Microstructural characterization of dendritic evolution using two-point statistics

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

doi:10.1016/j.scriptamat.2020.02.034

Microstructural characterization of dendritic evolution using two-point statistics

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

^*Corresponding author for this work

Materials Science and Engineering

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Characterizing large four-dimensional materials datasets is difficult due to the presence of complex microstructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evolution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into competitive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.

Original language	English (US)
Pages (from-to)	81-85
Number of pages	5
Journal	Scripta Materialia
Volume	182
DOIs	https://doi.org/10.1016/j.scriptamat.2020.02.034
State	Published - Jun 2020

Funding

This work was supported by the U.S. Department of Energy [ DE-FG02-99ER45782 ]; and the Natural Sciences and Engineering Research Council of Canada (NSERC) [ PGSD3-516809-2018 ]. Use of the Advanced Photon Source was supported by the U.S. Department of Energy , Office of Science, Office of Basic Energy Sciences [ DE-AC02-06CH11357 ].

Keywords

Aluminum alloys
Dendritic growth
Solidification microstructure
Three-dimensional tomography
Two-point statistics

ASJC Scopus subject areas

General Materials Science
Condensed Matter Physics
Mechanics of Materials
Mechanical Engineering
Metals and Alloys

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10.1016/j.scriptamat.2020.02.034

Cite this

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title = "Microstructural characterization of dendritic evolution using two-point statistics",

abstract = "Characterizing large four-dimensional materials datasets is difficult due to the presence of complex microstructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evolution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into competitive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.",

keywords = "Aluminum alloys, Dendritic growth, Solidification microstructure, Three-dimensional tomography, Two-point statistics",

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doi = "10.1016/j.scriptamat.2020.02.034",

language = "English (US)",

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AU - Elder, Kate L.M.

AU - Stan, Tiberiu

AU - Sun, Yue

AU - Xiao, Xianghui

AU - Voorhees, Peter W.

PY - 2020/6

Y1 - 2020/6

N2 - Characterizing large four-dimensional materials datasets is difficult due to the presence of complex microstructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evolution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into competitive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.

AB - Characterizing large four-dimensional materials datasets is difficult due to the presence of complex microstructures and time-varying length scales. We showcase the use of two-point statistics as an efficient and un-biased way of extracting materials parameters from an Al-Cu alloy during solidification. The evolution of dendrite primary arm thickness, average secondary arm spacing, and average tip-to-tip spacing were tracked using two-point Pearson auto-correlations of scaled mean curvatures. Insights into competitive side-branching are also reported. We show both visually and quantitatively that most length scales change rapidly during early stages of dendritic growth, but slow as diffusion fields of dendrites overlap.

KW - Aluminum alloys

KW - Dendritic growth

KW - Solidification microstructure

KW - Three-dimensional tomography

KW - Two-point statistics

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Microstructural characterization of dendritic evolution using two-point statistics

Abstract

Funding

Keywords

ASJC Scopus subject areas

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