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Metaheuristic Optimization of Perovskite Solar Cell Using Hybrid L32 Taguchi Doe-Based Genetic Algorithm

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dc.citedby0
dc.contributor.authorKaharudin K.E.en_US
dc.contributor.authorJalaludin N.A.en_US
dc.contributor.authorSalehuddin F.en_US
dc.contributor.authorArith F.en_US
dc.contributor.authorMohd Zain A.S.en_US
dc.contributor.authorAhmad I.en_US
dc.contributor.authorMat Junos S.A.en_US
dc.contributor.authorApte P.R.en_US
dc.contributor.authorid56472706900en_US
dc.contributor.authorid58861184200en_US
dc.contributor.authorid36239165300en_US
dc.contributor.authorid55799799900en_US
dc.contributor.authorid55925762500en_US
dc.contributor.authorid12792216600en_US
dc.contributor.authorid59474843400en_US
dc.contributor.authorid55725529100en_US
dc.date.accessioned2025-03-03T07:41:43Z
dc.date.available2025-03-03T07:41:43Z
dc.date.issued2024
dc.description.abstractSolar cells convert sunlight into electricity, and the efficiency of this conversion process largely depends on the material parameters. Optimizing these parameters, like thickness and carrier concentration, could significantly increase the efficiency of solar cells. This paper emphasizes the metaheuristic optimization approach in searching for the optimum input parameters of perovskite solar cell (PSC). The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. Based on Multiple Linear Regression (MLR) analysis, the thickness of mix halide perovskite (CH3NH3PbI3-XClX) was discovered to be the most crucial input parameter affecting the Power Conversion Efficiency (PCE) variations. Based on the result of the Genetic algorithm, the optimal values of the input parameters: Fluorine doped tin oxide (FTO) thickness, FTO donor density, Titanium Dioxide (TiO2) layer thickness, TiO2 donor density, CH3NH3PbI3-XClX layer thickness, CH3NH3PbI3-XClX donor density, graphene oxide (GO) layer thickness, and GO acceptor density are predicted to be 0.187 ?m, 9.965x1021 cm-3, 0.033 ?m, 9.629x1021 cm-3, 0.926 ?m, 9.983x1021 cm-3, 0.039 ?m and 9.671x1021 cm-3 respectively. Using the predicted optimum input parameters, the simulation generates the best value of open voltage (Voc), current density (Jsc), fill factor (FF), and PCE measured at 1.647 V, 25.68 mA/cm2, 92.03%, and 38.93%, respectively. ? 2024, Penerbit Akademia Baru. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.37934/ard.122.1.219233
dc.identifier.epage233
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85212175269
dc.identifier.spage219
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85212175269&doi=10.37934%2fard.122.1.219233&partnerID=40&md5=df85bc71c8148aa141e1dfde382d8708
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36258
dc.identifier.volume122
dc.pagecount14
dc.publisherPenerbit Akademia Baruen_US
dc.sourceScopus
dc.sourcetitleJournal of Advanced Research Design
dc.titleMetaheuristic Optimization of Perovskite Solar Cell Using Hybrid L32 Taguchi Doe-Based Genetic Algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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