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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.
The introduction of the near-field quantity of optical chirality has emerged in various numerical and few experimental studies of local chirality enhancement due to its relation to the excitation rate of chiral molecules. This time-even pseudoscalar has been dismissed as being a higher-order version of helicity. Nevertheless, we revisit the derivation of the underlying conservation law and define optical chirality in media similar to. We identify the mechanism of chirality conversion by either inhomogeneous or anisotropic space to complement the conservation of optical chirality.
The conservation law of optical chirality in arbitrary space enables the extension of the concept of polarization to the near-field where no distiniguished propagation direction of light is present. We show that the connection of electromagnetic energy and optical chirality provide the ability to define a circular polarization basis in time-harmonic near-field analysis.
In order to illustrate our theory, we present electromagnetic field simulations of simple as well as more complex nanostructures. Results using the well-known far-field polarization concept are readily reproduced and extended from the point of view of chirality conversion.
Reconstruction of photonic crystal geometries using a reduced basis method for nonlinear outputs
(2016)
Maxwell solvers based on the hp-adaptive finite element method allow for accurate geometrical modeling and high numerical accuracy. These features are indispensable for the optimization of optical properties or reconstruction of parameters through inverse processes. High computational complexity prohibits the evaluation of the solution for many parameters. We present a reduced basis method (RBM) for the time-harmonic electromagnetic scattering problem allowing to compute solutions for a parameter configuration orders of magnitude faster. The RBM allows to evaluate linear and nonlinear outputs of interest like Fourier transform or the enhancement of the electromagnetic field in milliseconds. We apply the RBM to compute light-scattering off two dimensional photonic crystal structures made of silicon and reconstruct geometrical parameters.
Model order reduction for the time-harmonic Maxwell equation applied to complex nanostructures
(2016)
Fields such as optical metrology and computational lithography require fast and efficient methods for solving the time-harmonic Maxwell's equation. Highly accurate geometrical modelling and numerical accuracy at low computational costs are a prerequisite for any simulation study of complex nano-structured photonic devices. We present a reduced basis method (RBM) for the time-harmonic electromagnetic scattering problem based on the hp-adaptive finite element solver JCMsuite capable of handling geometric and non-geometric parameter dependencies allowing for online evaluations in milliseconds. We apply the RBM to compute light-scattering at optical wavelengths of periodic arrays of fin field-effect transistors (FinFETs) where geometrical properties such as the width and height of the fin and gate can vary in a large range.
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 occurring e. g. in optical metrology. The reduced basis method pre-
sented here relies on a finite element modeling of the scattering problem with
parametrization of materials, geometries and sources.
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.
Gaining insights into the working principles of photocatalysts on an atomic scale is a challenging task. The obviously high complexity of the reaction mechanism involving photo-excited electrons and holes is one reason. Another complicating aspect is that the electromagnetic field, driving photocatalysis, is not homogeneous on a nanoscale level for particle based catalysts as it is influenced by the particle’s shape and size.
We present a simple model, inspired by the CO2 reduction on titania anatase, which addresses the impact of these heterogeneities on the photocatalytic kinetics by combining kinetic Monte Carlo with electromagnetic wave simulations. We find that average activity and especially efficiency might differ significantly between different particles. Moreover, we find sizable variation of the catalytic activity on a single facet of a nanocrystal. Besides this quantitative heterogeneity, the coverage situation in general changes laterally on this facet and we observe a concomitant change of the rate-determining steps.
This heterogeneity on all levels of photocatalytic activity is masked in experimental studies, where only the spatially averaged activity can be addressed. Microkinetic models based on experimental findings might therefore not represent the true micro- scopic behavior, and mechanistic conclusion drawn from these need to be handled with care.
Adaptive sampling strategies for efficient parameter scans in nano-photonic device simulations
(2014)
Rigorous optical simulations are an important tool in optimizing scattering properties of nano-photonic devices and are used, for example, in solar cell optimization. The finite element method (FEM) yields rigorous, time-harmonic, high accuracy solutions of the full 3D vectorial Maxwell's equations [1] and furthermore allows for great flexibility and accuracy in the geometrical modeling of these often complex shaped 3D nano-structures. A major drawback of frequency domain methods is the limitation of single frequency evaluations. For example the accurate computation of the short circuit current density of an amorphous silicon / micro-crystalline multi-junction thin film solar cell may require the solution of Maxwell's equations for over a hundred different wavelengths if an equidistant sampling strategy is employed. Also in optical metrology, wavelength scans are frequently used to reconstruct unknown geometrical and material properties of optical systems numerically from measured
scatterometric data.
In our contribution we present several adaptive numerical integration and sampling routines and study their efficiency in the context of the determination of generation rate profiles of solar cells. We show that these strategies lead to a reduction in the computational effort without loss of accuracy. We discuss the employment of tangential information in a Hermite interpolation scheme to achieve similar accuracy on coarser grids. We explore the usability of these strategies for scatterometry and solar cell simulations.
In many experimentally realized applications, e.g. photonic crystals, solar cells and light-emitting diodes, nano-photonic systems are coupled to a thick substrate layer, which in certain cases has to be included as a part of the optical system. The finite element method (FEM) yields rigorous, high accuracy solutions of full 3D vectorial Maxwell's equations [1] and allows for great flexibility and accuracy in the geometrical modelling. Time-harmonic FEM solvers have been combined with Fourier methods in domain decomposition algorithms to compute coherent solutions of these coupled system. [2,3] The basic idea of a domain decomposition approach lies in a decomposition of the domain into smaller subdomains, separate calculations of the solutions and coupling of these solutions on adjacent subdomains.
In experiments light sources are often not perfectly monochromatic and hence a comparision to simulation results might only be justified if the simulation results, which include interference patterns in the substrate, are spectrally averaged.
In this contribution we present a scattering matrix domain decomposition algorithm for Maxwell's equations based on FEM. We study its convergence and advantages in the context of optical simulations of silicon thin film multi-junction solar cells. This allows for substrate light-trapping to be included in optical simulations and leads to a more realistic estimation of light path enhancement factors in thin-film devices near the band edge.
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.
Hp-finite-elements for simulating electromagnetic fields in optical devices with rough textures
(2015)
Adaptive sampling strategies for effcient parameter scans in nano-photonic device simulations
(2014)
Rigorous optical simulations of 3-dimensional nano-photonic structures are an important tool in the analysis and optimization of scattering properties of nano-photonic devices or parameter reconstruction. To construct geometrically accurate models of complex structured nano-photonic devices the finite element method (FEM) is ideally suited due to its flexibility in the geometrical modeling and superior convergence properties. Reduced order models such as the reduced basis method (RBM) allow to construct self-adaptive, error-controlled, very low dimensional approximations for input-output relationships which can be evaluated orders of magnitude faster than the full model. This is advantageous in applications requiring the solution of Maxwell's equations for multiple parameters or a single parameter but in real time. We present a reduced basis method for 3D Maxwell's equations based on the finite element method which allows variations of geometric as well as material and frequency parameters. We demonstrate accuracy and efficiency of the method for a light scattering problem exhibiting a resonance in the electric field.
Determining 2D photonic crystal geometries from reflectance spectra with a reduced basis method
(2016)
Light Management for Engineering Luminescence in Nanoscale Environments By Numerical Optimization
(2018)
Model order reduction for the time-harmonic Maxwell equation applied to complex nanostructures
(2016)
Fields such as optical metrology and computational lithography require fast and efficient methods for solving
the time-harmonic Maxwell’s equation. Highly accurate geometrical modeling and numerical accuracy atcomputational costs are a prerequisite for any simulation study of complex nano-structured photonic devices.
We present a reduced basis method (RBM) for the time-harmonic electromagnetic scattering problem based
on the hp-adaptive finite element solver JCMsuite capable of handling geometric and non-geometric parameter
dependencies allowing for online evaluations in milliseconds. We apply the RBM to compute light-scatteringoptical wavelengths off periodic arrays of fin field-effect transistors (FinFETs) where geometrical properties such
as the width and height of the fin and gate can vary in a large range.
Reconstruction of photonic crystal geometries using a reduced basis method for nonlinear outputs
(2016)
Maxwell solvers based on the hp-adaptive finite element method allow for accurate geometrical modeling and high numerical accuracy. These features are indispensable for the optimization of optical properties or reconstruction of parameters through inverse processes. High computational complexity prohibits the evaluation of the solution for many parameters. We present a reduced basis method (RBM) for the time-harmonic electromagnetic scattering problem allowing to compute solutions for a parameter configuration orders of magnitude faster. The RBM allows to evaluate linear and nonlinear outputs of interest like Fourier transform or the enhancement of the electromagnetic field in milliseconds. We apply the RBM to compute light-scattering off two dimensional photonic crystal structures made of silicon and reconstruct geometrical parameters.
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.
Elementary, my dear Zernike: model order reduction for accelerating optical dimensional microscopy
(2022)
Cover Picture: Resonance Expansion of Quadratic Quantities with Regularized Quasinormal Modes
(2023)
In optical nano metrology numerical models are used widely for parameter reconstructions. Using the Bayesian target vector optimization method we fit a finite element numerical model to a Grazing Incidence x-ray fluorescence data set in order to obtain the geometrical parameters of a nano structured line grating. Gaussian process, stochastic machine learning surrogate models, were trained during the reconstruction and afterwards sampled with a Markov chain Monte Carlo sampler to determine the distribution of the reconstructed model parameters. The numerical discretization parameters of the used finite element model impact the numerical discretization error of the forward model. We investigated the impact of the polynomial order of the finite element ansatz functions on the reconstructed parameters as well as on the model parameter distributions. We showed that such a convergence study allows to determine numerical parameters which allows for efficient and accurate reconstruction results.
Modelling luminescent coupling in multi-junction solar cells: perovskite silicon tandem case study
(2024)
Machine-learning driven design of metasurfaces: learn the physics and not the objective function
(2024)