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Early-stage clustering in two Al-Mg-Zn(-Cu) alloys has been investigated using atom probe tomography and transmission electron microscopy. Cluster identification by the isoposition method and a statistical approach based on the pair correlation function have both been applied to estimate the cluster size, composition, and volume fraction from atom probe data sets. To assess the accuracy of the quantification of clusters of different mean sizes, synthesized virtual data sets were used, accounting for a simulated degraded spatial resolution. The quality of the predictions made by the two complementary methods is discussed, considering the experimental and simulated data sets.
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Precipitation-strengthening at ambient and high temperatures is examined in Al-0.5Mn-0.3Si (at.%) alloys with and without 0.02 at.% Sn micro-additions. Isochronal aging experiments reveal that Sn inoculation results in a pronounced age-hardening response: a hardening increment of 125 MPa is achieved at peak-aging (475 °C), which is five times greater than that of a Sn-free alloy. Scanning electron microscopy and synchrotron x-ray diffraction analyses demonstrate that, while the structure of the α-Al(Mn,Fe)Si precipitates formed in the peak-aged alloys is identical, their mean radius is smaller (R ~ 25 vs. 100-500 nm) and their number density is greater (~1021 vs. ~1019-20 m -3) in the Sn-modified alloy. Atom-probe tomography analyses reveal that the enhanced dispersion of the α-precipitates is related primarily to the formation of Sn-rich nanoprecipitates at intermediate temperatures, which act as nucleation sites for Mn-Si-rich nanoprecipitates. High-resolution transmission electron microscopy analyses demonstrate that these Mn-Si-rich nanoprecipitates exhibit icosahedral quasicrystal ordering (I-phase), which transform into the cubic-approximant α-phase upon peak aging. Significant Sn segregation at the semi-coherent interfaces of the α-precipitates in the peak-aged Sn-modified alloy is observed via APT, which promotes homogeneous nucleation of the I/α-precipitates at aging temperatures > 400 °C. At 300 °C, creep threshold stresses are observed in both alloys in the peak-aged state, which increases from ~30 MPa in the Sn-free alloy to ~52 MPa in the Sn-modified alloy. This boost in creep resistance is consistent with the enhanced aging response (higher Orowan stress).
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The effect of sample preparation on a pre-aged AlMgSiCu alloy has been evaluated using atom probe tomography. Three methods of preparation were investigated: electropolishing (control), Ga+ focused ion beam (FIB) milling, and Xe+ plasma FIB (PFIB) milling. Ga+-based FIB preparation was shown to introduce significant amount of Ga contamination throughout the reconstructed sample (≈1.3 at%), while no Xe contamination was detected in the PFIB-prepared sample. Nevertheless, a significantly higher cluster density was observed in the Xe+ PFIB-prepared sample (≈25.0 × 1023 m−3) as compared to the traditionally produced electropolished sample (≈3.2 × 1023 m−3) and the Ga+ FIB sample (≈5.6 × 1023 m−3). Hence, the absence of the ion milling species does not necessarily mean an absence of specimen preparation defects. Specifically, the FIB and PFIB-prepared samples had more Si-rich clusters as compared to electropolished samples, which is indicative of vacancy stabilization via solute clustering.
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The eutectic Al-6Ni (wt.%) alloy exhibits excellent strength at ambient and elevated temperature, provided by a high volume fraction of Al3Ni microfibers formed during solidification. Here, Al-6Ni is micro-alloyed with Sc and Zr (with 0.1Sc+0.2Zr, 0.2Sc+0.4Zr and 0.3Sc+0.2Zr, wt.%), creating two additional populations of primary and secondary Al3(Sc,Zr) precipitates. The fully eutectic microstructure (α-Al + Al3Ni) observed in Al-6Ni alloy changes, with Sc and Zr addition to hypoeutectic microstructure with primary α-Al grains nucleated on solidification by primary Al3(Sc,Zr) precipitates. Upon subsequent aging, fully-coherent Al3(Sc,Zr) nano-precipitates form in the α-Al matrix between Al3Ni microfibers, providing substantial precipitation strengthening, which is maintained for up to 1 month at 350 °C. Alloy strength - both at ambient temperature and during creep at 300 °C - can be quantitatively described through a superposition of precipitation strengthening by Al3(Sc,Zr) nanoprecipitates and load-transfer strengthening by Al3Ni microfibers.
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We examine the precipitation and creep behavior of Al-0.5Mn-0.02Si (at.%) alloys, with and without the L12-forming elements Zr and Er (0.09 and 0.05 at.%, respectively), utilizing isochronal aging experiments as well as compressive and tensile creep tests performed between 275 and 400 °C. The Al-0.5Mn-0.09Zr-0.05Er-0.05Si alloy exhibits an unusually high creep resistance in the peak-aged state, which is significantly better than that observed generally in its Mn-free L12-strengthened counterparts; for example, the creep threshold stresses at 300 °C are 34-37 MPa, about three times higher than those in a Mn-free Al-0.11Zr-0.005Er-0.02Si alloy. Scanning transmission electron microscopy illustrates that nanoscale Al 3 (Zr,Er) L1 2 -precipitates are formed in the dendritic cores and micron-sized Al(Mn,Fe)Si α-precipitates in the inter-dendritic channels. Moreover, the Al(f.c.c.)-matrix remains supersaturated with randomly distributed Mn solute atoms, as determined by atom-probe tomography and electrical conductivity measurements, for months at creep temperatures. Creep experiments on the Zr- and Er-free Al-0.5Mn-0.02Si solid-solution alloy reveal a small primary creep strain, a high apparent stress exponent, na ~9-7, and a threshold-stress-type behavior. After ruling out other possible mechanisms, we provide evidence that the threshold stress in this precipitate-free alloy originates from dislocation/solute elastic interactions leading to a strong drag force exerted on edge dislocations, hindering their ability to climb. The relatively high creep resistance of Al-0.5Mn-0.09Zr-0.05Er-0.05Si is interpreted in terms of the synergy between this solute-induced threshold stress (SITS, from Mn in solid-solution) and the known precipitate-bypass threshold stress (from the L12-nanoprecipitates).
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The processing of aluminum alloys in optimal conditions is a problem that has not yet been fully resolved. The research carried out so far has proposed various intelligent tools, but which cannot be used in the presence of cooling-lubricating fluids. The objective of the research carried out in the paper was to design intelligent tools that would allow a control of the vibrations of the tool tip and to determine a better roughness of the processed surfaces. The designed intelligent tools can be used successfully in the processing of aluminum alloys, not being sensitive to coolants-lubricants. In the research, the processing by longitudinal turning of a semi-finished product with a diameter Ø = 55 mm of aluminum alloy A2024-T3510 was considered. Two constructive variants of smart tools were designed, realized, and used, and the obtained results were compared with those registered for the tools in the classic constructive variant. The analysis of vibrations that occur during the cutting process was performed using the following methods: Fast Fourier Transform (FFT); Short-Time Fourier-Transformation (STFT); the analysis of signal of vibrations. A vibration analysis was also performed by modeling using the Finite Element Method (FEM). In the last part of the research, an analysis of the roughness of the processed surfaces, was carried out and a series of diagrams were drawn regarding curved profiles; filtered profiles; Abbott-Firestone curve. Research has shown that the use of smart tools in the proposed construction variants is a solution that can be used in very good conditions for processing aluminum alloys, in the presence of cooling-lubrication fluids.
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In this research, we intended to examine the effect of heating mode on the densification, microstructure, mechanical properties, and corrosion resistance of sintered aluminum alloys. The compacts were sintered in conventional (radiation-heated) and microwave (2.45 GHz, multimode) sintering furnaces followed by aging. Detailed analysis of the final sintered aluminum alloys was done using optical and scanning electron microscopes. The observations revealed that the microwave sintered sample has a relatively finer microstructure compared to its conventionally sintered counterparts. The experimental results also show that microwave sintered alloy has the best mechanical properties over conventionally sintered compacts. Similarly, the microwave sintered samples showed better corrosion resistance than conventionally sintered ones.
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The relations between the mechanical properties, heat treatment, and compositions of elements in aluminum alloys are extracted by a materials informatics technique. In our strategy, a machine learning model is first trained by a prepared database to predict the properties of materials. The dependence of the predicted properties on explanatory variables, that is, the type of heat treatment and element composition, is searched using a Markov chain Monte Carlo method. From the dependencies, a factor to obtain the desired properties is investigated. Using targets of 5000, 6000, and 7000 series aluminum alloys, we extracted relations that are difficult to find via simple correlation analysis. Our method is also used to design an experimental plan to optimize the materials properties while promoting the understanding of target materials.
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The morphology, composition, and structure of precipitates in an Al-Si-Mg-Hf alloy after heat treatment at 560°C for 20 h were studied by means of C s -corrected high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), energy dispersive X-ray spectrometry (EDS), high-resolution transmission electron microscopy (HRTEM), and first-principle calculations. Precipitates with three kinds of morphologies were observed. The rectangular and square precipitates were predominantly (Si2-x Al x )Hf phases, while the nanobelt-like precipitate is the Si2Hf phase. First-principle calculations were used to show that the Si6 and Si8 sites were the most favorable sites for Al incorporation in the orthorhombic Si2Hf phase.
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Nano zero-valent iron (NZVI) particles have been extensively investigated for nitrate reduction in water. However, the reduction by NZVI requires acidic pH conditions and the final product is exclusively ammonium, leading to secondary contamination. In addition, nanomaterials have potential threats to environment and the transport and storage of nanomaterials are of safety concerns. Aluminum, the most abundant metal element in the earth's crust, is able to reduce nitrate, but the passivation of aluminum limits its application. Here we report Al alloys (85% Al) with Fe, Cu or Si for aqueous nitrate reduction. The Al alloys particles of 0.85-0.08 mm were inactivate under ambient conditions and a simple treatment with warm water (45 °C) quickly activated the alloy particles for rapid reduction of nitrate. The Al-Fe alloy particles at a dosage of 5 g/L rapidly reduced 50 mg-N/L nitrate at a reaction rate constant (k) of 3.2 ± 0.1 (mg-N/L)1.5/min between pH 5-6 and at 4.0 ± 0.1 (mg-N/L)1.5/min between pH 9-11. Dopping Cu in the Al-Fe alloy enhanced the rates of reduction whereas dopping Si reduced the reactivity of the Al-Fe alloy. The Al alloys converted nitrate to 20% nitrogen and 80% ammonium. Al in the alloy particles provided electrons for the reduction and the intermetallic compounds in the alloys were likely to catalyze nitrate reduction to nitrogen.
Assuntos
Alumínio , Desnitrificação , Purificação da Água , Ligas , Ferro , Nitratos , Água , Poluentes Químicos da ÁguaRESUMO
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.
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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.
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Additively manufactured aluminum alloy parts attract extensive applications in various felids. To study the machinability of additively manufactured aluminum alloys, micro-milling experiments were conducted on the additively manufactured AlSi7Mg and AlSi10Mg. By comparing the machinability of Al-Si-Mg aluminum alloys with different Si content, the results show that due to the higher hardness of the AlSi10Mg, the cutting forces are higher than the AlSi7Mg by about 11.8% on average. Due to the increased Si content in additively manufactured Al-Si-Mg aluminum alloys, the surface roughness of AlSi10Mg is 26.9% higher than AlSi7Mg on average. The burr morphology of additively manufactured aluminum alloys in micro-milling can be divided into fence shape and branch shape, which are, respectively, formed by the plastic lateral flow and unseparated chips. The up-milling edge exhibits a greater burr width than the down-milling edge. Due to the better plasticity of AlSi7Mg, the burr width of the down-milling edge is 28.1% larger, and the burr width of the up-milling edge is 10.1% larger than the AlSi10Mg. This research can provide a guideline for the post-machining of additively manufactured aluminum alloys.
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Liquid aluminum containing the important alloying element magnesium in varying concentrations was analyzed using in-situ laser-induced breakdown spectroscopy (LIBS). Magnesium emission shows an exponential dependence on melt temperature that correlates well with the expected partial pressure of magnesium above the aluminum melt. Furthermore, comparison with LIBS measurements on corresponding solid samples supports the conclusion that a significant part of Mg emission from liquid metal samples originates from the vapor phase above the metal surface. Simultaneously, curves of growth measured over four orders of magnitude in Mg concentration reveal a level of self-absorption for liquid aluminum samples that is stronger than for solid aluminum samples having a corresponding Mg concentration, and beyond what is expected from conventional plasma models. The implications for measurements of volatile species in liquid metals in general are discussed.
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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.
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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.
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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, ß-Mg2Si, Q-Al4Cu2Mg8Si7, and α-Al15(FeMn)3 (SiCu)2, along with Pb particles. Most primary intermetallic precipitates such as θ-Al2Cu, ß-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.
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The safe service and wide applications of lightweight high-strength aluminum alloys are seriously challenged by diverse environmental corrosion, since high strength and corrosion resistance are mutually exclusive for metals while surface protection cannot provide life-long corrosion resistance. Here, inspired by fish secreting slime from glands to resist external changes, a strategy of incorporating precipitants as the slime into bulk metals using the inner cavity of opened carbon nanotubes (CNTs) as the glands is developed to enable high-strength aluminum alloys with life-long superior corrosion resistance. The resulting material has ultrahigh tensile strength (≈700 MPa) and extraordinary corrosion resistance in acidic, neutral and alkaline media. Notably, it has the highest resistance to intergranular corrosion, exfoliation corrosion and stress-corrosion cracking, compared with all previously reported aluminum alloys, and its corrosion rate is even much lower than that of corrosion-resistant pure aluminum, which results from the pronounced surface enrichment of precipitants released (secreted) from exposed CNTs forming a protective surface film. Such high corrosion resistance is life-long and self-healing due to the on-demand minimal self-supply of the precipitants dispersed throughout the bulk material. This strategy can be readily expanded to other aluminum alloys, and could pave the way for developing corrosion-resistant high-strength metallic materials.
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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.
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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.