Microstructural, mechanical, tribological, and corrosion behavior of ultrafine bio-degradable Mg/CeO2 nanocomposites: Machine learning-based modeling and experiment
dc.contributor.author | Deka, Surja | |
dc.contributor.author | Mozafari, Farzin | |
dc.contributor.author | Mallick, Ashis | |
dc.contributor.authorID | 0000-0001-8218-4410 | en_US |
dc.contributor.department | AGÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümü | en_US |
dc.contributor.institutionauthor | Mozafari, Farzin | |
dc.date.accessioned | 2024-01-15T09:37:58Z | |
dc.date.available | 2024-01-15T09:37:58Z | |
dc.date.issued | 2023 | en_US |
dc.description.abstract | The present study investigated the microstructural, mechanical, tribological, and corrosion behavior of near-dense and low-volume fraction magnesium-cerium dioxide (Mg/CeO2 ) (x = 0.5, 1, and 1.5 vol.%) nanocomposites synthesized by in-situ hot extrusion assisted powder metallurgy (PM) process. Results showed a significant improvement in wear resistance for Mg/CeO2 nanocomposite compared to monolithic Mg at varied applied loads. Microindentation tests were performed to access the Vickers microhardness homogeneity along the extrusion direction. The corrosion analysis revealed that introducing ceria nanoparticles enhanced Mg’s corrosion resistance and expedited the development of an apatite layer on the surface, providing enhanced protection. A feedforward neural network and Long Short-Term Memory (LSTM) network were also developed to characterize nanocomposites’ wear and corrosion behavior. | en_US |
dc.description.sponsorship | S.D. and A.M. sincerely acknowledge the financial support from the ASEAN-Indian Science and Technology Development Fund (AISTDF), DST, Govt. of India, under Grant No. IMRC/AISTDF/R&D/P-14/2018. F.M. acknowledges the partial support provided by the AGÜ foundation. The authors appreciate DST, India, for providing a 3D profilometer characterization facility through the FIST project grant number SR/FST/ET-II/2018/222(C). | en_US |
dc.identifier.endpage | 20 | en_US |
dc.identifier.issn | 0301-679X | |
dc.identifier.issn | 1879-2464 | |
dc.identifier.other | WOS:001109249000001 | |
dc.identifier.startpage | 1 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.triboint.2023.109063 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12573/1898 | |
dc.identifier.volume | 190 | en_US |
dc.language.iso | eng | en_US |
dc.publisher | ELSEVIER SCI LTD | en_US |
dc.relation.isversionof | 10.1016/j.triboint.2023.109063 | en_US |
dc.relation.journal | ELSEVIER SCI LTD | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Microstructural characterization | en_US |
dc.subject | Tribological properties | en_US |
dc.subject | Corrosion | en_US |
dc.subject | Machine learning | en_US |
dc.title | Microstructural, mechanical, tribological, and corrosion behavior of ultrafine bio-degradable Mg/CeO2 nanocomposites: Machine learning-based modeling and experiment | en_US |
dc.type | article | en_US |
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