Microstructure and mechanical properties of new die-cast quaternary Al-Cu-Si-Mg alloys

Cai, Qing; Mendis, C.L.; Chang, I.T.H.; Fan, Z.

doi:10.1016/j.msea.2020.140357

Cited by 20 publications

(8 citation statements)

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“…plunger, the entire development of dependence was similar to one of the values mentioned by the authors, Majernik 2016, Zhang 2020b, Cai 2021. About the aforementioned facts, it has been proved and confirmed that mechanical properties are considerably influenced by mould cavity filling mode and thus lower values of castings speed of plunger are recommended to be opted for.…”

supporting

confidence: 80%

Influence of Die Casting Speed on Properties of Casting Based on Al-Si Alloys

Ružbarský¹

2022

MM SJ

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The paper focuses on the research of the influence of chosen technological parameters of die casting on the selected mechanical properties of castings based on Al-Si alloys. The experiments conducted within the frame of the practical part examined the plunger pressing speed in the mould cavity influencing the mechanical properties of a casting which were represented by ultimate tensile strength and percentage share of porosity of Al-Si castings. Plunger pressing speed is closely related to mould cavity filling mode which affected the final porosity of casting. In the case of increased percentage porosity share, the ultimate tensile strength decrease was detected due to the reduction of the cross-section area of the casting. The increase in percentage porosity share in the casting was caused by the increase in plunger pressing speed. To achieve the desired quality of castings, higher production efficiency, and reduced occurrence of faulty pieces during production, an optimal set of technological parameters of die casting is inevitable.

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supporting

confidence: 80%

Influence of Die Casting Speed on Properties of Casting Based on Al-Si Alloys

Ružbarský¹

2022

MM SJ

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“…It is necessary to develop a new generation of software tools that support automated model selection, parameter optimization, and database development. Fortunately, the software package, Extensible Self-optimizing Phase Equilibria Infrastructure, which is built on DFT data developed by Bocklund et al [180] , offers a free and open-source tool for users to develop multicomponent databases. When the subsystem is updated, the thermodynamic parameters of the higher-order systems can be efficiently reevaluated, which reduces the time of database development.…”

Section: Beyond the Thermodynamic Databasementioning

confidence: 99%

Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques

Wang¹,

Liu²,

Gao³

et al. 2021

JMI

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Casting aluminum alloys are commonly used in industries due to their excellent comprehensive performance. Alloying/microalloying and post-solidification heat treatments are the most common measures to tune the microstructure for enhancing their mechanical properties. However, it is very challenging to achieve accurate and efficient development of novel casting aluminum alloys using the traditional trial-and-error method. With the rapid development of computer technology, the computational thermodynamics (CT) in the framework of the CALculation of PHAse Diagram approach, the data-driven machine learning (ML) technique, and also their combinations have been proved to be effective approaches for the design of casting aluminum alloys. In this review, the state-of-the-art computational alloy design approaches driven by CT and ML techniques, as well as their combinations, were comprehensively summarized. The current status of the thermodynamic database for aluminum alloys, as the core for CT, was also briefly introduced. After that, a variety of successful case studies on the design of different casting aluminum alloys driven by CT, ML, and their combinations were demonstrated, including common applications, CT-driven design of Sc-additional Al-Si-Mg series casting alloys, and design of Srmodified A356 alloys driven by combing CT and ML. Finally, the conclusions of this review were drawn, and perspectives for boosting the computational design approach driven by combining CT and ML techniques were pointed out.

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“…By adjusting processing conditions, pure ternary eutectic or a bimodal structure consisting of two-phase cells and highly regular ternary eutectic could be produced. These types of hierarchical microstructures show promise for a variety of highstrength, lightweight applications [11]. [12] at compositions along the tie line joining the binary Al-Cu and ternary Al-Cu-Mg eutectics, which deployed the constitutional undercooling model to describe the criterion for the breakdown of the planar growth front in the presence of varying Mg content.…”

Section: Introductionmentioning

confidence: 99%

Microstructure evolution during directional solidification of off-eutectic Al-Cu-Mg alloys

Ezemenaka

Small

Genau

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Building on previous studies of invariant ternary eutectic Al-Al2Cu-Al2CuMg, this work aims to deepen our understanding of the microstructural possibilities in the Al-rich region of the Al-Cu-Mg phase diagram by considering the solidification behaviour of several off-eutectic compositions. Four Al-Cu-Mg alloys were directionally solidified at a constant growth rate (1.25 μm/s) and thermal gradient (9-14 K/mm) using a Bridgman-type furnace and analysed using a combination of scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, and differential scanning calorimetry. Qualitative and quantitative analyses showed a preference for faceted Al2Cu dendrites surrounded by a ternary eutectic matrix in the two Mg-poor samples, even though one composition was not in the primary Al2Cu phase region. The two Al-poor samples consisted of large regions of three different intermetallic phases and little eutectic, making these samples very brittle.

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Microstructure and mechanical properties of new die-cast quaternary Al-Cu-Si-Mg alloys

Cited by 20 publications

References 50 publications

Influence of Die Casting Speed on Properties of Casting Based on Al-Si Alloys

Influence of Die Casting Speed on Properties of Casting Based on Al-Si Alloys

Boosting for concept design of casting aluminum alloys driven by combining computational thermodynamics and machine learning techniques

Microstructure evolution during directional solidification of off-eutectic Al-Cu-Mg alloys

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