spectrum to a desired color by the use of different photoactive materials. [2][3][4][5][6] These characteristics enable the production of power generating smart windows, awnings, building facades etc. [7][8][9] Still, semitransparent solar cells show lower effi ciencies than their opaque counterparts due to the inherent tradeoff between transmission and absorption. To overcome this problem different light trapping approaches such as microcavities, dielectric scatters, microlenses, and wavelength selective mirrors have been investigated. [10][11][12][13][14][15][16][17][18][19] Particularly the last approach allows to precisely adjust the transparency as well as the color of a device. Wavelength selective fi lters are also known as 1D photonic crystals, Bragg mirrors or dielectric mirrors (DMs). The working principle of DMs relies on constructive or destructive interference of thin layers. For this purpose, a high refractive index (HRI) and a low refractive index (LRI) material have to be arranged alternatingly and fulfi ll the equation 4 HRI HRI LRI LRI 0 n d n d λ = = , with n being the refractive index (RI), d being the layer thickness, and λ 0 being the wavelength with maximum refl ection at perpendicular incidence. An high RI contrast is desirable as this leads to a broad stopband with a large refl ection at λ 0 . [ 20 ] The production of a DM, however, is challenging as only slight variations in layer thicknesses cause a shift in λ 0 (see Figure S1, Supporting Information). Conventional techniques for DM fabrication are evaporation of inorganic materials under high vacuum conditions, electron beam evaporation, and magnetron sputtering. [ 15,16,[21][22][23] However, polymers or organic-inorganic nanocomposites are much more promising because they allow a controlled variation of n , better processability, and highly fl exible fi lms. [24][25][26] Methods such as spin coating or dip coating can be carried out with these ink-based materials. [ 17,24,[27][28][29][30] However, while these techniques allow precise settings in layer thickness, they only offer limited potential with respect to commercial and largearea processing as they are cost-intensive and diffi cult in terms of upscaling. In addition, DMs directly processed on the top of solar cells further complicate the whole device structure. For example, up to 16 additional layers are necessary to increase the short-circuit current ( J sc ) by ≈20% compared to a device without DM. [ 31 ] Building integrated semitransparent thin-fi lm solar cells is a strategy for future eco-friendly power generation. Organic photovoltaics in combination with dielectric mirrors (DMs) are a potential candidate as they promise high effi ciencies in parallel to the possibility to adjust the color and thus the transparency of the whole device. A fully solution processed and printable DM with an easily adjustable refl ection maximum is presented that can be facilely attached to solar cells. The DM is optimized via optical simulations to the particular needs of the device with regar...
Dielectric mirrors are wavelength‐selective mirrors which are based on thin film interference effects. Their optical band can precisely be adjusted in width, position, and reflectance by the refractive index of the applied materials, the layers' thicknesses, and the amount of deposited layers. Nowadays, they are a well‐known light management tool for efficiency enhancement in, for example, semitransparent organic solar cells (OSCs) and light guiding in organic light‐emitting diodes (OLEDs). However, most of the dielectric mirrors are still fabricated by lab‐scale techniques such as spin‐coating or physical vapor deposition under vacuum. Large‐scale, fully printed (maximum 20 × 20 cm2) dielectric mirrors with adjustable reflectance characteristics are fabricated, using temperatures of maximum 50 °C and alcohol‐based inks. According to the moderate processing conditions they can be easily deposited not only on rigid glass substrates but also on flexible foils. They show high stability against humidity, light irradiation, and temperature, positioning themselves as good candidates for applications in OLEDs and OSCs. Eventually, by simulations and experiments it is verified that a moderate degree of variations in layer thickness and surface roughness can suppress side interference fringes, while not impacting the main transmittance minimum or the main reflection maximum, respectively.
Understanding and optimizing the properties of solar cells is becoming a key issue in the search for alternatives to nuclear and fossil energy sources. A theoretical analysis via numerical simulations involves solving Maxwell's Equations in discretized form and typically requires substantial computing effort. We start from a hybrid-parallel (MPI+OpenMP) production code that implements the Time Harmonic Inverse Iteration Method (THIIM) with Finite-Difference Frequency Domain (FDFD) discretization. Although this algorithm has the characteristics of a strongly bandwidth-bound stencil update scheme, it is significantly different from the popular stencil types that have been exhaustively studied in the high performance computing literature to date. We apply a recently developed stencil optimization technique, multicore wavefront diamond tiling with multi-dimensional cache block sharing, and describe in detail the peculiarities that need to be considered due to the special stencil structure. Concurrency in updating the components of the electric and magnetic fields provides an additional level of parallelism. The dependence of the cache size requirement of the optimized code on the blocking parameters is modeled accurately, and an auto-tuner searches for optimal configurations in the remaining parameter space. We were able to completely decouple the execution from the memory bandwidth bottleneck, accelerating the implementation by a factor of three to four compared to an optimal implementation with pure spatial blocking on an 18-core Intel Haswell CPU.
We are studying the influence of spherical silver nanoparticles (AgNP) in absorbing media by numerically solving the Maxwell's equations. Our simulations show that the near-field absorption enhancement introduced by a single AgNP in the surrounding medium is increasing with the growing particle diameter. However, we observe that the relative absorption per particle volume is on a similar level for different particle sizes; hence, different numbers of particles with the same total volume yield the same near-field absorption enhancement. We also investigate the effect of non-absorbing shells around the AgNP with the conclusion that even very thin shells suppress the beneficial effects of the particles noticeably. Additionally, we include AgNP in an organic solar cell at different vertical positions with different particle spacings and observe the beneficial effects for small AgNP and the scattering dependent performance for larger particles.
Stencil algorithms have been receiving considerable interest in HPC research for decades. The techniques used to approach multi-core stencil performance modeling and engineering span basic runtime measurements, elaborate performance models, detailed hardware counter analysis, and thorough scaling behavior evaluation. Due to the plurality of approaches and stencil patterns, we set out to develop a generalizable methodology for reproducible measurements accompanied by state-of-the-art performance models. Our open-source toolchain and collected results are publicly available in the "Intranode Stencil Performance Evaluation Collection" (INSPECT). We present the underlying methods, models and tools involved in gathering and documenting the performance behavior of a collection of typical stencil patterns across multiple architectures and hardware configuration options. Our aim is to endow performance-aware application developers with reproducible baseline performance data and validated models to initiate a well-defined process of performance assessment and optimization. All data is available for inspection: source code, produced assembly, performance measurements, hardware performance counter data, single-core and multicore Roofline and ECM (execution-cache-memory) performance models, and machine properties. Deviations between measured performance and performance models become immediately evident and can be investigated. We also give hints as to how INSPECT can be used in practice for custom code analysis.
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