Alloy design strategies to increase strength and its trade-offs together

Han, Seung Zeon; Choi, Eun–Ae; Lim, Sung Hwan; Kim, Sangshik; Lee, Je-Hyun

doi:10.1016/j.pmatsci.2020.100720

Cited by 92 publications

(19 citation statements)

References 165 publications

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“…During solidification, the primary Si precipitates first, and then the metastable δ-Al 4 FeSi 2 should form [ 60 ]. Once the nucleation of δ-Al 4 FeSi 2 phase takes place, both Fe and Si elements diffuse to the edge of δ-Al 4 FeSi 2 phase because of the decreasing solubility of these two elements in α-Al matrix [ 61 ], promoting further growth of δ-Al 4 FeSi 2 phase with one fast growth direction and two slow directions, which contributes the needle-like morphology. Subsequently, δ-Al 4 FeSi 2 phase will be transformed into β-Al 5 FeSi phase [ 62 ], which can be accomplished via the diffusion of Fe and Si atoms from δ-Al 4 FeSi 2 phase to α-Al matrix.…”

Section: Resultsmentioning

confidence: 99%

Effect of Substrate Plate Heating on the Microstructure and Properties of Selective Laser Melted Al-20Si-5Fe-3Cu-1Mg Alloy

Jia

et al. 2021

Materials

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The Al-20Si-5Fe-3Cu-1Mg alloy was fabricated using selective laser melting (SLM). The microstructure and properties of the as-prepared SLM, post-treated SLM, and SLM with substrate plate heating are studied. The as-prepared SLM sample shows a non-uniform microstructure with four different phases: fcc-αAl, eutectic Al-Si, Al2MgSi, and δ-Al4FeSi2. With thermal treatment, the phases become coarser and the δ-Al4FeSi2 phase transforms partially to β-Al5FeSi. The sample produced with SLM substrate plate heating shows a relatively uniform microstructure without a distinct difference between hatch overlaps and track cores. Room temperature compression test results show that an as-prepared SLM sample reaches a maximum strength (862 MPa) compared to the heat-treated (524 MPa) and substrate plate heated samples (474 MPa) due to the presence of fine microstructure and the internal stresses. The reduction in strength of the sample produced with substrate plate heating is due to the coarsening of the microstructure, but the plastic deformation shows an improvement (20%). The present observations suggest that substrate plate heating can be effectively employed not only to minimize the internal stresses (by impacting the cooling rate of the process) but can also be used to modulate the mechanical properties in a controlled fashion.

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Section: Resultsmentioning

confidence: 99%

Effect of Substrate Plate Heating on the Microstructure and Properties of Selective Laser Melted Al-20Si-5Fe-3Cu-1Mg Alloy

Jia

et al. 2021

Materials

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“…For Al alloys, the mobility of electrons usually depends on the solid solution degree of solute elements in Al matrix, which has been investigated thoroughly in the past few decades [9,10]. However, when the chemical composition of solute elements is fixed for a given Al-Si hypoeutectic alloy, it is generally believed that the micro-structures of the alloy play a decisive role on the thermal conductivity, for example the morphology and size of the Si phase [7,11,12], and the density of defects such as grain boundary and phase boundary [10,13], which can be reflect by the secondary dendrite arm spacing (SDAS) in as-cast conditions.…”

Section: Introductionmentioning

confidence: 99%

Effect of Cooling Rate and Modification by Strontium on the Thermal Conductivity of Al-8Si Alloy

Wang

Guan

Wang

et al. 2021

Metals

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Cooling rate plays a critical role in determining the thermal conductivity of Al-Si alloys. Although the effect of morphology and size of Si (changed by heat treatment) on its thermal conductivity has been investigated, the effect of cooling rates on thermal conductivity has not been well studied. In this study, we investigated the microstructure of an Al-8Si (with and without modification by Strontium (Sr)) alloy with cooling rates from 46.2 °C/s to 234 °C/s. It was found that the effect of cooling rate on thermal conductivity of Sr modification and Sr-free samples are opposite from each other. As a result, while the cooling rate increased from 46.2 °C/s to 234 °C/s, the calculated thermal conductivity increased from 145.3 MS/m to 151.5 MS/m for Sr-free Al-8Si alloy, and the calculated thermal conductivity was reduced from 187.5 MS/m to 176.7 MS/m for the Sr-modified Al-8Si alloy. By discussing how thermal conductivity correlates with eutectic silicon morphology and secondary dendrite arm spacing, the relationship between cooling rate and thermal conductivity were explained. This work suggests a new design strategy for improving the thermal conductivity of Al-Si hypoeutectic alloys.

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“…Nano-structured materials, i.e. materials with a high density of GBs, dominate the development of new technologies for energy harvesting and storage [2], for data processing, but also of solutions for structural applications [16,29], where the presence of interfaces leads to strengthening of the material [9,4]. The stability of such nanostructures can be tuned by the chemical composition, or rather the distribution of chemical elements in the microstructure and their segregation to grain boundaries.…”

Section: Introductionmentioning

confidence: 99%

Efficient prediction of grain boundary energies from atomistic simulations via sequential design

Kroll,

Schmalofski,

Dette

et al. 2021

Preprint

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Data based materials science is the new promise to accelerate materials design. Especially in computational materials science, data generation can easily be automatized. Usually, the focus is on processing and evaluating the data to derive rules or to discover new materials, while less attention is being paid on the strategy to generate the data. In this work, we show that by a sequential design of experiment scheme, the process of generating and learning from the data can be combined to discover the relevant sections of the parameter space. Our example is the energy of grain boundaries as a function of their geometric degrees of freedom, calculated via atomistic simulations. The sampling of this grain boundary energy space, or even subspaces of it, represents a challenge due to the presence of deep cusps of the energy, which are located at irregular intervals of the geometric parameters. Existing approaches to sample grain boundary energy subspaces therefore either need a huge amount of datapoints or a priori knowledge of the positions of these cusps. We combine statistical methods with atomistic simulations and a sequential sampling technique and compare this strategy to a regular sampling technique. We thereby demonstrate that this sequential design is able to sample a subspace with a minimal amount of points while finding unknown cusps automatically.

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Alloy design strategies to increase strength and its trade-offs together

Cited by 92 publications

References 165 publications

Effect of Substrate Plate Heating on the Microstructure and Properties of Selective Laser Melted Al-20Si-5Fe-3Cu-1Mg Alloy

Effect of Substrate Plate Heating on the Microstructure and Properties of Selective Laser Melted Al-20Si-5Fe-3Cu-1Mg Alloy

Effect of Cooling Rate and Modification by Strontium on the Thermal Conductivity of Al-8Si Alloy

Efficient prediction of grain boundary energies from atomistic simulations via sequential design

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