This study explores the functional characteristics (erosion, corrosion, mechanical damage, and microstructural features) of non-stick cookware made from aluminum alloys. Typically coated with polytetrafluoroethylene (PTFE-Teflon) or ceramic for non-stick properties, we conducted a systematic investigation using corrosion, abrasion, and mechanical tests on six types of cookware from different manufacturers (Manuf-1-6). The cookware was heated at various temperatures [Room temperature (RT), 100, 175, 250, & 350 °C] and times (45 & 120 min). Tests included Taber wear, Adhesive Pull-off, hot & RT corrosion, and surface roughness measurements. Characterization involved optical microscopy, scanning electron microscope (SEM) with electron backscattered diffraction (EBSD), and x-ray diffraction (XRD). Ceramic-coated cookware from Manuf-4 demonstrated superior mechanical strength, wear, and corrosion resistance due to refined microstructures. Manuf-1\'s PTFE-coated cookware also performed well. Optimal results were observed when heating below 250 °C for up to 45 min. Prolonged heating and temperatures beyond 250 °C adversely affected internal structures of all cookware. Thus, it is advisable to use Al-based non-stick cookware below 250 °C for a maximum of 45 min.

High-strength dissimilar aluminum alloys are difficult to connect by fusion welding, while they can be successfully joined by friction stir welding (FSW). However, the asymmetrical deformation and heat input that occur during FSW result in the formation of a heterogeneous microstructure in their welded zone. In this work, the grain structure and texture evolution in the bottom zones of dissimilar FSW AA2024-T351 and AA7075-T651 joints at different welding speeds (feeding speeds) were quantitatively investigated. The results indicated that dynamic recrystallization occurs in the bottom zones of dissimilar FSW joints, and equiaxed grains with low grain sizes are formed at the welding speed of 60-240 mm/min. A high fraction of the recrystallized grains were generated in the bottom zones of the joints at a low welding speed, while a high fraction of the substructured grains are produced at a high welding speed. Different types of shear textures are produced in the bottom zones of the joints; the number fraction of shear texture types depends on different welding speeds. This study helps to understand the mechanism of microstructure homogenization in dissimilar FSW joints and provides a basis for further improving the microstructure of the welded zone for engineering applications.

The growing use of aluminum and its compounds has increased the volume of aluminum waste. To mitigate environmental impacts and cut down on manufacturing expenses, extensive investigations have recently been undertaken to recycle aluminum compounds. This paper outlines the outcomes of a study on fabricating standard EN AW-2007 alloy using industrial and secondary scrap through continuous casting. The resultant recycled bars were analyzed for their chemical makeup and examined for microstructural features in both the cast and T4 states, undergoing mechanical property evaluations. The study identified several phases in the cast form through LM, SEM + EDS, and XRD techniques: Al7Cu2Fe, θ-Al2Cu, β-Mg2Si, Q-Al4Cu2Mg8Si7, and α-Al15(FeMn)3 (SiCu)2, along with Pb particles. Most primary intermetallic precipitates such as θ-Al2Cu, β-Mg2Si, and Q-Al4Cu2Mg8Si7 dissolved into the α-Al solid solution during the solution heat treatment. In the subsequent natural aging process, the θ-Al2Cu phase predominantly emerged as a finely dispersed hardening phase. The peak hardness achieved in the EN AW-2007 alloy was 124.8 HB, following a solution heat treatment at 500 °C and aging at 25 °C for 80 h. The static tensile test assessed the mechanical and ductility properties of the EN AW-2007 alloy in both the cast and T4 heat-treated states. Superior strength parameters were achieved after solution heat treatment at 500 °C for 6 h, followed by water quenching and natural aging at 25 °C/9 h, with a tensile strength of 435.0 MPa, a yield strength of 240.5 MPa, and an appreciable elongation of 18.1% at break. The findings demonstrate the feasibility of producing defect-free EN AW-2007 alloy ingots with excellent mechanical properties from recycled scrap using the continuous casting technique.

The process of grain refinement during welding significantly influences both the final microstructure and performance of the weld joint. In the present work, merits of acoustic addition in the conventional Frictions Stir Welding (FSW) process were evaluated for joining dissimilar Al/Mg alloys. To capture the near \"in situ\" structure around the exit hole, an \"emergency stop\" followed by rapid cooling using liquid nitrogen was employed. Electron Backscatter Diffraction analysis was utilized to characterize and examine the evolution of grain microstructure within the aluminum matrix as the material flowed around the exit hole. The findings reveal that two mechanisms, continuous dynamic recrystallization (CDRX) and geometric dynamic recrystallization (GDRX), jointly or alternatively influence the grain evolution process. In conventional FSW, CDRX initially governs grain evolution, transitioning to GDRX as material deformation strain and temperature increase. Subsequently, as material deposition commences, CDRX reasserts dominance. Conversely, in acoustic addition, ultrasonic vibration accelerates GDRX, promoting its predominance by enhancing material flow and dislocation movements. Even during the material deposition, GDRX remains the dominant mechanism.

Aluminum technical alloys are well known for their outstanding mechanical properties, especially after heat treatment. However, quenching and aging, which improve the mechanical properties, by the formation of Cu-rich zones and phases that are coherent with the matrix and block the dislocation motion, cause uneven distribution of the elements in the alloy and consequently make it prone to corrosion. One method providing satisfactory corrosion protection of aluminum alloys is anodizing. On an industrial scale, it is usually carried out in electrolytes containing chromates that were found to be cancerogenic and toxic. Therefore, much effort has been undertaken to find substitutions. Currently, there are many Cr(VI)-free substitutes like tartaric-sulfuric acid anodizing or citric-sulfuric acid anodizing. Despite using such approaches even on the industrial scale, Cr(VI)-based anodizing still seems to be superior; therefore, there is an urge to find more complex but more effective approaches in anodizing. The incorporation of anions into anodic alumina from the electrolytes is a commonly known effect. Researchers used this phenomenon to entrap various other anions and organic compounds into anodic alumina to change their properties. In this review paper, the impact of the incorporation of various corrosion inhibitors into anodic alumina on the corrosion performance of the alloys is discussed. It is shown that Mo compounds are promising, especially when combined with organic acids.

With high strength and good fatigue resistance, Al-Cu alloys such as AA2024 are widely used in the aerospace and automotive industries. However, the system\'s susceptibility to hot cracking and other solidification defects hinders its development in metal additive manufacturing (AM). A nano-treated AA2024 deposition, with the addition of TiC nanoparticles, is successfully additively manufactured without cracks. Microstructural analysis suggests nanoparticles not only mitigate the hot cracking sensitivity but also significantly refine and homogenize grains, resulting in an average size of 23.2 ± 0.4 μm. Microhardness profiles show consistent mechanical performance along the build direction, regardless of cyclic thermal exposure. Finally, excellent tensile strength and elongation up to 428 MPa and 7.4% were achieved after heat treatment. The combined results show a great promise of nano-treating in high-strength aluminum AM.

The article describes machine learning using artificial neural networks (ANNs) to develop the parameters of the friction stir welding (FSW) process for three types of aluminum joints (EN AW 7075). The ANNs were built using a total of 608 experimental data. Two types of networks were built. The first one was used to classify good/bad joints with MLP 7-19-2 topology (one input layer with 7 neurons, one hidden layer with 19 neurons, and one output layer with 2 neurons), and the second one was used to regress the tensile load-bearing capacity with MLP 7-19-1 topology (one input layer with 7 neurons, one hidden layer with 19 neurons, and one output layer with 1 neuron). FSW parameters, such as rotational speed, welding speed, and joint and tool geometry, were used as input data for ANN training. The quality of the FSW joint was assessed in terms of microstructure and mechanical properties based on a case study. The usefulness of both trained neural networks has been demonstrated. The quality of the validation set for the regression network was approximately 93.6%, while the errors for the confusion matrix of the test set never exceeded 6%. Only 184 epochs were needed to train the regression network. The quality of the validation set was approximately 87.1%. Predictive maps were developed and presented in the work, allowing for the selection of optimal parameters of the FSW process for three types of joints.

The large-scale ingot of the 7xxx-series aluminum alloys fabricated by direct chill (DC) casting often suffers from foundry defects such as cracks and cold shut due to the formidable challenges in the precise controlling of casting parameters. In this manuscript, by using the integrated computational method combining numerical simulations with machine learning, we systematically estimated the evolution of multi-physical fields and grain structures during the solidification processes. The numerical simulation results quantified the influences of key casting parameters including pouring temperature, casting speed, primary cooling intensity, and secondary cooling water flow rate on the shape of the mushy zone, heat transport, residual stress, and grain structure of DC casting ingots. Then, based on the data of numerical simulations, we established a novel model for the relationship between casting parameters and solidification characteristics through machine learning. By comparing it with experimental measurements, the model showed reasonable accuracy in predicting the sump profile, microstructure evolution, and solidification kinetics under the complicated influences of casting parameters. The integrated computational method and predicting model could be used to efficiently and accurately determine the DC casting parameters to decrease the casting defects.

Friction stir welding (FSW) has been adopted in the aerospace industry for fabricating structural alloys due to the low melting point and high thermal conductivity of aviation aluminum alloys. However, welding residual stresses can lead to secondary deformation in friction stir welded (FSWed) structures. Additionally, microstructural characteristics impact the crack growth rates and directions in these structures. Therefore, it is necessary to investigate the effects of residual stress and microstructure on the fatigue responses of FSWed joints. In this paper, we studied the fatigue crack growth behavior of two homogeneous and dissimilar FSWed joints with varying welding parameters, namely 2024-T3 and 7075-T6. The residual stresses were measured with the X-ray diffraction method. The dislocations and precipitates in different zones of the FSWed joints were analyzed via transmission electron microscopy (TEM). The results demonstrated that the residual stress significantly affected the fatigue crack growth rate and direction; the tensile residual stress promoted fatigue crack growth and offset the decrease in the fatigue crack growth rate that occurred due to grain refinement. The results of the microstructural analysis indicated that dislocation density and sliding resistance increased with the decrease in rotational speed and led to a decreased rate of fatigue crack propagation.

Zero-valent iron (ZVI) has been extensively studied for its efficacy in removing heavy metals, nitrate, and chlorinated organic compounds from contaminated water. However, its limited effectiveness due to rapid passivation and poor selectivity is prompting for alternative solutions, such as the use of aluminium alloys. In this study, the efficacy of five distinct aluminium alloys, namely Al-Mg, Al-Fe, Al-Cu, and Al-Ni, each comprising 50 % Al by mass at a concentration of 10 g/L, was assessed using copper, nitrate and trichloromethane (TCM) as model contaminants. Results show that chemical pollutants reacted immediately with Al-Mg. On the contrary, the remaining three alloys exhibited a delay of 24 h before demonstrating significant reactivity. Remarkably, Al-Mg alloy reduced nitrate exclusively to ammonium, indicating minimal preference for nitrate reduction to N2. In contrast, the Al-Cu, Al-Ni, and Al-Fe alloys exhibited N2 selectivity of 3 %, 5 %, and 19 %, respectively. The removal efficiency of copper, nitrate and TCM reached 99 % within 24 h, 95 % within 48h and 48 % within 48h, respectively. Noteworthy findings included the correlation between Fe concentration within the Al-Fe alloy and an increased N2 selectivity from 9.3 % to 24.1 %. This resulted in an increase of Fe concentration from 10 % to 58 % albeit with a concurrent reduction in reactivity. Cu2+ removal by Al-Fe alloy occurred via direct electron transfer, while the removal of nitrate and TCM was facilitated by atomic hydrogen generated by the alloy\'s hydrolysis. Intriguingly, nitrate and TCM suppressed Cu2+ reduction, whereas Cu2+ improved nitrate reduction and TCM degradation. These findings demonstrate the great potential of Al-Mg and Al-Fe alloys as highly efficient agents for water remediation.