Sustainability through Optimal Compositional and Thermomechanical Design for the Al-7XXX Alloys: An ANOVA Case Study

Abstract

The quest for lightweight, high-performance structural materials for demanding applications such as in the fields of automotive, aerospace, and other high-tech and military industries pushes the boundaries of material science. The present work aims to draw attention to a novel, sustainable manufacturing approach for the development of next-generation 7xxx series aluminum alloys that have higher strength by rejuvenating a sustainable compositional and thermomechanical processing strategy. Our innovative strategy integrates two key synergies: trace hafnium (Hf) addition for microstructural refinement, unique thermomechanical treatment involving cryorolling, and a short annealing method. Experimental results revealed that our base alloy exhibited a 33 µm grain size and impressive initial mechanical properties (334 MPa UTS, 150 HV). Adding 0.6 wt.% Hf and employing 50% cryorolling with short annealing led to a remarkable 10 µm grain size reduction and significant mechanical property leaps. The resulting alloy boasts a 452 MPa UTS and 174 HV, showcasing the synergistic advantageous effect of Hf and cryorolling plus annealing treatment. The developed alloys were compositional- and work hardening-dependent, leading to a rich mix of strengthening mechanisms. Optical and scanning electron microscopy reveal several intermetallic phases within the fcc matrix, wherein the Al₃Hf phase plays a key role in strengthening by impeding dislocation movement. In addition to experimental results, a 12-full-factorial design experiment via ANOVA analysis was also utilized to validate the significant influence of Hf and cryorolling on properties with (p-values < 0.05). Among the different parameters, cryorolling plus annealing appeared as the most noteworthy factor, followed by the composition. Using the regression model, the ultimate tensile strength and hardness were predicted to be 626 MPa UTS and 192 HV for an alloy with 0.6 wt.% Hf and 85% cryorolling, which opens a new avenue for ultra-high-strength Al7xxx alloys.

1. Introduction

In recent years, researchers have studied the properties and microstructure of Al-Zn-Mg-Cu alloys under various treatments due to their high strength-to-weight ratio, superior absorption capacity, good machinability, good corrosion resistance, and excellent weldability. The aforementioned characteristics of Al-7XXX alloys make them a good choice for designing and manufacturing critical structural components in aviation, space, and defense industries [1,2,3,4,5,6,7,8,9,10,11,12]. However, the ever-growing demand for industrial sustainability presents a significant challenge for material scientists to develop novel processing routes to improve the mechanical properties of these materials further while ensuring a sizeable manufacturing scale.

For instance, from the viewpoint of compositional design, research has shown that rare earth elements offer significant advantages when added to Al alloys, leading to optimized properties [13,14,15,16,17,18,19,20]. Within the realm of rare-earth elements, hafnium (Hf) stands out as a particularly promising candidate for grain refinement. Typically, during solidification, Hf readily combines with Al to form Al₃Hf precipitates. Li et al. [20] demonstrated a significant reduction in grain size of Al-Hf-based cast alloys with increasing Hf content. These precipitates exhibit significant thermal stability, enhancing the overall thermal robustness of the alloy system. Furthermore, they hinder recrystallization and grain growth via the Zener drag mechanism, effectively promoting a fine-grained microstructure. As Hf content increased from 0% to 0.6%, a remarkable decrease in grain size from 443 μm to 196 μm was observed, attributed to the formation of Al₃Hf intermetallic compounds during solidification [21,22,23,24]. Indeed, the Al₃Hf binary or ternary precipitate holds significant potential for unlocking desirable mechanical properties and refined grain structures through thermomechanical processing, which warrants further investigation.

Worthy of note is that the thermomechanical treatment (TMT) is a versatile metallurgical process that combines plastic deformation (rolling, forging, or press forming) with thermal processing (heat treatment, quenching, or controlled heating/cooling) in a single operation [25,26,27,28,29]. This synergistic approach significantly influences the microstructure (precipitates and grain structure) and overall properties (mechanical, corrosion resistance, etc.) of the treated alloy, as evidenced by numerous studies [30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47].

To date, the outstanding characteristics of cryorolled materials have attracted significant attention from material scientists, underscoring the potential of this technique for enhancing the properties of these alloys [48,49]. Cryorolling (CR) significantly enhances the mechanical properties of Al alloys by manipulating several key microstructural features. This process suppresses dislocation movement, leading to increased dislocation density, which contributes to strengthening. Additionally, CR extensively alters grain size and shape due to inhibited dynamic recrystallization, resulting in a finer-grained microstructure. Furthermore, CR promotes the homogeneous distribution of secondary phases, further enhancing mechanical properties. Consequently, CR is recognized as an effective method for achieving a desirable balance between hardness, strength, and elongation in Al alloys [50,51]. Notably, cryorolled 7XXX alloys exhibit surprisingly high deformability even at large rolling reductions [46,49,51], making them particularly attractive for various applications. Compared to SPD techniques, cryorolling offers several advantages, including significantly higher production rates, continuous processing capabilities, lower costs, and simpler operation [52,53,54,55,56,57,58,59,60,61].

While cryorolled sheets boost impressive strength, their limited ductility and low strain-hardening ability at room temperature pose challenges for industrial applications, particularly in sheet metal forming [62]. To bridge this gap, investigating post-heat treatment parameters for cryorolled materials is crucial for achieving sufficient ductility for forming applications while minimizing strength loss. Indeed, post-processing after cryorolling has emerged as a promising approach for tailoring mechanical properties by manipulating the microstructure in a controlled manner [63]. Jayaganthan et al. [64] investigated the impact of annealing on the microstructural stability, precipitate evolution, and mechanical properties of the cryorolled Al 7075 alloy. Their findings revealed the onset of recrystallization at 150 °C, with completion at 250 °C. Notably, the ultrafine-grained microstructure of cryorolled Al 7075 exhibited thermal stability up to 350 °C. Consequently, annealing at 150 °C (423 K) led to a gradual increase in yield strength and ultimate tensile strength, accompanied by a sudden rise in ductility from 150 °C to 250 °C. Similarly, D. Singh et al. [65] studied the effect of annealing on the microstructure and mechanical properties of cryorolled Al 6061. Their research demonstrated an increase in strength and ductility upon annealing at 150 °C, followed by a decrease in hardness and strength but an increase in ductility at higher temperatures (200–350 °C). Notably, annealing at low temperatures (150 °C for 1 h) triggered a strengthening effect due to precipitation hardening, exceeding the softening effect from recovery, leading to a simultaneous increase in strength and ductility. The improvement was attributed primarily to the formation of nano-sized precipitates and the recovery effect, with reduced dislocation density contributing to increased ductility.

To date, the combined impact of alloy design, microalloying elements, and thermomechanical processing on the microstructure and mechanical properties of Al7xxx series alloys has received limited attention. This study delves into this unexplored territory. For the first time in quaternary Al-Zn-Mg-Cu alloys, hafnium (Hf) content was investigated to enhance microstructure and mechanical properties through the combined effect of composition design via Hf addition and thermomechanical treatments via cryorolling plus a short annealing approach. Hence, the present work aims to create a novel, sustainable manufacturing approach for Al-Zn-Mg-Cu alloys by combining compositional design with simple thermomechanical processing. Alloy is designed with microalloying elements (Hf) and plastic deformation (cryorolling) along with heat treatment (short annealing) to control precipitate evolution precisely during thermomechanical processing.

At the same time, for the statistical assessment of the experimental findings, the analysis of variance (ANOVA) was also adopted to analyze the results. Nevertheless, the ANOVA is one of the most significant methods that can be utilized to assess the influence of parameters on responses as well as the percentage contribution of each experimental parameter [66]. In the present study, the purpose of this kind of exploratory work is to elucidate the influence of multiple factors on the mechanical properties of the designed Al-Zn-Mg-Cu alloys as well as to study the influence of individual factors to determine which factor has more influence, which one less. The experimental results indicated that cryrolling appeared to be the most noteworthy factor among the different parameters, followed by composition.

2. Materials and Methods

Four aluminum alloys with varying hafnium (Hf) percentages were fabricated to investigate the combined impact of Hf addition and thermomechanical treatment on the microstructure and mechanical properties of redesigned Al-6Zn-0.98Mg-0.8Cu alloys. The chemical compositions were optimized based on the existing literature, aiming for grain refinement and enhanced performance. Alloy 1, the base, contained 6% Zn, 0.98% Mg, and 0.8% Cu, following a favorable Zn/Mg ratio of 6 (supported by [67,68,69]) and an optimal Cu content for Al7xxx series alloys (as indicated by [70,71,72]). Alloys 2, 3, and 4 were derived by introducing 0.2%, 0.4%, and 0.6% Hf, respectively, to investigate their impact on the microstructure and behavior of thermomechanical treated alloys. Based on prior research (e.g., [21,73]), increasing Hf content is expected to promote grain refinement. A full-factorial design experiment was employed to explore the combined effects of Hf addition and cryorolling with short annealing across all Hf levels, aiming for optimal grain size and mechanical properties. The fabrication of the four aluminum alloys employed high-purity raw materials: Al (>99.9%), Zn (>99.99%), Mg (>99.95%), Cu (>99.99%), and Hf powder (>99.9%). The process is initiated by melting pure Al ingot at 740–750 °C. Upon melting half the ingot, Zn was added and held for 30 min for homogeneous distribution. After melting, the temperature was reduced to 690–700 °C. Mg was then added and held for 20 min, followed by Cu addition and a 20 min holding period. Hf powder was incorporated and thoroughly stirred for uniform dispersion. The molten alloy, maintained at 700–710 °C, was carefully poured into a preheated (250 °C) steel mold (100 mm × 60 mm × 16 mm) for controlled solidification. Samples were then cooled to room temperature, removed from the mold, and homogenized for 24 h in an air furnace at 540 °C to ensure uniform alloying element distribution. Spectromax metal analysis verified individual element percentages in each ingot. Following homogenization, each alloy was machined into two specimens (100 mm × 60 mm × 8 mm) for thermomechanical treatments. Solution treatment was performed to dissolve alloying elements by placing the samples in a silica boat within a tube furnace at 470 °C for 1 h, followed by water quenching to achieve a supersaturated solid solution (SSSS). Before cryorolling, the solution-treated specimens were dipped in liquid nitrogen for 10 min to reach cryogenic temperatures. Thickness reduction after each pass was optimized to 2% to prevent edge cracks and ensure successful cryorolling. The dipping and rolling process was repeated until a total thickness reduction of 30% (approximately 15 passes) or 50% (approximately 25 passes) was achieved, resulting in strain rates of 0.36 and 0.7, respectively. Samples were subsequently cryogenically stored to prevent natural aging and later subjected to a low-temperature annealing treatment at 150 °C for 1 h to enhance ductility.

Table 1. Chemical composition and hafnium content of experimental alloys.

Alloys Nomenclature	Chemical Composition wt.%
	Al	Zn	Mg	Cu	Hf
Alloy 1	Balance	6	0.98	0.8	0.0
Alloy 2	Balance	6	0.98	0.8	0.2
Alloy 3	Balance	6	0.98	0.8	0.4
Alloy 4	Balance	6	0.98	0.8	0.6

summarizes the nominal compositions of the four alloys, their designated Hf contents, and corresponding nomenclatures.

The influence of composition on the hardness of the prepared alloys was assessed through Vickers hardness testing. This non-destructive technique provided insights into the combined effects of compositional design (Hf microalloying in the Al-Zn-Mg-Cu ternary system) and thermomechanical treatment (cryorolling and short annealing) on hardness behavior. Measurements were performed using a (WOLPERT UH930, Wilson Hard-ness, Shanghai, China) Vickers hardness tester applying a 10 kg load for 15 s. For each alloy (1–4), eight indentations were made to ensure statistically relevant average Vickers hardness values.

To evaluate the influence of compositional design (Hf content) and thermomechanical treatment (cryorolling and short annealing) on mechanical properties, tensile testing was conducted at room temperature (25 °C) following the established ASTM E-8 standard [74]. Tensile specimens were prepared from each set of samples for the four alloys (Alloy-1, 2, 3, and 4). Using a computer-controlled Instron tensile testing machine, uniaxial tensile tests were performed under a constant strain rate of 10⁻³ s⁻¹. An extensometer (epsilon 35420125M) recorded the total strain throughout each test. Engineering stress–strain curves were generated for each specimen based on the collected load and extension data. Key mechanical properties such as yield strength, ultimate tensile strength, and percentage elongation were carefully recorded and analyzed based on the tensile data. To ensure accuracy, at least four replicate measurements were performed for each alloy specimen.

To reveal microstructural features and average grain size, each sample underwent optical microscopy analysis. ImageJ software (v1.54) further measured smaller grains and precipitate sizes within high-resolution micrographs. Before observation, alloy ingots were machined into 20 mm × 20 mm pieces and polished to a mirror-like finish using 0.05 µm alumina particles. Surface imperfections were removed by grinding with 500–1200 grit emery papers. Cleanliness and contaminant-free surfaces were ensured by etching with a solution specified in ASTM E 407-99 [75] (2 mL H.F., 3 mL HCl, 5 mL HNO₃, and 190 mL H₂O). This fundamental technique selectively removes a thin surface layer, revealing the underlying grain structure and phases for deeper microscopy analysis. An Olympus BX51M microscope facilitated detailed microstructure observation following the etching process. To further scrutinize microstructure details and quantify phase composition, scanning electron microscopy (SEM/EDS mapping) analysis was conducted using a JXA-840A electron probe microanalyzer (JEOL, Tokyo, Japan). The analysis served two key purposes: (1) high-resolution SEM imaging, which allowed for precise examination of precipitate morphology and distribution within the grain structure, and (2) quantitative compositional analysis: energy-dispersive spectroscopy (EDS) enabled the determination of the elemental composition of various phases present within the material. For SEM analysis, the same samples used for optical microscopy were employed.

3. Results and Discussion

3.1. Microstructural Behavior of Alloys

3.1.1. Combined Effect of Hf Addition and Thermomechanical Treatment on Microstructure

To elucidate the structure–property relationship in the as-thermomechanical processed state, optical microscopy (OM) investigations were undertaken. The resulting micrographs provided detailed insights into the microstructure, encompassing average precipitate and grain sizes, which evolve during the thermomechanical process. ImageJ software analysis quantified these features for each specimen (Alloy-1 to 4) at two cryorolled-annealed conditions (30% and 50% reduction). As depicted in Figure 1, all 30% cryorolled samples exhibited elongated grains aligned with the rolling direction. Average grain sizes for the 30% cryorolled condition were 33 µm, 22 µm, 13 µm, and 11 µm for alloys 1–4, respectively. Similar trends were observed at 50% cryorolled reduction, with average grain sizes decreasing to 24 µm, 15 µm, 12 µm, and 10 µm, respectively, as shown in Figure 1. The initial grain size in Alloy 1 (Hf-free) is attributed to the synergetic effect of a balanced Zn/Mg ratio promoting fine precipitates, which effectively hinder grain growth, and cryorolled reduction leading to increased dislocation density acting as new grain nucleation sites [27]. Adding 0.2 wt.% Hf significantly refined the grains at both cryorolled conditions, further enhanced at 0.4 wt.% Hf. However, minimal additional refinement was observed at 0.6 wt.% Hf, likely due to a decrease in Al3Hf precipitate density at higher Hf contents. In Alloys 2–4, Al₃Hf precipitates contributed to grain refinement by increasing nucleation sites and inhibiting grain growth through pinning and enhancing dislocation density via cryorolled plastic deformation [20,33,34,73].

Optical microscopy (OM) revealed a multiphase microstructure in all alloys, consisting of secondary phases with diverse morphologies. Figure 1h highlights this diversity in Alloy 4 (0.6 wt.% Hf), showcasing precipitates within the α-Al matrix with varying size, spacing, and aspect ratios. Our analysis suggests a strong dependence of intermetallic phase formation on Hf content. Alloy 4 displayed a distinct microstructure compared to others. It exhibited both micron-scale precipitates along grain boundaries and sub-micron ones within the grains, while Alloy 1 (Hf-free) showed a lower volume fraction of precipitates Figure 1a. Further characterization of these precipitates using EDS is presented later. Based on our investigation, Hf content appears to influence both the dissolution and formation of primary intermetallic precipitates within the alloy during thermomechanical treatments.

3.1.2. Precipitates Identification Using SEM-EDS Microanalysis

To further scrutinize precipitate morphology and composition at higher resolution, SEM analysis was employed. SEM images were subsequently utilized for quantitative compositional analysis using EDS, enabling the identification of micron- and sub-micron-sized precipitates. As depicted in Figure 2, SEM micrographs reveal the contrasting precipitate morphologies of thermomechanical treated alloys: Alloy 1 (Hf-free) and Alloy 4 (0.6 wt.% Hf). Notably, Alloy 1 showcases larger precipitates with an average size of 10 µm compared to Alloy 4’s finer precipitates averaging 2 µm, both observed at 50% cryorolled reduction followed by short annealing.

EDS point analysis (yellow arrows in Figure 2) revealed the chemical composition of different regions in the alloys. Consistent with their optical micrographs, Alloy 1 displayed fewer, larger precipitates (≈10 µm) compared to Alloy 4, which exhibited numerous smaller precipitates (≈2 µm). Elemental weight percentages in

Table 2. Measured chemical compositions (at wt.%) of phase precipitate by SEM-EDS in Figure 2.

Alloy (Point)	Al	Zn	Mg	Cu	Hf	Phase
Alloy1-Hf = 0.0 (1#)	89.06	3.56	0.38	7.00	-	T-AlZnMgCu
Alloy1-Hf = 0.0 (2#)	89.25	7.82	0.86	2.06	-	MgZn2
Alloy4-Hf = 0.6 (3#)	82.31	4.63	0.59	12.46	-	T-AlZnMgCu
Alloy4-Hf = 0.6 (4#)	88.56	8.05	0.75	1.52	1.12	Al3Hf

corroborate this, suggesting an increase in precipitate volume with both Hf content and cryorolled reduction.

EDS analysis further indicated two key differences: first, Alloy 1 precipitates were rich in Zn and Mg, likely corresponding to MgZn₂, while Alloy 4 contained Hf-rich precipitates, likely forming a network. Second, Hf significantly affected morphology by promoting Al₃Hf precipitates at grain boundaries and reducing overall precipitate size. This size reduction can be attributed to Hf’s role as a grain refiner, which increases nucleation sites and results in finer grains. In finer grains, precipitates have a shorter diffusion distance to reach grain boundaries, ultimately leading to smaller sizes [20,76]. Additionally, cryorolled reduction likely plays a role by further reducing the precipitate size and increasing their volume fraction due to suppressed dynamic recrystallization and increased dislocation density, also contributing to finer grains [48,49,51].

Although Hf-containing precipitates are dispersed throughout the microstructure, the η-MgZn₂ phase persists in all alloys due to the inherent Zn/Mg ratio. This phase is readily identifiable in backscattered SEM images as a bright region owing to its lower atomic number compared to Hf-rich Al₃Hf precipitates.

The latter appear significantly darker due to their high atomic number resulting from the presence of heavy element Hf. This high atomic number leads to increased electron absorption from the SEM beam, thus enhancing contrast and producing a darker appearance compared to lighter elements like Zn and Mg. In short, the main reason for performing EDS analysis was to reveal the preliminary chemical composition of major secondary phases, such as black and white precipitates as seen on the surface of the specimen after cryrolling and annealing treatment. Indeed, the unraveling morphologies of black precipitate revealed after thermomechanical treatment are plausible due to the fact that they are mainly nucleated from pre-existing individual straight segments of dislocations or dislocations forming diffused networks during subsequent annealing heat treatment. Indeed, the dislocation provided the heterogeneous nucleation site, which has endangered this type of precipitation morphology for Hf-rich precipitates.

Interestingly, SEM and EDS analysis revealed the presence of a quaternary T-AlZnMgCu phase in both Alloy 1 and Alloy 4 in the as-thermomechanically treated state. This phase’s existence can be attributed to its similar crystal structure to η-MgZn₂, allowing Al and Cu atoms to substitute for Zn within the MgZn₂ lattice, forming a Mg(Zn,Cu,Al)₂ compound. The minimal lattice distortion caused by this substitution facilitates its formation. Notably, the T-AlZnMgCu phase adopts a hexagonal crystal structure analogous to Mg(Zn,Cu,Al)₂. Comparable phases have been observed in as-cast Al-Zn-Mg-Cu alloys [72]. On the above premise, to complement, further SEM-EDS mapping was also explored. Figure 3a–f shows the SEM-EDS mapping of the fine black secondary phase present in the matrix. The black precipitate obviously confirmed that Hf is slightly rich in the precipitate when compared with the other, which is consistent with the EDS results enlisted in Table 2. Since EDS offers valuable insights into the major phases present, its limitations hinder the detection of minor phases with lowered volume fractions or non-uniform distribution.

Nonetheless, to gain a comprehensive understanding of the alloy’s microstructure, employing high-resolution transmission electron microscopy (TEM) is crucial. Future studies on these alloys will undoubtedly benefit from TEM analysis to elucidate the finer details of their microstructure, and it would be the primary focus of our future research.

3.2. Mechanical Behavior of Alloys

3.2.1. Combined Effect of Hf Addition and Thermomechanical Treatment on Hardness

Micro-hardness testing explored the interplay between compositional design, particularly Hf content and cryorolled reduction, and hardness variation in thermomechanically treated Al-Zn-Mg-Cu alloys. While a baseline hardness of 150 HV (30% reduction) and 164 HV (50% reduction) was established for Alloy 1 (Hf-free), subsequent studies investigated how Hf and cryorolled reduction modulate this value. Notably, Hf addition systematically enhanced hardness, with Alloy 4 (0.6 wt.% Hf, 50% reduction) exhibiting the highest value of 174 HV compared to Alloy 1’s 164 HV. Alloys 2 and 3 also displayed a dose-dependent hardness increase, reaching 169 HV and 173 HV, respectively, at a 50% reduction. These findings suggest a synergistic effect of Hf and a cryorolled reduction on grain growth suppression and dislocation density, likely influencing eutectic phase precipitation along grain boundaries, ultimately enhancing hardness. At 30% cryorolled reduction and subsequent short annealing, statistically similar and slightly lower hardness values were observed compared to the 50% reduction, likely due to the reduced strain deformation. Alloys exhibited Vickers hardness values of 150, 154, 157, and 159 HV for a 30% reduction, as shown in Figure 4. Therefore, this suggests that the primary driver of property improvement is not simply strain hardening but rather the formation of Hf-rich precipitates during thermomechanical treatment and associated grain refinement.

SEM analysis revealed a clear trend: as Hf content and cryorolling reduction increased, the volume of precipitates visibly grew within the alloys. This suggests a two-pronged mechanism: Hf directly promotes precipitate formation due to its affinity for forming Hf-rich phases, while cryorolling-induced plastic deformation and suppressed dynamic recrystallization create more nucleation sites for these precipitates. The resulting abundance of precipitates plays a crucial role in hardness, alongside factors like crystallite size, dislocation density, and microstrain. Higher precipitate fractions translate to smaller grains and crystallites, both of which contribute to enhanced hardness. Additionally, smaller crystallites boost dislocation density, leading to increased microstrain along grain boundaries, which strengthens the grain boundaries and consequently elevates hardness [20,76].

3.2.2. Combined Effect of Hf Addition and Thermomechanical Treatment on Tensile Behavior

Figure 5 depicts the stress–strain curves for Alloys 1, 2, 3, and 4 specimens in their different thermomechanical treatment condition. Analysis of these stress–strain curves provides insights into the influence of compositional design and thermomechanical treatment on the mechanical properties of these alloys at room temperature. Figure 4 demonstrates that the compositional design and thermomechanical treatments significantly influence the ultimate tensile strength (UTS), showing a steady increase with increasing Hf content and cryorolling reduction. The UTS values for Alloy 1, Alloy 2, Alloy 3, and Alloy 4 specimens at a 30% cryorolling plus short annealing condition are recorded as 334 MPa, 357 MPa, 376 MPa, and 387 MPa, respectively. A significant statistical variation is observed in the mechanical properties of each alloy. Notably, Alloy 4, with its high Hf concentration, stands out for its remarkable synergy in mechanical properties at 30% cryorolling plus short annealing conditions. The UTS values for Alloy 1, Alloy 2, Alloy 3, and Alloy 4 specimens at a 50% cryorolling plus short annealing condition are recorded as 408 MPa, 423 MPa, 441 MPa, and 452 MPa, respectively. A significant statistical variation is observed in the mechanical properties of each alloy. Notably, Alloy 4, with its higher cryorolling reduction concentration, stands out for its remarkable synergy in mechanical properties at 50% cryorolling plus short annealing conditions. Among the alloys examined in this study, Alloy 4 at a 50% cryorolling plus short annealing condition exhibits an exceptional combination of mechanical properties, particularly demonstrating an ultimate tensile strength of 452 MPa and a yield strength of 366 MPa. The enhancement of tensile properties in the alloys under investigation is under combined compositional design and thermomechanical treatment and is attributed to the refinement of grains, increase in the precipitation fraction, and eliciting the formation of Al₃Hf dispersoids along the grain boundary. Adding Hf refines the grain size due to the precipitation enhancement along the grain boundary, leading to grain refinement and a significant increase in strength due to the well-known Hall–Petch strengthening mechanism [24,27,28,49,51,76,77]. An enhancement of the tensile strength of the alloys upon cryorolling treatment could occur because the cryogenic temperature can effectively suppress the dynamic recrystallization and build up a higher dislocation density in the samples. The influence of cryorolling treatment is well pronounced in yield strength (YS) as compared to the tensile strength of the samples due to effective grain refinement. These significant improvements in properties are attributed to the combined effects of grain refinement strengthening, Orowan strengthening, and dislocation strengthening described using the Taylor equation.

It was observed that when cryorolling was applied to alloys, the ductility initially increased with a reduction of 30%, as shown in Figure 5a. One possible explanation for this increase in ductility is that cryorolling in a lower reduction starts to generate the dislocation density of the alloy; this can improve ductility by providing more slip systems for dislocation movement. However, beyond a 30% reduction, the ductility starts to decrease, as shown in Figure 5b. This decrease could be explained due to dislocation entanglement; with increasing cryorolling reduction, the dislocation density becomes very high, and the dislocations become entangled. This can impede dislocation movement and lead to strain hardening, which can eventually reduce ductility [60].

3.3. Statistical Analysis

The research employed a rigorous statistical approach to analyze the effects of hafnium addition and cryogenic rolling on the microstructure and mechanical properties of an Al-Zn-Mg-Cu alloy. Utilizing full-factorial experimental designs, the experimental results were modeled and optimized through an analysis of variance (ANOVA) with a 95% confidence interval, providing a robust quantitative assessment of the significance and interaction of the investigated variables. ANOVA served as a statistical tool to identify model terms that represented studied process parameters and their interactions and exerted significant effects on experimental outputs. Within the ANOVA framework, the influence of each term on the variability of the observed data is quantified through its adjusted sum of squares (Adj. SS). The ratio of each term’s Adj. SS to the total Adj. SS reflects its relative contribution to the overall variability.

To further assess the importance of each term, the adjusted mean square (Adj. MS) is calculated by dividing the corresponding Adj. SS by its degrees of freedom. This value serves as an estimate of the population variance attributable to the specific term. Subsequent statistical tests then evaluate the significance of each term’s influence. The F-value, obtained by dividing each term’s Adj. MS by the error Adj. MS provides a quantitative measure of the evidence against the null hypothesis, which assumes that the considered term has no statistically significant effect. A larger F-value indicates stronger evidence contradicting the null hypothesis, suggesting the term’s potential significance. Another pivotal element is the p-value, which exhibits an inverse relationship with the F-value. A lower p-value corresponds to a higher F-value and, consequently, greater evidence against the null hypothesis. Typically, a p-value less than the pre-defined confidence level (usually 0.05) signifies that the considered term has a statistically significant effect on the experimental outputs [77].

Recognizing the nuanced relationship between experiment levels and accuracy, we carefully considered expanding our investigation on mechanical properties of Al-6Zn-0.98Mg-0.8Cu-xHf alloys on as cast condition (cryorolling free) presented in

Table 3. Full-factorial experimental design layout.

Level	Factors		Response
	Hf wt.%	CR %	Avg. UTS (MPa)	Avg. Hardness (HV)
1	0	0	150.4	135
2	0	30	334	150
3	0	50	408	164
4	0.2	0	201.8	142
5	0.2	30	357	154
6	0.2	50	423	169
7	0.4	0	238.2	147
8	0.4	30	376	157
9	0.4	50	441	173
10	0.6	0	255	149
11	0.6	30	387	159
12	0.6	50	452	174

. While increasing levels present challenges like complexity and resource limitations, the potential to uncover intricate interactions and achieve greater granularity in our conclusions outweighs these concerns. Therefore, we propose adding four additional levels of mechanical properties for the same alloys in the as-cast state (without thermomechanical treatments of cryorolling plus short annealing).

This study aimed to evaluate the hafnium addition and cryorolling reduction on the microstructure and mechanical properties of alloys. The 4 × 3 full-factorial experimental design levels and three replicates were employed, with hafnium addition varying across four levels and cryorolling reduction across three levels. The ultimate tensile strength (UTS) and hardness were chosen as response variables to capture the combined effects on mechanical performance. The complete experimental design layout, including factor and response variable levels, is presented in Table 3.

3.3.1. Ultimate Tensile Strength Statistical Analysis

In

Table 4. ANOVA response table for the ultimate tensile strength of alloys.

Source	DOF	Adj. SS	Adj. MS	F-Value	p-Value
Model	11	335,543	30,504	1380.20	0.000
Liner	5	332,581	66,516	3009.64	0.000
Hf wt.%	3	23,809	7936	359.09	0.000
CR %	2	308,773	154,386	6985.46	0.000
2-Way	6	2962	494	22.33	0.000
Error	24	530	22	-	-
Total	35	336,073	-	-	-

, the ANOVA response table for the ultimate tensile strength reveals the magnitude of each factor’s influence through the sum of squares (SS) values. Higher SS values denote larger variance contributions by the corresponding factors, thereby implying their potential impact on the response variable [78].

Statistical analysis revealed the model’s strong predictive power, evidenced by a high F-value of 1380.2 and a negligible p-value (p < 0.001). This statistically significant value indicates that the model effectively captures the true variations in ultimate tensile strength beyond pure noise. Further investigation into the individual factors through their p-values confirmed that both hafnium addition (p < 0.001) and cryorolling reduction (p < 0.001) exert significant influences on the observed variations. However, analysis of the adjusted sum of squares (Adj. SS) values from Table 4 revealed a critical finding: the majority of the variability in the measured ultimate tensile strength stems primarily from the cryorolling reduction, suggesting its dominant role in influencing this mechanical property.

Analysis of the model, summarized in

Table 5. Model summary of ultimate tensile strength.

S	R-sq	R-sq (Adj)	R-sq (Pred)
14.70	97.88%	97.75%	97.41%

, provides reassuring evidence of its predictive capabilities. The adjusted R-squared value of 0.9775 confirms the model’s ability to explain nearly all (97.75%) of the variance observed in the data. Furthermore, the predicted R-squared value of 0.9741, falling within the acceptable range (>0.2) of the adjusted R-squared value, further strengthens confidence in the model’s generalizability and prevents concerns about overfitting. This suggests that the model can reliably predict future observations based on the established relationships.

Keeping the cryorolling reduction constant at zero (without cryorolling), the ultimate tensile strength of alloys increased significantly with increasing hafnium addition. At the highest hafnium level (0.6 wt.%), the ultimate tensile strength increased by 255 MPa compared to the lowest hafnium level (0 wt.%), an approximately 70% enhancement due to the addition of hafnium-rich precipitates. This indicates that hafnium addition significantly influences the tensile properties of alloys. This is also evident from the main effects plot in Figure 5.

Keeping the hafnium addition constant at zero (without hafnium), the ultimate tensile strength of alloys increased significantly with increasing cryorolling reduction. At the highest cryorolling reduction level (50%), the ultimate tensile strength increased by 408 MPa compared to the lowest cryorolling reduction level (0%), an approximately 170% enhancement. This is due to the suppression of dynamic recrystallization during rolling at cryogenic temperature, which leads to a high volume of dislocations, grain refinement, dislocation strengthening, and Orowan strengthening. Therefore, cryorolling reduction significantly influences the tensile properties of alloys. This is also evident from the main effects plot in Figure 6.

The two factors, hafnium addition and cryorolling reduction, have a combined effect on the ultimate tensile strength of the alloys. Table 4 shows that the interaction between the two factors significantly influenced the ultimate tensile strength of all alloys (P = 0.000). The highest ultimate tensile strength (452 MPa) was achieved at the highest hafnium addition (0.6 wt.%) and cryorolling reduction (50%). This represents an approximately 200% enhancement compared to the lowest hafnium addition (0 wt.%) and cryorolling reduction (0%). This enhancement is due to the combined effect of hafnium-rich precipitate addition and the suppression of dynamic recrystallization during cryorolling, dislocation strengthening, and Orowan strengthening. Table 4 shows the combined effect of hafnium addition and cryorolling reduction on the ultimate tensile strength of the alloys. This is also evident from the interaction plot in Figure 7.

3.3.2. Hardness Statistical Analysis

The ANOVA response table for hardness, detailed in

Table 6. ANOVA response table of hardness of alloys.

Source	DOF	Adj. SS	Adj. MS	F-Value	p-Value
Model	11	4946.97	449.72	317.45	0.000
Liner	5	4918.14	983.63	694.33	0.000
Hf wt.%	3	635.42	211.81	149.51	0.000
CR %	2	4282.72	2141.36	1511.55	0.000
2-Way	6	28.83	4.81	3.39	0.014
Error	24	34	1.42	-	-
Total	35	4980.97	-	-	-

, reveals the magnitude of each factor’s effect through their sum of squares (SS) values. Higher SS values denote larger variance contributions by the corresponding factors, thereby implying their potential significance in affecting the response variable. Subsequent statistical tests will further evaluate the significance of these effects [78].

Statistical analysis revealed the robust predictive power of the model, indicated by a high F-value of 317.45 and a negligible p-value (p < 0.001). This statistically significant outcome demonstrates that the model effectively captures the true variations in hardness beyond mere noise. Further investigation into individual factor effects through their p-values confirmed that both hafnium addition (p < 0.001) and cryorolling reduction (p < 0.001) exert significant influences on the observed hardness variations. However, analysis of the adjusted sum of squares (Adj. SS) values from Table 6 revealed a critical finding: the majority of the variability in the measured hardness stems primarily from the cryorolling reduction, suggesting its dominant role in influencing this mechanical property.

An analysis of the model, summarized in

Table 7. Model summary of hardness.

S	R-sq	R-sq (Adj)	R-sq (Pred)
2.58	95.56%	95.29%	94.80%

, provides encouraging evidence of its predictive capabilities. The adjusted R-squared value of 0.952 confirms the model’s ability to account for nearly all (95.2%) of the variance observed in the data. Furthermore, the predicted R-squared value of 0.940, falling within the acceptable range (>0.2) of the adjusted R-squared value, further strengthens confidence in the model’s generalizability and mitigates concerns about overfitting. This suggests that the model can reliably predict future observations based on the established relationships.

The experimental results revealed a prominent influence of both hafnium addition and cryorolling reduction on the hardness of the investigated Al-Zn-Mg-Cu alloys. When cryorolling was excluded (0% reduction), increasing hafnium content up to 0.6 wt.% (Level 10) led to a significant hardness increase, reaching 149 HV compared to 135 HV for the hafnium-free reference material (Level 1). This 10% enhancement could be attributed to the formation of Hf-rich precipitates strengthening the microstructure. This trend is further evidenced by the main effects plot in Figure 7.

Similarly, increasing cryorolling reduction from 0% (Level 1) to 50% (Level 3) while maintaining zero hafnium addition significantly boosted hardness. Levels 1 and 3 exhibited hardness values of 135 HV and 164 HV, respectively, representing a 22% increase. This phenomenon can be attributed to the suppression of dynamic recrystallization during cryogenic rolling, leading to a high dislocation density and subsequent grain refinement. Figure 7 again highlights this trend through its main effects plot.

Notably, the synergistic effect of combined hafnium addition and cryorolling reduction further amplified hardness enhancement. As shown in Table 6, their interaction was statistically significant (p = 0.014). The highest hardness of 174 HV was achieved with the highest levels of both factors (0.6 wt.% Hf and 50% reduction), representing a substantial 29% improvement compared to the baseline (0 wt.% Hf and 0% reduction). This synergistic effect could be attributed to the combined strengthening mechanisms of Hf-rich precipitates and cryogenic deformation-induced grain refinement.

Table 6 and Figure 8 further illustrate the interactive influence of these factors on hardness, with Figure 9 providing a visual representation of their interaction plot.

3.3.3. Development of Regression (Mathematical) Models for the Ultimate Tensile Strength and Hardness

This research employed a regression modeling approach that is facilitated using the ANOVA within Minitab 17 software to predict the ultimate tensile strength (UTS) and hardness of Al-6Zn-0.98Mg-0.8Cu alloys. These response variables were modeled as functions of two independent factors: hafnium addition and cryorolling reduction. Both factors were varied across a pre-defined range of percentage chemical compositions and percentage thickness reductions, respectively.

The resulting model equations not only explain the interactions between the response variables and the independent factors but also provide valuable insights into their relative influence. Equations (1) and (2), presented below, specifically capture the interactive effects of hafnium addition and cryorolling reduction on UTS and hardness, respectively. These equations are crucial for understanding the combined impact of both factors on the response variables.

$$\mathrm{U}\mathrm{T}\mathrm{S}\left(\mathrm{M}\mathrm{P}\mathrm{a}\right)=178.89+113.6Hf\left(\mathrm{w}\mathrm{t}.\mathrm{\%}\right)+4.485CR\%$$

(1)

$$\mathrm{H}\mathrm{V}=136.575+18.39Hf\left(\mathrm{w}\mathrm{t}.\mathrm{\%}\right)+0.5226CR\%$$

(2)

However, it is important to emphasize that while these equations offer a comprehensive view of the combined influence, they do not isolate the individual effects of each factor. Their primary function is to predict UTS and hardness values for specific levels of both factors expressed in their original units [79,80,81].

Additionally, regression equations, essentially algebraic representations of the regression lines, provide further visualization of the underlying relationships between the response and independent variables. For a graphic representation of these relationships, please refer to Figure 10 and Figure 11, which depict the residual plots for UTS and hardness, respectively. By incorporating both textual explanations and visual representations, this analysis offers a comprehensive and nuanced understanding of the model and its predictive capabilities.

3.3.4. Models Vaildation

To validate the accuracy of the regression models developed in this study for Al-6Zn-Mg-Cu-xHf alloys, we employed an interaction-based approach. We used the combined equation derived from the models for Hf addition and cryorolling reduction to predict the ultimate tensile strength and hardness values of the alloys. These predicted values were then compared to the actual measured values presented in

Table 8. Predicted versus measured ultimate tensile strength values for the Al-6Zn-0.9Mg-0.8Cu-xHf alloy.

Factor		Ultimate Tensile Strength (MPa)
Hf wt.%	CR %	Measured	Predicted	Relative % Error
0	30	334	315	−5.6%
0	50	408	403	−0.98%
0.2	0	201.8	201.6	−0.09%
0.2	30	357	336	−5.8%
0.2	50	423	425	0.47%
0.4	0	238	224	−5.8%
0.4	30	376	359	−4.5%
0.4	50	441	449	1.78%
0.6	0	255	247	3.10%
0.6	30	387	381	1.50%
0.6	50	452	471	4%

and

Table 9. Predicted versus measured hardness values for the Al-6Zn-0.9Mg-0.8Cu-xHf alloy.

Factor		Hardness (HV)
Hf wt.%	CR %	Measured	Predicted	Relative % Error
0	30	150	152	1.3%
0	50	164	162	−1.2%
0.2	0	142	140	−1.4%
0.2	30	154	156	5.8%
0.2	50	169	166	−1.3%
0.4	0	147	144	−2%
0.4	30	157	159	1.2%
0.4	50	173	170	−1.7%
0.6	0	149	147	−1.3%
0.6	30	159	163	2.4%
0.6	50	174	173	−0.5%

. The results were highly encouraging. All models demonstrated statistically significant accuracy, with p-values of 0.000, indicating strong evidence against the null hypothesis that there is no relationship between the predicted and measured values. Additionally, the average relative error of the models was found to be less than 3%, signifying a close correspondence between the predicted and measured values. These findings provide robust evidence for the validity and reliability of the developed regression models in predicting the mechanical properties of Al-6Zn-Mg-Cu-xHf alloys.

3.3.5. Prediction of Ultimate Tensile Strength and Hardness of Al-6Zn-0.98Mg-0.8Cu-xHf Alloys under 85% Cryorolling Reduction Plus Short Annealing

This study leverages powerful regression model equations, developed as a function of the interplay between Hf addition and cryorolling reduction, to predict the ultimate tensile strength and hardness of Al-6Zn-0.98Mg-0.8Cu-xHf alloys subjected to 85% cryorolling reduction plus short annealing as enlisted in

Table 10. Model predicted values for (Al-6Zn-0.9Mg-0.8Cu-xHf) under an 85% cryorolling reduction for UTS and HV.

Factors		Response
Hf wt.%	CR %	Avg. UTS (MPa)	Avg. Hardness (HV)
0	85	560 ± 16	181 ± 5
0.2	85	583 ± 17	185 ± 5
0.4	85	606 ± 17	188 ± 5
0.6	85	629 ± 19	192 ± 5

. These models offer a valuable tool for elucidating the relative influence of each factor on these crucial mechanical properties. Notably, the relative error between the measured and predicted values for the studied alloys remained consistently below 3%, underscoring the remarkable accuracy and predictive power of the models.

In summary, the remarkable improvement in mechanical properties observed in Al-6Zn-0.98Mg-0.8Cu-xHf alloys, particularly with higher Hf content and cryorolled reduction, can be attributed to the synergistic effect of two factors: conjoint phases within the fcc matrix and increased dislocation density induced via plastic deformation. The microstructural analysis supports this conclusion, as evidenced by Figure 12. This figure schematically illustrates how compositional design (Hf content) and thermomechanical treatment (cryorolling and annealing) influence the microstructure. Decreasing grain and precipitate size, along with the enhanced volume fraction of conjoint phases and higher dislocation density, ultimately lead to the superior mechanical properties exhibited by these 7-series Al-Zn-Mg-Cu alloys. A comprehensive breakdown of the impact of hafnium addition and thermomechanical treatment on these alloys can be found in

Table 11. Summary of the mechanical properties and microstructural features of as-thermomechanically treated alloys.

Alloy	Hf wt.%	CR %	Avg. Yield Stress (MPa)	Avg. Tensile Stress (MPa)	Elongation (%)	Avg. Hardness (HV)	Avg. Grain Size (µm)
Alloy 1	0	30	267	334	9.1	150	33
Alloy 1	0	50	326	408	5.6	164	24
Alloy 2	0.2	30	285	357	9	154	22
Alloy 2	0.2	50	334	423	3.2	169	15
Alloy 3	0.4	30	315	376	4.1	157	13
Alloy 3	0.4	50	361	441	3.9	173	12
Alloy 4	0.6	30	326	387	1	159	11
Alloy 4	0.6	50	366	452	0.98	174	10

.

Prior research has extensively explored the impact of various elements on wrought Al-Zn-Mg-Cu alloys’ microstructure, rolling behavior, and heat treatment response [81,82]. Traditionally fabricated (wrought) Al-Zn-Mg-Cu alloys can achieve baseline mechanical properties (400 MPa UTS, 300 MPa YS) suitable for replacing ferrous materials. However, traditional subtractive methods like hot working and peak aging come with drawbacks: high costs, long processing times, and low sustainability. Additionally, producing ultra-fine grain structures via established severe plastic deformation (SPD) methods like equal channel angular pressing or high-pressure torsion remains complex, expensive, and inefficient, resulting in limited production capacities. While these methods achieve outstanding properties, the traditional fabrication of the 7xxx-series wrought alloys faces significant economic and sustainability challenges in alignment with lean manufacturing principles [83]. Therefore, we conducted a novel, sustainable manufacturing approach for Al-Zn-Mg-Cu-based cast alloys. Our innovative strategy combines compositional design and simple thermomechanical processing. Our research demonstrates that adding Hafnium (Hf) to the Al-Zn-Mg-Cu alloy significantly improves microstructure and mechanical performance, and employing a cryorolling plus annealing strategy further refines the microstructure and enhances mechanical properties.

This combinatorial optimization approach aims to achieve the desired mechanical properties for cast alloys to substitute traditional ferrous materials while adhering to sustainable lean manufacturing principles. Compared to the traditional fabrication of wrought 7xxx-series alloys, this method offers economic feasibility for aerospace and military applications due to lower processing costs, shorter processing cycles, increased material utilization, higher production volumes, and alignment with eco-friendly lean manufacturing practices.

By combining alloying element design with simple thermomechanical processing, we believe this novel approach opens a promising avenue for sustainable and economically viable fabrication of high-performance 7xxx-series aluminum-based cast alloys for lightweight and environmental solutions in the aerospace, military, and other demanding industries.

4. Conclusions

Our primary focus was developing a novel, sustainable manufacturing approach for Al-Zn-Mg-Cu-based cast alloys by incorporating trace amounts of the hafnium (Hf) element followed by thermomechanical treatment that is cryorolling plus short annealing processes.

The following conclusions are summarized:

• Depending on the composition (that is, for Hf-added and Hf-free alloys), the optical microscopy (OM) observations revealed a significant amount of grain refinement and simultaneous increase in the volume fraction of intermetallic phases within the face-centered cubic (fcc) matrix;
• The scanning electron microscopy (SEM) corroborated with EDS revealed the elemental composition of these intermetallic phases to be MgZn₂ phase and Al₃Hf phase precipitates, respectively;
• Subsequently, the monotonic improvement in mechanical characteristics of the developed is closely associated with the transformation of the microstructure after thermomechanical treatments;
• For instance, the addition of 0.6 wt.% Hf, followed by 50% cryorolling and subsequent short annealing at 150 °C for 1 h, resulted in a substantial grain size refinement of 10 μm. This optimization led to a 36% increase in ultimate tensile strength (from 334 MPa to 452 MPa) and a 16% increase in hardness (from 150 HV to 174 HV) compared to the Al-6Zn-0.98Mg-0.8Cu without Hf content;
• It is plausible that this significant improvement in the mechanical properties of Alloy 4 is attributed to a high precipitate volume fraction and finer grain size;
• A full-factorial design was utilized to develop an effective regression mathematical model for predicting the optimal levels of Hf addition and thermomechanical treatments. The average relative error between the measured and predicted values was less than 3%;
• Owing to their remarkable mechanical characteristics, the developed alloy holds great promise as a structural material for fabricating structures for aerospace, military, and other demanding industry applications.