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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm

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dc.citedby4
dc.contributor.authorLee H.J.en_US
dc.contributor.authorAli Gamel M.M.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorJamaludin M.Z.en_US
dc.contributor.authorWong Y.H.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorWillmott J.R.en_US
dc.contributor.authorHobbs M.J.en_US
dc.contributor.authorDavid J.P.R.en_US
dc.contributor.authorTan C.H.en_US
dc.contributor.authorid57190622221en_US
dc.contributor.authorid57280351300en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid57216839721en_US
dc.contributor.authorid36605495300en_US
dc.contributor.authorid24448864400en_US
dc.contributor.authorid55697476100en_US
dc.contributor.authorid37116995800en_US
dc.contributor.authorid25647614700en_US
dc.contributor.authorid57189468185en_US
dc.date.accessioned2024-10-14T03:22:05Z
dc.date.available2024-10-14T03:22:05Z
dc.date.issued2023
dc.description.abstractLattice-mismatched InGaAs has appeared to be emerging semiconductor materials for sensors and photovoltaic applications. The absorption coefficients of the materials are crucial in designing high-performance semiconductor devices. Nevertheless, the absorption coefficient of lattice-mismatched InGaAs were not comprehensively studied to cater for the 2000�3000 nm applications. This study aims to determine the absorption coefficients of lattice-mismatched In0.73Ga0.27As and In0.83Ga0.17As semiconductor materials through photocurrent measurement which enables the absorption tail information to be extracted. In addition, this work demonstrates the incorporation of an innovative artificial intelligence-based method in solving the absorption coefficient of lattice-mismatched InGaAs, considering the detailed information of the structure design and material parameters. By selecting the best gene for the next iteration, the utilization of Genetic Algorithm has significantly reduced the number of iterations from a maximum of 10 000 to 300. Validation of the algorithm was conducted, showing a good agreement of absorption coefficient result compared to the published work on In0.72Ga0.28As. The absorption coefficient of In0.83Ga0.17As with an extended cutoff wavelength near 2.6 ?m is newly reported in this paper. In addition, the extrapolation of the obtained absorption results demonstrates energy gaps of 0.475 eV for In0.73Ga0.27As and 0.55 eV for In0.83Ga0.17As, which are compatible with the reported bandgaps of these materials. The extracted absorption coefficient information can be used in the design of semiconductor devices for emerging technologies such as focal plane array, short wave infrared sensing and thermophotovoltaic. � 2022 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.ArtNo107135
dc.identifier.doi10.1016/j.mssp.2022.107135
dc.identifier.scopus2-s2.0-85139333714
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85139333714&doi=10.1016%2fj.mssp.2022.107135&partnerID=40&md5=44f3f070a06b8e1fbe33f86557f4e4ff
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34724
dc.identifier.volume153
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleMaterials Science in Semiconductor Processing
dc.subjectAbsorption
dc.subjectAlgorithm
dc.subjectCoefficient
dc.subjectGenetic
dc.subjectInGaAs
dc.subjectLattice-mismatched
dc.subjectExtraction
dc.subjectGallium alloys
dc.subjectGenetic algorithms
dc.subjectIndium alloys
dc.subjectInfrared radiation
dc.subjectIterative methods
dc.subjectSemiconducting indium
dc.subjectSemiconducting indium gallium arsenide
dc.subjectSemiconductor alloys
dc.subjectSemiconductor devices
dc.subjectAbsorption coefficients
dc.subjectCoefficient
dc.subjectGenetic
dc.subjectHigh-performance semiconductors
dc.subjectLattice-mismatched
dc.subjectPhotocurrent measurement
dc.subjectPhotovoltaic applications
dc.subjectSensor applications
dc.subjectStructure design
dc.subjectStructure materials
dc.subjectEnergy gap
dc.titleDeriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
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