Mechanical properties optimization and microstructures of diffusion bonded AA2014/AA7075 al alloys

2.1. Experimental procedure and design

For the diffusion bonding sample, a 6 mm thick aluminium alloy in grades AA2014 and AA7075 was obtained from M/s. PMC corporation in Bangalore, India and machined to a scale of 50x50 mm. Table 1 shows the chemical composition of the Al alloys that were examined. The specimen’s surfaces were polished with SiC paper of 200#, 400#, and 600# grit and then cleaned with acetone before being subjected to diffusion bonding (Britto et al., 2017Britto, A.S.F., Raj, R.E., Mabel, C.M. (2017). Prediction of shear and tensile strength of the diffusion bonded AA5083 and AA7075 aluminium alloy using ANN. Mater. Sci. Eng. A 692, 1-8. https://doi.org/10.1016/j.msea.2017.03.056.; Britto et al., 2022Britto, A.S.F., Binoj, J.S., Manikandan, N., Surendranatha, G.M., Naidu, B.V.V., Saji Raveendran, P. (2022). Effect of interfacial thickness on microstructure, mechanical properties, and modelling of diffusion fused dissimilar Al alloys for process optimization using ANN-GA method. Multiscale and Multidiscip. Model. Exp. and Des. 5, 105-117. https://doi.org/10.1007/s41939-021-00106-5.).

Figure 1 depicts the diffusion bonding setup (a). The specimens were placed into a special 316L stainless steel die assembly (Fig. 1b) and interleaved into a vacuum chamber (see Fig. 1c) maintained at 29 mm Hg (Fernandus et al., 2012Fernandus, M.J., Senthilkumar, T., Balasubramanian, V., Rajakumar, S. (2012). Optimising diffusion bonding parameters to maximize the strength of AA6061 aluminium and AZ31B magnesium alloy joints. Mater. Design 33, 31-41. https://doi.org/10.1016/j.matdes.2011.06.022.) to minimize oxidation. With the aid of a PID controller, the temperature of the specimen can be raised at a rate of 25 °C·min^-1 and maintained at the desired temperature. The hydraulic system, which is equipped with a load cell, is used to apply and calculate the necessary pressure. The specimen was cooled to room temperature for further characterization and testing after being held at the planned conditions for a specified period of time.

2.2. Microstructural characterization

To reveal the microstructure, the specimen was polished with progressive grade SiC Paper and then etched with Keller’s solution (190 ml distilled water, 5 ml nitric acid, 3 ml hydrochloric acid, and 2 ml hydrofluoric acid) (Kong et al., 2004Kong, C.Y., Soar, R.C., Dickens, P.M. (2004). Optimum process parameters for ultrasonic consolidation of 3003 aluminium. J. Mater. Process. Technol. 146 (2), 181-187. https://doi.org/10.1016/j.jmatprotec.2003.10.016.). An optical microscope (Make: MEIJI, Japan; Model: MIL-7100) was used to examine the microstructure of the interface bond, accompanied by a metallurgical microscope (Make: HUVITZ, Korea; Model: HRM-300M) to measure the thickness of the interface bond using ‘panasis’ software. Under a scanning electron microscope, energy-dispersive X-ray spectroscopy (EDS) was used to map the elemental composition of micro-zones near the joints (Make: ZEISS, Germany; Model: EVO -18). X-ray diffraction (XRD) of CuK radiation, with a 2ϴ total range from 0˚ to 80˚ with a step size of 0.02˚ was performed to identify the phases present in the microstructure (Make: PANalytical; Model: X’Pert PRO). To make the indentation and calculate the diffusion layer hardness across the joint, Vickers used a 0.5 kg load and a dwell time of 10 sec on a microhardness tester (Make: SHIMADZU, Japan; Model: HMV-T1) (normal to the interface region).

2.3. Mechanical characterization

The lap shear and ram tensile strength of the bonds were determined using nonstandard test specimens. Figure 2 depicts the dimensional details of specimens. The lap shear specimens were machined with a spark erosion machine (Make: ELECTROICA, Japan; model: super cut-734) at a cutting speed of 1.5 mm·min^-1, while the ram tensile specimens were machined with an electric spark line cutting machine (Model: super cut-734) at a cutting speed of 1.5 mm·min^-1 (Make: ELEKTRA, Japan; model: cut-500). Both tests were performed at a constant ram speed of 5 mm·min^-1 in a 100 kN capacity servo operated universal testing machine (Make: FIE-BLUESTAR, India; Model UNITEK 94100) with data acquisition system. Figure 2 depicts the lap shear and ram tensile test specimens.

A three-factor, five-level central composite design (CCD) was chosen for testing in this research. Twenty joints were created using the designed combinations of bonding process parameters such as temperature, bonding pressure, and holding time based on the design matrix. Due to insufficient thermal excitation to cause atom diffusion, good bonding was not achieved until 325 °C, and temperatures above 425 °C seem to be too high for sound bonding. Similarly, a bonding pressure of less than 2 MPa was insufficient to create enough contact points (between surface asperities) for atom diffusion to cross over. When the pressure is greater than 18 MPa, the specimens deform plastically, causing the outer edges to bulge. It has been discovered that diffusion requires a minimum holding time of 15 min, and that holding times of more than 75 minutes are detrimental. The defined process parameters and their range are tabulated in Table 2 after several trial runs to examine the effect of the process parameters.

3.1. Microstructural analysis

The thickness of the diffusion layer has a major impact on the diffusion bond’s shear and tensile strength. Due to a lack of diffusion, a thin inter-diffusion area forms, resulting in a poor bond power. On the other hand, excessive diffusion of materials causes deeper penetration at the inter-diffusion area of the elements resulting in a dense diffusion layer and poor bonding.

The microstructure of the different test samples, as well as their interface thickness, are shown in Fig. 3. The average interface thickness ranges from 0.346 µm to 9.363 µm, as determined by the programme for a specific specimen at different locations. Figure 4 depicts the relationship between the bond thickness and weight. The strength of the bond increases as the inter-diffusion element’s area thickness increases up to 6 µm, but as the interface thickness increases further, the bond strength decreases. This may be due to the presence of more inter-diffusion area of element constituents such as Al₃Ti_0.75Fe_0.25, Al₂MgCu, Mg₂Si, and MgZn_2, resulting in decreased material strength (Fig. 5). Also, the presence of transition metals such as Mg, Cu, Zn, Fe, and Ti in the bonding alloys is revealed by chemical examination, indicating that they form these inter-diffusion area during diffusion. The element mapping of the bonded surface was used to determine the degree of diffusion of a specific element from one material to the other (Fig. 6). The percentage content of a particular element in the parent metal before bonding, such as Mg, Cu, Zn, Si, Fe, and Ti, was noted above each elemental mapping micrograph (Fig. 6). These mapping micrographs will reveal the extent of each element’s diffusion after the diffusion process.

For example, while AA2014 alloy does not contain Ti (Fig. 6f), it can be seen that Ti has diffused from AA7075 alloy to AA2014 alloy. Furthermore, X-ray diffraction analysis of the bonded joints confirmed the presence of inter-diffusion area of elements produced during diffusion (Fig. 5). To classify the phases, the X-ray diffraction patterns were analyzed and compared to Joint Committee on Powder Diffraction Standards (JCPDS) results. In addition, through the elemental mapping, it was confirmed that the reported peaks belong to Al₃Ti_0.75Fe_0.25, Al₂MgCu, Mg₂Si, and MgZn_2, as noted in the microstructural image.

The microhardness plot of some diffusion bonded joints was studied 5 mm away from the fusion line on both sides of the interface zone (Fig. 7). For the high strength bonds (Exp. No: 10, 20), a standard bell-shaped curve was obtained, with 190 Hv and 180 Hv reported in the interface area, respectively. The effect of diffusion can be seen up to 3 mm on either side of the joint due to differences in the parent metal’s hardness. On the other hand, it was observed that maximum strength was not achieved either for more or less inter-diffusional areas (Fig. 3 and Fig. 4) due to the inability of the material to withstand the applied load. Hence, it should be emphasized that in diffusion bonding, an optimum narrow area such as 6 µm formation at the inter-diffusion of elements is needed to achieve a higher bond strength.

3.2. Analysis of mechanical properties and process optimization

The interaction of process variables such as the bonding temperature, the pressing load, and the pressure application length is important, and a single adjustment at a time procedure is insufficient to draw successful control, necessitating a multi-variate method for experimentation and study. The significance and suitability of the established empirical models to relate the relationship of process parameters with the ram tensile and lap shear strength were confirmed using analysis of variance (ANOVA). Tables 4 and 5 show the ANOVA results for shear and ram tensile power, respectively.

Table 4 shows that the shear strength model’s p-value is very tiny, indicating that the model is significant. The model’s fitness is demonstrated by its R² determination coefficient, which is 0.9988, implying that the overall variability is 99.88% when all the relevant variables are taken into account. The overall deviation outside of the model’s preview is less than 1%. The 0.9933 expected R-Square value is in reasonable accordance with the 0.9977 Adjusted R-Squared value. The adequacy precision ratio is far higher than 4 at 85.365, indicating that the signal is adequate. The coefficient of variance, which calculates residual variability, is just 1.68%, indicating that the tests are more precise and reliable. Inferences can be drawn with respect to the variables since the majority of the model parameters match well.

The ANOVA analysis of the ram tensile strength model (Table 5) reveals that the model’s determination coefficient is R² 0.9983, implying that the model explains 99.83 percent of the overall uncertainty when all significant variables are taken into account. The Adjusted R-Squared value of 0.996 is very similar to the Predicted R-Squared value of 0.989. The adequacy accuracy, which indicates the signal’s adequacy by measuring the signal to noise ratio as 75.7 The model’s F-value of 667.6 and p-value of 0.0001 indicate that it is important enough to draw conclusions.

For lap shear and ram tensile power, the standard likelihood plot versus residuals indicates a consistent closeness to the straight line (Fig. 8a and Fig. 8b), implying that the errors are distributed normally and confirming the model significance (Kadaganchi et al., 2015Kadaganchi, R., Gankidi, M.R., Gokhale, H. (2015). Optimization of process parameters of aluminum alloy AA 2014-T6 friction stir welds by response surface methodology. Def. Technol. 11 (3), 209-219. https://doi.org/10.1016/j.dt.2015.03.003.).

The perturbation map depicts the influence of a factor in the design space when controlling other variables. The perturbation plot for the shear strength of diffusion bonded joints with respect to process variables including temperature, strain, and holding time is shown in Fig. 9a. The slope of the curve determines the influence of a factor. The temperature (factor A) is found to be the most influential factor in determining the bond’s quality. The higher the applied temperature, the faster the atom Diffusion is. This diffusion is accompanied by a chemical reaction that creates a diffusion bond of a thickness wide enough to obtain an optimum strength in the joint. The shear strength rises with temperature up to about 400 °C, then falls as the temperature keeps increasing due to an excess in size of the inter-diffusion area as well as decohesion occurring between the materials. Similarly, pressure (factor B) is a determining factor that must be maintained at around 10 MPa for proper bonding. Decreasing or rising the pressure has a negative impact on bond power, as does the holding time (factor C) of about 45 min.

Figure 9b shows the perturbation plots for Ram tensile strength, where (Factor A) is the most controlling parameter for the same purpose as shear strength. The effects of pressure (Factor B) and keeping time (Factor C) are close to those of shear strength, where it is best to maintain it at the experiment’s mid-range value to have a better strength. The empirical results of bond strengths, lap shear power, and ram tensile with reference to the process parameters in the experimental context are used to construct statistical models, as shown below, Eq. (1) and Eq. (2).

where, A: temperature (°C), B: Pressure (MPa), C: holding time (min).

RSM is used to determine the best set of process parameters for obtaining a maximum or minimum answer value (Singh et al., 2017Singh, A., Garg, H., Lall, A.K. (2017). Optical polishing process: Analysis and optimization using response surface methodology (RSM) for large diameter fused silica flat substrates. J. Manuf. Process. 30, 439-451. https://doi.org/10.1016/j.jmapro.2017.10.017. ). Via 3D surface plots and contour plots, the optimized input parameters for obtaining the maximum shear and ram tensile strength were realized in this work. Figures 10 and 11 show the 3D surface plots for shear and tensile power, as well as their contour plots. Figure 10a shows that the shear strength increases with increasing temperature and pressure, but these factors become saturated at their mid-range values, and that further increases in these factors are detrimental to the strength. Sound bonding occurs in the temperature range of 382 °C to 410 °C, according to the contour map. Similarly, Fig.10b supports the same temperature range for achieving high shear power, regardless of the keeping period used in the experiment. The effect of pressure and keeping time on shear strength is shown in Fig. 10c. It’s designed to keep the pressure between 9 and 15 MPa and the holding time between 45 and 60 min.

The effect of pressure and temperature on the ram tensile strength of the bonded joints is shown in Fig. 11a. The ram tensile strength is also optimum at the mid-range value of the process parameters, similar to the shear strength. The contour plot indicates that the temperature for sound joints should be kept between 370 °C and 410 °C, and the pressure should be kept between 5 MPa and 15 MPa. The holding time should be held between 35 and 50 min, as shown in Fig. 11b, which was further supported by the contour plot in Fig. 11c.

Overlay counterplots were used for graphical optimization to select the best process parameters from the planned domain for optimum power (Fig. 12). With respect to temperature and pressure, the overlay plot shows the coordinates for the optimum pressure and temperature conditions at a holding time of 46 min and 43 sec. Experiments were conducted in the expected conditions, and the maximum shear and ram tensile strengths of 84.1 + 0.7 MPa and 93.8 + 0.6 MPa respectively, were obtained. The experimental results are similar to the expected values, indicating that the model is accurate.