Microstructural characterization of dendritic evolution using two-point statistics

Elder, Kate L. M.; Stan, Tiberiu; Sun, Yue; Xiao, Xianghui; Voorhees, Peter W.

doi:10.1016/j.scriptamat.2020.02.034

Cited by 11 publications

(5 citation statements)

References 29 publications

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“…Even though we attempted to correct for the misorientation of the dendrite growth direction, we expect that underlying assumptions also lead to some amount of error in the PDAS measurements. Such issues could be tackled in further studies using three-dimensional visualization methods, such as X-ray tomography [103][104][105][106][107], which would provide an unambiguous representation of dendritic arrays and spacings.…”

Section: Methodsmentioning

confidence: 99%

Multiscale prediction of microstructure length scales in metallic alloy casting

Bellón

Boukellal

Isensee

et al. 2021

Preprint

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Microstructural length scales, such as dendritic spacings in cast metallic alloys, play an essential role in the properties of structural components. Therefore, quantitative prediction of such length scales through simulations is important to design novel alloys and optimize processing conditions through integrated computational materials engineering (ICME). Thus far, quantitative comparisons between experiments and simulations of primary dendrite arms spacings (PDAS) selection in metallic alloys have been mainly limited to directional solidification of thin samples and quantitative phase-field simulations of dilute alloys. In this article, we combine casting experiments and quantitative simulations to present a novel multiscale modeling approach to predict local primary dendritic spacings in metallic alloys solidified in conditions relevant to industrial casting processes. To this end, primary dendritic spacings were measured in instrumented casting experiments in Al-Cu alloys containing 1 wt% and 4 wt% of Cu, and they were compared to spacing stability ranges and average spacings in dendritic arrays simulated using phase-field (PF) and dendritic needle network (DNN) models. It is first shown that PF and DNN lead to similar results for the Al-1 wt%Cu alloy, using a dendrite tip selection constant calculated with PF in the DNN simulations. PF simulations cannot achieve quantitative predictions for the Al-4 wt%Cu alloy because they are too computationally demanding due to the large separation of scale between tip radius and diffusion length, a characteristic feature of nondilute alloys. Nevertheless, the results of DNN simulations for non-dilute Al-Cu alloys are in overall good agreement with our experimental results as well as with those of an extensive literature review. Simulations consistently suggest a widening of the PDAS stability range with a decrease of the temperature gradient as the microstructure goes from cellular-dendrites to well-developed hierarchical dendrites.

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Section: Methodsmentioning

confidence: 99%

Multiscale prediction of microstructure length scales in metallic alloy casting

Bellón

Boukellal

Isensee

et al. 2021

Preprint

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“…Because the three-dimensional observations provide significant information on the microstructure evolution in the three-dimensional space, time-resolved in situ tomography (referred to as 4D-TC) has been developed [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. For example, the late stage of solidification of Al-4mass%Cu alloys (1 mm in diameter, cooling rate of 0.1 K/s) was observed using a pink beam (peak energy of 40 keV) to increase the transmission X-ray intensity [19].…”

Section: Introductionmentioning

confidence: 99%

“…Particular attention has been paid to image processing in 4D-CT analysis [29,31]. Our previous study reported a preliminary result for image processing of dendrites in Fe-C alloys and proposed a filtering technique using a phase field model [29].…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of dendritic growth by fast tomography and phase field filtering

Yasuda,

Nishiguchi,

Xue

et al. 2023

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

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Three dimensional models of dendritic structures during solidification are valuable for building physical models, validating simulated results, estimating some properties such as permeability in the mushy, simulating semisolid deformation and so on. Thus, it is of interest to observe microstructure evolution in situ. Time-resolved tomography combined with X-ray diffraction has allowed us to observe the evolution of dendritic structures and to measure crystallographic orientation in situ. Reconstruction still proves to be difficult for some alloy systems because of the tradeoff between time and spatial resolution. This paper demonstrates the reconstruction of dendritic structures for three different alloy systems (Al-10mass%Cu alloy with a diameter of 4 mm, CrMnFeCoNi alloy with 1 mm, and Zn-4mass%Al alloy with 0.7 mm). The observations were performed in a synchrotron radiation facility SPring-8. A filter using a phase field model was introduced to reconstruct the three-dimensional images. Parameters used in the filtering were consistently determined based on the raw reconstruction images. Evaluation of solid-liquid interface area and curvature was significantly improved by the filter. For the Al-Cu alloy, a three-dimensional model containing approximately 300 million voxels was obtained. For the CrMnFeCoNi alloys, the preferred growth direction <100> was confirmed by tomography and X-ray diffraction. For the Zn-Al alloy, the observed 14 growth directions were not simply defined by the crystallographic orientations, although the directions were consistent with the hexagonal symmetry. This study verifies that time resolved tomography, X-ray diffraction and the filter using a phase field model provide three dimensional models for light metal alloys with rather large diameters and 3d transition-metal alloys with rather large X-ray absorption coefficients. The models are expected to be used for further studies.

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“…In most cases the metallic alloys solidify through the formation of dendritic microstructures [2]. The morphologies of dendritic crystals impact many mechanical, thermal, electrical, and chemical properties [1,3,4]. Thus, characterizing the formation and evolution of dendritic microstructures is critical for understanding and applying processing-structureproperty relationships in materials [5].…”

Section: Introductionmentioning

confidence: 99%