Numerical optimization is an important tool in the field of computational physics in general and in nano-optics in specific. It has attracted attention with the increase in complexity of structures that can be realized with nowadays nano-fabrication technologies for which a rational design is no longer feasible. Also, numerical resources are available to enable the computational photonic material design and to identify structures that meet predefined optical properties for specific applications. However, the optimization objective function is in general non-convex and its computation remains resource demanding such that the right choice for the optimization method is crucial to obtain excellent results. Here, we benchmark five global optimization methods for three typical nano-optical optimization problems: downhill simplex optimization, the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, particle swarm optimization, differential evolution, and Bayesian optimization. In the shown examples from the field of shape optimization and parameter reconstruction, Bayesian optimization, mainly known from machine learning applications, obtains significantly better results in a fraction of the run times of the other optimization methods. AbstractThis document provides supporting information to "Benchmarking five global optimization approaches for nano-optical shape optimization and parameter reconstruction" regarding the implementation and numerical setting of the optimization methods as well as a visualization of the different optimization strategies.

Crystalline silicon photonic crystal slabs are widely used in various photonics applications. So far, the commercial success of such structures is still limited owing to the lack of cost-effective fabrication processes enabling large nanopatterned areas (≫ 1 cm2). We present a simple method for producing crystalline silicon nanohole arrays of up to 5 × 5 cm2 size with lattice pitches between 600 and 1000 nm on glass and flexible plastic substrates. Exclusively up-scalable, fast fabrication processes are applied such as nanoimprint-lithography and silicon evaporation. The broadband light trapping efficiency of the arrays is among the best values reported for large-area experimental crystalline silicon nanostructures. Further, measured photonic crystal resonance modes are in good accordance with light scattering simulations predicting strong near-field intensity enhancements greater than 500. Hence, the large-area silicon nanohole arrays might become a promising platform for ultrathin solar cells on lightweight substrates, high-sensitive optical biosensors, and nonlinear optics.

We numerically study coupling of light into silicon (Si) on glass using different square and hexagonal sinusoidal nanotextures. After describing sinusoidal nanotextures mathematically, we investigate how their design affects coupling of light into Si using a rigorous solver of Maxwell's equations. We discuss nanotextures with periods between 350 nm and 1050 nm and aspect ratios up to 0.5. The maximally observed gain in the maximal achievable photocurrent density coupled into the Si absorber is 7.0 mA/cm² and 3.6 mA/cm² for a layer stack without and with additional antireflective silicon nitride layers, respectively. A promising application is the use as smooth anti-reflective coatings in liquid-phase crystallized Si thin-film solar cells.

Perovskite/silicon tandem solar cells are regarded as a promising candidate to surpass current efficiency limits in terrestrial photovoltaics. Tandem solar cell efficiencies meanwhile reach more than 29%. However, present high-end perovskite/silicon tandem solar cells still suffer from optical losses. We review recent numerical and experimental perovskite/silicon tandem solar cell studies and analyse the applied measures for light management. Literature indicates that highest experimental efficiencies are obtained using fully planar perovskite top cells, being in contradiction to the outcome of optical simulations calling for textured interfaces. The reason is that the preferred perovskite top cell solution-processing is often incompatible with usual micropyramidal textures of silicon bottom cells. Based on the literature survey, we propose a certain gentle nanotexture as an example to reduce optical losses in perovskite/silicon tandem solar cells. Optical simulations using the finite-element method reveal that an intermediate texture between top and bottom cell does not yield an optical benefit when compared with optimized planar designs. A double-side textured top-cell design is found to be necessary to reduce reflectance losses by the current density equivalent of 1 mA/cm2. The presented results illustrate a way to push perovskite/silicon tandem solar cell efficiencies beyond 30% by improved light management.