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Faculty / Organisational entity
- Kaiserslautern - Fachbereich Mathematik (1182)
- Kaiserslautern - Fachbereich Informatik (927)
- Kaiserslautern - Fachbereich Maschinenbau und Verfahrenstechnik (577)
- Kaiserslautern - Fachbereich Chemie (428)
- Kaiserslautern - Fachbereich Sozialwissenschaften (351)
- Kaiserslautern - Fachbereich Physik (329)
- Fraunhofer (ITWM) (224)
- Kaiserslautern - Fachbereich Biologie (183)
- Kaiserslautern - Fachbereich Elektrotechnik und Informationstechnik (171)
- Distance and Independent Studies Center (DISC) (168)
Sound localization involves information analysis in the lateral superior olive (LSO), a conspicuous nucleus in the mammalian auditory brainstem. LSO neurons weigh interaural level differences (ILDs) through precise integration of glutamatergic excitation from the cochlear nucleus (CN) and glycinergic inhibition from the medial nucleus of the trapezoid body (MNTB). Sound sources can be localized even during sustained perception, an accomplishment that requires robust neurotransmission. Virtually nothing is known about the sustained performance and the temporal precision of MNTB–LSO inputs after postnatal day (P)12 (time of hearing onset) and whether acoustic experience guides development. Here we performed whole-cell patch-clamp recordings to investigate neurotransmission of single MNTB-LSO fibres upon sustained electrical stimulation (1–200 Hz/60 s) at P11 and P38 in wild-type (WT) and deaf otoferlin (Otof) knock-out (KO) mice. At P11, WT and KO inputs performed remarkably similarly. In WTs, the performance increased drastically between P11 and P38, e.g. manifested by an 8 to 11-fold higher replenishment rate (RR) of synaptic vesicles and action potential robustness. Together, these changes resulted in reliable and highly precise neurotransmission at frequencies ≤100 Hz. In contrast, KO inputs performed similarly at both ages, implying impaired synaptic maturation. Computational modelling confirmed the empirical observations and established a reduced RR per release site for P38 KOs. In conclusion, acoustic experience appears to contribute massively to the development of reliable neurotransmission, thereby forming the basis for effective ILD detection. Collectively, our results provide novel insights into experience-dependent maturation of inhibitory neurotransmission and auditory circuits at the synaptic level.
Development of a simple substitute model to describe the normal force of fluids in narrow gaps
(2023)
Fluids in narrow gaps are employed frequently in many applications. The motivation for their use is diverse and ranges from hydrodynamic lubrication in plain bearings to the transport of hard particles into the working gap for the purpose of machining workpiece surfaces in lapping processes. Depending on the focus of the analysis, it may be useful to investigate the entire pressure field or to calculate only individual quantities. For example, in sophisticated simulations it may be of interest to know the resulting force of a fluid as a function of the external system state in order to describe its damping characteristics. Especially for the simulation of flows in narrow gaps, the Reynolds equation is a convenient choice, which, in contrast to the more general Navier-Stokes equations, can lead to considerable savings in computational time because no three-dimensional discretization is required, but only a two-dimensional discretization. However, if not a highly detailed pressure field is of interest, but only simple relations such as the resulting force as a function of distance and velocity, and if this relation to be evaluated many times for different parameter combinations over a wide range of values, the use of a robust substitute model is a good choice. This article deals with the creation of such a substitute model based on the Reynolds equation taking cavitation into account.
Machine learning algorithms are widely applied to create powerful prediction models. With increasingly complex models, humans' ability to understand the decision function (that maps from a high-dimensional input space) is quickly exceeded. To explain a model's decisions, black-box methods have been proposed that provide either non-linear maps of the global topology of the decision boundary, or samples that allow approximating it locally. The former loses information about distances in input space, while the latter only provides statements about given samples, but lacks a focus on the underlying model for precise ‘What-If'-reasoning. In this paper, we integrate both approaches and propose an interactive exploration method using local linear maps of the decision space. We create the maps on high-dimensional hyperplanes—2D-slices of the high-dimensional parameter space—based on statistical and personal feature mutability and guided by feature importance. We complement the proposed workflow with established model inspection techniques to provide orientation and guidance. We demonstrate our approach on real-world datasets and illustrate that it allows identification of instance-based decision boundary structures and can answer multi-dimensional ‘What-If'-questions, thereby identifying counterfactual scenarios visually.
In the last decades, the phase field method has drawn much attention for its application in fracture mechanics because it offers a simple unified framework for crack propagation. The core idea of phase field models for fracture is to introduce a continuous scalar field representing the discontinuous crack. Recently, a phase field model for fatigue has been proposed along this path. The fatigue failure differs from the other fracture scenarios since cracks only occur after a considerable number of load cycles. As fracturing happens, changes of the material microstructure are involved, which causes the evolution of the structural configuration. Thus, a new mathematical description not based on traditional spatial coordinates but the material manifold is desired, which will serve as an elegant analysis tool to understand the energetic forces for crack propagation. Configurational forces are a suitable choice for this purpose, as they describe the energetic driving forces associated with phenomena changing the material itself. In this work, we present a phase field model for fatigue. Furthermore, the phase field fatigue model is analyzed within the concept of configurational forces, which provides a straightforward way to understand the phase field simulations of fatigue fracture.
Citizen conceptions of democracy and support for artificial intelligence in government and politics
(2022)
How much do citizens support artificial intelligence (AI) in government and politics at different levels of decision-making authority and to what extent is this AI support associated with citizens’ conceptions of democracy? Using original survey data from Germany, the analysis shows that people are overall sceptical toward using AI in the political realm. The findings suggest that how much citizens endorse democracy as liberal democracy as opposed to several of its disfigurations matters for AI support, but only in high-level politics. While a stronger commitment to liberal democracy is linked to lower support for AI, the findings contradict the idea that a technocratic notion of democracy lies behind greater acceptance of political AI uses. Acceptance is higher only among those holding reductionist conceptions of democracy which embody the idea that whatever works to accommodate people's views and preferences is fine. Populists, in turn, appear to be against AI in political decision making.
CFD-DEM Simulation of Superquadric Cylindrical Particles in a Spouted Bed and a Rotor Granulator
(2023)
The fluidization behavior of cylindrical particles in a spouted bed was first investigated experimentally using a camera setup. The obtained average spouted bed height was used to evaluate the accuracy of different drag models in CFD-DEM simulations with the superquadric approach to model the particle shape. The drag model according to Sanjeevi et al. showed the best agreement. With this model, cylindrical particles were simulated in a rotor granulator and the particle dynamics were compared with the fluidization of volume equivalent spherical particles.
Drawing on theorising on digital technologies as external enablers of entrepreneurial activities and an interactionist perspective on corporate entrepreneurship, this article examines the relationship between digital technology support and employee intrapreneurial behaviour. We propose that management support for innovation as an organisational characteristic and intrapreneurial self-efficacy as an individual characteristic moderate this relationship. Findings from a metric conjoint experiment with 1360 decisions nested within 85 employees showed that support by social media, support by collaborative technologies, and support by intelligent decision support systems were significant predictors of employee intrapreneurial behaviour. However, the relative impact of support by these digital technologies varied with different levels of management support for innovation and intrapreneurial self-efficacy.
Edit distances between merge trees of scalar fields have many applications in scientific visualization, such as ensemble analysis, feature tracking or symmetry detection. In this paper, we propose branch mappings, a novel approach to the construction of edit mappings for merge trees. Classic edit mappings match nodes or edges of two trees onto each other, and therefore have to either rely on branch decompositions of both trees or have to use auxiliary node properties to determine a matching. In contrast, branch mappings employ branch properties instead of node similarity information, and are independent of predetermined branch decompositions. Especially for topological features, which are typically based on branch properties, this allows a more intuitive distance measure which is also less susceptible to instabilities from small-scale perturbations. For trees with 𝒪(n) nodes, we describe an 𝒪(n4) algorithm for computing optimal branch mappings, which is faster than the only other branch decomposition-independent method in the literature by more than a linear factor. Furthermore, we compare the results of our method on synthetic and real-world examples to demonstrate its practicality and utility.
The direct regioselective C−H-functionalization of simple, unfunctionalized pyridines is considered a long-standing challenge in heterocyclic chemistry. Herein, we report a novel one-pot protocol for the C4-selective sulfonylation of pyridines via triflic anhydride (Tf2O) activation, base-mediated addition of a sulfinic acid salt, and subsequent elimination/re-aromatization. Contrary to previous approaches employing tailored blocking groups, positional selectivity can be controlled by using N-methylpiperidine as simple, readily available external base. This method offers a highly modular and streamlined access to C4-sulfonylated pyridines.
Janus-Materialien sind anisotrope Nano- und Mikroarchitekturen, die zwei verschiedene Seiten mit unterschiedlichen oder entgegengesetzten physikochemischen Eigenschaften aufweisen. Parallel zur Entwicklung neuer Methoden zur Herstellung dieser Materialien wurden entscheidende Fortschritte in Bezug auf Anwendungen erzielt, z. B. in der Biologie, der Katalyse, der Pharmazie und neuerdings auch in der Batterietechnologie. Dieser Kurzaufsatz stellt die jüngsten und wichtigsten Erfolge bei der Anwendung aufgabenspezifisch funktionalisierter Janus-Nanomaterialien im Bereich der heterogenen Katalyse für unterschiedliche chemische Transformationen vor. Er umfasst Reduktionreaktionen, oxidative Entschwefelung und Farbstoffabbau, asymmetrische Katalyse, Biomassetransformationen, Kaskadenreaktionen, Oxidationsreaktionen, übergangsmetallkatalysierte Kreuzkupplungsreaktionen, elektro- und photokatalytische Reaktionen sowie Gasphasenreaktionen. Zum Abschluss folgt ein Ausblick auf mögliche zukünftige Anwendungen.
Algorithms increasingly govern people's lives, including through rapidly spreading applications in the public sector. This paper sheds light on acceptance of algorithms used by the public sector emphasizing that algorithms, as parts of socio-technical systems, are always embedded in a specific social context. We show that citizens' acceptance of an algorithm is strongly shaped by how they evaluate aspects of this context, namely the personal importance of the specific problems an algorithm is supposed to help address and their trust in the organizations deploying the algorithm. The objective performance of presented algorithms affects acceptance much less in comparison. These findings are based on an original dataset from a survey covering two real-world applications, predictive policing and skin cancer prediction, with a sample of 2661 respondents from a representative German online panel. The results have important implications for the conditions under which citizens will accept algorithms in the public sector.
The development of algorithmic differentiation (AD) tools focuses mostly on handling floating point types in the target language. Taping optimizations in these tools mostly focus on specific operations like matrix vector products. Aggregated types like std::complex are usually handled by specifying the AD type as a template argument. This approach provides exact results, but prevents the use of expression templates. If AD tools are extended and specialized such that aggregated types can be added to the expression framework, then this will result in reduced memory utilization and improve the timing for applications where aggregated types such as complex number or matrix vector operations are used. Such an integration requires a reformulation of the stored data per expression and a rework of the tape evaluation process. We will demonstrate the overheads on a synthetic benchmark and show the improvement when aggregated types are handled properly by the expression framework of the AD tool.
A stereoselective synthesis of isoindolo[2,1-a]quinolin-11(5H)-ones containing three contiguous stereogenic centers is described. This Lewis-acid mediated reaction of enamides with N-aryl-acylimines affords the desired fused heterocyclic isoindolinones in high yields and diastereoselectivities. Scope and limitations of this method are discussed. The stereochemical outcome of this transformation indicates a stepwise reaction pathway.
The measurement of self-diffusion coefficients using pulsed-field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy is a well-established method. Recently, benchtop NMR spectrometers with gradient coils have also been used, which greatly simplify these measurements. However, a disadvantage of benchtop NMR spectrometers is the lower resolution of the acquired NMR signals compared to high-field NMR spectrometers, which requires sophisticated analysis methods. In this work, we use a recently developed quantum mechanical (QM) model-based approach for the estimation of self-diffusion coefficients from complex benchtop NMR data. With the knowledge of the species present in the mixture, signatures for each species are created and adjusted to the measured NMR signal. With this model-based approach, the self-diffusion coefficients of all species in the mixtures were estimated with a discrepancy of less than 2 % compared to self-diffusion coefficients estimated from high-field NMR data sets of the same mixtures. These results suggest benchtop NMR is a reliable tool for quantitative analysis of self-diffusion coefficients, even in complex mixtures.
We compute three-dimensional displacement vector fields to estimate the deformation of microstructural data sets in mechanical tests. For this, we extend the well-known optical flow by Brox et al. to three dimensions, with special focus on the discretization of nonlinear terms. We evaluate our method first by synthetically deforming foams and comparing against this ground truth and second with data sets of samples that underwent real mechanical tests. Our results are compared to those from state-of-the-art algorithms in materials science and medical image registration. By a thorough evaluation, we show that our proposed method is able to resolve the displacement best among all chosen comparison methods.
Coastal port-industrial areas are becoming increasingly significant due to urban shrinkage, population
decline, and climate change. To address social and economic issues and enhance climate resilience, it
is crucial to anticipate urban shrinkage in both stable and growing coastal areas that are undergoing
economic transformation. Urban planning can better understand the dynamics of planning for urban
shrinkage and climate resilience, as port-industrial areas have a large economic impact on nearby
coastal communities.
This dissertation examines the long-term implications of urban shrinkage in coastal port-industrial
areas in the context of climate change and sea level rise in England. The research problem is that
current urban policy does not adequately address the challenges of urban shrinkage and climate
resilience in these areas. The research questions are: What are the population changes in local areas
in England? What effect does population decline have on changing urbanisation patterns in older
industrial areas? What type of adaptation efforts were made in North East Lincolnshire, England, and
Bremerhaven, Germany, in response to the 2013 tidal surge, and how did this affect urban
shrinkage?
The dissertation applies an integrated concept of Shrinkage-Resilience as a framework for analysis.
The methodology includes a review of existing models and frameworks, as well as case studies of
international and local contexts. The findings suggest that between 2013-2019, 68% of older
industrial areas (including coastal ports) in England are undergoing changing urbanisation patterns
relative to population, land use, and green belt areas, and are key areas for urban policy, such as the
Levelling Up agenda. One of the areas, North East Lincolnshire is discussed and compared to
Bremerhaven. These examples demonstrate the link between Shrinkage-Resilience approaches and
their practical implementation in coastal port-industrial areas affected by urban shrinkage.
This research advances the scientific practice of urban planning and policy-making for shrinking cities
by introducing the approach of Shrinkage-Resilience, which emphasises the importance of
considering long-term social, economic, and environmental impacts in urban shrinkage contexts. This
approach is crucial in the transition to a more sustainable and inclusive society, where the welfare of
present and future generations, the environment, and economic development are taken into
account. The dissertation provides recommendations for urban planning to incorporate policy
changes for shrinking cities and coastal port-industrial areas worldwide, to include disaster risk
reduction and climate change adaptation approaches.
To increase situational awareness of the crane operator, the aim of this thesis is to develop a vision-based deep learning object detection from crane load-view using an adaptive perception in the construction area. Conventional worker detection methods are based on simple shape or color features from the worker's appearances. Nonetheless, these methods can fail to recognize the workers who do not wear the protective gears. To find out an image representation of the object from the top view manually or handcrafted feature is crucial. We, therefore, employed deep learning methods to automatically learn those features.
To yield optimal results, deep learning methods require mass amount of data.
Due to the data deficit especially in the construction domain, we developed the photorealistic world to create the data in addition to our samples collected from the real construction area. The simulated platform does not benefit only from diverse data types, but also concurrent research development which speeds up the pipeline at a low cost.
Our research findings indicate that the combination of synthetic and real training samples improved the state-of-the-art detector. In line with previous studies to bridge the gap between synthetic and real data, the results of preprocessed synthetic images are substantially better than using the raw data by approximately 10%.
Finding the right deep learning model for load-view detection is challenging.
By investigating our training data, it becomes evident that the majority of bounding box sizes are very small with a complex background.
In addition, we gave the priority to speed over accuracy based on the construction safety criteria. Finally, RetinaNet is chosen out of the three primary object detection models.
Nevertheless, the data-driven detection algorithm can fail to handle scale invariance, especially for detectors whose input size is changed in an extremely wide range.
The adaptive zoom feature can enhance the quality of the worker detection.
To avoid further data gathering and extensive retraining, the proposed automatic zoom method of the load-view crane camera supports the deep learning algorithm, specifically in the high scale variant problem. The finite state machine is employed for control strategies to adapt the zoom level to cope not only with inconsistent detection but also abrupt camera movement during lifting operation. Consequently, the detector is able to detect a small size object by smooth continuous zoom control without additional training.
The adaptive zoom control not only enhances the performance of the top-view object detection but also reduces the interaction of the crane operator with camera system, reducing the risk of fatality during load lifting operation.
We study the sensor fault estimation and accommodation problems in a data-driven \(\mathcal{H}_\infty\) setting, leading to a data-driven sensor fault-tolerant control scheme. First, we formulate the fault estimation problem as a finite-horizon minimax \(\mathcal{H}_\infty\)-optimization problem in a data-driven setup, whose solution yields the fault estimate. The estimated fault is then used for output compensation. This compensated output and the experimental input are used to achieve certain control objectives in a data-driven \(\mathcal{H}_\infty\) setting. Next, the data-driven \(\mathcal{H}_\infty\) fault estimation and control problems are solved using a subspace predictor-based approach. Finally, the proposed algorithm is applied to the steering subsystem of the remotely operated underwater vehicle.
Opposition parties under minority governments find themselves in a fundamental dilemma. They are competing with other parties, including the government, for electoral support while also having a common responsibility to make stable government work. This dilemma is especially pronounced for opposition parties signing support agreements with the government. While not formally in a coalition, they nonetheless publicly commit to supporting a government. They may thus be concerned about losing distinctiveness and have an interest in strategically timing cooperation with the minority government. The present paper tests whether this is the case using data on opposition party voting on committee proposals from 23 years of Swedish minority governments between 1991 and 2018. The findings indicate that support parties are less likely to support the government towards the beginning and end of the election cycle, that is, when public attention is intense – a pattern that is not observable for other opposition parties.
With direct laser writing micro structures can be manufactured by solidifying a photo resist when the laser beam triggers a photochemical reaction in the focal voxel. We have used direct laser writing to fabricate a thermally actuated microgripper, which can move its two cantilever like arms to grip micro-objects. One cantilever consists thereby of two strips with different coefficients of thermal expansion such that both cantilevers bends towards each other for an increasing temperature like a welded bimetal.This work investigates the impact of each cantilever's geometry on the gripping performance of the micro gripper theoretically. The tip deflection of the gripper is calculated by the analytical model of Timoshenko's theory of elasticity. After fabricaiton of the microgripper, its gripping performance is observed under the microscope while heated by a heating element.
The quality of risk reports: Integrating requirement levels of standard setters into text analysis
(2021)
The intention of this paper is to shed light on the analysis of financial disclosure through the integration of requirement levels. This in return will lead to the development of a general applicable evaluation methodology based on Bloom's taxonomy system. Therefore, it will be possible to explicitly consider the relevance of the given information. To underline the appropriateness of our method, we combine the requirement levels with a qualitative content analysis. Based on the German accounting standard DRS 20, we clarify the respective application of the requirement levels in the context of the qualitative content analysis. Hence, we will discuss the limitations of our developed approach. In addition, we analyze further areas of application in the context of qualitative analysis of financial disclosure. All things considered, it is evident that our chosen approach, through the integration of a taxonomy system, contributes to the validity of established text analyzing methods.
Firn describes the interstage product between snow and ice in cold regions of the earth, where annual snow fall exceeds the amount of snow melting. The continuing accumulation of snow leads to its densificiation due to overburden stress until it becomes ice. In the field of glaciology various attempts on simulating firn densification have been made and new models are still developed, as the knowledge of the firn column's density structure allows important derivations.
The presented study reassesses a model description for low density firn based on the process of grain boundary sliding presented by Alley in 1987 [1] using an optimisation approach. By comparing simulation results to 159 measured firn density profiles from Greenland and Antarctica it finds a possible additional dependency of the constitutive relation on the mean surface mass balance. This result is interpreted as an insufficient description of the stress regime.
Disorder and photonics have long been seen as natural adversaries and designers of optical systems have often driven systems to perfection by minimizing deviations from the ideal design. Especially in the field of photonic crystals and metamaterials but also for optical circuits, disorder has been avoided as a nuisance for many years. However, starting from the very robust structural colors found in nature, scientists learn to analyze and tailor disorder to achieve functionalities beyond what is possible with perfectly ordered or ideal systems alone. This review article covers theoretical and materials aspects of tailored disorder as well as experimental results. Furthermore selected examples are highlighted in greater detail, for which the intentional use of disorder adds additional functionality or provides novel functionality impossible without disorder.
A novel method for the synthesis of nitro fatty acids (NFAs), an intriguing class of endogenously occurring lipid mediators, is reported. This one-pot procedure enables the controlled and stereoselective construction of nitro fatty acids from a simple set of common building blocks in a highly facile manner. Thereby, this methodology offers a streamlined, highly modular access to naturally occurring nitro fatty acids as well as non-natural NFA derivatives.
Sulfones play a pivotal role in modern organic chemistry. They are highly versatile building blocks and find various applications as drugs, agrochemicals, or functional materials. Therefore, sustainable access to this class of molecules is of great interest. Herein, the goal was to provide a summary on recent developments in the field of sustainable sulfone synthesis. Advances and existing limitations in traditional approaches towards sulfones were reviewed on selected examples. Furthermore, novel emerging technologies for a more sustainable sulfone synthesis and future directions were discussed.
A concept for the quantification of cooperative effects in transition-metal complexes is presented. It is demonstrated for a series of novel N,N- (mononuclear) and C,N-coordinated homo- and heterometallic binuclear complexes based on the (2-dimethylamino)-4-(2-pyrimidinyl)pyrimidine ligand, which are accessible by applying roll-over cyclometallation. These iridium-, platinum-, and palladium-containing compounds are investigated with respect to their absorption and fluorescence spectra. The cooperative effects in the electronic absorptions, i. e., the energetic shifts between mononuclear and dinuclear complexes, and free ligands are analyzed on the basis of the lowest energy π-π* transitions and compared to calculated data, obtained from TD-DFT calculations. Furthermore the corresponding fluorescence spectra are presented and analyzed with respect to the concept of cooperativity.
Aquatic habitats are closely linked to the adjacent riparian area. Fluxes of nutrients, energy and matter through emerging aquatic insects are a key component of the aquatic subsidy to terrestrial systems. In fact, adult insects serve as high-quality prey for riparian predators. Stressors impacting the aquatic subsidy can thus translate to consequences for the receiving terrestrial food web, while mechanistic knowledge is extremely limited. Against this background, this thesis aimed at (i) assessing the impact of a model stressor specifically targeting insect emergence, that is the mosquito control agent Bacillus thuringiensis var. israelensis, on quantity, temporal dynamics and (ii) quality of emerging aquatic insects. For this purpose, outdoor floodplain pond mesocosms (n = 6) were employed. Since emergence is, in most cases, no point event but occurs over a longer period emergence was monitored over 3.5 months. The model stressor, i.e., Bti applied three times during spring at 2.88 × 10^9 ITU/ha, shifted the emergence time of aquatic insects, especially of non-biting midges (Diptera: Chironomidae), by ten days with a 26% reduced peak, while the nutrient content was not altered. On this basis, (ii) the propagation of the effects in aquatic subsidy emergence to riparian predators was investigated. Stable isotope analyses were used to assess the diet of a model predator, that is the web-building riparian spider Tetragnatha extensa. Results suggested changes in the composition of the spider’s diet to replace missing Chironomidae by other aquatic and terrestrial prey organisms pointing to further negative consequences. Finally, the thesis aimed at (iii) the understanding of processes underlying an altered emergence of aquatic subsidy mainly consisting of chironomids. Using a laboratory-based test design, populations of Chironomus riparius (n = 6) were assessed for their sensitivity towards Bti under different food qualities (high and low nutritious) before and after a long-term (six months) Bti exposure. Signs of phenotypic adaptation were observed in emergence time and nutrient content over multiple generations, resulting in changes in chironomids’ quantity and quality as food source. Overall, it can be concluded that direct and indirect effects of an aquatic stressor, as well as the adaptive response to it, can alter ecosystems at different levels, including individual, population and community level. Furthermore, this thesis highlights the importance of a temporal perspective when investigating the impact of aquatic stressors beyond ecosystem boundaries. It illustrates potential bottom-up effects on riparian predators through altered emergence of aquatic insects, feeding our understanding of meta-ecosystems and how stressors and their effects are transferred across systems. These insights will support efforts to protect and conserve natural ecosystems.
In nanobiotechnology, viral nanoparticles have come into focus as interesting nano building blocks. In this context, the formation of 2D and 3D structures is of particular interest. Herein, the creation of defined 2D patterns of an icosahedral plant virus, the tomato bushy stunt virus (TBSV), by means of different techniques is reported on: the top-down lithography ebeam and focused ion beam (FIB) as well as the bottom-up fluidic force microscope (FluidFM) approach. The obtained layer structures are imaged by scanning force and scanning electron microscopy. The data show that a defined 2D structure can successfully be created either top down by FIB or bottom up by FluidFM. Electron beam lithography is not able to remove viruses from the substrate under the chosen conditions. FIB has an advantage if larger areas covered with viruses combined with smaller areas without being desired. FluidFM is advantageous if only small areas with viruses are required. A further benefit is that the uncovered areas are not affected. The pattern formation in FluidFM is influenced not only by the spotting parameters, but in particular by the drying process. Deegan and Marangoni effects are shown to play a role if the spotted droplets are not very small.
A highly diastereoselective one-pot synthesis of the 1,3-diamino-2-alcohol unit bearing three continuous stereocenters is described. This method utilizes 2-oxyenamides as a novel type of building block for the rapid assembly of the 1,3-diamine scaffold containing an additional stereogenic oxygen functionality at the C2 position. A stereoselective preparation of the required (Z)-oxyenamides is reported as well.
In the present work, microfibrillar composites (MFCs) consisting of polypropylene (PP) and poly(ethylene terephthalate) (PET) were successfully produced by melt extrusion and cold stretching. The resulting filaments were then printed using fused filament fabrication. The morphological results demonstrate that the highly oriented PET fibrils after stretching are still well preserved in the printed components. Since the printing process defines the alignment of the fibrils in the final component the fibers can be perfectly adapted to the load paths. Comparative analyses of the mechanical properties reveal that the PET fibrils act as an effective reinforcement in the 3D printed components, resulting in the superior mechanical performance of the PP/PET MFCs compared to a PP/PET blend and a neat PP. Due to the combination of material and innovative processing, the study opens up a new way of using the morphology-based enormous potential of polymer fibers for lightweight, cost-effective and recyclable full polymer solutions in compact components.
Turbulence models, which are a means to fix the closure problem arising from Reynolds averaging of Navier-Stokes equations, are economical stop-gaps but suffer from accuracy issues. Modifying turbulence models by incorporating corrections in their functional form is one approach to improve their accuracy. We estimate correction functionals for the Spalart - Allmaras turbulence model, based on an inverse problem with PDE constraints emphasizing the issue of regularization.
Tribological systems are often characterized based on time-averaged quantities such as wear rates, friction coefficients and material properties. It is well known that some tribological metrics show variations depending on the laboratory conducting the study and the reproduction method selected. Perhaps the key to overcome this problem is to avoid a strong compression of the information generated. In this context, the arising forces and the coefficient of friction in three-body wear systems are investigated in more detail. The mean value of a time series of these physical quantities is only a single property and by no means an exhaustive description. A more detailed consideration of the variances could be a necessary condition to allow an appropriate comparison of tribological parameters and a correct interpretation of the properties of tribological systems. For this purpose, we examine two very simple tribological systems exemplarily and take a closer look at the properties of some characteristic process quantities.
Palladium-Catalyzed Decarboxylative 1,2-Addition of Carboxylic Acids to Glyoxylic Acid Esters
(2021)
The formation of C−C-bonds constitutes one of the most fundamental synthetic operations in organic chemistry. The nucleophilic addition of preformed organometallic reagents to an electrophilic carbonyl functionality represents a classical method for the selective construction of a C−C-bond. However, the synthesis and utilization of an organometallic reagent is associated with an unfavorable environmental profile. Herein, we disclose a Palladium-catalyzed decarboxylative 1,2-addition of carboxylic acids to glyoxylic acid esters. This novel method provides access to the mandelic acid scaffold in good yields. Easy-to-handle and readily available benzoic acids are utilized as more sustainable alternative to preformed organometallic nucleophiles.
Es wird eine hochgradig diastereoselektive Eintopf-Synthese der 1,3-Diamino-2-Alkohol-Einheit mit drei fortlaufenden Stereozentren beschrieben. Bei dieser Methode werden 2-Oxyenamide als neue Bausteine für den raschen Aufbau des 1,3-Diamin-Gerüsts, mit einer zusätzlichen stereogenen Sauerstofffunktionalität in C2-Position, eingesetzt. Zusätzlich wird über eine stereoselektive Synthese der erforderlichen (Z)-Oxyenamide berichtet.
Using the mixed-metal approach, a direct synthesis route at ambient pressure was developed for a new type of bimetallic metal-organic framework based on the CPO-27 structure. The structural characterization of CPO-27(Cu0.6−CS−Co0.4) using X-ray diffraction, transmission electron microscopy, energy-dispersive X-ray mapping and X-ray absorption spectroscopy revealed that the Cu2+ and Co2+ ions were exclusively incorporated at the metal positions of the CPO-27 lattice, but with a core-shell distribution within the crystallites. The parent framework material was then utilized as a precursor for the generation of novel bimetallic carbon-supported materials using the controlled thermal decomposition in a reducing atmosphere. During this decomposition process, the distribution of the two metals remained the same, which resulted in unique needle-shaped particles with a high dispersion of cobalt at the periphery of the amorphous carbon and agglomerated copper particles in the inside.
Weyl points are point degeneracies that occur in momentum space of 3D periodic materials and are associated with a quantized topological charge. Here, the splitting of a quadratic (charge-2) Weyl point into two linear (charge-1) Weyl points in a 3D micro-printed photonic crystal is observed experimentally via Fourier-transform infrared spectroscopy. Using a theoretical analysis rooted in symmetry arguments, it is shown that this splitting occurs along high-symmetry directions in the Brillouin zone. This micro-scale observation and control of Weyl points is important for realizing robust topological devices in the near-infrared.
Based on experimental pure component data for the characterization of the isostructural imidazolate framework Potsdam (IFP) series reported in Part I, a model for the simulation of non-isothermal dynamic adsorption of CO2/CH4-mixtures in fixed-bed columns is presented in this Part II. The robustness of the model is examined and validated, by comparison to experimental breakthrough data at different process conditions, such as varying concentration, temperature, and pressure. Thereby, different predictive methods for the estimation of adsorption equilibria of mixtures are compared (RAST, IAST, ML). The results show that ideal behaviour can be assumed with good accuracy for the system under consideration, except for IFP-2, which shows significant deviations at increased pressures and temperatures. A detailed kinetic analysis reveals that mass transfer is significantly influenced by micropore diffusion. Thus, only for IFP-1 the dynamic separation of CO2 and CH4 is equilibrium-driven, while for the remaining IFPs the kinetic regime dominates the process, which in some cases increases the separation efficiency (IFP-2 to -7) but can also inhibit it (IFP-8). The determined intracrystalline diffusion coefficients show very good agreement with values for metal organic framework (MOF) compounds of similar structure reported in the literature.
It is known from the literature that freedom from macroscopic defects (voids) is an essential prerequisite for good mechanical properties of 3D-printed components manufactured using fused filament fabrication. The present study further shows that the morphology and mechanical properties of void free components are significantly influenced by the choice of process parameters. Components that were printed at low temperatures and high speeds show fair and inhomogeneous supermolecular morphology, clearly visible weld seams and a special flow-induced staggered structure of the individual strands laid-up. At higher magnification in the optical microscope, transcrystalline structures are visible starting from the contact area between the strands, that is, crystallization has started at the interface between the strands and is moving forward towards the center of the strands. In contrast, the samples printed at high temperatures and low speeds show a homogeneous supermolecular morphology with overall larger spherulites and a higher degree of crystallinity and compared to the specimens printed with the low temperature/high speed-set much better mechanical properties. A numerical simulation of the temperature at the contact point of the strand emerging from the hot nozzle and the cooled strand neighbor agrees well with the measured behavior. The thermal simulation thus enables the temperature to be calculated at any point in time in the welding contact and thus access to the local thermal conditions during joining, cooling and the formation of the morphology.
[Halb]- trocken im Unterstockbereich?
„Untersuchungen meteorologisch-hydrologischer Messgrößen im Weinbau als Anpassungsstrategie an den Klimawandel sowie für eine nachhaltige Wassernutzung von Vitis vinifera [cv. Riesling]. “
Christian Ihrig & Sascha Henninger
RPTU Kaiserslautern
Der vom Menschen verursachte Klimawandel beeinflusst sowohl langfristige Klimaprozesse, als auch das aktuelle, kurzfristige Wettergeschehen in allen Regionen der Erde. Er äußert sich in einer Vielzahl an Phänomenen, die sich je nach Klimagebiet unterschiedlich manifestieren lassen oder auch unterschiedliche Auswirkungen mit sich bringen. Diese Forschungsarbeit beschäftigt sich mit dem Wasserhaushalt von Weinreben im Rahmen des rezenten Klimawandels. Ziel dieses Projektes ist es, mittels meteorologisch-hydrologischen Messgrößen eine Anpassungsstrategie zu generieren, die auf alle Weinbauregionen in Rheinland-Pfalz übertragen werden kann, um Winzer*innen die Möglichkeit zu eröffnen, auf natürlicher Art und Weise der Rebe Wasser zugänglich zu machen.
Durch die Zunahme abiotischer Schäden (z.B. Niederschlag) und die Veränderung der Vegetationszeit sowie die Zunahme invasiver Schaderreger ist vermehrt eine Steigerung der Vulnerabilität des Ökosystems „Wingert“ zu erkennen. Winzer*innen werden aufgrund der Zunahme von Extremwetterereignissen (Hitze-/Dürrephasen) zur langfristigen Bewässerung ihrer Weinbauflächen gezwungen. Große Mengen Wasser werden bereits vereinzelt in Weinbergsregionen gepumpt, was langfristig hinsichtlich eines sinkenden Grundwasserspiegels einen fatalen Fehler darstellt. Die ressourcenschonende Gestaltung des Wasserhaushaltes sollte daher in den Mittelpunkt der Weinbauforschung gestellt werden. Weinbauer*innen sind an regional-/ lokalklimatischen Lösungsmöglichkeiten und Anpassungsstrategien interessiert, um Risiken für die Anbaufrucht reduzieren und auf die lokalklimatischen Auswirkungen des Klimawandels reagieren zu können. Um gegen dieses Risiko anzugehen und den Produktionsausfall zu minimieren, muss die Anpassungsfähigkeit in Sachen Wasserhaushalt der Reben bekräftigt werden. Demzufolge wird das Mikroklima in der Weinbauregion Rheinhessen mittels des Einsatzes der Scholander-Druckkammer untersucht. Die Bestimmung des Wasserstatus hinsichtlich der exakten Bewässerungssteuerung von Weinreben hat sich durch das frühmorgendliche Blattwasser- (Ψpd) und mittägliche Stammwasserpotential (Ψstem) bewährt. Physiologische Prozesse, wie die stomatäre Leitfähigkeit der Blattschließzellen sowie das vegetative Wachstum, aber auch die Photosynthese, sind direkt oder indirekt an Ψpd + Ψstem gekoppelt. Darüber hinaus lässt sich der Wasserhaushalt durch ein an Trockenstandorten angepasstes Bodenpflegesystem, wie zum Beispiel einer flächendeckenden Bodenabdeckung mittels Holzhäcksel, deutlich verbessern. Des Weiteren wird das Mikroklima im Weinberg durch die Laubwandstruktur mitbestimmt, was durch eine gesteigerte Photosyntheseleistung der Laubwand, eine optimale Belüftung und Belichtung gewährleistet wird. Im praktischen Weinbau wird dies durch die Höhe der Laubwand realisiert. Um dem Herbizid im Unterstockraum durch das anstehende Glyphosatverbot eine Alternative zu bieten, entwickelt die Landmaschinenbranche bereits heute alternative Arbeitsgeräte, die eine Möglichkeit darstellen, dem Wuchs des Unkrautes im Unterstockbereich entgegenzuwirken.
Daher ist es von gesteigertem Interesse zu analysieren, inwiefern sich eine Bodenabdeckung im Unterstockbereich von einer flächendeckenden bzw. moderaten Tropfbewässerung in Flachlage unterscheidet. Darüber hinaus sollen Möglichkeiten zur Reduzierung des Wasserverbrauchs und zur Reifeverzögerung (Verminderung des Botrytisbefalls, Verlängerung der Reifedauer, Vermeidung eines zu hohen Alkoholgehaltes) durch eine kürzere Laubwandhöhe beim Riesling in Flachlage in diesem Projekt erprobt werden. Als Versuchsvarianten dienen vier Variationen, um abgrenzbare und eindeutige Ergebnisse erzielen zu können (V1: Tropfbewässerung; V2: Unterstockabdeckung Holzhäcksel; V3: Flächendeckende Holzhäcksel; V4: Kontrollvariante).
Lattice Boltzmann methods [1] have been extended beyond their initial usage in transport problems, and can be used to solve a broader range of partial differential equations, e.g. the wave equation [2]. Thereby they can be utilized for fracture mechanics [3]. In the context of antiplane shear deformation we previously examined a stationary crack [4, 5] with a finite width. In this work we present two implementation strategies for non-mesh conforming boundary conditions, for which the bounding geometry does not need to adhere to the underlying lattice. This rectifies problems in modeling the crack. A numerical example shows the improvement compared to the previous results.
The influence of the specimen size of ultra-high-performance fibre-reinforced concrete samples on the spatial distribution and orientation of the steel fibres is investigated. Specimens of varying size are produced by using the same protocol. They are imaged by micro-computed tomography to perform a statistical analysis of the spatial arrangement of the fibres. The tensile strength of the specimens is measured by tensile tests on subspecimens of equal size. The results are correlated to geometric characteristics of the fibre systems determined from the image data. Increasing the specimen size results in a larger variability of the local fibre geometry. This effect was most prominent when increasing the height of the specimens.
The formation of protein aggregates is a hallmark of neurodegenerative diseases. Observations on patient samples and model systems demonstrated links between aggregate formation and declining mitochondrial functionality, but causalities remain unclear. We used Saccharomyces cerevisiae to analyze how mitochondrial processes regulate the behavior of aggregation‐prone polyQ protein derived from human huntingtin. Expression of Q97‐GFP rapidly led to insoluble cytosolic aggregates and cell death. Although aggregation impaired mitochondrial respiration only slightly, it considerably interfered with the import of mitochondrial precursor proteins. Mutants in the import component Mia40 were hypersensitive to Q97‐GFP, whereas Mia40 overexpression strongly suppressed the formation of toxic Q97‐GFP aggregates both in yeast and in human cells. Based on these observations, we propose that the post‐translational import of mitochondrial precursor proteins into mitochondria competes with aggregation‐prone cytosolic proteins for chaperones and proteasome capacity. Mia40 regulates this competition as it has a rate‐limiting role in mitochondrial protein import. Therefore, Mia40 is a dynamic regulator in mitochondrial biogenesis that can be exploited to stabilize cytosolic proteostasis.
As additive manufacturing offers only low surface quality, a subsequent machining of functional and highly loaded areas is required. Thus, a sound knowledge of the interrelation between the additive and subtractive manufacturing process as well as the resulting mechanical properties is indispensable. In this work, specimens were manufactured by using laser-based powder bed fusion (L-PBF) with substantially different sets of process parameters as well as subsequent grinding (G) or milling (M). Despite the substantially different surface topographies, the fatigue tests revealed only a slight influence of the subtractive manufacturing on the fatigue behavior, whereas the different laser-based powder bed fusion process parameters led to pronounced changes in fatigue strength. In contrast, a significant influence of subtractive finishing on the fatigue properties of the defect-free continuously cast (CC) reference specimens was observed. This can be explained by a dominating influence of process-induced defects in laser-based powder bed fusion material, which overruled the influence of surface machining. However, although both laser-based powder bed fusion parameter sets resulted in substantial defects, one set yielded similar fatigue strength compared to continuously cast specimens.
We show that every convergent power series with monomial extended Jacobian ideal is right equivalent to a Thom–Sebastiani polynomial. This solves a problem posed by Hauser and Schicho. On the combinatorial side, we introduce a notion of Jacobian semigroup ideal involving a transversal matroid. For any such ideal, we construct a defining Thom–Sebastiani polynomial. On the analytic side, we show that power series with a quasihomogeneous extended Jacobian ideal are strongly Euler homogeneous. Due to a Mather–Yau-type theorem, such power series are determined by their Jacobian ideal up to right equivalence.
An FEM-based physical force model is an important step to obtain a full understanding of the grinding process itself. Such a physical force model is already under development and is based on Abaqus-FEM. In order to examine basic material behavior and material parameters for such a physical force model and to validate it, scratch tests have been carried out with single grains. However, the current physical force model is only designed for grinding processes that do not require cooling lubricants. Therefore, the aim of this work is to extend this physical force model in such a way that grinding processes with cooling lubricants can also be considered. In order to include the cooling lubricants in the FEM model, it is essential to carry out scratch tests with cooling lubricants in addition to the scratch tests in a dry environment. The aim is to identify basic mechanisms in connection with cooling lubricants, which are needed to expand the FEM model and to create a data basis for subsequent validation.
Computational-Fluid-Dynamics (CFD)-Simulationen in Kombination mit Tropfenpopulationsbilanzen führen zu einem praxisgerechten Standard, um auf Basis verfügbarer Prozessdaten den Strömungsverlauf – und damit die Verweilzeitverteilung – in liegenden Abscheidern beliebiger Größe zu berechnen. Durch Implementierung des Tropfenverhaltens wird auch die Berechnung eines tropfenspezifischen Abscheider-Wirkungsgrades ermöglicht. Die Methodenentwicklung erfolgte mit baugleichen Anlagen an drei verschiedenen Standorten. Die darauf beruhenden CFD-Simulationen wurden erfolgreich mit experimentellen Daten der beteiligten Industriepartner validiert.
The German energy mix, which provides an overview of the sources of electricity available in Germany, is changing as a result of the expansion of renewable energy sources. With this shift towards sustainable energy sources such as wind and solar power, the electricity market situation is also in flux. Whereas in the past there were few uncertainties in electricity generation and only demand was subject to stochastic uncertainties, generation is now subject to stochastic fluctuations as well, especially due to weather dependency. To provide a supportive framework for this different situation, the electricity market has introduced, among other things, the intraday market, products with half-hourly and quarter-hourly time slices, and a modified balancing energy market design. As a result, both electricity price forecasting and optimization issues remain topical.
In this thesis, we first address intraday market modeling and intraday index forecasting. To do so, we move to the level of individual bids in the intraday market and use them to model the limit order books of intraday products. Based on statistics of the modeled limit order books, we present a novel estimator for the intraday indices. Especially for less liquid products, the order book statistics contain relevant information that allows for significantly more accurate predictions in comparison to the benchmark estimator.
Unlike the intraday market, the day ahead market allows smaller companies without their own trading department to participate since it is operated as a market with daily auctions. We optimize the flexibility offer of such a small company in the day ahead market and model the prices with a stochastic multi-factor model already used in the industry. To make this model accessible for stochastic optimization, we discretize it in time and space using scenario trees. Here we present existing algorithms for scenario tree generation as well as our own extensions and adaptations. These are based on the nested distance, which measures the distance between two distributions of stochastic processes. Based on the resulting scenario trees, we apply the stochastic optimization methods of stochastic programming, dynamic programming, and reinforcement learning to illustrate in which context the methods are appropriate.
Diafiltration of Highly Concentrated Suspensions with Fine Particles by Dynamic Disk Filtration
(2021)
A method for washing highly concentrated suspensions with fine particles by using a filter with overlapping disks was studied. For the experiments, alumina and titanium dioxide suspensions were used. It was demonstrated that the used suspensions have non-Newtonian behavior. The viscosity is influenced by the type of particle system, the solid concentration, and the shear rate. The washing process is operated in a discontinuous and a continuous way. The rotation of the disks and the shear flow across their surface prevents the formation of a filter cake and facilitates the handling of suspensions. The shear stresses at the filter disk and the rheology of the processed suspensions are both influenced by the type of particle system, the solid concentration, and the process parameters.
In the present study, tribological properties of PEEK/CF/nanosilica composites with distinct amounts of silica nanoparticles against steel were studied by using a block-on-ring tribometer followed by the characterizations of associated transfer films and polymer worn surfaces. The results demonstrate that the content of silica nanoparticles exerts an obvious influence on the friction and wear properties of PEEK/CF/nanosilica composites. Under low-load conditions, the friction coefficient and specific wear rate exhibit opposite dependence on the nanosilica content. The friction coefficient decreases with increasing nanofiller content, while the specific wear rate increases with enhancing nanosilica loading. When the load conditions were changed toward high values, the divergence of the tribological properties becomes insignificant, which show less dependence on the nanosilica loading. Taking into account the practical applications of such composites, the composite containing 2 wt.% silica nanoparticles can serve as an excellent candidate for manufacturing tribological components in the practical applications.
Design improvement by a simulative investigation of the locomotion of a snake-like soft robot
(2021)
This work aims to improve the design of a snake-like soft robot in terms of its velocity of locomotion by a geometric model. Therefore, we determine the locomotion of the snake-like soft robot as the result of a given excitation curvature and a given friction anisotropy between the robot and the ground.Varying the design parameters of the robot in the model allows to identify important parameters to increase the velocity of locomotion of the snake-like soft robot. Whereas its body design is sufficient, the transverse friction of its artificial skin is the main parameter to be improved. The transverse friction can be adjusted by turning the scales of the artificial skin. The velocity of locomotion of the robot increases significantly by this simple trick.