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- West Africa (5)
- lignin (5)
- Crystallinity (3)
- Extrusion blow molding (3)
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- Lattice Boltzmann Method (3)
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Several species of (poly)saccharides and organic acids can be found often simultaneously in various biological matrices, e.g., fruits, plant materials, and biological fluids. The analysis of such matrices sometimes represents a challenging task. Using Aloe vera (A. vera) plant materials as an example, the performance of several spectroscopic methods (80 MHz benchtop NMR, NIR, ATR-FTIR and UV-Vis) for the simultaneous analysis of quality parameters of this plant material was compared. The determined parameters include (poly)saccharides such as aloverose, fructose and glucose as well as organic acids (malic, lactic, citric, isocitric, acetic, fumaric, benzoic and sorbic acids). 500 MHz NMR and high-performance liquid chromatography (HPLC) were used as the reference methods.
UV-VIS data can be used only for identification of added preservatives (benzoic and sorbic acids) and drying agent (maltodextrin) and semiquantitative analysis of malic acid. NIR and MIR spectroscopies combined with multivariate regression can deliver more informative overview of A. vera extracts being able to additionally quantify glucose, aloverose, citric, isocitric, malic, lactic acids and fructose. Low-field NMR measurements can be used for the quantification of aloverose, glucose, malic, lactic, acetic, and benzoic acids. The benchtop NMR method was successfully validated in terms of robustness, stability, precision, reproducibility and limit of detection (LOD) and quantification (LOQ), respectively.
All spectroscopic techniques are useful for the screening of (poly)saccharides and organic acids in plant extracts and should be applied according to its availability as well as information and confidence required for the specific analytical goal. Benchtop NMR spectroscopy seems to be the most feasible solution for quality control of A. vera products.
Der Nutzen von Prozessmanagement für die Effizienz und Effektivität der Organisation von Unternehmen ist vielfach bestätigt. Eine Studie der gfo-Gesellschaft für Organisation stellt fest, dass der Umsetzungsgrad der Prozessorganisation in Unternehmen dennoch mangelhaft ist. Es fehlt die Unterstützung der Leitung, die selbst noch überwiegend funktional organisiert ist.
Battery lifespan estimation is essential for effective battery management systems, aiding users and manufacturers in strategic planning. However, accurately estimating battery capacity is complex, owing to diverse capacity fading phenomena tied to factors such as temperature, charge-discharge rate, and rest period duration. In this work, we present an innovative approach that integrates real-world driving behaviors into cyclic testing. Unlike conventional methods that lack rest periods and involve fixed charge-discharge rates, our approach involves 1000 unique test cycles tailored to specific objectives and applications, capturing the nuanced effects of temperature, charge-discharge rate, and rest duration on capacity fading. This yields comprehensive insights into cell-level battery degradation, unveiling growth patterns of the solid electrolyte interface (SEI) layer and lithium plating, influenced by cyclic test parameters. The results yield critical empirical relations for evaluating capacity fading under specific testing conditions.
The actomyosin system generates mechanical work with the execution of the power stroke, an ATP-driven, two-step rotational swing of the myosin-neck that occurs post ATP hydrolysis during the transition from weakly to strongly actin-bound myosin states concomitant with Pi release and prior to ADP dissociation. The activating role of actin on product release and force generation is well documented; however, the communication paths associated with weak-to-strong transitions are poorly characterized. With the aid of mutant analyses based on kinetic investigations and simulations, we identified the W-helix as an important hub coupling the structural changes of switch elements during ATP hydrolysis to temporally controlled interactions with actin that are passed to the central transducer and converter. Disturbing the W-helix/transducer pathway increased actin-activated ATP turnover and reduced motor performance as a consequence of prolonged duration of the strongly actin-attached states. Actin-triggered Pi release was accelerated, while ADP release considerably decelerated, both limiting maximum ATPase, thus transforming myosin-2 into a high-duty-ratio motor. This kinetic signature of the mutant allowed us to define the fractional occupancies of intermediate states during the ATPase cycle providing evidence that myosin populates a cleft-closure state of strong actin interaction during the weak-to-strong transition with bound hydrolysis products before accomplishing the power stroke.
Polyurethane (PU) coatings were successfully produced using unmodified kraft lignin (KL) as an environmentally benign component in contents of up to 80 wt%. Lignin samples were precipitated from industrial black liquor in aqueous solution working at room temperature and different pH levels (pH 2 to pH 5). Lignins were characterized by UV-Vis, FTIR, pyrolysis-GC/MS, SEC and 31P-NMR. Results show a correlation between pH level, OH number and molecular weight Mw of isolated lignins. Lignin-based polyurethane coatings were prepared in an efficient one step synthesis dissolving lignin in THF and PEG425 in an ultrasonic bath followed by addition of 4,4-diphenylmethanediisocyanate (MDI) and triethylamine (TEA). Crosslinking was achieved under very mild conditions (1 hour at room temperature followed by 3 hours at 35 °C). The resulting coatings were characterized regarding their physical properties including ATR-IR, TGA, optical contact angle, light microscopy, REM-EDX and AFM data. Transparent homogeneous films of high flexibility resulted from lignins isolated at pH 4, possessing a temperature resistance up to 160 °C. Swelling tests revealed a resistance against water. Swelling in DMSO depends on index, pH of precipitation and catalyst utilization for PU preparation. According to AFM studies, surface roughness is between 10 and 28 nm.
The development of metals tailored to the metallurgical conditions of laser-based additive manufacturing is crucial to advance the maturity of these materials for their use in structural applications. While efforts in this regard are being carried out around the globe, the use of high strength eutectic alloys have, so far, received minor attention, although previous works showed that rapid solidification techniques can result in ultrafine microstructures with excellent mechanical performance, albeit for small sample sizes. In the present work, a eutectic Ti-32.5Fe alloy has been produced by laser powder bed fusion aiming at exploiting rapid solidification and the capability to produce bulk ultrafine microstructures provided by this processing technique.
Process energy densities between 160 J/mm³ and 180 J/mm³ resulted in a dense and crack-free material with an oxygen content of ~ 0.45 wt.% in which a hierarchical microstructure is formed by µm-sized η-Ti4Fe2Ox dendrites embedded in an ultrafine eutectic β-Ti/TiFe matrix. The microstructure was studied three-dimensionally using near-field synchrotron ptychographic X-ray computed tomography with an actual spatial resolution down to 39 nm to analyse the morphology of the eutectic and dendritic structures as well as to quantify their mass density, size and distribution. Inter-lamellar spacings down to ~ 30–50 nm were achieved, revealing the potential of laser-based additive manufacturing to generate microstructures smaller than those obtained by classical rapid solidification techniques for bulk materials. The alloy was deformed at 600 °C under compressive loading up to a strain of ~ 30% without damage formation, resulting in a compressive yield stress of ~ 800 MPa.
This study provides a first demonstration of the feasibility to produce eutectic Ti-Fe alloys with ultrafine microstructures by laser powder bed fusion that are suitable for structural applications at elevated temperature.
Ultra-fast photopolymerization of experimental composites: DEA and FT-NIRS measurement comparison
(2015)
Trueness and precision of milled and 3D printed root-analogue implants: A comparative in vitro study
(2023)
Microarray-based experiments revealed that thyroid hormone triiodothyronine (T3) enhanced the binding of Cy5-labeled ATP on heat shock protein 90 (Hsp90). By molecular docking experiments with T3 on Hsp90, we identified a T3 binding site (TBS) near the ATP binding site on Hsp90. A synthetic peptide encoding HHHHHHRIKEIVKKHSQFIGYPITLFVEKE derived from the TBS on Hsp90 showed, in MST experiments, the binding of T3 at an EC50 of 50 μM. The binding motif can influence the activity of Hsp90 by hindering ATP accessibility or the release of ADP.
Airborne and spaceborne platforms are the primary data sources for large-scale forest mapping, but visual interpretation for individual species determination is labor-intensive. Hence, various studies focusing on forests have investigated the benefits of multiple sensors for automated tree species classification. However, transferable deep learning approaches for large-scale applications are still lacking. This gap motivated us to create a novel dataset for tree species classification in central Europe based on multi-sensor data from aerial, Sentinel-1 and Sentinel-2 imagery. In this paper, we introduce the TreeSatAI Benchmark Archive, which contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony, Germany. We propose models and guidelines for the application of the latest machine learning techniques for the task of tree species classification with multi-label data. Finally, we provide various benchmark experiments showcasing the information which can be derived from the different sensors including artificial neural networks and tree-based machine learning methods. We found that residual neural networks (ResNet) perform sufficiently well with weighted precision scores up to 79 % only by using the RGB bands of aerial imagery. This result indicates that the spatial content present within the 0.2 m resolution data is very informative for tree species classification. With the incorporation of Sentinel-1 and Sentinel-2 imagery, performance improved marginally. However, the sole use of Sentinel-2 still allows for weighted precision scores of up to 74 % using either multi-layer perceptron (MLP) or Light Gradient Boosting Machine (LightGBM) models. Since the dataset is derived from real-world reference data, it contains high class imbalances. We found that this dataset attribute negatively affects the models' performances for many of the underrepresented classes (i.e., scarce tree species). However, the class-wise precision of the best-performing late fusion model still reached values ranging from 54 % (Acer) to 88 % (Pinus). Based on our results, we conclude that deep learning techniques using aerial imagery could considerably support forestry administration in the provision of large-scale tree species maps at a very high resolution to plan for challenges driven by global environmental change. The original dataset used in this paper is shared via Zenodo (https://doi.org/10.5281/zenodo.6598390, Schulz et al., 2022). For citation of the dataset, we refer to this article.
Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies
(2018)
In addition to the long-term goal of mitigating climate change, the current geopolitical upheavals heighten the urgency to transform Europe's energy system. This involves expanding renewable energies while managing intermittent electricity generation. Hydrogen is a promising solution to balance generation and demand, simultaneously decarbonizing complex applications. To model the energy system's transformation, the project TransHyDE-Sys, funded by the German Federal Ministry of Education and Research, takes an integrated approach beyond traditional energy system analysis, incorporating a diverse range of more detailed methods and tools. Herein, TransHyDE-Sys is situated within the recent policy discussion. It addresses the requirements for energy system modeling to gain insights into transforming the European hydrogen and energy infrastructure. It identifies knowledge gaps in the existing literature on hydrogen infrastructure-oriented energy system modeling and presents the research approach of TransHyDE-Sys. TransHyDE-Sys analyzes the development of hydrogen and energy infrastructures from “the system” and “the stakeholder” perspectives. The integrated modeling landscape captures temporal and spatial interactions among hydrogen, electricity, and natural gas infrastructure, providing comprehensive insights for systemic infrastructure planning. This allows a more accurate representation of the energy system's dynamics and aids in decision-making for achieving sustainable and efficient hydrogen network development integration.
The general method of topological reduction for the network problems is presented on example of gas transport networks. The method is based on a contraction of series, parallel and tree-like subgraphs for the element equations of quadratic, power law and general monotone dependencies. The method allows to reduce significantly the complexity of the graph and to accelerate the solution procedure for stationary network problems. The method has been tested on a large set of realistic network scenarios. Possible extensions of the method have been described, including triangulated element equations, continuation of the equations at infinity, providing uniqueness of solution, a choice of Newtonian stabilizer for nearly degenerated systems. The method is applicable for various sectors in the field of energetics, including gas networks, water networks, electric networks, as well as for coupling of different sectors.
This study investigates the effects of four multifunctional chain-extending cross-linkers (CECL) on the processability, mechanical performance, and structure of polybutylene adipate terephthalate (PBAT) and polylactic acid (PLA) blends produced using film blowing technology. The newly developed reference compound (M·VERA® B5029) and the CECL modified blends are characterized with respect to the initial properties and the corresponding properties after aging at 50 °C for 1 and 2 months. The tensile strength, seal strength, and melt volume rate (MVR) are markedly changed after thermal aging, whereas the storage modulus, elongation at the break, and tear resistance remain constant. The degradation of the polymer chains and crosslinking with increased and decreased MVR, respectively, is examined thoroughly with differential scanning calorimetry (DSC), with the results indicating that the CECL-modified blends do not generally endure thermo-oxidation over time. Further, DSC measurements of 25 µm and 100 µm films reveal that film blowing pronouncedly changes the structures of the compounds. These findings are also confirmed by dynamic mechanical analysis, with the conclusion that tris(2,4-di-tert-butylphenyl)phosphite barely affects the glass transition temperature, while with the other changes in CECL are seen. Cross-linking is found for aromatic polycarbodiimide and poly(4,4-dicyclohexylmethanecarbodiimide) CECL after melting of granules and films, although overall the most synergetic effect of the CECL is shown by 1,3-phenylenebisoxazoline.
Pollution with anthropogenic waste, particularly persistent plastic, has now reached every remote corner of the world. The French Atlantic coast, given its extensive coastline, is particularly affected. To gain an overview of current plastic pollution, this study examined a stretch of 250 km along the Silver Coast of France. Sampling was conducted at a total of 14 beach sections, each with five sampling sites in a transect. At each collection site, a square of 0.25 m2 was marked. The top 5 cm of beach sediment was collected and sieved on-site using an analysis sieve (mesh size 1 mm), resulting in a total of approximately 0.8 m3 of sediment, corresponding to a total weight of 1300 kg of examined beach sediment. A total of 1972 plastic particles were extracted and analysed using infrared spectroscopy, corresponding to 1.5 particles kg−1 of beach sediment. Pellets (885 particles), polyethylene as the polymer type (1349 particles), and particles in the size range of microplastics (943 particles) were most frequently found. The significant pollution by pellets suggests that the spread of plastic waste is not primarily attributable to tourism (in February/March 2023). The substantial accumulation of meso- and macro-waste (with 863 and 166 particles) also indicates that research focusing on microplastics should be expanded to include these size categories, as microplastics can develop from them over time.
Die allgemeine Konnotation von Technik mit Männlichkeit hat Auswirkungen auf die Berufswahlentscheidungen und das Technikverständnis von jungen Frauen. Nur gut 22 Prozent aller Studierenden in den Ingenieurswissenschaften waren 2014 in Deutschland weiblich (vgl. MonitorING)1. Seit Jahren wird versucht, diese Zahlen nach oben zu korrigieren, indem man Programme für Mädchen und junge Frauen anbietet, die erste Kontakte zu technischen Arbeitsfeldern her stellen. Auch für bereits berufstätige Ingenieurinnen gibt es zahlreiche Förderprogramme, um den Drop-out hochqualiizierter Frauen auf der Karriere leiter zu verhindern. Dennoch verändern sich die prozentualen Anteile von Frauen in ingenieurswissenschaftlichen Studiengängen und Berufen kaum. Aktuelle Studien belegen, dass vor allem kulturell bedingte Erwartungen und Einstellungen hierfür verantwortlich sind (vgl. Paulitz 2012).
Background: To protect renewable packaging materials against autoxidation and decomposition when substituting harmful synthetic stabilizers with bioactive and bio-based compounds, extracts from Aesculus hippocastanum L. seeds were evaluated. The study objectives were to determine the antioxidant efficacy of bioactive compounds in horse chestnut seeds with regard to different seed fractions, improve their extraction, and to evaluate waste reuse. Methods: Different extraction techniques for field samples were evaluated and compared with extracts of industrial waste samples based on total phenolic content and total antioxidant capacity (2,2’-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS)). The molecular weight distribution and absorbance in ultraviolet range (UV) of seed coat extracts were determined, and the possibility of extracts containing proanthocyanidins was examined. Results: Seed coat extracts show a remarkable antioxidant activity and a high UV absorbance. Passive extractions are efficient and much less laborious. Applying waste product seed coats leads to a reduced antioxidant activity, total phenolic content, and UV absorbance compared to the field sample counterparts. In contrast to peeled seed extracts, all seed coat extracts contain proanthocyanidins. Discussion: Seed coats are a potential source of bioactive compounds, particularly regarding sustainable production and waste reuse. With minimum effort, highly bioactive extracts with high potential as additives can be prepared.
This paper investigates the effect of voltage sensors on the measurement of transient voltages for power semiconductors in a Double Pulse Test (DPT) environment.We adapt previously published models that were developed for current sensors and apply them to voltage sensors to evaluate their suitability for DPT applications. Similarities and differences between transient current and voltage sensors are investigated and the resulting methodology is applied to commercially available and experimental voltage sensors. Finally, a selection aid for given measurement tasks is derived that focuses on the measurement of fast-switching power semiconductors.
Suitability of Current Sensors for the Measurement of Switching Currents in Power Semiconductors
(2021)
This paper investigates the impact of current sensors on the measurement of transient currents in fast-switching power semiconductors in a double pulse test (DPT environment. We review previous research that assesses the influence of current sensors on a DPT circuit through mathematical modeling. The developed selection aids can be used to identify suitable current sensors for transient current measurements of fast-switching power semiconductors and to estimate the error introduced by their insertion into the DPT circuit. Afterwards, this analysis is extended by including further elements from real DPT applications to increase the consistency of the error estimation with practical situations and setups. Both methods are compared and their individual advantages and drawbacks are discussed. Finally, a recommendation on when to use which method is derived.
The motor protein myosin drives a wide range of cellular and muscular functions by generating directed movement and force, fueled through adenosine triphosphate (ATP) hydrolysis. Release of the hydrolysis product adenosine diphosphate (ADP) is a fundamental and regulatory process during force production. However, details about the molecular mechanism accompanying ADP release are scarce due to the lack of representative structures. Here we solved a novel blebbistatin-bound myosin conformation with critical structural elements in positions between the myosin pre-power stroke and rigor states. ADP in this structure is repositioned towards the surface by the phosphate-sensing P-loop, and stabilized in a partially unbound conformation via a salt-bridge between Arg131 and Glu187. A 5 Å rotation separates the mechanical converter in this conformation from the rigor position. The crystallized myosin structure thus resembles a conformation towards the end of the two-step power stroke, associated with ADP release. Computationally reconstructing ADP release from myosin by means of molecular dynamics simulations further supported the existence of an equivalent conformation along the power stroke that shows the same major characteristics in the myosin motor domain as the resolved blebbistatin-bound myosin-II·ADP crystal structure, and identified a communication hub centered on Arg232 that mediates chemomechanical energy transduction.
Stably stratified Taylor–Green vortex simulations are performed by lattice Boltzmann methods (LBM) and compared to other recent works using Navier–Stokes solvers. The density variation is modeled with a separate distribution function in addition to the particle distribution function modeling the flow physics. Different stencils, forcing schemes, and collision models are tested and assessed. The overall agreement of the lattice Boltzmann solutions with reference solutions from other works is very good, even when no explicit subgrid model is used, but the quality depends on the LBM setup. Although the LBM forcing scheme is not decisive for the quality of the solution, the choice of the collision model and of the stencil are crucial for adequate solutions in underresolved conditions. The LBM simulations confirm the suppression of vertical flow motion for decreasing initial Froude numbers. To gain further insight into buoyancy effects, energy decay, dissipation rates, and flux coefficients are evaluated using the LBM model for various Froude numbers.
This research studies in detail four different assays, namely DPPH (2,2-diphenyl-1-picrylhydrazyl), ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)), FRAP (ferric ion reducing antioxidant potential) and FC (Folin-Ciocalteu), to determine the antioxidant capacity of standard substances as well as 50 organosolv lignins, and two kraft lignins. The coefficient of variation was determined for each method and was lowest for ABTS and highest for DPPH. The best correlation was found for FRAP and FC, which both rely on a single electron transfer mechanism. A good correlation between ABTS, FRAP and FC, respectively, could be observed, even though ABTS relies on a more complex reaction mechanism. The DPPH assay merely correlates with the others, implying that it reflects different antioxidative attributes due to a different reaction mechanism. Lignins obtained from paulownia and silphium have been investigated for the first time regarding their antioxidant capacity. Paulownia lignin is in the same range as beech wood lignin, while silphium lignin resembles wheat straw lignin. Miscanthus lignin is an exception from the grass lignins and possesses a significantly higher antioxidant capacity. All lignins possess a good antioxidant capacity and thus are promising candidates for various applications, e. g. as additives in food packaging or for biomedical purposes.
Pipeline transport is an efficient method for transporting fluids in energy supply and other technical applications. While natural gas is the classical example, the transport of hydrogen is becoming more and more important; both are transmitted under high pressure in a gaseous state. Also relevant is the transport of carbon dioxide, captured in the places of formation, transferred under high pressure in a liquid or supercritical state and pumped into underground reservoirs for storage. The transport of other fluids is also required in technical applications. Meanwhile, the transport equations for different fluids are essentially the same, and the simulation can be performed using the same methods. In this paper, the effect of control elements such as compressors, regulators and flaptraps on the stability of fluid transport simulations is studied. It is shown that modeling of these elements can lead to instabilities, both in stationary and dynamic simulations. Special regularization methods were developed to overcome these problems. Their functionality also for dynamic simulations is demonstrated for a number of numerical experiments.
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
The elucidation of conformations and relative potential energies (rPEs) of small molecules has a long history across a diverse range of fields. Periodically, it is helpful to revisit what conformations have been investigated and to provide a consistent theoretical framework for which clear comparisons can be made. In this paper, we compute the minima, first- and second-order saddle points, and torsion-coupled surfaces for methanol, ethanol, propan-2-ol, and propanol using consistent high-level MP2 and CCSD(T) methods. While for certain molecules more rigorous methods were employed, the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pV5Z theory level was used throughout to provide relative energies of all minima and first-order saddle points. The rPE surfaces were uniformly computed at the CCSD(T)/aug-cc-pVTZ//MP2/aug-cc-pVTZ level. To the best of our knowledge, this represents the most extensive study for alcohols of this kind, revealing some new aspects. Especially for propanol, we report several new conformations that were previously not investigated. Moreover, two metrics are included in our analysis that quantify how the selected surfaces are similar to one another and hence improve our understanding of the relationship between these alcohols.
The utilization of simulation procedures is gaining increasing attention in the product development of extrusion blow molded parts. However, some simulation steps, like the simulation of shrinkage and warpage, are still associated with uncertainties. The reason for this is on the one hand a lack of standardized interfaces for the transfer of simulation data between different simulation tools, and on the other hand the complex time-, temperature- and process-dependent material behavior of the used semi crystalline polymers. Using a new vendor neutral interface standard for the data transfer, the shrinkage analysis of a simple blow molded part is investigated and compared to experimental data. A linear viscoelastic material model in combination with an orthotropic process- and temperature-dependent thermal expansion coefficient is used for the shrinkage prediction. A good agreement is observed. Finally, critical parameters in the simulation models that strongly influence the shrinkage analysis are identified by a sensitivity study.
This work thoroughly investigates a semi-Lagrangian lattice Boltzmann (SLLBM) solver for compressible flows. In contrast to other LBM for compressible flows, the vertices are organized in cells, and interpolation polynomials up to fourth order are used to attain the off-vertex distribution function values. Differing from the recently introduced Particles on Demand (PoD) method , the method operates in a static, non-moving reference frame. Yet the SLLBM in the present formulation grants supersonic flows and exhibits a high degree of Galilean invariance. The SLLBM solver allows for an independent time step size due to the integration along characteristics and for the use of unusual velocity sets, like the D2Q25, which is constructed by the roots of the fifth-order Hermite polynomial. The properties of the present model are shown in diverse example simulations of a two-dimensional Taylor-Green vortex, a Sod shock tube, a two-dimensional Riemann problem and a shock-vortex interaction. It is shown that the cell-based interpolation and the use of Gauss-Lobatto-Chebyshev support points allow for spatially high-order solutions and minimize the mass loss caused by the interpolation. Transformed grids in the shock-vortex interaction show the general applicability to non-uniform grids.
Characterization methods of pressure sensitive adhesives (PSA) originate from technical bonding and do not cover relevant data for the development and quality assurance of medical applications, where PSA with flexible backing layers are adopted to human skin. In this study, a new method called RheoTack is developed to determine (mechanically and optically) an adhesion and detaching behavior of flexible and transparent PSA based patches. Transdermal therapeutic systems (TTS) consisting of silicone-based PSAs on a flexible and transparent backing layer were tested on a rotational rheometer with an 8 mm plate as a probe rod at retraction speeds of 0.01, 0.1, and 1 mm/s with respect to their adhesion and detaching behavior in terms of force-retraction displacement curves. The curves consist of a compression phase to affirm wetting; a tensile deformation phase intercepting stretching, cavity, and fibril formation; and a failure phase with detaching. Their analysis provides values for stiffness, force, and displacement of the beginning of fibril formation, force and displacement of the beginning of a failure due to fibril breakage and detaching, as well as corresponding activation energies. All these parameters exhibit the pronounced dependency on the retraction speed. The force-retraction displacement curves together with the simultaneous video recordings of the TTS deformation from three different angles (three cameras) provide deeper insight into the deformation processes and allow for interpreting the properties’ characteristics for PSA applications.
In her recent article, Bender discusses several aspects of research–practice–collaborations (RPCs). In this commentary, we apply Bender's arguments to experiences in engineering research and development (R&D). We investigate the influence of interaction with practice partners on relevance, credibility, and legitimacy in the special engineering field of product development and analyze which methodological approaches are already being pursued for dealing with diverging interests and asymmetries and which steps will be necessary to include interests of civil society beyond traditional customer relations.
The epithelial sodium channel (ENaC) is a key regulator of sodium homeostasis that contributes to blood pressure control. ENaC open probability is adjusted by extracellular sodium ions, a mechanism referred to as sodium self-inhibition (SSI). With a growing number of identified ENaC gene variants associated with hypertension, there is an increasing demand for medium- to high-throughput assays allowing the detection of alterations in ENaC activity and SSI. We evaluated a commercially available automated two-electrode voltage-clamp (TEVC) system that records transmembrane currents of ENaC-expressing Xenopus oocytes in 96-well microtiter plates. We employed guinea pig, human and Xenopus laevis ENaC orthologs that display specific magnitudes of SSI. While demonstrating some limitations over traditional TEVC systems with customized perfusion chambers, the automated TEVC system was able to detect the established SSI characteristics of the employed ENaC orthologs. We were able to confirm a reduced SSI in a gene variant, leading to C479R substitution in the human α-ENaC subunit that has been reported in Liddle syndrome. In conclusion, automated TEVC in Xenopus oocytes can detect SSI of ENaC orthologs and variants associated with hypertension. For precise mechanistic and kinetic analyses of SSI, optimization for faster solution exchange rates is recommended.
The genetic basis of brain tumor development is poorly understood. Here, leukocyte DNA of 21 patients from 15 families with ≥ 2 glioma cases each was analyzed by whole-genome or targeted sequencing. As a result, we identified two families with rare germline variants, p.(A592T) or p.(A817V), in the E-cadherin gene CDH1 that co-segregate with the tumor phenotype, consisting primarily of oligodendrogliomas, WHO grade II/III, IDH-mutant, 1p/19q-codeleted (ODs). Rare CDH1 variants, previously shown to predispose to gastric and breast cancer, were significantly overrepresented in these glioma families (13.3%) versus controls (1.7%). In 68 individuals from 28 gastric cancer families with pathogenic CDH1 germline variants, brain tumors, including a pituitary adenoma, were observed in three cases (4.4%), a significantly higher prevalence than in the general population (0.2%). Furthermore, rare CDH1 variants were identified in tumor DNA of 6/99 (6%) ODs. CDH1 expression was detected in undifferentiated and differentiating oligodendroglial cells isolated from rat brain. Functional studies using CRISPR/Cas9-mediated knock-in or stably transfected cell models demonstrated that the identified CDH1 germline variants affect cell membrane expression, cell migration and aggregation. E-cadherin ectodomain containing variant p.(A592T) had an increased intramolecular flexibility in a molecular dynamics simulation model. E-cadherin harboring intracellular variant p.(A817V) showed reduced β-catenin binding resulting in increased cytosolic and nuclear β-catenin levels reverted by treatment with the MAPK interacting serine/threonine kinase 1 inhibitor CGP 57380. Our data provide evidence for a role of deactivating CDH1 variants in the risk and tumorigenesis of neuroepithelial and epithelial brain tumors, particularly ODs, possibly via WNT/β-catenin signaling.
Qualitätsverbesserung und Zeitersparnis bei der Stipendienvergabe durch automatisierten Workflow
(2013)
Für die Vergabe der Deutschlandstipendien hatte die Hochschule anfangs ein Verfahren festgelegt, das viel manuelle Arbeitsschritte umfasst: Die Studierenden hatten ihre Bewerbungsunterlagen schriftlich einzureichen. Dazu gehörten neben einem Motivationsschreiben, einem Ausdruck des aktuellen Notenspiegels alle weiteren Referenzen zur Einschätzung der Bewerbung gemäß den gesetzlichen Auswahlkriterien. Als Grundlage zur Bewertung der „sozialen Kriterien“ sollten die Bewerberinnen und Bewerber ein Gutachten eines Professors oder einer Professorin der Hochschule einholen.
Unternehmen agieren in einem dynamischen Umfeld mit hoher Komplexität und Unsicherheit. Um dabei langfristig wettbewerbsfähig zu bleiben, ist eine kontinuierliche Optimierung der Prozesse erforderlich. Eine konsequente Prozessorientierung wird daher seit langem angestrebt. Zur Ermittlung des aktuellen Standes der Prozessorganisation in deutschen Unternehmen hat die Gesellschaft für Organisation e. V. (gfo) eine Studie durchführen lassen, deren erste Ergebnisse hier vorgestellt werden.
Protocol for conducting advanced cyclic tests in lithium-ion batteries to estimate capacity fade
(2024)
Using advanced cyclic testing techniques improves accuracy in estimating capacity fade and incorporates real-world scenarios in battery cycle aging assessment. Here, we present a protocol for conducting cyclic tests in lithium-ion batteries to estimate capacity fade. We describe steps for implementing strategies for accounting for variations in rest periods, charge-discharge rates, and temperatures. We also detail procedures for validating tests experimentally within a climate-controlled chamber and for developing an empirical model to estimate capacity fading under various testing objectives. For complete details on the use and execution of this protocol, please refer to Mulpuri et al.1.
Process-induced changes in the morphology of biodegradable polybutylene adipate terephthalate (PBAT) and polylactic acid (PLA) blends modified with various multifunctional chainextending cross-linkers (CECLs) are presented. The morphology of unmodified and modified films produced with blown film extrusion is examined in an extrusion direction (ED) and a transverse direction (TD). While FTIR analysis showed only small peak shifts indicating that the CECLs modify the molecular weight of the PBAT/PLA blend, SEM investigations of the fracture surfaces of blown extrusion films revealed their significant effect on the morphology formed during the processing. Due to the combined shear and elongation deformation during blown film extrusion, rather spherical PLA islands were partly transformed into long fibrils, which tended to decay to chains of elliptical islands if cooled slowly. The CECL introduction into the blend changed the thickness of the PLA fibrils, modified the interface adhesion, and altered the deformation behavior of the PBAT matrix from brittle to ductile. The results proved that CECLs react selectively with PBAT, PLA, and their interface. Furthermore, the reactions of CECLs with PBAT/PLA induced by the processing depended on the deformation directions (ED and TD), thus resulting in further non-uniformities of blown extrusion films.
This work proposes a novel approach for probabilistic end-to-end all-sky imager-based nowcasting with horizons of up to 30 min using an ImageNet pre-trained deep neural network. The method involves a two-stage approach. First, a backbone model is trained to estimate the irradiance from all-sky imager (ASI) images. The model is then extended and retrained on image and parameter sequences for forecasting. An open access data set is used for training and evaluation. We investigated the impact of simultaneously considering global horizontal (GHI), direct normal (DNI), and diffuse horizontal irradiance (DHI) on training time and forecast performance as well as the effect of adding parameters describing the irradiance variability proposed in the literature. The backbone model estimates current GHI with an RMSE and MAE of 58.06 and 29.33 W m−2, respectively. When extended for forecasting, the model achieves an overall positive skill score reaching 18.6 % compared to a smart persistence forecast. Minor modifications to the deterministic backbone and forecasting models enables the architecture to output an asymmetrical probability distribution and reduces training time while leading to similar errors for the backbone models. Investigating the impact of variability parameters shows that they reduce training time but have no significant impact on the GHI forecasting performance for both deterministic and probabilistic forecasting while simultaneously forecasting GHI, DNI, and DHI reduces the forecast performance.
Bone tissue engineering is an ever-changing, rapidly evolving, and highly interdisciplinary field of study, where scientists try to mimic natural bone structure as closely as possible in order to facilitate bone healing. New insights from cell biology, specifically from mesenchymal stem cell differentiation and signaling, lead to new approaches in bone regeneration. Novel scaffold and drug release materials based on polysaccharides gain increasing attention due to their wide availability and good biocompatibility to be used as hydrogels and/or hybrid components for drug release and tissue engineering. This article reviews the current state of the art, recent developments, and future perspectives in polysaccharide-based systems used for bone regeneration.
This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20° N and 20° W to 16° E) and the implications for photovoltaic systems. Here, we use satellite irradiance (Surface Solar Radiation Data Set – Heliosat, Edition 2.1 – SARAH-2.1) and temperature data from a reanalysis (ERA5) to derive photovoltaic yields. Based on 35 years of data (1983–2017), the temporal and regional variability as well as long-term trends in global and direct horizontal irradiance are analyzed. Furthermore, a detailed time series analysis is undertaken at four locations. According to the high spatial resolution SARAH-2.1 data record (0.05°×0.05°), solar irradiance is largest (up to a 300 W m−2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W m−2 per decade) and a lower temporal variability (<75 W m−2 between 1983 and 2017 for daily averages). In contrast, the solar irradiance is lower in southern West Africa (between 200 W m−2 and 250 W m−2) with a negative trend (up to −5 W m−2 per decade) and a higher temporal variability (up to 150 W m−2). The positive trend in the north is mostly connected to the dry season, whereas the negative trend in the south occurs during the wet season. Both trends show 95 % significance. Photovoltaic (PV) yields show a strong meridional gradient with the lowest values of around 4 kWh kWp−1 in southern West Africa and values of more than 5.5 kWh kWp−1 in the Sahara and Sahel zone.
The cystic fibrosis transmembrane conductance regulator (CFTR) anion channel and the epithelial Na+ channel (ENaC) play essential roles in transepithelial ion and fluid transport in numerous epithelial tissues. Inhibitors of both channels have been important tools for defining their physiological role in vitro. However, two commonly used CFTR inhibitors, CFTRinh-172 and GlyH-101, also inhibit non-CFTR anion channels, indicating they are not CFTR specific. However, the potential off-target effects of these inhibitors on epithelial cation channels has to date not been addressed. Here, we show that both CFTR blockers, at concentrations routinely employed by many researchers, caused a significant inhibition of store-operated calcium entry (SOCE) that was time-dependent, poorly reversible and independent of CFTR. Patch clamp experiments showed that both CFTRinh-172 and GlyH-101 caused a significant block of Orai1-mediated whole cell currents, establishing that they likely reduce SOCE via modulation of this Ca2+ release-activated Ca2+ (CRAC) channel. In addition to off-target effects on calcium channels, both inhibitors significantly reduced human αβγ-ENaC-mediated currents after heterologous expression in Xenopus oocytes, but had differential effects on δβγ-ENaC function. Molecular docking identified two putative binding sites in the extracellular domain of ENaC for both CFTR blockers. Together, our results indicate that caution is needed when using these two CFTR inhibitors to dissect the role of CFTR, and potentially ENaC, in physiological processes.
Alkaline methanol oxidation is an important electrochemical process in the design of efficient fuel cells. Typically, a system of ordinary differential equations is used to model the kinetics of this process. The fitting of the parameters of the underlying mathematical model is performed on the basis of different types of experiments, characterizing the fuel cell. In this paper, we describe generic methods for creation of a mathematical model of electrochemical kinetics from a given reaction network, as well as for identification of parameters of this model. We also describe methods for model reduction, based on a combination of steady-state and dynamical descriptions of the process. The methods are tested on a range of experiments, including different concentrations of the reagents and different voltage range.
Am Beispiel einer jahrelang in Präsenz gelehrten Veranstaltung mit Vorlesungen, Übungen und Laborpraktika wird gezeigt, wie die Vermittlung prüfungsrelevanter Kompetenzen auch „online“ gelang. Das passende „Setting“ des Lehr- und Lernprozesses unter Beachtung von Handlungsempfehlungen ist auch für die Zukunft relevant.
Healing of large bone defects requires implants or scaffolds that provide structural guidance for cell growth, differentiation, and vascularization. In the present work, an agarose-hydroxyapatite composite scaffold was developed that acts not only as a 3D matrix, but also as a release system. Hydroxyapatite (HA) was incorporated into the agarose gels in situ in various ratios by a simple procedure consisting of precipitation, cooling, washing, and drying. The resulting gels were characterized regarding composition, porosity, mechanical properties, and biocompatibility. A pure phase of carbonated HA was identified in the scaffolds, which had pore sizes of up to several hundred micrometers. Mechanical testing revealed elastic moduli of up to 2.8 MPa for lyophilized composites. MTT testing on Lw35human mesenchymal stem cells (hMSCs) and osteosarcoma MG-63 cells proved the biocompatibility of the scaffolds. Furthermore, scaffolds were loaded with model drug compounds for guided hMSC differentiation. Different release kinetic models were evaluated for adenosine 5′-triphosphate (ATP) and suramin, and data showed a sustained release behavior over four days.
Modeling of Creep Behavior of Particulate Composites with Focus on Interfacial Adhesion Effect
(2022)
Evaluation of creep compliance of particulate composites using empirical models always provides parameters depending on initial stress and material composition. The effort spent to connect model parameters with physical properties has not resulted in success yet. Further, during the creep, delamination between matrix and filler may occur depending on time and initial stress, reducing an interface adhesion and load transfer to filler particles. In this paper, the creep compliance curves of glass beads reinforced poly(butylene terephthalate) composites were fitted with Burgers and Findley models providing different sets of time-dependent model parameters for each initial stress. Despite the finding that the Findley model performs well in a primary creep, the Burgers model is more suitable if secondary creep comes into play; they allow only for a qualitative prediction of creep behavior because the interface adhesion and its time dependency is an implicit, hidden parameter. As Young’s modulus is a parameter of these models (and the majority of other creep models), it was selected to be introduced as a filler content-dependent parameter with the help of the cube in cube elementary volume approach of Paul. The analysis led to the time-dependent creep compliance that depends only on the time-dependent creep of the matrix and the normalized particle distance (or the filler volume content), and it allowed accounting for the adhesion effect. Comparison with the experimental data confirmed that the elementary volume-based creep compliance function can be used to predict the realistic creep behavior of particulate composites.
Miscanthus x giganteus Stem Versus Leaf-Derived Lignins Differing in Monolignol Ratio and Linkage
(2019)
As a renewable, Miscanthus offers numerous advantages such as high photosynthesis activity (as a C4 plant) and an exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. In this paper, we present a systematic study analyzing the correlation of the lignin structure with the Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. The lignin amount has been determined for M. x giganteus (Gig17, Gig34, Gig35), M. nagara (NagG10), M. sinensis (Sin2), and M. robustus (Rob4) harvested at different time points (September, December, and April). The influence of the Miscanthus genotype and plant component (leaf vs. stem) has been studied to develop corresponding structure-property relationships (i.e., correlations in molecular weight, polydispersity, and decomposition temperature). Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes compositional analysis, Fourier transform infradred (FTIR), ultraviolet/visible (UV-Vis), hetero-nuclear single quantum correlation nuclear magnetic resonsnce (HSQC-NMR), thermogravimetric analysis (TGA), and pyrolysis gaschromatography/mass spectrometry (GC/MS). Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (<1.5 Miscanthus vs. >2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as a low-input resource and a Miscanthus-derived lignin as promising agricultural feedstock.
Approximately 45% of global greenhouse gas emissions are caused by the construction and use of buildings. Thermal insulation of buildings in the current context of climate change is a well-known strategy to improve the energy efficiency of buildings. The development of renewable insulation material can overcome the drawbacks of widely used insulation systems based on polystyrene or mineral wool. This study analyzes the sustainability and thermal conductivity of new insulation materials made of Miscanthus x giganteus fibers, foaming agents, and alkali-activated fly ash binder. Life cycle assessments (LCA) are necessary to perform benchmarking of environmental impacts of new formulations of geopolymer-based insulation materials. The global warming potential (GWP) of the product is primarily determined by the main binder component sodium silicate. Sodium silicate's CO2 emissions depend on local production, transportation, and energy consumption. The results, which have been published during recent years, vary in a wide range from 0.3 kg to 3.3 kg CO2-eq. kg-1. The overall GWP of the insulation system based on Miscanthus fibers, with properties according to current thermal insulation regulations, reaches up to 95% savings of CO2 emissions compared to conventional systems. Carbon neutrality can be achieved through formulations containing raw materials with carbon dioxide emissions and renewable materials with negative GWP, thus balancing CO2 emissions.
The use of wearable devices or “wearables” in the physical activity domain has been increasing in the last years. These devices are used as training tools providing the user with detailed information about individual physiological responses and feedback to the physical training process. Advantages in sensor technology, miniaturization, energy consumption and processing power increased the usability of these wearables. Furthermore, available sensor technologies must be reliable, valid, and usable. Considering the variety of the existing sensors not all of them are suitable to be integrated in wearables. The application and development of wearables has to consider the characteristics of the physical training process to improve the effectiveness and efficiency as training tools. During physical training, it is essential to elicit individual optimal strain to evoke the desired adjustments to training. One important goal is to neither overstrain nor under challenge the user. Many wearables use heart rate as indicator for this individual strain. However, due to a variety of internal and external influencing factors, heart rate kinetics are highly variable making it difficult to control the stress eliciting individually optimal strain. For optimal training control it is essential to model and predict individual responses and adapt the external stress if necessary. Basis for this modeling is the valid and reliable recording of these individual responses. Depending on the heart rate kinetics and the obtained physiological data, different models and techniques are available that can be used for strain or training control. Aim of this review is to give an overview of measurement, prediction, and control of individual heart rate responses. Therefore, available sensor technologies measuring the individual heart rate responses are analyzed and approaches to model and predict these individual responses discussed. Additionally, the feasibility for wearables is analyzed.
Lignocellulose feedstock (LCF) provides a sustainable source of components to produce bioenergy, biofuel, and novel biomaterials. Besides hard and soft wood, so-called low-input plants such as Miscanthus are interesting crops to be investigated as potential feedstock for the second generation biorefinery. The status quo regarding the availability and composition of different plants, including grasses and fast-growing trees (i.e., Miscanthus, Paulownia), is reviewed here. The second focus of this review is the potential of multivariate data processing to be used for biomass analysis and quality control. Experimental data obtained by spectroscopic methods, such as nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR), can be processed using computational techniques to characterize the 3D structure and energetic properties of the feedstock building blocks, including complex linkages. Here, we provide a brief summary of recently reported experimental data for structural analysis of LCF biomasses, and give our perspectives on the role of chemometrics in understanding and elucidating on LCF composition and lignin 3D structure.
Antioxidant activity is an essential aspect of oxygen-sensitive merchandise and goods, such as food and corresponding packaging, cosmetics, and biomedicine. Technical lignin has not yet been applied as a natural antioxidant, mainly due to the complex heterogeneous structure and polydispersity of lignin. This report presents antioxidant capacity studies completed using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The influence of purification on lignin structure and activity was investigated. The purification procedure showed that double-fold selective extraction is the most efficient (confirmed by ultraviolet-visible (UV/Vis), Fourier transform infrared (FTIR), heteronuclear single quantum coherence (HSQC) and 31P nuclear magnetic resonance spectroscopy, size exclusion chromatography, and X-ray diffraction), resulting in fractions of very narrow polydispersity (3.2⁻1.6), up to four distinct absorption bands in UV/Vis spectroscopy. Due to differential scanning calorimetry measurements, the glass transition temperature increased from 123 to 185 °C for the purest fraction. Antioxidant capacity is discussed regarding the biomass source, pulping process, and degree of purification. Lignin obtained from industrial black liquor are compared with beech wood samples: antioxidant activity (DPPH inhibition) of kraft lignin fractions were 62⁻68%, whereas beech and spruce/pine-mixed lignin showed values of 42% and 64%, respectively. Total phenol content (TPC) of the isolated kraft lignin fractions varied between 26 and 35%, whereas beech and spruce/pine lignin were 33% and 34%, respectively. Storage decreased the TPC values but increased the DPPH inhibition.
Renewable resources are gaining increasing interest as a source for environmentally benign biomaterials, such as drug encapsulation/release compounds, and scaffolds for tissue engineering in regenerative medicine. Being the second largest naturally abundant polymer, the interest in lignin valorization for biomedical utilization is rapidly growing. Depending on its resource and isolation procedure, lignin shows specific antioxidant and antimicrobial activity. Today, efforts in research and industry are directed toward lignin utilization as a renewable macromolecular building block for the preparation of polymeric drug encapsulation and scaffold materials. Within the last five years, remarkable progress has been made in isolation, functionalization and modification of lignin and lignin-derived compounds. However, the literature so far mainly focuses lignin-derived fuels, lubricants and resins. The purpose of this review is to summarize the current state of the art and to highlight the most important results in the field of lignin-based materials for potential use in biomedicine (reported in 2014⁻2018). Special focus is placed on lignin-derived nanomaterials for drug encapsulation and release as well as lignin hybrid materials used as scaffolds for guided bone regeneration in stem cell-based therapies.
The lattice Boltzmann method (LBM) stands apart from conventional macroscopic approaches due to its low numerical dissipation and reduced computational cost, attributed to a simple streaming and local collision step. While this property makes the method particularly attractive for applications such as direct noise computation, it also renders the method highly susceptible to instabilities. A vast body of literature exists on stability-enhancing techniques, which can be categorized into selective filtering, regularized LBM, and multi-relaxation time (MRT) models. Although each technique bolsters stability by adding numerical dissipation, they act on different modes. Consequently, there is not a universal scheme optimally suited for a wide range of different flows. The reason for this lies in the static nature of these methods; they cannot adapt to local or global flow features. Still, adaptive filtering using a shear sensor constitutes an exception to this. For this reason, we developed a novel collision operator that uses space- and time-variant collision rates associated with the bulk viscosity. These rates are optimized by a physically informed neural net. In this study, the training data consists of a time series of different instances of a 2D barotropic vortex solution, obtained from a high-order Navier–Stokes solver that embodies desirable numerical features. For this specific text case our results demonstrate that the relaxation times adapt to the local flow and show a dependence on the velocity field. Furthermore, the novel collision operator demonstrates a better stability-to-precision ratio and outperforms conventional techniques that use an empirical constant for the bulk viscosity.
Solar photovoltaic power output is modulated by atmospheric aerosols and clouds and thus contains valuable information on the optical properties of the atmosphere. As a ground-based data source with high spatiotemporal resolution it has great potential to complement other ground-based solar irradiance measurements as well as those of weather models and satellites, thus leading to an improved characterisation of global horizontal irradiance. In this work several algorithms are presented that can retrieve global tilted and horizontal irradiance and atmospheric optical properties from solar photovoltaic data and/or pyranometer measurements. The method is tested on data from two measurement campaigns that took place in the Allgäu region in Germany in autumn 2018 and summer 2019, and the results are compared with local pyranometer measurements as well as satellite and weather model data. Using power data measured at 1 Hz and averaged to 1 min resolution along with a non-linear photovoltaic module temperature model, global horizontal irradiance is extracted with a mean bias error compared to concurrent pyranometer measurements of 5.79 W m−2 (7.35 W m−2) under clear (cloudy) skies, averaged over the two campaigns, whereas for the retrieval using coarser 15 min power data with a linear temperature model the mean bias error is 5.88 and 41.87 W m−2 under clear and cloudy skies, respectively.
During completely overcast periods the cloud optical depth is extracted from photovoltaic power using a lookup table method based on a 1D radiative transfer simulation, and the results are compared to both satellite retrievals and data from the Consortium for Small-scale Modelling (COSMO) weather model. Potential applications of this approach for extracting cloud optical properties are discussed, as well as certain limitations, such as the representation of 3D radiative effects that occur under broken-cloud conditions. In principle this method could provide an unprecedented amount of ground-based data on both irradiance and optical properties of the atmosphere, as long as the required photovoltaic power data are available and properly pre-screened to remove unwanted artefacts in the signal. Possible solutions to this problem are discussed in the context of future work.
The mechanical properties of plastic components, especially if they are made of semi-crystalline polymers, are considerably influenced by the process conditions. The degree of crystallization influences thermal and mechanical properties. Even more important is the orientation of molecules due to stretching of the polymer melt. Anisotropic material properties are the result of such orientations. Up to now all these effects are not considered within the simulation models of blow molded parts.
Polyether and polyether/ester based TPU (thermoplastic polyurethanes) were investigated with wide-angle XRD (X-ray diffraction) and SAXS (small angle X-ray scattering). Furthermore, SAXS measurements were performed in the temperature range of 30 °C to 130 °C. Polyether based polymers exhibit only one broad diffraction signal in a region of 2 θ 15° to 25°. In case of polyurethanes with ether/ester modification, the broad diffraction signal arises with small sharp diffraction signals. SAXS measurements of polymers reveal the size and shape of the crystalline zones of the polymer. Between 30 °C and 130 °C the size of the crystalline zone changes significantly. The size decreases in most of investigated TPU. In the case of Desmopan 9365D an increase of the particle size was observed.
In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.
The cube in cube approach was used by Paul and Ishai-Cohen to model and derive formulas for filler content dependent Young's moduli of particle filled composites assuming perfect filler matrix adhesion. Their formulas were chosen because of their simplicity, and recalculated using an elementary volume approach which transforms spherical inclusions to cubic inclusions. The EV approach led to expression of the composites moduli that allows introducing an adhesion factor kadh ranging from 0 and 1 to take into account reduced filler matrix adhesion. This adhesion factor scales the edge length of the cubic inclusions, thus reducing the stress transfer area between matrix and filler. Fitting the experimental data with the modified Paul model provides reasonable kadh for PA66, PBT, PP, PE-LD and BR which are in line with their surface energies. Further analysis showed that stiffening only occurs if kadh exceeds [Formula: see text] and depends on the ratio of matrix modulus and filler modulus. The modified model allows for a quick calculation of any particle filled composites for known matrix modulus EM, filler modulus EF, filler volume content vF and adhesion factor kadh. Thus, finite element analysis (FEA) simulations of any particle filled polymer parts as well as materials selection are significantly eased. FEA of cubic and hexagonal EV arrangements show that stress distributions within the EV exhibit more shear stresses if one deviates from the cubic arrangement. At high filler contents the assumption that the property of the EV is representative for the whole composite, holds only for filler volume contents up to 15 or 20% (corresponding to 30 to 40 weight %). Thus, for vast majority of commercially available particulate composites, the modified model can be applied. Furthermore, this indicates that the cube in cube approach reaches two limits: (i) the occurrence of increasing shear stresses at filler contents above 20% due to deviations of EV arrangements or spatial filler distribution from cubic arrangements (singular), and (ii) increasing interaction between particles with the formation of particle network within the matrix violating the EV assumption of their homogeneous dispersion.
This study investigates the initial stage of the thermo-mechanical crystallization behavior for uni- and biaxially stretched polyethylene. The models are based on a mesoscale molecular dynamics approach. We take constraints that occur in real-life polymer processing into account, especially with respect to the blowing stage of the extrusion blow-molding process. For this purpose, we deform our systems using a wide range of stretching levels before they are quenched. We discuss the effects of the stretching procedures on the micro-mechanical state of the systems, characterized by entanglement behavior and nematic ordering of chain segments. For the cooling stage, we use two different approaches which allow for free or hindered shrinkage, respectively. During cooling, crystallization kinetics are monitored: We precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influence crystallization behavior. Our models reveal that the main stretching direction dominates microscopic states of the different systems. We are able to show that crystallization mainly depends on the (dis-)entanglement behavior. Nematic ordering plays a secondary role.
Bonding wires made of aluminum are the most used materials for the transmission of electrical signals in power electronic devices. During operation, different cyclic mechanical and thermal stresses can lead to fatigue loads and a failure of the bonding wires. A prediction or prevention of the wire failure is not yet possible by design for all cases. The following work presents meaningful fatigue tests in small wire dimensions and investigates the influence of the R-ratio on the lifetime of two different aluminum wires with a diameter of 300 μm each. The experiments show very reproducible fatigue results with ductile failure behavior. The endurable stress amplitude decreases linearly with an increasing stress ratio, which can be displayed by a Smith diagram, even though the applied maximum stresses exceed the initial yield stresses determined by tensile tests. A scaling of the fatigue results by the tensile strength indicates that the fatigue level is significantly influenced by the strength of the material. Due to the very consistent findings, the development of a generalized fatigue model for predicting the lifetime of bonding wires with an arbitrary loading situation seems to be possible and will be further investigated.
In mathematical modeling by means of performance models, the Fitness-Fatigue Model (FF-Model) is a common approach in sport and exercise science to study the training performance relationship. The FF-Model uses an initial basic level of performance and two antagonistic terms (for fitness and fatigue). By model calibration, parameters are adapted to the subject’s individual physical response to training load. Although the simulation of the recorded training data in most cases shows useful results when the model is calibrated and all parameters are adjusted, this method has two major difficulties. First, a fitted value as basic performance will usually be too high. Second, without modification, the model cannot be simply used for prediction. By rewriting the FF-Model such that effects of former training history can be analyzed separately – we call those terms preload – it is possible to close the gap between a more realistic initial performance level and an athlete's actual performance level without distorting other model parameters and increase model accuracy substantially. Fitting error of the preload-extended FF-Model is less than 32% compared to the error of the FF-Model without preloads. Prediction error of the preload-extended FF-Model is around 54% of the error of the FF-Model without preloads.
Atmospheric aerosols affect the power production of solar energy systems. Their impact depends on both the atmospheric conditions and the solar technology employed. By being a region with a lack in power production and prone to high solar insolation, West Africa shows high potential for the application of solar power systems. However, dust outbreaks, containing high aerosol loads, occur especially in the Sahel, located between the Saharan desert in the north and the Sudanian Savanna in the south. They might affect the whole region for several days with significant effects on power generation. This study investigates the impact of atmospheric aerosols on solar energy production for the example year 2006 making use of six well instrumented sites in West Africa. Two different solar power technologies, a photovoltaic (PV) and a parabolic through (PT) power plant, are considered. The daily reduction of solar power due to aerosols is determined over mostly clear-sky days in 2006 with a model chain combining radiative transfer and technology specific power generation. For mostly clear days the local daily reduction of PV power (at alternating current) (PVAC) and PT power (PTP) due to the presence of aerosols lies between 13 % and 22 % and between 22 % and 37 %, respectively. In March 2006 a major dust outbreak occurred, which serves as an example to investigate the impact of an aerosol extreme event on solar power. During the dust outbreak, daily reduction of PVAC and PTP of up to 79 % and 100 % occur with a mean reduction of 20 % to 40 % for PVAC and of 32 % to 71 % for PTP during the 12 days of the event.
Impact of atmospheric aerosols on photovoltaic energy production - Scenario for the Sahel zone
(2017)
Photovoltaic (PV) energy is one option to serve the rising global energy need with low environmental impact. PV is of particular interest for local energy solutions in developing countries prone to high solar insolation. In order to assess the PV potential of prospective sites, combining knowledge of the atmospheric state modulating solar radiation and the PV performance is necessary. The present study discusses the PV power as function of atmospheric aerosols in the Sahel zone for clear-sky-days. Daily yields for a polycrystalline silicon PV module are reduced by up to 48 % depending on the climatologically-relevant aerosol abundances.
Bei Thymian (Thymus vulgaris) handelt es sich um eine sehr varietätenreiche Art, die aufgrund ihres Gehaltes an therapeutisch wirksamen Inhaltsstoffen als Arzneipflanze monographiert ist. Insbesondere das ätherische Öl mit dem Hauptbestandteil Thymol (ca. 50%) hat eine hohe antioxidative Wirkung. Ziel ist es, dieses Potential als nachhaltig produzierte Additive zu nutzen. Hierfür eignen sich antioxidativ bzw. antimikrobiell wirksame sowie UV-absorbierende Substanzen, die das Produkt bei Zusatz vor oxidativem Stress, mikrobiellem Abbau und Qualitätsverlust schützen.
Hierzu werden zunächst sechs Varianten auf verschiedene Parameter analysiert, um die potenteste Variante auszuwählen. Auf diese Variante wird sich die weitere Forschung konzentrieren.
Daher wird das ätherische Öl durch azeotrope Destillation extrahiert und mittels GCMS analysiert. In Extrakten werden zudem das AP und Absorptionsverhalten bestimmt. Auch die chemische Zusammensetzung des Extrakts sowie die flüchtigen Stoffe des Thymians werden untersucht. Generell gibt es wenig qualitative, teilweise jedoch quantitative Unterschiede: Eine Variante weist u.a. einen deutlich höheren Thymolgehalt im Öl (ca. 65 %) und ein hohes hydrophiles AP auf. Somit ist eine vielversprechende Variante für die weitere Entwicklung und Optimierung bioaktiver Additive gefunden.