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1 October 2015 In-the-cloud optimization tool for retrieving experimentally fitted conductivity of graphene (Presentation Recording)
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Abstract
Graphene is one of the emerging active nanophotonics materials with optical properties that can be controlled in real time by an applied bias voltage. Different applications from sensing to active nanophotonics have been discussed in the literature recently and the field is still developing especially with an eye on structured and multi-layer graphene. To design new devices there is a need for precise modeling of multivariate and dynamic optical responses of graphene elements in frequency and time domains. Taking into account the complexity that comes along with multiple unknown parameters, including edge effects in nanostructured graphene elements, graphene impurities, imperfections of characterization optics etc., it is hard to build an adequate multivariate model to reach good quantitative agreement with experiment. Here, we present an approach that uses optimization methods to retrieve the optical properties of a given graphene sample from experiment. We show that with these techniques good quantitative agreement with experiments can be achieved; additionally we encapsulate our techniques in an online data-fitting tool. The tool includes several options to precisely fit the conductivity function to a given experiment - general spline approximations and physically meaningful random phase approximation models for frequency domain solvers, along with the relaxed Lorentz oscillator models for confident time domain simulations. A pilot version of our free online tool entitled Photonics2D-Fit (to be staged at nanoHUB.org) is presented.
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Ludmila J. Prokopeva, You-Chia Chang, Naresh K. Emani, Ted Norris, and Alexander V. Kildishev "In-the-cloud optimization tool for retrieving experimentally fitted conductivity of graphene (Presentation Recording)", Proc. SPIE 9546, Active Photonic Materials VII, 95461W (1 October 2015); https://doi.org/10.1117/12.2190139
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