6 resultados para Load flow with step size optimization
em ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha
Resumo:
Aufbau einer kontinuierlichen, mehrdimensionalen Hochleistungs-flüssigchromatographie-Anlage für die Trennung von Proteinen und Peptiden mit integrierter größenselektiver ProbenfraktionierungEs wurde eine mehrdimensionale HPLC-Trennmethode für Proteine und Peptide mit einem Molekulargewicht von <15 kDa entwickelt.Im ersten Schritt werden die Zielanalyte von höhermolekularen sowie nicht ionischen Bestandteilen mit Hilfe von 'Restricted Access Materialien' (RAM) mit Ionenaustauscher-Funktionalität getrennt. Anschließend werden die Proteine auf einer analytischen Ionenaustauscher-Säule sowie auf Reversed-Phase-Säulen getrennt. Zur Vermeidung von Probenverlusten wurde ein kontinuierlich arbeitendes, voll automatisiertes System auf Basis unterschiedlicher Trenngeschwindigkeiten und vier parallelen RP-Säulen aufgebaut.Es werden jeweils zwei RP-Säulen gleichzeitig, jedoch mit zeitlich versetztem Beginn eluiert, um durch flache Gradienten ausreichende Trennleistungen zu erhalten. Während die dritte Säule regeneriert wird, erfolgt das Beladen der vierte Säule durch Anreicherung der Proteine und Peptide am Säulenkopf. Während der Gesamtanalysenzeit von 96 Minuten werden in Intervallen von 4 Minuten Fraktionen aus der 1. Dimension auf die RP-Säulen überführt und innerhalb von 8 Minuten getrennt, wobei 24 RP-Chromatogramme resultieren.Als Testsubstanzen wurden u.a. Standardproteine, Proteine und Peptide aus humanem Hämofiltrat sowie aus Lungenfibroblast-Zellkulturüberständen eingesetzt. Weiterhin wurden Fraktionen gesammelt und mittels MALDI-TOF Massenspektrometrie untersucht. Bei einer Injektion wurden in den 24 RP-Chromatogrammen mehr als 1000 Peaks aufgelöst. Der theoretische Wert der Peakkapazität liegt bei ungefähr 3000.
Resumo:
Five different methods were critically examined to characterize the pore structure of the silica monoliths. The mesopore characterization was performed using: a) the classical BJH method of nitrogen sorption data, which showed overestimated values in the mesopore distribution and was improved by using the NLDFT method, b) the ISEC method implementing the PPM and PNM models, which were especially developed for monolithic silicas, that contrary to the particulate supports, demonstrate the two inflection points in the ISEC curve, enabling the calculation of pore connectivity, a measure for the mass transfer kinetics in the mesopore network, c) the mercury porosimetry using a new recommended mercury contact angle values. rnThe results of the characterization of mesopores of monolithic silica columns by the three methods indicated that all methods were useful with respect to the pore size distribution by volume, but only the ISEC method with implemented PPM and PNM models gave the average pore size and distribution based on the number average and the pore connectivity values.rnThe characterization of the flow-through pore was performed by two different methods: a) the mercury porosimetry, which was used not only for average flow-through pore value estimation, but also the assessment of entrapment. It was found that the mass transfer from the flow-through pores to mesopores was not hindered in case of small sized flow-through pores with a narrow distribution, b) the liquid penetration where the average flow-through pore values were obtained via existing equations and improved by the additional methods developed according to Hagen-Poiseuille rules. The result was that not the flow-through pore size influences the column bock pressure, but the surface area to volume ratio of silica skeleton is most decisive. Thus the monolith with lowest ratio values will be the most permeable. rnThe flow-through pore characterization results obtained by mercury porosimetry and liquid permeability were compared with the ones from imaging and image analysis. All named methods enable a reliable characterization of the flow-through pore diameters for the monolithic silica columns, but special care should be taken about the chosen theoretical model.rnThe measured pore characterization parameters were then linked with the mass transfer properties of monolithic silica columns. As indicated by the ISEC results, no restrictions in mass transfer resistance were noticed in mesopores due to their high connectivity. The mercury porosimetry results also gave evidence that no restrictions occur for mass transfer from flow-through pores to mesopores in the small scaled silica monoliths with narrow distribution. rnThe prediction of the optimum regimes of the pore structural parameters for the given target parameters in HPLC separations was performed. It was found that a low mass transfer resistance in the mesopore volume is achieved when the nominal diameter of the number average size distribution of the mesopores is appr. an order of magnitude larger that the molecular radius of the analyte. The effective diffusion coefficient of an analyte molecule in the mesopore volume is strongly dependent on the value of the nominal pore diameter of the number averaged pore size distribution. The mesopore size has to be adapted to the molecular size of the analyte, in particular for peptides and proteins. rnThe study on flow-through pores of silica monoliths demonstrated that the surface to volume of the skeletons ratio and external porosity are decisive for the column efficiency. The latter is independent from the flow-through pore diameter. The flow-through pore characteristics by direct and indirect approaches were assessed and theoretical column efficiency curves were derived. The study showed that next to the surface to volume ratio, the total porosity and its distribution of the flow-through pores and mesopores have a substantial effect on the column plate number, especially as the extent of adsorption increases. The column efficiency is increasing with decreasing flow through pore diameter, decreasing with external porosity, and increasing with total porosity. Though this tendency has a limit due to heterogeneity of the studied monolithic samples. We found that the maximum efficiency of the studied monolithic research columns could be reached at a skeleton diameter of ~ 0.5 µm. Furthermore when the intention is to maximize the column efficiency, more homogeneous monoliths should be prepared.rn
Resumo:
Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. Knowledge of the spatial and temporal distribution of CCN in the atmosphere is essential to understand and describe the effects of aerosols in meteorological models. In this study, CCN properties were measured in polluted and pristine air of different continental regions, and the results were parameterized for efficient prediction of CCN concentrations.The continuous-flow CCN counter used for size-resolved measurements of CCN efficiency spectra (activation curves) was calibrated with ammonium sulfate and sodium chloride aerosols for a wide range of water vapor supersaturations (S=0.068% to 1.27%). A comprehensive uncertainty analysis showed that the instrument calibration depends strongly on the applied particle generation techniques, Köhler model calculations, and water activity parameterizations (relative deviations in S up to 25%). Laboratory experiments and a comparison with other CCN instruments confirmed the high accuracy and precision of the calibration and measurement procedures developed and applied in this study.The mean CCN number concentrations (NCCN,S) observed in polluted mega-city air and biomass burning smoke (Beijing and Pearl River Delta, China) ranged from 1000 cm−3 at S=0.068% to 16 000 cm−3 at S=1.27%, which is about two orders of magnitude higher than in pristine air at remote continental sites (Swiss Alps, Amazonian rainforest). Effective average hygroscopicity parameters, κ, describing the influence of chemical composition on the CCN activity of aerosol particles were derived from the measurement data. They varied in the range of 0.3±0.2, were size-dependent, and could be parameterized as a function of organic and inorganic aerosol mass fraction. At low S (≤0.27%), substantial portions of externally mixed CCN-inactive particles with much lower hygroscopicity were observed in polluted air (fresh soot particles with κ≈0.01). Thus, the aerosol particle mixing state needs to be known for highly accurate predictions of NCCN,S. Nevertheless, the observed CCN number concentrations could be efficiently approximated using measured aerosol particle number size distributions and a simple κ-Köhler model with a single proxy for the effective average particle hygroscopicity. The relative deviations between observations and model predictions were on average less than 20% when a constant average value of κ=0.3 was used in conjunction with variable size distribution data. With a constant average size distribution, however, the deviations increased up to 100% and more. The measurement and model results demonstrate that the aerosol particle number and size are the major predictors for the variability of the CCN concentration in continental boundary layer air, followed by particle composition and hygroscopicity as relatively minor modulators. Depending on the required and applicable level of detail, the measurement results and parameterizations presented in this study can be directly implemented in detailed process models as well as in large-scale atmospheric and climate models for efficient description of the CCN activity of atmospheric aerosols.
Resumo:
I present a new experimental method called Total Internal Reflection Fluorescence Cross-Correlation Spectroscopy (TIR-FCCS). It is a method that can probe hydrodynamic flows near solid surfaces, on length scales of tens of nanometres. Fluorescent tracers flowing with the liquid are excited by evanescent light, produced by epi-illumination through the periphery of a high NA oil-immersion objective. Due to the fast decay of the evanescent wave, fluorescence only occurs for tracers in the ~100 nm proximity of the surface, thus resulting in very high normal resolution. The time-resolved fluorescence intensity signals from two laterally shifted (in flow direction) observation volumes, created by two confocal pinholes are independently measured and recorded. The cross-correlation of these signals provides important information for the tracers’ motion and thus their flow velocity. Due to the high sensitivity of the method, fluorescent species with different size, down to single dye molecules can be used as tracers. The aim of my work was to build an experimental setup for TIR-FCCS and use it to experimentally measure the shear rate and slip length of water flowing on hydrophilic and hydrophobic surfaces. However, in order to extract these parameters from the measured correlation curves a quantitative data analysis is needed. This is not straightforward task due to the complexity of the problem, which makes the derivation of analytical expressions for the correlation functions needed to fit the experimental data, impossible. Therefore in order to process and interpret the experimental results I also describe a new numerical method of data analysis of the acquired auto- and cross-correlation curves – Brownian Dynamics techniques are used to produce simulated auto- and cross-correlation functions and to fit the corresponding experimental data. I show how to combine detailed and fairly realistic theoretical modelling of the phenomena with accurate measurements of the correlation functions, in order to establish a fully quantitative method to retrieve the flow properties from the experiments. An importance-sampling Monte Carlo procedure is employed in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for both modern desktop PC machines and massively parallel computers. The latter allows making the data analysis within short computing times. I applied this method to study flow of aqueous electrolyte solution near smooth hydrophilic and hydrophobic surfaces. Generally on hydrophilic surface slip is not expected, while on hydrophobic surface some slippage may exists. Our results show that on both hydrophilic and moderately hydrophobic (contact angle ~85°) surfaces the slip length is ~10-15nm or lower, and within the limitations of the experiments and the model, indistinguishable from zero.
Resumo:
The thesis deals with numerical algorithms for fluid-structure interaction problems with application in blood flow modelling. It starts with a short introduction on the mathematical description of incompressible viscous flow with non-Newtonian viscosity and a moving linear viscoelastic structure. The mathematical model consists of the generalized Navier-Stokes equation used for the description of fluid flow and the generalized string model for structure movement. The arbitrary Lagrangian-Eulerian approach is used in order to take into account moving computational domain. A part of the thesis is devoted to the discussion on the non-Newtonian behaviour of shear-thinning fluids, which is in our case blood, and derivation of two non-Newtonian models frequently used in the blood flow modelling. Further we give a brief overview on recent fluid-structure interaction schemes with discussion about the difficulties arising in numerical modelling of blood flow. Our main contribution lies in numerical and experimental study of a new loosely-coupled partitioned scheme called the kinematic splitting fluid-structure interaction algorithm. We present stability analysis for a coupled problem of non-Newtonian shear-dependent fluids in moving domains with viscoelastic boundaries. Here, we assume both, the nonlinearity in convective as well is diffusive term. We analyse the convergence of proposed numerical scheme for a simplified fluid model of the Oseen type. Moreover, we present series of experiments including numerical error analysis, comparison of hemodynamic parameters for the Newtonian and non-Newtonian fluids and comparison of several physiologically relevant computational geometries in terms of wall displacement and wall shear stress. Numerical analysis and extensive experimental study for several standard geometries confirm reliability and accuracy of the proposed kinematic splitting scheme in order to approximate fluid-structure interaction problems.
Resumo:
In der vorliegenden Dissertation wird ein Körpergrößengedächtnis untersucht. Es wird dargestellt, wie diese Information über die Reichweite der Fliege beim Lückenklettern unter kotrollierten Umweltbedingungen erworben und prozessiert wird. Zusätzlich wird geklärt, welche biochemischen Signale benötigt werden, um daraus ein lang anhalten-des Gedächtnis zu formen. Adulte Fliegen sind in der Lage, ihre Körperreichweite zu lernen. Naive Fliegen, die in der Dunkelheit gehalten wurden, versuchen erfolglos, zu breite Lücken zu überqueren, während visuell erfahrene Fliegen die Kletterversuche an ihre Körpergröße anpassen. Erfahrene kleine Fliegen scheinen Kenntnis ihres Nachteils zu haben. Sie kehren an Lückenbreiten um, welche ihre größeren Artgenos-sen durchaus noch versuchen. Die Taufliegen lernen die größenabhängige Reichweite über die visuelle Rückmeldung während des Laufens (aus Parallaxenbewegung). Da-bei reichen 15 min in strukturierter, heller Umgebung aus. Es gibt keinen festgelegten Beginn der sensiblen Phase. Nach 2 h ist das Gedächtnis jedoch konsolidiert und kann durch Stress nicht mehr zerstört oder durch sensorische Eingänge verändert werden. Dunkel aufgezogene Fliegen wurden ausgewählten Streifenmustern mit spezifischen Raumfrequenzen ausgesetzt. Nur die Insekten, welche mit einem als „optimal“ klassi-fizierten Muster visuell stimuliert wurden, sind in der Lage, die Körperreichweite einzu-schätzen, indem die durchschnittliche Schrittlänge in Verbindung mit der visuellen Wahrnehmung gebracht wird. Überraschenderweise ist es sogar mittels partieller Kompensation der Parallaxen möglich, naive Fliegen so zu trainieren, dass sie sich wie kleinere Exemplare verhalten. Da die Experimente ein Erlernen der Körperreich-weite vermuten lassen, wurden lernmutante Stämme beim Lückenüberwinden getes-tet. Sowohl die Ergebnisse von rut1- und dnc1-Mutanten, als auch das defizitäre Klet-tern von oc1-Fliegen ließ eine Beteiligung der cAMP-abhängigen Lernkaskade in der Protocerebralbrücke (PB) vermuten. Rettungsexperimente der rut1- und dnc1-Hinter-gründe kartierten das Gedächtnis in unterschiedliche Neuronengruppen der PB, wel-che auch für die visuelle Ausrichtung des Kletterns benötigt werden. Erstaunlicher-weise haben laterale lokale PB-Neurone und PFN-Neurone (Projektion von der PB über den fächerförmigen Körper zu den Noduli) verschiedene Erfordernisse für cAMP-Signale. Zusammenfassend weisen die Ergebnisse darauf hin, dass hohe Mengen an cAMP/PKA-Signalen in den latero-lateralen Elementen der PB benötigt werden, wäh-rend kolumnäre PFN-Neurone geringe oder keine Mengen an cAMP/PKA erfordern. Das Körperreichweitengedächtnis ist vermutlich das am längsten andauernde Ge-dächtnis in Drosophila. Wenn es erst einmal konsolidiert ist hält es länger als drei Wo-chen.rnAußerdem kann die Fruchtliege Drosophila melanogaster trainiert werden, die kom-plexe motorische Aufgabe des Lückenkletterns zu optimieren. Die trainierten Fliegen werden erfolgreicher und schneller beim Überqueren von Lücken, welche größer sind als sie selbst. Dabei existiert eine Kurzeitkomponente (STM), die 40 min nach dem ersten Training anhält. Nach weiteren vier Trainingsdurchläufen im Abstand von 20 min wird ein Langzeitgedächtnis (LTM) zum Folgetag geformt. Analysen mit Mutati-onslinien wiesen eine Beteiligung der cAMP-abhängigen Lernkaskade an dieser Ge-dächtnisform auf. Rettungsexperimente des rut2080-Hintergrunds kartierten sowohl das STM, als auch das LTM in PFN-Neuronen. Das STM kann aber ebenso in den alpha- und beta- Loben der Pilzkörper gerettet werden.rnLetztendlich sind wildtypische Fliegen sogar in der Lage, sich an einen Verlust eines Mittelbeintarsuses und dem einhergehenden Fehlen des Adhäsionsorgans am Tarsusende anzupassen. Das Klettern wird zwar sofort schlechter, erholt sich aber bis zum Folgetag wieder auf ein normales Niveau. Dieser neue Zustand erfordert ein Ge-dächtnis für die physischen Möglichkeiten, die nur durch plastische Veränderungen im Nervensystem des Insekts erreicht werden können.