Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/88728
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dc.contributorDepartment of Mechanical Engineering-
dc.creatorXiong, J-
dc.creatorShi, SQ-
dc.creatorZhang, TY-
dc.date.accessioned2020-12-22T01:07:21Z-
dc.date.available2020-12-22T01:07:21Z-
dc.identifier.issn0264-1275-
dc.identifier.urihttp://hdl.handle.net/10397/88728-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Xiong, J., Shi, S. Q., & Zhang, T. Y. (2020). Corrigendum to “A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys” [Mat. Des., Volume 187 (2020), 108378]. Materials and Design, 191, 108651, 1 is available at https://dx.doi.org/10.1016/j.matdes.2020.108651en_US
dc.titleCorrigendum to “A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys” [Mat. Des., Volume 187 (2020), 108378]en_US
dc.typeErratumen_US
dc.identifier.spage1-
dc.identifier.epage1-
dc.identifier.volume191-
dc.identifier.doi10.1016/j.matdes.2020.108651-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMaterials and design, June 2020, v. 191, 108651, p. 1-1-
dcterms.isPartOfMaterials and design-
dcterms.issued2020-06-
dc.identifier.isiWOS:000536937200067-
dc.identifier.eissn1873-4197-
dc.identifier.artn108651-
dc.description.validate202012 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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