parameters on the alloy’s microhardness were analyzed using a digital Vickers microhardness tester. According to the ASTM E112-13 standard, The Anelli grain growth models were established to illustrate the grain size evolution during solution heat treatment, and a modified Anelli grain growth model was established. The results indicated that the grain size significantly increases with the increase in the solution heat treatment time and temperature. The Anelli grain growth model can illustrate the phenomenon of grain growth more accurately in the solution heat treatment process of 7050 aluminum alloy. It was found that prolonging the time and elevating the temperature of the solution heat treatment reduced the microhardness of the aluminum alloy because of the dissolution of the precipitates.

1. Introduction

As a typical precipitate-hardened metallic material, 7050 aluminum alloy has been widely used in the aerospace and automotive fields, in accordance with the development trend of lightweight structural materials, because of its light weight, high strength, good anticorrosion properties, antioxidant properties, fatigue performance, resistance to stress corrosion cracking, and other advantages [1,2,3,4]. Generally, 7050 aluminum alloy is used in aircraft structures, such as fuselage frames, wing walls, landing gear support components [5,6]. The 7050 aluminum alloy is an age-strengthened material that is commonly heat-treated to achieve the desired properties. It is important to note that during the heat treatment process, the distribution, content, morphology, and grain size of the precipitates will undergo changes, which have a significant impact on the alloy’s mechanical properties [7,8,9]. The objective of solution heat treatment is to dissolve the alloying elements into the matrix. This is followed by a quenching process to obtain a supersaturated solid solution. The extent to which the precipitated phases dissolve in the matrix will have a significant influence on the subsequent aging precipitation process, ultimately affecting its mechanical properties [10,11]. However, finding ways to increase the solution saturation of aluminum alloys without promoting grain growth has become a major challenge. Many researchers have investigated the recrystallization grain growth model for aluminum alloy plates and other alloys to predict the grain size changes during recrystallization. Li et al. [12] established a dynamic recrystallization model for 7055 aluminum alloy and the model can be implemented in the DEFORM-3D software to predict the dynamic recrystallization during hot compression and hot rolling, which can accurately predict the evolution of grain size during hot rolling of the sheet. Sun et al. [13] predicted the dislocation density, subgrain size, grain size, and average subgrain boundary orientation deviation of AA7075 alloy under different deformation conditions, based on the developed recrystallization model. Zhang et al. [14] developed a mathematical model of two-segment grain growth based on the improved Sellars and Anelli mathematical grain growth model, and their results can better describe the high-temperature grain growth behavior of GH4065 alloy. Li et al. [15] modified the existing grain growth model and applied it to titanium alloys. The other heat treatment parameters also affect the properties of the alloy. Song et al. [16] studied the effects of different quenching transfer times on the spalling corrosion behavior of 7050-T6 aluminum alloy and found that the precipitations at grain boundaries were different at different quenching rates, which is the key to affecting the corrosion performance. Nie et al. [17] studied the effect of composition on the quenching sensitivity of 7050 and 7085 alloys and showed that the difference in composition also affects the properties of the alloys by changing the quenching sensitivity of the alloys. Similarly, solution treatment or annealing treatment will affect the properties of the alloy by changing its microstructure. Yasnii et al. [18] established a linear relationship between microstructure and microhardness, including dislocation density and substructure.

However, few studies have focused on the growth model of grains during solution treatment of 7xxx aluminum alloys. In this study, the microstructural evolution and the grain growth of 7050 aluminum alloy in the solution heat treatment process were analyzed, and two grain growth models were established to predict the grain size under different solution processes. The accuracy of the proposed models was evaluated by calculating the correlation coefficient (R) and the average absolute relative error (AARE).

2. Materials and Methods

The material used in this study was a commercial 7050 aluminum alloy rolled plate; its chemical composition is shown in

Table 1. Chemical composition of the as-received 7050 aluminum alloy (wt. %).

Zn	Mg	Cu	Zr	Fe	Si	Mn	Cr	Ti	Al
5.78	2.14	1.87	0.134	0.0690	0.0152	0.0194	0.0263	0.0408	Bal.

. The experimental sample was a cylindrical specimen with a height of 10 mm and a diameter of 4 mm in the ND direction (perpendicular to the rolling direction of the plate), and the Ferret diameter of the initial grains was about 84.74 µm. The microstructure of the as-received 7050 aluminum alloy plate is shown in Figure 1, where it can be seen that the recrystallized grains and individual grains of secondary recrystallization grains formed during rolling.

The samples were heated to temperatures of 440 °C, 450 °C, 460 °C, and 470 °C at a heating rate of 5 °C/s, held for 30 min, 120 min, 240 min, and 480 min, and finally cooled to room temperature at a cooling velocity of 100 °C/s using a DIL 805A thermomechanical test machine (TA Instruments, Hüllhorst, Germany), as shown in Figure 2a. The microstructural evolution of 7050 aluminum alloy under different solution heat treatment parameters was characterized using a J-X3 optical microscope (OM, NREEOHY J-X3, Shenzhen NREEOHY Technology Co., Ltd, Shenzhen, China), a VEGA3 scanning electron microscope (SEM, VEGA3, TESCAN, Brno, Czech Republic), and a Talos F200X high-resolution field-emission transmission electron microscope (HRTEM, Talos F200X G2 TEM, Thermo Fisher Scientific, MA, USA). The effect of the solution heat treatment parameters on the microhardness was analyzed using a DHV-1000Z digital Vickers microhardness tester (Shanghai Shang material testing machine Co., Ltd., Shanghai, China) and JMatPro 13.2 software (sente software, surrey, England). The grain growth model of 7050 aluminum alloy was constructed using the metallographic method. The samples were etched using Keller reagent (95 mL of H₂O + 2.5 mL of HNO₃ + 1.5 mL of HCl + 1.0 mL of HF) and Graff reagent (83 mL of H₂O + 16 mL of HNO₃ + 3 g of CrO₃ + 1.0 mL of HF) to observe the grain boundary morphology. The grain size after the solution heat treatment was calculated according to the ASTM E112-13 standard [19]. According to the standards in ASTM E112-13, three methods for statistically measuring grain size are available: the comparison method, the area method, and the intercept method. Each of these methods has its own advantages and disadvantages in grading the ASTM grain size. In this experiment, the sample underwent rolling, resulting in elongated and non-uniform, non-equiaxed grain structures. A comparison of the three methods revealed that the intercept method is more effective for structures with elongated grain morphology. Additionally, it is relatively more convenient and quicker compared to the other two statistical methods. Therefore, for this experiment, the intercept method was selected to determine the grain size grade and subsequently characterize the grain size. The intercept method assesses the grain size grade within a region by statistically counting the number of intercepts, as shown in Figure 2b. To provide a more intuitive description of the variation in grain size, the statistically obtained grain sizes were converted to Ferret diameters for the development of the grain growth model.

3. Results and Discussion

3.1. Influence of Solution Heat Treatment Parameters on the Grain Size

3.1.1. Influence of Heat Treatment Time on the Grain Size

As shown in Figure 3, when the solution temperature was 440 °C, the recrystallized grains gradually disappeared and turned into long grains with the extension of the solution holding time. The essence of grain growth is the migration process of the interface, the curvature of the grain boundaries is the driving force, the elements on the adjacent grain interfaces are diffused more and more completely, and the curved grain boundary moves toward the center of curvature to reduce curvature and reduce energy. When three grains are adjacent, the migration of the interface will develop toward the trend of the interfacial tension balance, as shown in Figure 4a. Until the angle between the three grain boundaries is 120°, the interfacial tension reaches equilibrium and the grains no longer grow, while the stable shape of the grains is expected to be a regular hexagon, as shown in Figure 4b. Madhumanti [20] proposed a similar conclusion in the study of austenite grain growth in high-manganese steel, where the grain growth is driven by the curvature of the grain boundaries; the grain boundaries with different angles will also affect the grain growth, and some special grain boundaries will restrict the grains’ growth. If the grain’s final shape is not hexagonal, the grain boundaries will adjust to balance the interfacial tension by either bending outward or intruding inward. Generally, grain boundaries with more than six sides tend to have an outward bulging, while those with less than six sides tend to have an inward concavity, as shown in Figure 4c,d. Under the action of the interfacial curvature, the interface migrates towards the center of the curvature, which leads to the growth of grains with more sides than hexagons, while grains with fewer sides than hexagons shrink and disappear, resulting in the phenomenon of large grains engulfing small grains.

Frederick et al. [21] proposed a similar conclusion, that the surface tension influences the final morphology of the grains. Figure 3e,f also show several black dots, which are due to the process of corrosion of the grain boundary caused by excessive corrosion. When the solution holding time is short, the location of these black dots is most likely MPt (matrix precipitation texture) that was left after corrosion or polishing. With the extension of the holding time during solution heat treatment, the solubility of the crystal’s precipitation phase increases, and the black dots are reduced. When the solution temperature was 440 °C, and with the extension of the holding time, it can be seen in Figure 3a that the presence of needle-shaped second-phase particles gradually dissolved in the matrix, changing from continuous needle-like structures to point-like structures discretely distributed on the grain boundaries. A small number of second-phase particles distributed around the grain boundary can be observed in Figure 3b; these second-phase particles will hinder the migration of the grain boundary. By using in situ observation, Lin et al. [22] demonstrated that inclusions hinder the migration of austenite grain boundaries and restrict the grain growth. Robson et al. [23] found that the content of zirconium significantly affects the distribution of second-phase particles on the grain boundaries, which, in turn, influences the recrystallization volume fraction. Consequently, the increase in the solution holding time promotes the dissolution of the second-phase particles on the grain boundaries. The reduction in the second-phase particle content reduces the resistance of the grain boundary mobility, resulting in greater mobility at the grain boundary and a higher degree of recrystallization.

3.1.2. Effect of Heat Treatment Temperature on the Grain Size

As shown in Figure 5, with the increase in the solution temperature, the effect of the temperature on the grain boundary mobility becomes greater than the holding time, and the grain boundaries are more clearly stacked in the SEM images. However, there are still individual insoluble second-phase particles distributed on the grain boundaries. With the increase in the solution temperature, the size of the second-phase particles becomes smaller [24], and Wen et al. [25] similarly concluded that the solution temperature is the main factor affecting the dissolution of the second-phase particles, which also accelerate the process of grain boundary mobility, resulting in an increased degree of recrystallization. The undissolved second-phase particles will act as a potential source of cracks that reduce the strength of the alloy. In Figure 5e,f there are some large corrosion pits and black dots, where the black dots represent the location of the second-phase particles. In Figure 5g,h, it can be seen that the number of corrosion pits decreases. The results show that the degree of dissolution of the second-phase particles increases with the increase in the solution temperature and the extension of the holding time.

From Figure 6, it can be seen that when holding at 440 °C for 480 min, the degree of continuous distribution of the second-phase particles distributed on the grain boundaries decreased. When the temperature was increased to 460 °C for 30 min, the distribution pattern of the second-phase particles on the grain boundary changed from continuous to discontinuous [26]. At the same time, the corrosion pits also gradually reduce, but there are still a small number of insoluble coarse phases distributed on the grain boundaries. As shown in Figure 6c, when the temperature was increased to 470 °C with a holding time of 30 min, the energy spectrum analysis of the residual second-phase particles revealed that the main components of the second-phase particles were Al, Cu, and Fe, with a small amount of Zn; these insoluble second-phase particles were most likely the original place where fracture occurred, thus reducing the strength of the alloy [27]. Additionally, these insoluble second-phase particles also hinder the migration of the grain boundaries, which results in reducing the degree of recrystallization of the alloy [28]. In conclusion, as the recrystallization volume fraction increases, the growth rate of recrystallized grains will decrease [29].

3.1.3. Effect of Second-Phase Particles on the Grain Size

As shown in Figure 7a, there were a few coarse second-phase particles in the matrix before the heat treatment. It was found to be an AlCuFe phase via energy spectrum analysis. Some fine second-phase particles were also distributed within the matrix and on the grain boundaries. The second-phase particles play a key role in grain boundary migration in the process of static recrystallization of aluminum alloys. A large number of second-phase particles were distributed both at the grain boundary and in the matrix, as can be seen in Figure 7b–d; all of them played an obstructive role in migrating the grain boundary and reducing the rate of interfacial migration. When the maximum cross-section of the second-phase particles encounters the grain boundary, the total surface energy of the system can be expressed as shown in Equation (1):

$$\gamma =\left(A-4\pi r^2\right)·{\gamma }_1+4\pi r^2{\gamma }_2,$$

(1)

where $\gamma$ is the total surface energy, $A$ is the boundary area, $r$ is the particle radius, and ${\gamma }_1$ and ${\gamma }_2$ are the interface and the specific interface energy of the second-phase particles and the matrix, respectively. If the grain boundary is separated from the particle, the total surface energy is $4{\gamma }_1+4\pi r^2{\gamma }_2$. Therefore, if the grain boundary is separated from the second-phase particles, the surface energy will increase, resulting in resistance that will prevent the grain boundary migration and cause the grain boundary curvature. When the driving force of the grain boundary and the resistance reach equilibrium, the movement of the grain boundary stops and the grain grows to a limit size. External factors such as heat treatment or deformation will provide additional energy for grain boundary migration, and the grain will keep growing until the interfacial tension reaches equilibrium and the grain has a stable hexagonal shape. The solute atoms in the 7050 aluminum alloy are mainly composed of Zn, Mg, Cu, and Fe. The second-phase particles at the grain boundary also prevent the migration of the grain boundary, which is why a large number of solute atoms will accumulate at the grain boundary and drag the solute atoms together during the process of the grain boundary migration. Thus, the movement velocity of the grain boundary is influenced by the solute atoms in the matrix. Heinrich et al. [30] found that the hindering effect of solute atoms becomes increasingly pronounced with the increase in the alloying elements. If the temperature increases during the migration of the grain boundaries, it will provide energy for the movement of solute atoms. When the temperature reaches the dissolution temperature of the second-phase particles, it also reduces the hindering effect of the second-phase particles on the migration of grain boundaries, which, in turn, speeds up the migration rate of the grain boundaries.

3.2. Establishment of Grain Growth Models

3.2.1. Establishment of the Anelli Grain Growth Model

The microstructure of the 7050 aluminum grains with different heat treatment parameters after etching with Graff reagent is shown in Figure 8.

The average grain size of 7050 aluminum alloy after different solution heat treatments can be determined by converting the number of grains into the average cross-sectional area of the grains, using the intercept method and Ferret diameter to describe the grain size as described in the ASTM standard, as shown in

Table 2. Average grain size of the 7050 aluminum alloy under different solution heat treatment parameters (μm).

	30 min	120 min	240 min	480 min
440 °C	130 ± 21	180 ± 26	301 ± 24	342 ± 26
450 °C	159 ± 13	214 ± 27	327 ± 28	346 ± 24
460 °C	167 ± 16	250 ± 31	335 ± 20	362 ± 27
470 °C	186 ± 22	267 ± 30	336 ± 28	369 ± 24

.

The thermodynamics and kinetics of grain growth for aluminum alloys are similar to those of austenitic steel, so the general austenitic steel grain growth model was used to explore the aluminum alloy grain growth model [31,32]. Usually, the models describing grain growth are the Anelli model [31] and the Sellars model [33], as shown in Equations (2) and (3), respectively:

$$D=A{t}^n\exp [-Q/(RT\left)\right],$$

(2)

$$D^n=D_0^n+At\exp [-Q/(RT\left)\right],$$

(3)

where $D$ is the grain size at time $t$ ($\mathrm{\mu }\mathrm{m}$), $A$ and $n$ are the coefficients, $t$ is the holding time ($s$), $R$ is the gas constant (8.314 $\mathrm{J}/(\mathrm{mol}·\mathrm{K})$), $T$ is the heating temperature ($K$), and $Q$ is the grain growth activation energy ($\mathrm{J}/\mathrm{mol}$). For the convenience of the solution, the logarithm operation was performed on Equation (2); $lnD$ was the dependent variable, $lnt$ and $1/T$ were the independent variables, and the average values of slope and intercept at different temperatures were solved to obtain Equation (4). Therefore, the Anelli model was obtained by solving Equation (4), as shown in Equation (5):

$$\left\{\begin{array}{c}\mathit{ln}A-\left(\frac{Q}{R}\right)\left(\frac{1}{T}\right)=2.7695325\hfill \\ \mathit{ln}A+n\mathit{ln}t=11.1735925\hfill \end{array}\right.,$$

(4)

$$D=4495.224895t^{0.30531}\exp \left(\frac{-34133.23165}{RT}\right),$$

(5)

The average grain size of 7050 aluminum alloy, as predicted using Equation (5), is shown in

Table 3. Average grain size (μm) values calculated using Equation (5).

	30 min	120 min	240 min	480 min
440 °C	140	214	264	326
450 °C	152	231	289	353
460 °C	164	250	309	382
470 °C	177	270	333	412

.

The relationship between $lnD$-$lnt$ and $lnD$-$\mathrm{10,000}/\mathrm{T}$ can be found in Figure 9. It can be seen that the grain size increases significantly with the increase in the heat treatment time and the increase in the solution heat treatment temperature.

3.2.2. Sellars–Anelli Grain Growth Model

In addition to the Anelli model, the Sellars model was also used to predict the grain growth during the solution heat treatment process, but the Sellars model did not describe the grain growth phenomenon of the 7050 aluminum alloy. Therefore, the characteristics of the two models were combined to build a new model to describe the grain growth phenomenon of 7050 aluminum alloy, which was named the Sellars–Anelli grain growth model, as shown in Equation (6):

$$D^n=D_0^n+A{t}^m\exp [-Q/(RT\left)\right],$$

(6)

All of the parameters in Equation (6) have the same meaning as in the Sellars model mentioned above. A logarithm operation was performed on both sides of the equation to obtain the parameter values. When the holding time was constant, the $Q$, $m$, and $A$ values could be calculated using a nonlinear fitting method based on the experimental data. The relative error of $Q$ and $m$ was dependent on their distribution, i.e., the deviation from their average values. Defining $y\left(n\right)$ as the sum of squares of the relative errors of $Q$ and $m$, the relationship between $y\left(n\right)$ and $n$ can be found in Equation (7) and Figure 10a. Once $y\left(n\right)$ reached its minimum value, the optimized $n$ value could be obtained, which was 1.218.

$$y\left(n\right)=0.49821-1.07595n-0.8254n^2-0.29274n^3-0.05998n^4-0.00568n^5$$

(7)

After determining the value of $n$, taking the logarithm operation on both sides of Equation (6) again, a similar method was used to obtain the values of $m$ and $Q$, which can be seen in Figure 10b. Finally, the Sellars–Anelli grain growth model was obtained with $m$ and $Q$ equal to 0.509 and $\mathrm{66,308}$, respectively, as shown in Equation (8). The average grain size of the 7050 aluminum alloy was predicted using Equation (8), as shown in

Table 4. Calculated value of average grain size obtained according to Equation (8) (μm).

	30 min	120 min	240 min	480 min
440 °C	147	206	252	314
450 °C	157	224	277	348
460 °C	168	245	305	386
470 °C	180	267	335	427

.

$$D^{1.218}=D_0^{1.218}+\mathrm{339,839.895}{t}^{0.509}\exp [-\mathrm{66,308}/(RT\left)\right],$$

(8)

3.2.3. Grain Growth Model Comparison

The deviation of the predicted grain sizes from the experimental values was studied quantitatively by using two parameters: the correlation coefficient (R) and the absolute average error (AARE); their equations are as follows [34,35]:

$$R=\frac{{\sum }_{i=1}^N(y_i-\bar{y})(Y_i-\bar{Y})}{\sqrt{{\sum }_{i=1}^N({y_i-\bar{y})}^2{\sum }_{i=1}^N({Y_i-\bar{Y})}^2}},$$

(9)

$$AARE=\frac{1}{n}{\sum }_{i=1}^n\left|\frac{Y_i-y_i}{y_i}\right|\times 100\%,$$

(10)

where $Y_i$ represents the predicted grain size values ($\mathrm{\mu }\mathrm{m}$), $y_i$ represents the measured values obtained from the experiments ($\mathrm{\mu }\mathrm{m}$), and $\overline{y}$ is the average predicted grain size value ($\mathrm{\mu }\mathrm{m}$). Comparisons between the predicted and experimental grain sizes of 7050 aluminum using the Sellars and Sellars–Anelli models are shown in Figure 11. It can be seen that the $R$ value of the Sellars–Anelli grain growth model is lower than that of the Anelli grain growth model, and the $AARE$ value of the Anelli grain growth model is lower than that of the Sellars–Anelli grain growth model. In contrast, the Anelli grain growth model can illustrate the phenomenon of grain growth more accurately in the solution heat treatment process of the 7050 aluminum alloy. Even though the initial grain size is considered in the Sellars–Anelli model, the deformation of the surface layer of the plate cannot be identical to that of the central layer during the rolling process. The grain recrystallization near the surface layer will be higher than that of the central layer [36]. Therefore, the fitting results of the Anelli model are better.

3.3. Effects of Solution Heat Treatment Parameters on the Microhardness

The statistics of the experimental Vickers microhardness values of each specimen are given in Figure 12a, and when the temperature was increased from 440 °C to 450 °C, a sudden drop in the hardness values occurred. The possible reasons for this result are that the number of residual precipitated phases decreased, the recrystallization fraction increased, and the grain size increased with the increase in the solution temperature during the single-stage solution treatment [37]. The decrease in the amount of MgZn₂, which is the most dominant strengthening phase in 7050 aluminum alloy, and the increase in the grain size are the main factors behind the decrease in the microhardness of the alloy [38]. Moreover, the level of metal reinforcement of the solution strengthening during grain growth is much lower than that of the diffusion strengthening, so when the precipitated phase dissolves in the matrix, the increase in strength due to the solution strengthening is much lower than that due to the diffusion strengthening. The contents of the precipitated phases in equilibrium at various temperatures, as determined using the JMatPro 13.2 software, are illustrated in Figure 12b. It can be observed that when the temperature reaches about 410 °C, the MgZn₂ phase is essentially dissolved, which is consistent with the experimental results. At the same time, the Al₇Cu₂X phase will begin to precipitate, and the hard precipitation phase will significantly reduce the strength of the alloy. When the solution temperature is 450 to 470 °C, the microhardness of the alloy does not change much with the extension of the solution time. This is because the main internal strengthening phase, i.e., the MgZn₂ phase, is fundamentally dissolved within the matrix.

4. Conclusions

In this study, the effects of solution heat treatment parameters on the microstructure and microhardness of 7050 aluminum alloy were studied; several conclusions can be drawn:

(1)

Two grain growth models for the single-stage solution heat treatment process of commercial 7050 aluminum were established. The correlation coefficient (R) of the Anelli grain growth model is 0.96, while that of the Sellars–Anelli grain growth model is 0.94. Moreover, compared to the Sellars–Anelli grain growth model, the AARE value of the Anelli grain growth model is lower. The Anelli grain growth model can illustrate the phenomenon of grain growth more accurately in the solution heat treatment process of 7050 aluminum alloy.

(2)

As the solution heat treatment temperature increases and the heat treatment time increases, the grain size increases, and the microhardness value has a trend of decreasing and then stabilizing. The solution temperature has more influence on the microhardness value. Therefore, to prevent grain growth during the solution heat treatment, it is advisable to maintain the optimal solution treatment temperature below 450 °C.