Stochastic Multi-Scale Reconstruction of 3D Microstructure Consisting of Polycrystalline Grains and Second-Phase Particles from 2D Micrographs.
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| Title: | Stochastic Multi-Scale Reconstruction of 3D Microstructure Consisting of Polycrystalline Grains and Second-Phase Particles from 2D Micrographs. |
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| Authors: | Chen, Shaohua1, Kirubanandham, Antony1, Chawla, Nikhilesh1, Jiao, Yang1 yang.jiao.2@asu.edu |
| Source: | Metallurgical & Materials Transactions. Part A. Mar2016, Vol. 47 Issue 3, p1440-1450. 11p. |
| Subjects: | Microstructure, Micrographics, Crystal grain boundaries, Particulate matter, Colloids, Metals, Thermomechanical treatment |
| Abstract: | An accurate knowledge of the 3D polycrystalline microstructure of a material is crucial to its property prediction, performance optimization, and design. Here, we present a multi-scale computational scheme that allows one to stochastically reconstruct the 3D microstructure of a highly heterogeneous polycrystalline material with large variation in grain size, morphology, and spatial distribution, as well as the distribution of second-phase particles, from single-2D electron back-scattered diffraction (EBSD) micrograph. Specifically, the two-point correlation functions S are employed to statistically characterize grain morphology, orientation, and spatial distribution and are incorporated into the simulated annealing procedure for microstructure reconstruction. During the reconstruction, the original polycrystalline microstructure is coarsened such that the large grains are reconstructed first and the smaller ones are generated later. The second-phase particles are then inserted into the reconstructed polycrystalline material based on the pair-correlation function g sampled from the 2D back-scattered electron micrograph. The utility of our multi-scale scheme is demonstrated by successfully reconstructing a highly heterogeneous polycrystalline Sn-rich solder joint with CuSn intermetallic particles. The accuracy of our reconstruction is ascertained by comparing the virtual microstructure with the actual 3D structure of the joint obtained via serial sectioning techniques. [ABSTRACT FROM AUTHOR] |
| Copyright of Metallurgical & Materials Transactions. Part A is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 112732861 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Stochastic Multi-Scale Reconstruction of 3D Microstructure Consisting of Polycrystalline Grains and Second-Phase Particles from 2D Micrographs. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chen%2C+Shaohua%22">Chen, Shaohua</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kirubanandham%2C+Antony%22">Kirubanandham, Antony</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chawla%2C+Nikhilesh%22">Chawla, Nikhilesh</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Jiao%2C+Yang%22">Jiao, Yang</searchLink><relatesTo>1</relatesTo><i> yang.jiao.2@asu.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Metallurgical+%26+Materials+Transactions%2E+Part+A%22">Metallurgical & Materials Transactions. Part A</searchLink>. Mar2016, Vol. 47 Issue 3, p1440-1450. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Microstructure%22">Microstructure</searchLink><br /><searchLink fieldCode="DE" term="%22Micrographics%22">Micrographics</searchLink><br /><searchLink fieldCode="DE" term="%22Crystal+grain+boundaries%22">Crystal grain boundaries</searchLink><br /><searchLink fieldCode="DE" term="%22Particulate+matter%22">Particulate matter</searchLink><br /><searchLink fieldCode="DE" term="%22Colloids%22">Colloids</searchLink><br /><searchLink fieldCode="DE" term="%22Metals%22">Metals</searchLink><br /><searchLink fieldCode="DE" term="%22Thermomechanical+treatment%22">Thermomechanical treatment</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: An accurate knowledge of the 3D polycrystalline microstructure of a material is crucial to its property prediction, performance optimization, and design. Here, we present a multi-scale computational scheme that allows one to stochastically reconstruct the 3D microstructure of a highly heterogeneous polycrystalline material with large variation in grain size, morphology, and spatial distribution, as well as the distribution of second-phase particles, from single-2D electron back-scattered diffraction (EBSD) micrograph. Specifically, the two-point correlation functions S are employed to statistically characterize grain morphology, orientation, and spatial distribution and are incorporated into the simulated annealing procedure for microstructure reconstruction. During the reconstruction, the original polycrystalline microstructure is coarsened such that the large grains are reconstructed first and the smaller ones are generated later. The second-phase particles are then inserted into the reconstructed polycrystalline material based on the pair-correlation function g sampled from the 2D back-scattered electron micrograph. The utility of our multi-scale scheme is demonstrated by successfully reconstructing a highly heterogeneous polycrystalline Sn-rich solder joint with CuSn intermetallic particles. The accuracy of our reconstruction is ascertained by comparing the virtual microstructure with the actual 3D structure of the joint obtained via serial sectioning techniques. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Metallurgical & Materials Transactions. Part A is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11661-015-3283-8 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1440 Subjects: – SubjectFull: Microstructure Type: general – SubjectFull: Micrographics Type: general – SubjectFull: Crystal grain boundaries Type: general – SubjectFull: Particulate matter Type: general – SubjectFull: Colloids Type: general – SubjectFull: Metals Type: general – SubjectFull: Thermomechanical treatment Type: general Titles: – TitleFull: Stochastic Multi-Scale Reconstruction of 3D Microstructure Consisting of Polycrystalline Grains and Second-Phase Particles from 2D Micrographs. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chen, Shaohua – PersonEntity: Name: NameFull: Kirubanandham, Antony – PersonEntity: Name: NameFull: Chawla, Nikhilesh – PersonEntity: Name: NameFull: Jiao, Yang IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 10735623 Numbering: – Type: volume Value: 47 – Type: issue Value: 3 Titles: – TitleFull: Metallurgical & Materials Transactions. Part A Type: main |
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