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Multi-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithm

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dc.citedby5
dc.contributor.authorGamel M.M.A.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorLee H.J.en_US
dc.contributor.authorRashid W.E.S.W.A.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorDavid J.P.R.en_US
dc.contributor.authorJamaludin M.Z.en_US
dc.contributor.authorid57215306835en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid57190622221en_US
dc.contributor.authorid57204586520en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid25647614700en_US
dc.contributor.authorid57216839721en_US
dc.date.accessioned2023-05-29T09:05:28Z
dc.date.available2023-05-29T09:05:28Z
dc.date.issued2021
dc.description.abstractThe optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of In0.53Ga0.47As TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of In0.53Ga0.47As TPV cell mostly remain < 15%. Therefore, this work develops a multi-variable or multi-dimensional optimization of In0.53Ga0.47As TPV cell using the real coded genetic algorithm (RCGA) at various radiation temperatures. RCGA was developed using Visual Basic and it was hybridized with Silvaco TCAD for the electrical characteristics simulation. Under radiation temperatures from 800 to 2000�K, the optimized In0.53Ga0.47As TPV cell efficiency increases by an average percentage of 11.86% (from 8.5 to 20.35%) as compared to the non-optimized structure. It was found that the incorporation of a thicker base layer with the back-barrier layers enhances the separation of charge carriers and increases the collection of photo-generated carriers near the band-edge, producing an optimum output power of 0.55�W/cm2 (cell efficiency of 22.06%, without antireflection coating) at 1400�K radiation spectrum. The results of this work demonstrate the great potential to generate electricity sustainably from industrial waste heat and the multi-dimensional optimization methodology can be adopted to optimize semiconductor devices, such as solar cell, TPV cell and photodetectors. � 2021, The Author(s).en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7741
dc.identifier.doi10.1038/s41598-021-86175-5
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85104083186
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85104083186&doi=10.1038%2fs41598-021-86175-5&partnerID=40&md5=58e8705a88a0c77b893a4f01fe7ef483
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25894
dc.identifier.volume11
dc.publisherNature Researchen_US
dc.relation.ispartofAll Open Access, Gold, Green
dc.sourceScopus
dc.sourcetitleScientific Reports
dc.titleMulti-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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