Publication:
Design of a NiTiHf shape memory alloy with an austenite finish temperature beyond 400? utilizing artificial intelligence

dc.contributor.coauthorYılmaz, R.
dc.contributor.departmentDepartment of Mechanical Engineering
dc.contributor.departmentGraduate School of Sciences and Engineering
dc.contributor.kuauthorCanadinç, Demircan
dc.contributor.kuauthorÇatal, Aysel Aysu
dc.contributor.kuauthorKılıç, Elif Bedir
dc.contributor.schoolcollegeinstituteCollege of Engineering
dc.contributor.schoolcollegeinstituteGRADUATE SCHOOL OF SCIENCES AND ENGINEERING
dc.date.accessioned2024-11-09T23:01:15Z
dc.date.issued2022
dc.description.abstractThis paper details the design process of a ternary NiTiHf shape memory alloy (SMA) with an austenite finish temperature (A(f)) beyond 400 ?. Specifically, available experimental data on the ternary NiTiHf SMA system was utilized to construct a database, which was employed to train and test a machine learning (ML) algorithm to predict the ideal NiTiHf SMA composition to exhibit an A(f) beyond 400 ?& nbsp;and a relatively smaller hysteresis. For this purpose, a multi-layer feedforward neural network (MLFFNN) model was proposed, trained, and tested. Consequently, the Ni49.7Ti26.6Hf23.7 and Ni(50)Ti27Hf23 alloys predicted by this ML algorithm were selected for validation experiments to assess the accuracy of the ML model's predictions. As a result, the Ni49.7Ti26.6Hf23.7 alloy with an A(f) temperature of 403.5 ? and remarkable cyclic stability was established as a new NiTiHf SMA composition, which can be utilized in applications demanding reversible austenite-to-martensite phase transformation beyond 400 ?. (C) 2022 Elsevier B.V. All rights reserved.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume904
dc.identifier.doi10.1016/j.jallcom.2022.164135
dc.identifier.eissn1873-4669
dc.identifier.issn0925-8388
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-85124247508
dc.identifier.urihttps://doi.org/10.1016/j.jallcom.2022.164135
dc.identifier.urihttps://hdl.handle.net/20.500.14288/8197
dc.identifier.wos779695600002
dc.keywordsHigh-temperature shape memory alloy
dc.keywordsNiTiHf
dc.keywordsMachine learning
dc.keywordsAlloy design
dc.keywordsMartensitic phase transformation
dc.language.isoeng
dc.publisherElsevier Science Sa
dc.relation.ispartofJournal of Alloys and Compounds
dc.subjectChemistry
dc.subjectPhysical
dc.subjectMaterials science
dc.subjectEngineering
dc.subjectMetallurgy metallurgical engineering
dc.titleDesign of a NiTiHf shape memory alloy with an austenite finish temperature beyond 400? utilizing artificial intelligence
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorÇatal, Aysel Aysu
local.contributor.kuauthorBedir, Elif
local.contributor.kuauthorCanadinç, Demircan
local.publication.orgunit1GRADUATE SCHOOL OF SCIENCES AND ENGINEERING
local.publication.orgunit1College of Engineering
local.publication.orgunit2Department of Mechanical Engineering
local.publication.orgunit2Graduate School of Sciences and Engineering
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