Publication:

Combination of ab initio descriptors and machine learning approach for the prediction of the plasticity mechanisms in beta-metastable Ti alloys

Date

2024
Journal article
https://doi.org/10.1016/j.matdes.2024.112801
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dc.contributor.authorCoffigniez, M.
dc.contributor.authorDe Breuck, P. -P.
dc.contributor.authorChoisez, L.
dc.contributor.authorMarteleur, M.
dc.contributor.authorvan Setten, Michiel
dc.contributor.authorPetretto, G.
dc.contributor.authorRignanese, G. -M.
dc.contributor.authorJacques, P. J.
dc.contributor.imecauthorvan Setten, Michiel
dc.contributor.orcidimecvan Setten, Michiel::0000-0003-0557-5260
dc.date.accessioned2024-11-04T10:01:32Z
dc.date.available2024-05-03T17:58:09Z
dc.date.available2024-11-04T10:01:32Z
dc.date.embargo2024-02-25
dc.date.issued2024
dc.description.wosFundingTextThe Fonds de la Recherche Scientifique F.R.S.-FNRS (Belgium) is gratefully acknowledged for the grant no T.0127.19. Computational resources have been provided by the Consortium des Equipements de Calcul Intensif (CECI) , funded by the Fonds de la Recherche Scientifique de Belgique (F.R.S.-FNRS) under Grant No. 2.5020.11 and by the Walloon Region.
dc.identifier.doi10.1016/j.matdes.2024.112801
dc.identifier.issn0264-1275
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/43898
dc.publisherELSEVIER SCI LTD
dc.source.beginpageArt. 112801
dc.source.endpageN/A
dc.source.issueN/A
dc.source.journalMATERIALS & DESIGN
dc.source.numberofpages12
dc.source.volume239
dc.subject.keywordsDEFORMATION-BEHAVIOR
dc.subject.keywordsPHASE-STABILITY
dc.subject.keywordsTITANIUM-ALLOYS
dc.subject.keywordsNB-TA
dc.subject.keywordsZR
dc.subject.keywordsDESIGN
dc.subject.keywordsSN
dc.subject.keywordsTRANSFORMATION
dc.subject.keywordsELECTRON
dc.subject.keywordsSUPERELASTICITY
dc.title

Combination of ab initio descriptors and machine learning approach for the prediction of the plasticity mechanisms in beta-metastable Ti alloys

dc.typeJournal article
dspace.entity.typePublication
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