Artificial intelligence approach on predicting current values of polymer interface Schottky diode based on temperature and voltage: An experimental study

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dc.authoridColak, Andac Batur/0000-0001-9297-8134
dc.contributor.authorGuzel, Tamer
dc.contributor.authorColak, Andac Batur
dc.date.accessioned2024-11-07T13:24:57Z
dc.date.available2024-11-07T13:24:57Z
dc.date.issued2021
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractIn this study, an artificial neural network model has been developed to predict the current values of a 6H?SiC/MEH-PPV Schottky diode with polymer-interface, depending on temperature and voltage. In the training of the multi-layer perceptron network model with 13 neurons in its hidden layer, the experimentally measured current values between 100 and 250 K temperature and -3V to + 3V voltage range have been used. In the input layer of the model developed with a total of 244 experimental data, temperature, and voltage values have been defined and current values were obtained in the output layer. The mean square error value of the artificial neural network is 1.63E-08 and the R-value is 0.99999. The developed model has been able to predict the current values of the polymer-interfaced 6H?SiC/MEH-PPV Schottky diode with an average error rate of -0.15% depending on temperature and voltage, with high accuracy.
dc.identifier.doi10.1016/j.spmi.2021.106864
dc.identifier.issn0749-6036
dc.identifier.issn1096-3677
dc.identifier.scopus2-s2.0-85102525282
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.1016/j.spmi.2021.106864
dc.identifier.urihttps://hdl.handle.net/11480/14419
dc.identifier.volume153
dc.identifier.wosWOS:000640452900002
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAcademic Press Ltd- Elsevier Science Ltd
dc.relation.ispartofSuperlattices and Microstructures
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectSchottky diode
dc.subjectBarrier diode
dc.subjectMEH-PPV
dc.subjectCurrent-voltage characteristics
dc.subjectArtificial neural network
dc.titleArtificial intelligence approach on predicting current values of polymer interface Schottky diode based on temperature and voltage: An experimental study
dc.typeArticle

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