Estimation of microhardness and crystal grain size values of electrodeposited Ni-B/TiC nanocomposite coatings by artificial neural networks (ANN) method

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dc.authoridUNAL, Ersin/0000-0002-3183-9592
dc.contributor.authorUnal, Ersin
dc.contributor.authorYasar, Abdulkadir
dc.contributor.authorKarahan, Ismail Hakki
dc.date.accessioned2024-09-18T20:52:44Z
dc.date.available2024-09-18T20:52:44Z
dc.date.issued2023
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description.abstractIn this study, composite coatings with Ni-B alloy main structure reinforced with TiC nanoparticles were coated on a stainless steel substrate by electrodeposition method. The microhardness and crystal structures of the produced nanocomposite films were examined and the relations between the obtained results and the production parameters were discussed in detail. In addition, the surface and section morphologies of the coatings were analyzed by SEM and EDS. Furthermore the complex relationship between the experimentally obtained microhardness, crystal grain size values and the production parameters was modeled by artificial neural networks (ANN) method. According to the hardness results, nanocomposite coatings microhardness values varied between about 470 HV and 820 HV. In XRD examinations, the crystal grain size values of nanocomposite coatings were found ranging from 6.6 nm to 17.4 nm. From the morphology results, it is understood that the surface structure and coating thicknesses are remarkably affected by the production parameters. Considering the EDS results, it was observed that the alloying with boron and the TiC reinforcement were successfully applied in nanocomposite coatings. With respect to the results obtained with ANN, the best results were obtained in the model with 10 neurons in the hidden layer and the highest error value of 2.02% was achieved for microhardness values. For the crystal grain size, the most successful results were acquired in the model with 12 neurons and the highest error value was obtained as 3.397%.en_US
dc.description.sponsorshipScientific Research Projects of Cukurova University [12868]en_US
dc.description.sponsorshipThe authors thank to the Scientific Research Projects of Cukurova University for financial support of this research (CU-BAP, Proje ID: 12868).en_US
dc.identifier.doi10.1016/j.jallcom.2023.171677
dc.identifier.issn0925-8388
dc.identifier.issn1873-4669
dc.identifier.scopus2-s2.0-85166958745en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.jallcom.2023.171677
dc.identifier.urihttps://hdl.handle.net/20.500.12483/11354
dc.identifier.volume966en_US
dc.identifier.wosWOS:001064856500001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Saen_US
dc.relation.ispartofJournal of Alloys and Compoundsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNi -B alloyen_US
dc.subjectElectrodeposited coatingsen_US
dc.subjectTiCen_US
dc.subjectANNen_US
dc.subjectMicrohardnessen_US
dc.subjectCrystal grain sizeen_US
dc.titleEstimation of microhardness and crystal grain size values of electrodeposited Ni-B/TiC nanocomposite coatings by artificial neural networks (ANN) methoden_US
dc.typeArticleen_US

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