05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Start date: 2020Institute: search.filters.UBSInstitut.Institut für PhotovoltaikSubject: search.filters.subject.620

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Now showing 1 - 10 of 25
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    A dual‐layered anode buffer layer structure for all solid‐state batteries
    (2024) Lu, Yushi; Chang, Hansen Michael; Birke, Kai Peter
    Over the past few decades, lithium‐ion batteries have garnered considerable attention, especially for their use in electric vehicles (EVs). In recent years, solid‐state batteries have become increasingly popular due to their excellent safety features and potential for high energy density. However, solid‐state batteries with lithium metal anodes present challenges in terms of electrochemical reactivity and cost. To address these challenges, alternative anode systems such as the “anode‐free” approach are being explored. In this study, we introduced a dual‐layered anode comprising a primary layer of physically vapor‐deposited zinc and a secondary layer of carbon black, focusing on investigating the influence of varying thicknesses of the lithiophilic zinc layer on cell cycling performance. Among the three different zinc thicknesses chosen for this purpose - categorized as thin (286 nm), medium (1.802 μm), and thick (6.519 μm) - the dual‐layered anode buffer layer was analyzed in a single‐layer full pouch cell. An in‐depth investigation into the lithium‐zinc alloying behavior was conducted through post‐mortem analysis. From the results, we found that the combination of the zinc layer with the carbon black layer improved cell cycling performance in terms of discharge capacity retention compared to a single layer of either zinc or carbon black. The cycling performance of this dual‐layered anode could be further enhanced by optimizing the zinc layer thickness, likely due to the irreversible alloying step of zinc and lithium. Among the various thicknesses evaluated, the thin zinc layer (286 nm) combined with the carbon black layer demonstrated the most promising cycling performance in all solid‐state batteries.
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    Analytic free-energy expression for the 2D-Ising model and perspectives for battery modeling
    (2023) Markthaler, Daniel; Birke, Kai Peter
    Although originally developed to describe the magnetic behavior of matter, the Ising model represents one of the most widely used physical models, with applications in almost all scientific areas. Even after 100 years, the model still poses challenges and is the subject of active research. In this work, we address the question of whether it is possible to describe the free energy A of a finite-size 2D-Ising model of arbitrary size, based on a couple of analytically solvable 1D-Ising chains. The presented novel approach is based on rigorous statistical-thermodynamic principles and involves modeling the free energy contribution of an added inter-chain bond DAbond(b, N) as function of inverse temperature b and lattice size N. The identified simple analytic expression for DAbond is fitted to exact results of a series of finite-size quadratic N N-systems and enables straightforward and instantaneous calculation of thermodynamic quantities of interest, such as free energy and heat capacity for systems of an arbitrary size. This approach is not only interesting from a fundamental perspective with respect to the possible transfer to a 3D-Ising model, but also from an application-driven viewpoint in the context of (Li-ion) batteries where it could be applied to describe intercalation mechanisms.
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    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, Małgorzata
    A 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.
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    Laser doping for silicon solar cells : modeling and application
    (2024) Hassan, Mohamed; Werner, Jürgen H. (Prof. Dr. rer. nat. habil.)
    In meiner Dissertation geht es um die Simulation des Laserdotierungsprozess der Oberfläche des Siliziumwafers um hoch effizienten Solarzellen herzustellen. Die Simulation ermöglicht die genaue Vorhersage der Dimensionen eines dotierten Bereiches. Das hat ermöglicht, nicht nur die Abhängigkeit des ergebenden Schichtleitwerts von der benutzten Rastergeschwindigkeit des Laserstrahls auf die Siliziumoberfläche zu verstehen, sondern auch der Schichtleitwert einer laserdotierten Schicht basierend auf ein einfaches geometrisches Modell vorherzusagen.
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    The influence of micro-structured anode current collectors in combination with highly concentrated electrolyte on the Coulombic efficiency of in-situ deposited Li-metal electrodes with different counter electrodes
    (2020) Heim, Fabian; Kreher, Tina; Birke, Kai Peter
    This paper compares and combines two common methods to improve the cycle performance of lithium metal (Li) electrodes. One technique is to establish a micro-structured current collector by chemical separation of a copper/zinc alloy. Furthermore, the use of a highly concentrated ether-based electrolyte is applied as a second approach for improving the cycling behavior. The influence of the two measures compared with a planar current collector and a 1 M concentrated carbonate-based electrolyte, as well as the combination of the methods, are investigated in test cells both with Li and lithium nickel cobalt manganese oxide (NCM) as counter electrodes. In all cases Li is in-situ plated onto the micro-structured current collectors respectively a planar copper foil without presence of any excess Li before first deposition. In experiments with Li counter electrodes, the effect of a structured current collector is not visible whereas the influence of the electrolyte can be observed. With NCM counter electrodes and carbonate-based electrolyte structured current collectors can improve Coulombic efficiency. The confirmation of this outcome in experiments with highly concentrated ether-based electrolyte is challenging due to high deviations. However, these results indicate, that improvements in Coulombic efficiency achieved by structuring the current collector’s surface and using ether-based electrolyte do not necessarily add up, if both methods are combined in one cell.
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    Influence of temperature and pressure on the wetting progress in 21700 lithium‐ion battery cells : experiment, model, and lattice Boltzmann simulation
    (2024) Wanner, Johannes; Burgard, Matthias; Othman, Nabih; Singh, Soumya; Birke, Kai Peter
    The electrolyte filling and subsequent wetting of the active material is a time‐critical process in the manufacturing of lithium‐ion batteries. Due to the metallic cell housing, the process phenomena are insufficiently accessible, preventing the replication of the wetting processes by mathematical or simulative methods and hindering efforts to accelerate the wetting process. Therefore, this publication employs a glass cell housing for electrolyte filling of a 21700 cylindrical cell to investigate the wetting at different temperatures and process pressures. In parallel, a mathematical replication of the wetting, as well as a lattice Boltzmann pore‐scale simulation, is used to evaluate the influence of these varying process boundary conditions. The results show a strong temperature dependence on electrolyte wetting and the positive effect of pressure changes in the wetting process. These findings are particularly relevant to the process design of large‐scale cylindrical cell manufacturing.
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    Cycling of double-layered graphite anodes in pouch-cells
    (2022) Müller, Daniel; Fill, Alexander; Birke, Kai Peter
    Incremental improvement to the current state-of-the-art lithium-ion technology, for example regarding the physical or electrochemical design, can bridge the gap until the next generation of cells are ready to take Li-ions place. Previously designed two-layered porosity-graded graphite anodes, together with LixNi0.6Mn0.2Co0.2O2 cathodes, were analysed in small pouch-cells with a capacity of around 1 Ah. For comparison, custom-made reference cells with the average properties of two-layered anodes were tested. Ten cells of each type were examined in total. Each cell pair, consisting of one double-layer and one single-layer (reference) cell, underwent the same test procedure. Besides regular charge and discharge cycles, electrochemical impedance spectroscopy, incremental capacity analysis, differential voltage analysis and current-pulse measurement are used to identify the differences in ageing behaviour between the two cell types. The results show similar behaviour and properties at beginning-of-life, but an astonishing improvement in capacity retention for the double-layer cells regardless of the cycling conditions. Additionally, the lifetime of the single-layer cells was strongly influenced by the cycling conditions, and the double-layer cells showed less difference in ageing behaviour.
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    Multi-method model for the investigation of disassembly scenarios for electric vehicle batteries
    (2023) Baazouzi, Sabri; Grimm, Julian; Birke, Kai Peter
    Disassembly is a pivotal technology to enable the circularity of electric vehicle batteries through the application of circular economy strategies to extend the life cycle of battery components through solutions such as remanufacturng, repurposing, and efficient recycling, ultimately reintegrating gained materials into the production of new battery systems. This paper aims to develop a multi-method self-configuring simulation model to investigate disassembly scenarios, taking into account battery design as well as the configuration and layout of the disassembly station. We demonstrate the developed model in a case study using a Mercedes-Benz battery and the automated disassembly station of the DeMoBat project at Fraunhofer IPA. Furthermore, we introduce two disassembly scenarios: component-oriented and accessibility-oriented disassembly. These scenarios are compared using the simulation model to determine several indicators, including the frequency of tool change, the number and distribution of robot routes, tool utilization, and disassembly time.
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    Artificial feature extraction for estimating state-of-temperature in lithium-ion-cells using various long short-term memory architectures
    (2022) Kopp, Mike; Ströbel, Marco; Fill, Alexander; Pross-Brakhage, Julia; Birke, Kai Peter
    The temperature in each cell of a battery system should be monitored to correctly track aging behavior and ensure safety requirements. To eliminate the need for additional hardware components, a software based prediction model is needed to track the temperature behavior. This study looks at machine learning algorithms that learn physical behavior of non-linear systems based on sample data. Here, it is shown how to improve the prediction accuracy using a new method called “artificial feature extraction” compared to classical time series approaches. We show its effectiveness on tracking the temperature behavior of a Li-ion cell with limited training data at one defined ambient temperature. A custom measuring system was created capable of tracking the cell temperature, by installing a temperature sensor into the cell wrap instead of attaching it to the cell housing. Additionally, a custom early stopping algorithm was developed to eliminate the need for further hyperparameters. This study manifests that artificially training sub models that extract features with high accuracy aids models in predicting more complex physical behavior. On average, the prediction accuracy has been improved by ΔTcell=0.01 °C for the training data and by ΔTcell=0.007 °C for the validation data compared to the base model. In the field of electrical energy storage systems, this could reduce costs, increase safety and improve knowledge about the aging progress in an individual cell to sort out for second life applications.