05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Top‐down approach to study chemical and electronic properties of perovskite solar cells : sputtered depth profiling versus tapered cross‐sectional photoelectron spectroscopies(2021) Das, Chittaranjan; Zia, Waqas; Mortan, Claudiu; Hussain, Navid; Saliba, Michael; Ingo Flege, Jan; Kot, MałgorzataA study of the chemical and electronic properties of various layers across perovskite solar cell (PSC) stacks is challenging. Depth‐profiling photoemission spectroscopy can be used to study the surface, interface, and bulk properties of different layers in PSCs, which influence the overall performance of these devices. Herein, sputter depth profiling (SDP) and tapered cross‐sectional (TCS) photoelectron spectroscopies (PESs) are used to study highly efficient mixed halide PSCs. It is found that the most used SDP‐PES technique degrades the organic and deforms the inorganic materials during sputtering of the PSCs while the TCS‐PES method is less destructive and can determine the chemical and electronic properties of all layers precisely. The SDP‐PES dissociates the chemical bonding in the spiro‐MeOTAD and perovskite layer and reduces the TiO2, which causes the chemical analysis to be unreliable. The TCS‐PES revealed a band bending only at the spiro‐MeOTAD/perovskite interface of about 0.7 eV. Both the TCS and SDP‐PES show that the perovskite layer is inhomogeneous and has a higher amount of bromine at the perovskite/TiO2 interface.Item Open Access Efficient exploratory clustering analyses in large-scale exploration processes(2021) Fritz, Manuel; Behringer, Michael; Tschechlov, Dennis; Schwarz, HolgerClustering is a fundamental primitive in manifold applications. In order to achieve valuable results in exploratory clustering analyses, parameters of the clustering algorithm have to be set appropriately, which is a tremendous pitfall. We observe multiple challenges for large-scale exploration processes. On the one hand, they require specific methods to efficiently explore large parameter search spaces. On the other hand, they often exhibit large runtimes, in particular when large datasets are analyzed using clustering algorithms with super-polynomial runtimes, which repeatedly need to be executed within exploratory clustering analyses. We address these challenges as follows: First, we present LOG-Means and show that it provides estimates for the number of clusters in sublinear time regarding the defined search space, i.e., provably requiring less executions of a clustering algorithm than existing methods. Second, we demonstrate how to exploit fundamental characteristics of exploratory clustering analyses in order to significantly accelerate the (repetitive) execution of clustering algorithms on large datasets. Third, we show how these challenges can be tackled at the same time. To the best of our knowledge, this is the first work which simultaneously addresses the above-mentioned challenges. In our comprehensive evaluation, we unveil that our proposed methods significantly outperform state-of-the-art methods, thus especially supporting novice analysts for exploratory clustering analyses in large-scale exploration processes.Item Open Access Impedance based temperature estimation of lithium ion cells using artificial neural networks(2021) Ströbel, Marco; Pross-Brakhage, Julia; Kopp, Mike; Birke, Kai PeterItem Open Access Cross-lingual citations in English papers : a large-scale analysis of prevalence, usage, and impact(2021) Saier, Tarek; Färber, Michael; Tsereteli, TornikeCitation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation-based machine learning approaches heavily depend on the completeness of such data. One particular shortcoming of scholarly data nowadays is that non-English publications are often not included in data sets, or that language metadata is not available. Because of this, citations between publications of differing languages (cross-lingual citations) have only been studied to a very limited degree. In this paper, we present an analysis of cross-lingual citations based on over one million English papers, spanning three scientific disciplines and a time span of three decades. Our investigation covers differences between cited languages and disciplines, trends over time, and the usage characteristics as well as impact of cross-lingual citations. Among our findings are an increasing rate of citations to publications written in Chinese, citations being primarily to local non-English languages, and consistency in citation intent between cross- and monolingual citations. To facilitate further research, we make our collected data and source code publicly available.Item Open Access Optimized planning of distribution grids considering grid expansion, battery systems and dynamic curtailment(2021) Laribi, Ouafa; Rudion, KrzysztofThe increasing integration of renewable energies into the grid is calling for the expansion of the power transport capacities in the distribution system. Yet, the expansion of the grid could require long authorization procedures and cannot be always asserted. Therefore, a higher utilization of the existing grid is becoming increasingly necessary today. This paper proposes a new time series-based planning method for distribution systems using classical grid expansion instruments as well as innovative planning instruments such as battery storage systems (BSS) and dynamic power curtailment (DPC). These planning instruments could be applied individually or combined. The aim of the BSS and DPC application is to enable a higher utilization of the grid at minimal costs. The proposed method, which has been implemented as an automated planning algorithm, determines the cost optimal grid reinforcement measures that ensure the prevention of prognosticated congestions in the considered grid. Furthermore, the application of the proposed planningmethod on the considered power system has proven that a combination of BSS and grid expansion could be more economical than an individual application of BSS and grid expansion.Item Open Access Non-uniform circumferential expansion of cylindrical Li-ion cells - the potato effect(2021) Hemmerling, Jessica; Guhathakurta, Jajnabalkya; Dettinger, Falk; Fill, Alexander; Birke, Kai PeterThis paper presents the non-uniform change in cell thickness of cylindrical Lithium (Li)-ion cells due to the change of State of Charge (SoC). Using optical measurement methods, with the aid of a laser light band micrometer, the expansion and contraction are determined over a complete charge and discharge cycle. The cell is rotated around its own axis by an angle of α=10° in each step, so that the different positions can be compared with each other over the circumference. The experimental data show that, contrary to the assumption based on the physical properties of electrode growth due to lithium intercalation in the graphite, the cell does not expand uniformly. Depending on the position and orientation of the cell coil, there are different zones of expansion and contraction. In order to confirm the non-uniform expansion around the circumference of the cell in 3D, X-ray computed tomography (CT) scans of the cells are performed at low and at high SoC. Comparison of the high resolution 3D reconstructed volumes clearly visualizes a sinusoidal pattern for non-uniform expansion. From the 3D volume, it can be confirmed that the thickness variation does not vary significantly over the height of the battery cell due to the observed mechanisms. However, a slight decrease in the volume change towards the poles of the battery cells due to the higher stiffness can be monitored.Item Open Access Editorial - autonomous health monitoring and assistance systems with IoT(2021) Azzopardi, George; Karastoyanova, Dimka; Aiello, Marco; Schizas, Christos N.Item Open Access Automated quantum hardware selection for quantum workflows(2021) Weder, Benjamin; Barzen, Johanna; Leymann, Frank; Salm, MarieThe execution of a quantum algorithm typically requires various classical pre- and post-processing tasks. Hence, workflows are a promising means to orchestrate these tasks, benefiting from their reliability, robustness, and features, such as transactional processing. However, the implementations of the tasks may be very heterogeneous and they depend on the quantum hardware used to execute the quantum circuits of the algorithm. Additionally, today’s quantum computers are still restricted, which limits the size of the quantum circuits that can be executed. As the circuit size often depends on the input data of the algorithm, the selection of quantum hardware to execute a quantum circuit must be done at workflow runtime. However, modeling all possible alternative tasks would clutter the workflow model and require its adaptation whenever a new quantum computer or software tool is released. To overcome this problem, we introduce an approach to automatically select suitable quantum hardware for the execution of quantum circuits in workflows. Furthermore, it enables the dynamic adaptation of the workflows, depending on the selection at runtime based on reusable workflow fragments. We validate our approach with a prototypical implementation and a case study demonstrating the hardware selection for Simon’s algorithm.Item Open Access Classification of superimposed partial discharge patterns(2021) Adam, Benjamin; Tenbohlen, StefanPhase resolved partial discharge patterns (PRPD) are routinely used to assess the condition of power transformers. In the past, classification systems have been developed in order to automate the fault identification task. Most of those systems work with the assumption that only one source is active. In reality, however, multiple PD sources can be active at the same time. Hence, PRPD patterns can overlap and cannot be separated easily, e.g., by visual inspection. Multiple PD sources in a single PRPD represent a multi-label classification problem. We present a system based on long short-term memory (LSTM) neural networks to resolve this task. The system is generally able to classify multiple overlapping PRPD by while only being trained by single class PD sources. The system achieves a single class accuracy of 99% and a mean multi-label accuracy of 43% for an imbalanced dataset. This method can be used with overlapping PRPD patterns to identify the main PD source and, depending on the data, also classify the second source. The method works with conventional electrical measuring devices. Within a detailed discussion of the presented approach, both its benefits but also its problems regarding different repetition rates of different PD sources are being evaluated.Item Open Access Unified model for laser doping of silicon from precursors(2021) Hassan, Mohamed; Dahlinger, Morris; Köhler, Jürgen R.; Zapf-Gottwick, Renate; Werner, Jürgen H.Laser doping of silicon with the help of precursors is well established in photovoltaics. Upon illumination with the constant or pulsed laser beam, the silicon melts and doping atoms from the doping precursor diffuse into the melted silicon. With the proper laser parameters, after resolidification, the silicon is doped without any lattice defects. Depending on laser energy and on the kind of precursor, the precursor either melts or evaporates during the laser process. For high enough laser energies, even parts of the silicon’s surface evaporate. Here, we present a unified model and simulation program, which considers all these cases. We exemplify our model with experiments and simulations of laser doping from a boron oxide precursor layer. In contrast to previous models, we are able to predict not only the width and depth of the patterns on the deformed silicon surface but also the doping profiles over a wide range of laser energies. In addition, we also show that the diffusion of the boron atoms in the molten Si is boosted by a thermally induced convection in the silicon melt: the Gaussian intensity distribution of the laser beam increases the temperature-gradient-induced surface tension gradient, causing the molten Si to circulate by Marangoni convection. Laser pulse energy densities above H > 2.8 J/cm2 lead not only to evaporation of the precursor, but also to a partial evaporation of the molten silicon. Without considering the evaporation of Si, it is not possible to correctly predict the doping profiles for high laser energies. About 50% of the evaporated materials recondense and resolidify on the wafer surface. The recondensed material from each laser pulse forms a dopant source for the subsequent laser pulses.