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DOI: 10.1016/j.jmrt.2018.05.021
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Experimental study of the evolution of tertiary dendritic arms and microsegregation in directionally solidified Al–Si–Cu alloys castings
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Luis Antonio de Souza Baptistaa,
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lbaptista@id.uff.br

Corresponding author.
, Kessia Gomes Paradelaa, Ivaldo Leão Ferreirab,c, Amauri Garciac, Alexandre Furtado Ferreiraa
a Graduate Program on Metallurgical Engineering, Universidade Federal Fluminense, 27255-125 Volta Redonda, RJ, Brazil
b Federal University of Pará – UFPA, 66075-110 Belém, PA, Brazil
c Department of Manufacturing and Materials Engineering, University of Campinas – UNICAMP, 13083-860 Campinas, SP, Brazil
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Abstract

It is widely recognized that moderate addition of copper to aluminum, especially when added together with silicon, significantly improves the resulting mechanical properties. Hypoeutectic ternary Al–Si–Cu alloys were used in the present experimental study to investigate the effect associated with the Cu content and the solidification thermal parameters on the microstructural and microsegregation features. Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys were directionally solidified under transient heat flow conditions under a range of cooling rates from 0.2 to 9°C/s. A quite complex dendritic arrangement prevailed along the entire length of both examined castings, giving rise to well-defined tertiary dendritic arms (λ3). Experimental growth laws relating λ3 to the cooling rate have been determined indicating that the increase in the Cu alloy content from 2 to 4wt% has induced a thickening effect leading to increase of about 50% in λ3. The effect of the solidification kinetics on microsegregation has been experimentally investigated for different positions along the castings length. The Cu profiles were shown to move upwards with the increase in the solidification velocity for both examined alloys. In contrast, an inverse trend was shown to occur with the Si segregation profiles for both alloys, which moved downward with the increase in the solidification velocity.

Keywords:
Aluminum ternary alloys
Solidification
Alloying elements
Dendritic microstructure and microsegregation
Full Text
1Introduction

The automotive industry is the main area where aluminum-based casting alloys are widely applied. This is due to their excellent casting characteristics, mechanical properties, weldability and good corrosion resistance. Copper (Cu) and magnesium (Mg) are the main alloying elements added to aluminum–silicon based casting materials (Al–Si). In the next years, the application of aluminum casting alloys, in particular Al–Si–Cu, in the manufacture of engine blocks and cylinder heads is expected to grow significantly. Addition of Cu to Al–Si alloys leads to increased alloy fluidity, and better mechanical properties such as tensile strength [1]. It is well known from the Al–Si phase diagram, that at 577°C, the amount of Si in solid solution in Al is about 1.65wt%. This value decreases with decreasing temperature, reaching 0.16wt% at 300°C. Copper addition to Al–Si alloys leads to the formation of the Al2Cu intermetallic compound. After solidification, the resulting microstructure of Al–Si–Cu alloys has direct influence on the mechanical properties of the cast material. The mechanical properties uniformity and the corrosion resistance of the cast are also affected by the resulting microstructure [2,3].

Both the solidification microstructure and microsegregation have been extensively studied theoretically [4–7] and experimentally [8–11] along the last decades. Several works [4–12] have been carried out and highlighted the importance of taking into account the effect of solidification thermal parameters on the resulting microstructural features and microsegregation. Several different experimental researches for binary alloys of metallurgical interest have been developed focusing on such aspects [7–12]. On the other hand, experimental works on multicomponent alloys are scarce in the literature [3–15]. An Al–Si–Cu alloy has been chosen by Medrano et al. [13], in order to study the changes in microstructure and hardness after nickel additions (1 and 2wt%Ni). Microstructural changes in morphology, size and spatial distribution of precipitates, revealed by transmission electron microscopy, have been reported to increase hardness by 6–8% with mean values reaching about 142HV. An experimental study by Dobrzánski et al. [14] reported the effect of the solidification rate on the dendritic arm spacing and microhardness of ternary Al–Si–Cu alloys. The experimental results obtained by these authors, revealed that the solidification rate plays a critical role on the refinement of microstructure, with the increase in such solidification thermal parameter having a strong effect on the resulting microhardness.

The present study focuses on the effects of solidification thermal parameters on the complexity of the dendritic morphology, the size of a representative dendritic structure and, also, the resulting microsegregation along adjacent dendritic arms of Al–Si–Cu alloys. Dendritic spacing usually refers to the spacing between the secondary arms of the dendrites. However, if tertiary arms are present, with smaller dimensions, the spacing will be referred to this one since its smaller dimensions become more significant for the properties of the material [16]. Two hypoeutectic ternary alloys (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu) are directionally solidified (DS) under transient heat flow conditions in a cooled mold, thus permitting the effect of a wide range of solidification thermal parameters to be analyzed. Furthermore, in order to investigate the effect of Cu content on the dendritic arm spacing and microsegregation profiles along the length of the castings, two Cu concentrations are examined: 2 and 4wt%Cu.

2Experimental procedure

Two ternary alloys (Al–Si–Cu), the first containing 9wt%Si and 2wt%Cu and the second containing 9wt%Si and 4wt%Cu, were prepared in an electric resistance furnace at 800°C, from commercially pure metals, i.e., 99.9% Al, 99.7%Si and 99.9%Cu. The ternary alloys were directionally solidified under unsteady-state heat flow conditions. The experiment would allow that solidification thermal parameters (solidification velocity and cooling rate) to be experimentally determined and correlated with the tertiary dendritic arm spacing. The solidification experiment was carried out on a unidirectional vertical upward cooling apparatus. The apparatus is detailed in previous article [11]. The melt was poured into a steel mold, and then directionally solidified under unsteady-state heat flow conditions. A thin steel sheet was used as the base of the mold. This steel sheet separates the melt from a water-cooling system. The pouring temperature (TP) was setup at 50°C above the alloy liquidus temperature (TL). Along the solidification process, temperature was monitored by the output of a bank of K type thermocouples positioned at the central line of the castings at 5, 10, 15, 20, 35, 45, 60, 85mm from the water cooled bottom.

A transverse sample was extracted from a position as close as possible of the tip of each thermocouple (from 5 to 85mm from the mold bottom). The resulting 8 samples were polished and etched with a 0.5%HF solution [17,18]. An Olympus Optical Microscope (Olympus Corporation, Japan) was used to produce digital images that were analyzed using the Goitaca (https://sourceforge.net/projects/goitacaeq) image processing software in order to measure the dendritic arm spacing. Two scanning electron microscopes JEOL (JEOL, Ltd., Japan) model JSM 5800LV and JSM 6460LV with energy-dispersive spectrometer NORAN System 6 (Thermo Fisher Scientific) and WDS/EDS Oxford (Oxford Instruments) respectively were used to determine the solutes concentration between adjacent dendritic arms. Both WDS and EDS have been used but, although WDS could present a better detection limit than EDS, for the elements and composition range involved, the EDS was mostly used since the obtained results did not justify the greater time and cost involved in the use of the WDS.

The concentration measurement initiates at the center of a dendritic arm and ends at the midpoint of the interdendritic region between adjacent arms, defining the microsegregation path, as shown in Fig. 1. About 40 concentration measurements were performed for each examined position along the length of the castings.

Fig. 1.
(0.22MB).

Track adopted for microsegregation profiles along tertiary adjacent dendritic arms of Al–9wt%Si–2wt%Cu alloy.

3Results and discussion

Fig. 2a and b shows the pseudo-binary phase diagram of the alloy system investigated in the present work, calculated by thermodynamics software [19]. In Fig. 2a both hyper and hypo eutectic regions are in evidence. Fig. 2b emphasizes the liquid–solid transformation region, particularly the beginning of silicon phase solubility curve at 12.2wt%Cu and 556.7°C. The precipitation of Si is also noticed as the solidification proceeds along the liquidus line.

Fig. 2.
(0.16MB).

Pseudo-binary phase diagram for the Al–9wt%Si–Xwt%Cu system: (a) hyper and hypo eutectic regions and (b) magnification of liquid–solid transformation region.

Fig. 3 shows the cooling curves obtained for both alloys (Al–9wt%Si–2wt%Cu alloy and Al–9wt%Si–4wt%Cu alloy), by the thermocouples placed at different positions along the casting length. The temperature profiles decrease faster at regions closer to the water cooled bottom of the steel mold. The cooling rate then gradually dwindles toward completion of local solidification.

Fig. 3.
(0.18MB).

Temperature vs. time curves recorded at different positions along the length of the castings: (a) Al–9wt%Si–2wt%Cu alloy and (b) Al–9wt%Si–4wt%Cu alloy.

By using the cooling curves and the liquidus temperature of each alloy, the position (P) of each thermocouple can be correlated with the time (t) of passage of the liquidus isotherm by each thermocouple, thus permitting curves P vs. t to be plotted, as shown in Fig. 4 (solid line). The derivative of the experimentally generated P=f(t) functions with respect to time, permits the solidification velocity (VL) to be determined as a function of time, as also plotted in Fig. 4 (dashed line).

Fig. 4.
(0.14MB).

Position of liquidus temperature (P) and solidification velocity (VL) vs. time along the length of the castings: (a) Al–9wt%Si–2wt%Cu alloy and (b) Al–9wt%Si–4wt%Cu alloy.

In both Fig. 4a and b, the solidification velocity (VL) is seen to decrease faster at the onset of solidification, followed by a gradual decrease over time. This is due to the fact that the water-cooling system favors higher solidification velocity at the beginning of solidification, which decreases along the process because of the increasing thermal resistance of the solidified layer. The relationship between VL and P for both alloys is depicted in Fig. 5, where the experimental results of both alloys (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys), are plotted for comparison purposes. One can see a slight deviation between the experimental curves, which indicates that the increase in the alloy copper content from 2 to 4wt%Cu caused a decrease in the VL profile along the casting length.

Fig. 5.
(0.07MB).

Solidification velocity (VL) vs. position (P) along the casting length.

The cooling rate (T˙) has been calculated considering the temperatures vs. time data immediately after the passage of the liquidus isotherm for the different thermocouples positions in the casting. The temperature data were collected at intervals of 0.001s, in order to permit an accurate determination of the cooling rate. To investigate the effects of solidification thermal parameters (VL and T˙) and alloy copper content on microstructural features and microsegregation, samples were taken from locations close to the thermocouples tip along the castings. A quite complex dendritic arrangement prevailed along the entire length of both examined castings, giving rise to well-defined tertiary dendritic arms of the main Aluminum matrix, as shown in Fig. 1. In such dendritic network the tertiary dendritic arms play an important role, since they contribute for a more extensive distribution of both solutes (microsegregation) and of the intermetallic phase (Al2Cu) throughout the microstructure. It is important to emphasize that T˙ and VL will also have an important role, since they vary continuously along the castings length, and may affect the microsegregation pattern between adjacent tertiary dendritic arms. Fig. 6 shows the evolution of transverse microstructures along the castings length of both examined alloys (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys). At the right side of each microstructure, one can see information of sample position in the casting (P), solidification velocity (VL), cooling rate (T˙) and tertiary dendritic arm spacing (λ3). It can be observed that, the λ3 increases significantly with the decrease in VL and T˙. It can also be seen that, the increase in the alloy copper content (from 2 to 4wt%Cu) has a significant effect on the size of λ3, as shown in Fig. 7, where a comparison of λ3 vs. T˙ is shown for both alloys (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys). We can see that for both alloys castings λ3 decreases exponentially as T˙ increases with a behavior similar to the observed in the literature [7] although the coefficients in the equation are affected by the solutes in the alloy which have a direct effect on the dendritic solidification. It is observed that the results of Al–9wt%Si–4wt%Cu alloy lie above those obtained for Al–9wt%Si–2wt%Cu alloy, that is, the increase in copper content has a significant thickening effect on λ3, which increases of about 90% as compared with the corresponding values of Al–9wt%Si–2wt%Cu alloy.

Fig. 6.
(0.79MB).

Photomicrographs of samples taken from transverse sections along the castings.

Fig. 7.
(0.08MB).

Tertiary dendritic arm spacing (λ3) vs. cooling rate (T˙).

Fig. 8 a and b depicts the experimentally measured composition profiles of Cu and Si for Al–9wt%Si–2wt%Cu alloy along a microsegregation path taken from the center of a tertiary dendritic arm (0) up to the center of the interdendritic region, considering adjacent tertiary dendritic branches (λ3/2). Fig. 8c and d depicts the results obtained for Al–9wt%Si–4wt%Cu alloy.

Fig. 8.
(0.35MB).

Effect of solidification kinetics on microsegregation of Cu and Si along the length of the ternary alloys castings (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys).

In Fig. 8a–d, both Cu and Si concentration increase gradually from the center of the tertiary arm (0) to the center of the interdendritic region (λ3/2). It can be seen in Fig. 8a and c that the Cu profiles move upward with the increase in VL. This is in agreement with the effect of VL on microsegregation reported in a previous study with binary Al-alloys and solutes having redistribution coefficient k<1, i.e., Al–Cu and Al–Fe alloys [12]. When Fig. 8a and c are compared it can be seen that for Al–9wt%Si–2wt%Cu alloy, which have more refined λ3 values, the highest Cu profile varies from about 2wt%Cu at the center of tertiary dendritic arm to 12wt%Cu at the center of the interdendritic region, while for the Al–9wt%Si–4wt%Cu alloy the maximum microsegregation profile varies from about 3wt%Cu to 6wt%Cu. In other words, despite having lower Cu content, the Al–9wt%Si–2wt%Cu alloy casting has a higher solidification velocity profile, finer λ3 and higher Cu segregation profile as compared with the corresponding values of Al–9wt%Si–4wt%Cu alloy. In contrast, an inverse trend can be observed with Si microsegregation, i.e., the Si profiles move downward with the increase in VLFig. 8b and d. Closer examination in the experimental results of Fig. 8a–d, suggests that the solubility of Si in the solid phase is influenced by multielement interaction effects in both ternary alloys (Al–9wt%Si–2wt%Cu and Al–9wt%Si–4wt%Cu alloys). As the material solidifies the solutes Cu and Si are rejected from the solidification front to the remaining liquid. In the case of binary alloys this would result in the classical microsegregation model where an increase in solute amount in the solid is observed along the solidification. However, the presence of Cu in the Al–Si alloy decreases the maximum solubility of Si in the liquid. Therefore, the Cu rejection at the solidification front causes a reduction in the Si content in the liquid as it precipitates as other phases. As the solidification proceeds the continuous increase of the Cu content in the liquid limits the Si content in the liquid and, therefore, reduces de Si content along the dendritic matrix. In the experimental results shown in Fig. 8a–d, this effect can be observed. It seems that the dendritic growth of Al-rich matrix has been accompanied by progressive enrichment of Cu in the residual liquid and only minute amounts of Si are found in solid solution after solidification. The experimental results obtained in present work point that the presence of Cu solute in the alloy decreases the solubility of Si in the solid region. As the solidification proceeds, the continuous increase of the Cu content in the solid region limits the Si content in dendritic matrix. This effect can be observed in the experimental results shown in Fig. 8a–d.

4Conclusions

The effect of solidification thermal parameters and Cu concentration on microstructure features and microsegregation has been experimentally investigated on Al–9wt%Si–Cu alloys. It was shown that a quite complex dendritic arrangement prevailed along the entire length of both examined castings, giving rise to well-defined tertiary dendritic arms. The increase in the copper content from 2 to 4wt%Cu was shown to induce decrease in the solidification velocity profile along the casting length, and thickening effect on the tertiary dendritic arm spacing, which increased about 50% as compared with the corresponding values of the Al–9wt%Si–2wt%Cu alloy casting. The microsegregation profiles between adjacent tertiary dendritic arms revealed that both solutes profiles increase gradually from the center of a tertiary dendritic arm toward the center of the interdendritic region. The Cu profiles were shown to move upwards with the solidification velocity increase for both examined alloys. The Al–9wt%Si–2wt%Cu alloy was shown to combine higher solidification velocity profile, finer λ3 and higher Cu segregation profile as compared with the corresponding values of the Al–9wt%Si–4wt%Cu casting. In contrast, an inverse trend was shown to occur with the Si segregation profiles for both alloys, which are lower as compared with the corresponding Cu profiles and moved downward with the increase in the solidification velocity. This trend suggests that the Si solute in the solid phase is influenced by multielement interaction effects during solidification of the ternary alloys.

Conflicts of interest

The authors declare no conflicts of interest.

Acknowledgements

We would like to express our deep appreciation for the support provided by the Instituto Militar de Engenharia through its Material and Mechanical Engineering Section and PETROBRAS through its Research Center – CENPES, for the use of their Scanning Electron Microscopy and X-ray Microanalyses laboratories that allowed the development of the present study. Special thanks to the staff of these institutions that have greatly helped in the activities.

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Luis Antonio de Souza Baptista Professor at Universidade Federal Fluminense, Metallurgical Engineer (74) Instituto Militar de Engenharia, Brazil, MASc (78) University of British Columbia, Canada. Graduate Program on Metallurgical Engineering, Universidade Federal Fluminense, Brazil.

Kessia Gomes Paradela Graduate Program on Metallurgical Engineering Universidade Federal Fluminense, Brazil, Chemical Engineer.

Ivaldo Leão Ferreira Professor, Graduate Program on Metallurgical Engineering Universidade Federal Fluminense, Brazil Mechanical Engineer (97) Universidade Federal do Pará, Brazil, MSc (99) Mechanical Engineering Universidade Federal do Pará, Brazil, DSc (05) Mechanical Engineering UNICAMP, Brazil.

Amauri Garcia Professor at UNICAMP Universidade Estadual de Campinas, Brazil, DSc (78) UNICAMP Mechanical Engineering, MSc (75) UNICAMP Mechanical Engineering, Mechanical Engineer (72) UNICAMP.

Alexandre Furtado Ferreira Professor, Graduate Program on Metallurgical Engineering, Universidade Federal Fluminense, DSc (05) UFF Metallurgical Engineering, MSc (00) UFF Metallurgical Engineering, Metallurgical Engineer (97) Universidade Federal Fluminense.

Copyright © 2018. Brazilian Metallurgical, Materials and Mining Association
Journal of Materials Research and Technology

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