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dc.contributor.authorPolat, Omer
dc.contributor.authorYildiz, Nihat
dc.contributor.authorSan, Sait Eren
dc.date.accessioned2019-07-27T12:10:23Z
dc.date.accessioned2019-07-28T10:05:00Z
dc.date.available2019-07-27T12:10:23Z
dc.date.available2019-07-28T10:05:00Z
dc.date.issued2011
dc.identifier.issn0167-7322
dc.identifier.urihttps://dx.doi.org/10.1016/j.molliq.2011.08.012
dc.identifier.urihttps://hdl.handle.net/20.500.12418/9438
dc.descriptionWOS: 000297189700007en_US
dc.description.abstractIn this paper, we realized two objectives. Firstly, birefringence of azo and anthraquinone dye-doped nematic liquid crystal (NLC) molecules was investigated by applied electric field dependent laser scattering intensities. The birefringence was essentially calculated from ordinary and extraordinary ray phase difference, which is determined from the measured intensities corresponding to parallel and perpendicular orientations of analyzer to polarizer. The birefringence was found to be dependent on both applied voltage and the kind of the doping dye. As the second objective, by nonlinear universal function approximator layered feedforward neural network (LFNN), we constructed explicit form of empirical physical formulas (EPFs) for experimentally measured dye-doped NLC nonlinear scattering intensities. Excellent LFNN test set predictions over yet-to-be measured experimental data proved that the constructed LFNN-EPFs estimated the measured intensities consistently. The correlation coefficients assessing the goodness of predictions were about r = 0.998 for all cases. The LFNN-EPFs also extracted the intensity dependency on the kind of dye used. When theoretical and LFNN-EPFs intensities are compared, we conclude that given certain experimental conditions, theoretical and LFNN-EPFs predictions are in excellent agreement. In this sense, we can say that the physical laws embedded in the birefringence scattering data can be consistently extracted by LFNN. Therefore, judging from the consistent extraction of the molecular dependencies of pure and doped NLC intensities, we predict that the LFNN-EPFs can help to identify unknown molecular structural parameters in liquid crystal extracts. More concretely, by suitable mathematical operations such as differentiation, integration, minimization on these intensity LFNN-EPFs, some useful information into the charge distributions of the LC molecules can be gained. (C) 2011 Elsevier B.V. All rights reserved.en_US
dc.language.isoengen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.isversionof10.1016/j.molliq.2011.08.012en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectBirefringenceen_US
dc.subjectNeural networken_US
dc.subjectScattering intensityen_US
dc.subjectLiquid crystalen_US
dc.subjectMolecular structureen_US
dc.titleApplied electric field effect on light-scattering birefringence of dye-doped liquid crystal molecule and consistent neural network empirical physical formula construction for scattering intensitiesen_US
dc.typearticleen_US
dc.relation.journalJOURNAL OF MOLECULAR LIQUIDSen_US
dc.contributor.department[Yildiz, Nihat] Cumhuriyet Univ, Dept Phys, TR-58140 Sivas, Turkey -- [Polat, Omer] Bahcesehir Univ, Dept Sci, TR-34353 Istanbul, Turkey -- [San, Sait Eren] Gebze Inst Technol, Dept Phys, TR-41400 Gebze, Turkeyen_US
dc.contributor.authorIDPolat, Omer -- 0000-0002-4797-1774en_US
dc.identifier.volume163en_US
dc.identifier.issue3en_US
dc.identifier.endpage160en_US
dc.identifier.startpage153en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US


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