Statistical characterization of twin transmission across grain boundaries in magnesium
A detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in rolled, commercial purity magnesium compressed along the rolling direction. EBSD images are acquired from two different cuts: a section containing the rolling (RD) and normal (ND) directions; and a sect...
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description | A detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in rolled, commercial purity magnesium compressed along the rolling direction. EBSD images are acquired from two different cuts: a section containing the rolling (RD) and normal (ND) directions; and a section at 35° to the ND which contains transverse direction (TD). An automated twinning analysis software, METIS, is used to obtain the statistical correlations between deformation twins and other microstructural features by analyzing EBSD microstructures comprising thousands of grains and twins. This detailed statistical analysis reveals that the TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis. Specifically, TT propensity decreases with increasing GB misorientation angle; however, the decreasing trend is not monotonic. Further, the detailed analysis of TT events combining macroscopic Schmid factor and the geometric measures (m’: accounts for the alignment of both twin plane normal and shear directions; m”: accounts for the alignment of only twin shear directions; and m”’: accounts for the alignment of only twin plane normal) helps in understanding and identifying the process of twin-pair formation, i.e., co-nucleation versus transmission, also to identify the role of local stresses at GBs induced by inter-grain interaction versus twinning shear transformation processes. In addition, Bayesian inference is used to draw statistically meaningful conclusions as to the likelihood of transmission given misorientation angles. Lastly, twin chain frequency as a function of chain length is predicted using the probability distribution obtained from the Bayesian inference and compared with the actual data from the EBSD microstructures.
•Detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in magnesium.•TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis.•Two-point statistical correlation between the geometric measure and Schmid factor elucidates the process of ATP formation.•Bayesian inference-based probability distributions correctly predict the twin chain frequency as a function of its length. |
doi_str_mv | 10.1016/j.matchar.2022.112457 |
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•Detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in magnesium.•TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis.•Two-point statistical correlation between the geometric measure and Schmid factor elucidates the process of ATP formation.•Bayesian inference-based probability distributions correctly predict the twin chain frequency as a function of its length.</description><identifier>ISSN: 1044-5803</identifier><identifier>EISSN: 1873-4189</identifier><identifier>DOI: 10.1016/j.matchar.2022.112457</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Bayesian inference ; Deformation twinning ; EBSD ; Magnesium ; MATERIALS SCIENCE ; Microstructure</subject><ispartof>Materials characterization, 2022-12, Vol.194, p.112457, Article 112457</ispartof><rights>2022 Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2987-caa0d3f2ef82e54ae5668117c494a4c8d591133f10716a538956978a0e54ab803</citedby><cites>FETCH-LOGICAL-c2987-caa0d3f2ef82e54ae5668117c494a4c8d591133f10716a538956978a0e54ab803</cites><orcidid>0000000216863391 ; 0000000334050500 ; 0000000266847410 ; 0000000180797790</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.matchar.2022.112457$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3549,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://www.osti.gov/servlets/purl/1898358$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Kumar, Mariyappan Arul</creatorcontrib><creatorcontrib>McCabe, Rodney J.</creatorcontrib><creatorcontrib>Taupin, Vincent</creatorcontrib><creatorcontrib>Tomé, Carlos N.</creatorcontrib><creatorcontrib>Capolungo, Laurent</creatorcontrib><creatorcontrib>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</creatorcontrib><title>Statistical characterization of twin transmission across grain boundaries in magnesium</title><title>Materials characterization</title><description>A detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in rolled, commercial purity magnesium compressed along the rolling direction. EBSD images are acquired from two different cuts: a section containing the rolling (RD) and normal (ND) directions; and a section at 35° to the ND which contains transverse direction (TD). An automated twinning analysis software, METIS, is used to obtain the statistical correlations between deformation twins and other microstructural features by analyzing EBSD microstructures comprising thousands of grains and twins. This detailed statistical analysis reveals that the TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis. Specifically, TT propensity decreases with increasing GB misorientation angle; however, the decreasing trend is not monotonic. Further, the detailed analysis of TT events combining macroscopic Schmid factor and the geometric measures (m’: accounts for the alignment of both twin plane normal and shear directions; m”: accounts for the alignment of only twin shear directions; and m”’: accounts for the alignment of only twin plane normal) helps in understanding and identifying the process of twin-pair formation, i.e., co-nucleation versus transmission, also to identify the role of local stresses at GBs induced by inter-grain interaction versus twinning shear transformation processes. In addition, Bayesian inference is used to draw statistically meaningful conclusions as to the likelihood of transmission given misorientation angles. Lastly, twin chain frequency as a function of chain length is predicted using the probability distribution obtained from the Bayesian inference and compared with the actual data from the EBSD microstructures.
•Detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in magnesium.•TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis.•Two-point statistical correlation between the geometric measure and Schmid factor elucidates the process of ATP formation.•Bayesian inference-based probability distributions correctly predict the twin chain frequency as a function of its length.</description><subject>Bayesian inference</subject><subject>Deformation twinning</subject><subject>EBSD</subject><subject>Magnesium</subject><subject>MATERIALS SCIENCE</subject><subject>Microstructure</subject><issn>1044-5803</issn><issn>1873-4189</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNqFUMlOwzAQtRBIlMInIEXcE7wmzgmhik2qxIHlak0dp3XVOMh2QfD12KR3TrO9eTPvIXRJcEUwqa-31QBRb8BXFFNaEUK5aI7QjMiGlZzI9jjlmPNSSMxO0VkIW4xxLUkzQ-8vEaIN0WrYFZkDdDTe_qTm6IqxL-KXdUX04MJgQ8hN0H4MoVh7SJPVuHcdeGtCkaoB1s4Eux_O0UkPu2AuDnGO3u7vXheP5fL54Wlxuyw1bWVTagDcsZ6aXlIjOBhRp7dIo3nLgWvZiZYQxnqCG1KDYLIVddtIwBm8Smrm6GriHZMEFbSNRm_06JzRUSXlkgmZQGIC_T3uTa8-vB3AfyuCVXZQbdXBQZUdVJODae9m2jNJwac1Ph8wTpvO-szfjfYfhl-tbn0g</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Kumar, Mariyappan Arul</creator><creator>McCabe, Rodney J.</creator><creator>Taupin, Vincent</creator><creator>Tomé, Carlos N.</creator><creator>Capolungo, Laurent</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>OIOZB</scope><scope>OTOTI</scope><orcidid>https://orcid.org/0000000216863391</orcidid><orcidid>https://orcid.org/0000000334050500</orcidid><orcidid>https://orcid.org/0000000266847410</orcidid><orcidid>https://orcid.org/0000000180797790</orcidid></search><sort><creationdate>20221201</creationdate><title>Statistical characterization of twin transmission across grain boundaries in magnesium</title><author>Kumar, Mariyappan Arul ; McCabe, Rodney J. ; Taupin, Vincent ; Tomé, Carlos N. ; Capolungo, Laurent</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2987-caa0d3f2ef82e54ae5668117c494a4c8d591133f10716a538956978a0e54ab803</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bayesian inference</topic><topic>Deformation twinning</topic><topic>EBSD</topic><topic>Magnesium</topic><topic>MATERIALS SCIENCE</topic><topic>Microstructure</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kumar, Mariyappan Arul</creatorcontrib><creatorcontrib>McCabe, Rodney J.</creatorcontrib><creatorcontrib>Taupin, Vincent</creatorcontrib><creatorcontrib>Tomé, Carlos N.</creatorcontrib><creatorcontrib>Capolungo, Laurent</creatorcontrib><creatorcontrib>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</creatorcontrib><collection>CrossRef</collection><collection>OSTI.GOV - Hybrid</collection><collection>OSTI.GOV</collection><jtitle>Materials characterization</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kumar, Mariyappan Arul</au><au>McCabe, Rodney J.</au><au>Taupin, Vincent</au><au>Tomé, Carlos N.</au><au>Capolungo, Laurent</au><aucorp>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Statistical characterization of twin transmission across grain boundaries in magnesium</atitle><jtitle>Materials characterization</jtitle><date>2022-12-01</date><risdate>2022</risdate><volume>194</volume><spage>112457</spage><pages>112457-</pages><artnum>112457</artnum><issn>1044-5803</issn><eissn>1873-4189</eissn><abstract>A detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in rolled, commercial purity magnesium compressed along the rolling direction. EBSD images are acquired from two different cuts: a section containing the rolling (RD) and normal (ND) directions; and a section at 35° to the ND which contains transverse direction (TD). An automated twinning analysis software, METIS, is used to obtain the statistical correlations between deformation twins and other microstructural features by analyzing EBSD microstructures comprising thousands of grains and twins. This detailed statistical analysis reveals that the TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis. Specifically, TT propensity decreases with increasing GB misorientation angle; however, the decreasing trend is not monotonic. Further, the detailed analysis of TT events combining macroscopic Schmid factor and the geometric measures (m’: accounts for the alignment of both twin plane normal and shear directions; m”: accounts for the alignment of only twin shear directions; and m”’: accounts for the alignment of only twin plane normal) helps in understanding and identifying the process of twin-pair formation, i.e., co-nucleation versus transmission, also to identify the role of local stresses at GBs induced by inter-grain interaction versus twinning shear transformation processes. In addition, Bayesian inference is used to draw statistically meaningful conclusions as to the likelihood of transmission given misorientation angles. Lastly, twin chain frequency as a function of chain length is predicted using the probability distribution obtained from the Bayesian inference and compared with the actual data from the EBSD microstructures.
•Detailed statistical analysis of twin transmission (TT) across grain boundaries is performed in magnesium.•TT propensity is sensitive to the grain boundary (GB) misorientation angle but not to the GB misorientation axis.•Two-point statistical correlation between the geometric measure and Schmid factor elucidates the process of ATP formation.•Bayesian inference-based probability distributions correctly predict the twin chain frequency as a function of its length.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><doi>10.1016/j.matchar.2022.112457</doi><orcidid>https://orcid.org/0000000216863391</orcidid><orcidid>https://orcid.org/0000000334050500</orcidid><orcidid>https://orcid.org/0000000266847410</orcidid><orcidid>https://orcid.org/0000000180797790</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Bayesian inference Deformation twinning EBSD Magnesium MATERIALS SCIENCE Microstructure |
title | Statistical characterization of twin transmission across grain boundaries in magnesium |
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