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We present a Newton-like method to solve inverse problems and to quantify parameter uncertainties. We apply the method to parameter reconstruction in optical scatterometry, where we take into account a priori information and measurement uncertainties using a Bayesian approach. Further, we discuss the influence of numerical accuracy on the reconstruction result.
Numerical characterization of symmetry properties for photonic crystals with hexagonal lattice
(2016)
We present a numerical method to characterize the symmetry properties of photonic crystal (PhC) modes based on field distributions, which themselves can be obtained numerically. These properties can be used to forecast specific features of the optical response of such systems, e.g. which modes are allowed to couple to external radiation fields. We use 2D PhCs with a hexagonal lattice of holes in dielectric as an example and apply our technique to reproduce results from analytical considerations. Further, the method is extended to fully vectorial problems in view of 3D PhCs and PhC slabs, its functionality is demonstrated using test cases and, finally, we provide an efficient implementation. The technique can thus readily be applied to output data of all band structure computation methods or even be embedded – gaining additional information about the mode symmetry.
Simulations of optical processes and complex nanostructured devices have become omnipresent in recent years in several fields of current research and industrial applications, not limited to the field of photovoltaics. Devices or processes are optimized with respect to a certain objective where the underlying physical processes are described by partial differential equations. In photovoltaics and photonics electromagnetic fields are investigated which are governed by Maxwell’s equations.
In this thesis a reduced basis method for the solution of the parameter dependent electromagnetic scattering problem with arbitrary parameters is developed. The method is developed with the specific challenges arising in optical simulations of thin-film silicon solar cells in mind. These are large in domain size and have a complex three-dimensional structure, making optimization tasks infeasible if high-accuracy of the electromagnetic field solution is required. The application of the empirical interpolation methods allows to expand an arbitrary parameter dependence affinely. Thus not only geometries, but also material tensors and source fields can be parameterized. Additionally, the required non-linear post-processing steps of the electromagnetic field to derive energy fluxes or volume absorption are addressed. The reduced basis method allows to reduce the computational costs by orders of magnitude compared to efficient finite element solvers.
In addition, an efficient tailored domain decomposition algorithm is presented to model incoherent layers or illuminations in optical systems efficiently. This is of particular interest for solar cells in superstrate configuration where the absorber is illuminated through a glass substrate.
The developed methods are employed in application examples taken from collaborations with experimentalists active in the joint lab “BerOSE” (Berlin Joint Lab for Optical Simulations for Energy Research). The optical model of a thin-film silicon multi-junction with incoherent light-trapping is characterized in great detail. The computational gains through hybrid, hp adaptive finite elements are studied and the incoherent domain decomposition algorithm is applied to model
a more realistic light-trapping by the glass substrate.
The numerical examples of a hexagonal nano-hole array and multi-junction silicon solar cell with a tunable intermediate reflector layer show that the reduced basis method is well suited as a forward solver for modeling and optimization tasks arising in photovoltaics and photonics. Reduced models for illumination and geometric parameters are built providing up to five orders of magnitude savings in computational costs. Resonance phenomena present in the nano-hole array example are detected and the model adapts itself automatically.
Optical 3D simulations in many-query and real-time contexts require new solution strategies. We study an adaptive, error controlled reduced basis method for solving parametrized time-harmonic optical scattering problems. Application fields are, among others, design and optimization problems of nano-optical devices as well as inverse problems for parameter reconstructions occuring e. g. in optical metrology. The reduced basis method presented here relies on a finite element modeling of the scattering problem with parametrization of materials, geometries and sources.