964 resultados para Modeling dynamics


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In this thesis different approaches for the modeling and simulation of the blood protein fibrinogen are presented. The approaches are meant to systematically connect the multiple time and length scales involved in the dynamics of fibrinogen in solution and at inorganic surfaces. The first part of the thesis will cover simulations of fibrinogen on an all atom level. Simulations of the fibrinogen protomer and dimer are performed in explicit solvent to characterize the dynamics of fibrinogen in solution. These simulations reveal an unexpectedly large and fast bending motion that is facilitated by molecular hinges located in the coiled-coil region of fibrinogen. This behavior is characterized by a bending and a dihedral angle and the distribution of these angles is measured. As a consequence of the atomistic detail of the simulations it is possible to illuminate small scale behavior in the binding pockets of fibrinogen that hints at a previously unknown allosteric effect. In a second step atomistic simulations of the fibrinogen protomer are performed at graphite and mica surfaces to investigate initial adsorption stages. These simulations highlight the different adsorption mechanisms at the hydrophobic graphite surface and the charged, hydrophilic mica surface. It is found that the initial adsorption happens in a preferred orientation on mica. Many effects of practical interest involve aggregates of many fibrinogen molecules. To investigate such systems, time and length scales need to be simulated that are not attainable in atomistic simulations. It is therefore necessary to develop lower resolution models of fibrinogen. This is done in the second part of the thesis. First a systematically coarse grained model is derived and parametrized based on the atomistic simulations of the first part. In this model the fibrinogen molecule is represented by 45 beads instead of nearly 31,000 atoms. The intra-molecular interactions of the beads are modeled as a heterogeneous elastic network while inter-molecular interactions are assumed to be a combination of electrostatic and van der Waals interaction. A method is presented that determines the charges assigned to beads by matching the electrostatic potential in the atomistic simulation. Lastly a phenomenological model is developed that represents fibrinogen by five beads connected by rigid rods with two hinges. This model only captures the large scale dynamics in the atomistic simulations but can shed light on experimental observations of fibrinogen conformations at inorganic surfaces.

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This thesis deals with the investigation of charge generation and recombination processes in three different polymer:fullerene photovoltaic blends by means of ultrafast time-resolved optical spectroscopy. The first donor polymer, namely poly[N-11"-henicosanyl-2,7-carbazole-alt-5,5-(4',7'-di-2-thienyl-2',1',3'-benzothiadiazole)] (PCDTBT), is a mid-bandgap polymer, the other two materials are the low-bandgap donor polymers poly[2,6-(4,4-bis-(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b']-dithiophene)-alt-4,7-(2,1,3-benzothiadiazole) (PCPDTBT) and poly[(4,4'-bis(2-ethylhexyl)dithieno[3,2-b:2',3'-d]silole)-2,6-diyl-alt-(2,1,3-benzothiadiazole)-4,7-diyl] (PSBTBT). Despite their broader absorption, the low-bandgap polymers do not show enhanced photovoltaic efficiencies compared to the mid-bandgap system.rnrnTransient absorption spectroscopy revealed that energetic disorder plays an important role in the photophysics of PCDTBT, and that in a blend with PCBM geminate losses are small. The photophysics of the low-bandgap system PCPDTBT were strongly altered by adding a high boiling point cosolvent to the polymer:fullerene blend due to a partial demixing of the materials. We observed an increase in device performance together with a reduction of geminate recombination upon addition of the cosolvent. By applying model-free multi-variate curve resolution to the spectroscopic data, we found that fast non-geminate recombination due to polymer triplet state formation is a limiting loss channel in the low-bandgap material system PCPDTBT, whereas in PSBTBT triplet formation has a smaller impact on device performance, and thus higher efficiencies are obtained.rn

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Introduction: Advances in biotechnology have shed light on many biological processes. In biological networks, nodes are used to represent the function of individual entities within a system and have historically been studied in isolation. Network structure adds edges that enable communication between nodes. An emerging fieldis to combine node function and network structure to yield network function. One of the most complex networks known in biology is the neural network within the brain. Modeling neural function will require an understanding of networks, dynamics, andneurophysiology. It is with this work that modeling techniques will be developed to work at this complex intersection. Methods: Spatial game theory was developed by Nowak in the context of modeling evolutionary dynamics, or the way in which species evolve over time. Spatial game theory offers a two dimensional view of analyzingthe state of neighbors and updating based on the surroundings. Our work builds upon this foundation by studying evolutionary game theory networks with respect to neural networks. This novel concept is that neurons may adopt a particular strategy that will allow propagation of information. The strategy may therefore act as the mechanism for gating. Furthermore, the strategy of a neuron, as in a real brain, isimpacted by the strategy of its neighbors. The techniques of spatial game theory already established by Nowak are repeated to explain two basic cases and validate the implementation of code. Two novel modifications are introduced in Chapters 3 and 4 that build on this network and may reflect neural networks. Results: The introduction of two novel modifications, mutation and rewiring, in large parametricstudies resulted in dynamics that had an intermediate amount of nodes firing at any given time. Further, even small mutation rates result in different dynamics more representative of the ideal state hypothesized. Conclusions: In both modificationsto Nowak's model, the results demonstrate the network does not become locked into a particular global state of passing all information or blocking all information. It is hypothesized that normal brain function occurs within this intermediate range and that a number of diseases are the result of moving outside of this range.

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Signal proteins are able to adapt their response to a change in the environment, governing in this way a broad variety of important cellular processes in living systems. While conventional molecular-dynamics (MD) techniques can be used to explore the early signaling pathway of these protein systems at atomistic resolution, the high computational costs limit their usefulness for the elucidation of the multiscale transduction dynamics of most signaling processes, occurring on experimental timescales. To cope with the problem, we present in this paper a novel multiscale-modeling method, based on a combination of the kinetic Monte-Carlo- and MD-technique, and demonstrate its suitability for investigating the signaling behavior of the photoswitch light-oxygen-voltage-2-Jα domain from Avena Sativa (AsLOV2-Jα) and an AsLOV2-Jα-regulated photoactivable Rac1-GTPase (PA-Rac1), recently employed to control the motility of cancer cells through light stimulus. More specifically, we show that their signaling pathways begin with a residual re-arrangement and subsequent H-bond formation of amino acids near to the flavin-mononucleotide chromophore, causing a coupling between β-strands and subsequent detachment of a peripheral α-helix from the AsLOV2-domain. In the case of the PA-Rac1 system we find that this latter process induces the release of the AsLOV2-inhibitor from the switchII-activation site of the GTPase, enabling signal activation through effector-protein binding. These applications demonstrate that our approach reliably reproduces the signaling pathways of complex signal proteins, ranging from nanoseconds up to seconds at affordable computational costs.

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Our dynamic capillary electrophoresis model which uses material specific input data for estimation of electroosmosis was applied to investigate fundamental aspects of isoelectric focusing (IEF) in capillaries or microchannels made from bare fused-silica (FS), FS coated with a sulfonated polymer, polymethylmethacrylate (PMMA) and poly(dimethylsiloxane) (PDMS). Input data were generated via determination of the electroosmotic flow (EOF) using buffers with varying pH and ionic strength. Two models are distinguished, one that neglects changes of ionic strength and one that includes the dependence between electroosmotic mobility and ionic strength. For each configuration, the models provide insight into the magnitude and dynamics of electroosmosis. The contribution of each electrophoretic zone to the net EOF is thereby visualized and the amount of EOF required for the detection of the zone structures at a particular location along the capillary, including at its end for MS detection, is predicted. For bare FS, PDMS and PMMA, simulations reveal that EOF is decreasing with time and that the entire IEF process is characterized by the asymptotic formation of a stationary steady-state zone configuration in which electrophoretic transport and electroosmotic zone displacement are opposite and of equal magnitude. The location of immobilization of the boundary between anolyte and most acidic carrier ampholyte is dependent on EOF, i.e. capillary material and anolyte. Overall time intervals for reaching this state in microchannels produced by PDMS and PMMA are predicted to be similar and about twice as long compared to uncoated FS. Additional mobilization for the detection of the entire pH gradient at the capillary end is required. Using concomitant electrophoretic mobilization with an acid as coanion in the catholyte is shown to provide sufficient additional cathodic transport for that purpose. FS capillaries dynamically double coated with polybrene and poly(vinylsulfonate) are predicted to provide sufficient electroosmotic pumping for detection of the entire IEF gradient at the cathodic column end.

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EPON 862 is an epoxy resin which is cured with the hardening agent DETDA to form a crosslinked epoxy polymer and is used as a component in modern aircraft structures. These crosslinked polymers are often exposed to prolonged periods of temperatures below glass transition range which cause physical aging to occur. Because physical aging can compromise the performance of epoxies and their composites and because experimental techniques cannot provide all of the necessary physical insight that is needed to fully understand physical aging, efficient computational approaches to predict the effects of physical aging on thermo-mechanical properties are needed. In this study, Molecular Dynamics and Molecular Minimization simulations are being used to establish well-equilibrated, validated molecular models of the EPON 862-DETDA epoxy system with a range of crosslink densities using a united-atom force field. These simulations are subsequently used to predict the glass transition temperature, thermal expansion coefficients, and elastic properties of each of the crosslinked systems for validation of the modeling techniques. The results indicate that glass transition temperature and elastic properties increase with increasing levels of crosslink density and the thermal expansion coefficient decreases with crosslink density, both above and below the glass transition temperature. The results also indicate that there may be an upper limit to crosslink density that can be realistically achieved in epoxy systems. After evaluation of the thermo-mechanical properties, a method is developed to efficiently establish molecular models of epoxy resins that represent the corresponding real molecular structure at specific aging times. Although this approach does not model the physical aging process, it is useful in establishing a molecular model that resembles the physically-aged state for further use in predicting thermo-mechanical properties as a function of aging time. An equation has been predicted based on the results which directly correlate aging time to aged volume of the molecular model. This equation can be helpful for modelers who want to study properties of epoxy resins at different levels of aging but have little information about volume shrinkage occurring during physical aging.

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Volcanoes are the surficial expressions of complex pathways that vent magma and gasses generated deep in the Earth. Geophysical data record at least the partial history of magma and gas movement in the conduit and venting to the atmosphere. This work focuses on developing a more comprehensive understanding of explosive degassing at Fuego volcano, Guatemala through observations and analysis of geophysical data collected in 2005 – 2009. A pattern of eruptive activity was observed during 2005 – 2007 and quantified with seismic and infrasound, satellite thermal and gas measurements, and lava flow lengths. Eruptive styles are related to variable magma flux and accumulation of gas. Explosive degassing was recorded on broadband seismic and infrasound sensors in 2008 and 2009. Explosion energy partitioning between the ground and the atmosphere shows an increase in acoustic energy from 2008 to 2009, indicating a shift toward increased gas pressure in the conduit. Very-long-period (VLP) seismic signals are associated with the strongest explosions recorded in 2009 and waveform modeling in the 10 – 30 s band produces a best-fit source location 300 m west and 300 m below the summit crater. The calculated moment tensor indicates a volumetric source, which is modeled as a dike feeding a SW-dipping (35°) sill. The sill is the dominant component and its projection to the surface nearly intersects the summit crater. The deformation history of the sill is interpreted as: 1) an initial inflation due to pressurization, followed by 2) a rapid deflation as overpressure is explosively release, and finally 3) a reinflation as fresh magma flows into the sill and degasses. Tilt signals are derived from the horizontal components of the seismometer and show repetitive inflation deflation cycles with a 20 minute period coincident with strong explosions. These cycles represent the pressurization of the shallow conduit and explosive venting of overpressure that develops beneath a partially crystallized plug of magma. The energy released during the strong explosions has allowed for imaging of Fuego’s shallow conduit, which appears to have migrated west of the summit crater. In summary, Fuego is becoming more gas charged and its summit centered vent is shifting to the west - serious hazard consequences are likely.

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Reducing the uncertainties related to blade dynamics by the improvement of the quality of numerical simulations of the fluid structure interaction process is a key for a breakthrough in wind-turbine technology. A fundamental step in that direction is the implementation of aeroelastic models capable of capturing the complex features of innovative prototype blades, so they can be tested at realistic full-scale conditions with a reasonable computational cost. We make use of a code based on a combination of two advanced numerical models implemented in a parallel HPC supercomputer platform: First, a model of the structural response of heterogeneous composite blades, based on a variation of the dimensional reduction technique proposed by Hodges and Yu. This technique has the capacity of reducing the geometrical complexity of the blade section into a stiffness matrix for an equivalent beam. The reduced 1-D strain energy is equivalent to the actual 3-D strain energy in an asymptotic sense, allowing accurate modeling of the blade structure as a 1-D finite-element problem. This substantially reduces the computational effort required to model the structural dynamics at each time step. Second, a novel aerodynamic model based on an advanced implementation of the BEM(Blade ElementMomentum) Theory; where all velocities and forces are re-projected through orthogonal matrices into the instantaneous deformed configuration to fully include the effects of large displacements and rotation of the airfoil sections into the computation of aerodynamic forces. This allows the aerodynamic model to take into account the effects of the complex flexo-torsional deformation that can be captured by the more sophisticated structural model mentioned above. In this thesis we have successfully developed a powerful computational tool for the aeroelastic analysis of wind-turbine blades. Due to the particular features mentioned above in terms of a full representation of the combined modes of deformation of the blade as a complex structural part and their effects on the aerodynamic loads, it constitutes a substantial advancement ahead the state-of-the-art aeroelastic models currently available, like the FAST-Aerodyn suite. In this thesis, we also include the results of several experiments on the NREL-5MW blade, which is widely accepted today as a benchmark blade, together with some modifications intended to explore the capacities of the new code in terms of capturing features on blade-dynamic behavior, which are normally overlooked by the existing aeroelastic models.

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The development of innovative carbon-based materials can be greatly facilitated by molecular modeling techniques. Although molecular modeling has been used extensively to predict elastic properties of materials, modeling of more complex phenomenon such as fracture has only recently been possible with the development of new force fields such as ReaxFF, which is used in this work. It is not fully understood what molecular modeling parameters such as thermostat type, thermostat coupling, time step, system size, and strain rate are required for accurate modeling of fracture. Selection of modeling parameters to model fracture can be difficult and non-intuitive compared to modeling elastic properties using traditional force fields, and the errors generated by incorrect parameters may be non-obvious. These molecular modeling parameters are systematically investigated and their effects on the fracture of well-known carbon materials are analyzed. It is determined that for coupling coefficients of 250 fs and greater do not result in substantial differences in the stress-strain response of the materials using any thermostat type. A time step of 0.5 fs of smaller is required for accurate results. Strain rates greater than 2.2 ns-1 are sufficient to obtain repeatable results with slower strain rates for the materials studied. The results of this study indicate that further refinement of the Chenoweth parameter set is required to accurately predict the mechanical response of carbon-based systems. The ReaxFF has been used extensively to model systems in which bond breaking and formation occur. In particular ReaxFF has been used to model reactions of small molecules. Some elastic and fracture properties have been successfully modeled using ReaxFF in materials such as silicon and some metals. However, it is not clear if current parameterizations for ReaxFF are able to accurately reproduce the elastic and fracture properties of carbon materials. The stress-strain response of a new ReaxFF parameterization is compared to the previous parameterization and density functional theory results for well-known carbon materials. The new ReaxFF parameterization makes xv substantial improvements to the predicted mechanical response of carbon materials, and is found to be suitable for modeling the mechanical response of carbon materials. Finally, a new material composed of carbon nanotubes within an amorphous carbon (AC) matrix is modeled using the ReaxFF. Various parameters that may be experimentally controlled are investigated such as nanotube bundling, comparing multi-walled nanotube with single-walled nanotubes, and degree of functionalization of the nanotubes. Elastic and fracture properties are investigated for the composite systems and compared to results of pure-nanotube and pure-AC models. It is found that the arrangement of the nanotubes and degree of crosslinking may substantially affect the properties of the systems, particularly in the transverse directions.

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Polycarbonate (PC) is an important engineering thermoplastic that is currently produced in large industrial scale using bisphenol A and monomers such as phosgene. Since phosgene is highly toxic, a non-phosgene approach using diphenyl carbonate (DPC) as an alternative monomer, as developed by Asahi Corporation of Japan, is a significantly more environmentally friendly alternative. Other advantages include the use of CO2 instead of CO as raw material and the elimination of major waste water production. However, for the production of DPC to be economically viable, reactive-distillation units are needed to obtain the necessary yields by shifting the reaction-equilibrium to the desired products and separating the products at the point where the equilibrium reaction occurs. In the field of chemical reaction engineering, there are many reactions that are suffering from the low equilibrium constant. The main goal of this research is to determine the optimal process needed to shift the reactions by using appropriate control strategies of the reactive distillation system. An extensive dynamic mathematical model has been developed to help us investigate different control and processing strategies of the reactive distillation units to increase the production of DPC. The high-fidelity dynamic models include extensive thermodynamic and reaction-kinetics models while incorporating the necessary mass and energy balance of the various stages of the reactive distillation units. The study presented in this document shows the possibility of producing DPC via one reactive distillation instead of the conventional two-column, with a production rate of 16.75 tons/h corresponding to start reactants materials of 74.69 tons/h of Phenol and 35.75 tons/h of Dimethyl Carbonate. This represents a threefold increase over the projected production rate given in the literature based on a two-column configuration. In addition, the purity of the DPC produced could reach levels as high as 99.5% with the effective use of controls. These studies are based on simulation done using high-fidelity dynamic models.

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PMR-15 polyimide is a polymer that is used as a matrix in composites. These composites with PMR-15 matrices are called advanced polymer matrix composite that is abundantly used in the aerospace and electronics industries because of its high temperature resistivity. Apart from having high temperature sustainability, PMR-15 composites also display good thermal-oxidative stability, mechanical properties, processability and low costs, which makes it a suitable material for manufacturing aircraft structures. PMR-15 uses the reverse Diels-Alder (RDA) method for crosslinking which provides it with the groundwork for its distinctive thermal stability and a range of 280-300 degree Centigrade use temperature. Regardless of such desirable properties, this material has a number of limitations that compromises its application on a large scale basis. PMR-15 composites has been known to be very vulnerable to micro-cracking at inter and intra-laminar cracking. But the major factor that hinders its demand is PMR-15's carcinogenic constituent, methylene dianilineme (MDA), also a liver toxin. The necessity of providing a safe working environment during its production adds up to the cost of this material. In this study, Molecular Dynamics and Energy Minimization techniques are utilized to simulate a structure of PMR-15 at a given density of 1.324 g/cc and an attempt to recreate the polyimide to reduce the number of experimental testing and hence subdue the health hazards as well as the cost involved in its production. Even though this study does not involve in validating any mechanical properties of the model, it could be used in future for the validation of its properties and further testing for different properties like aging, microcracking, creep etc.

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For half a century the integrated circuits (ICs) that make up the heart of electronic devices have been steadily improving by shrinking at an exponential rate. However, as the current crop of ICs get smaller and the insulating layers involved become thinner, electrons leak through due to quantum mechanical tunneling. This is one of several issues which will bring an end to this incredible streak of exponential improvement of this type of transistor device, after which future improvements will have to come from employing fundamentally different transistor architecture rather than fine tuning and miniaturizing the metal-oxide-semiconductor field effect transistors (MOSFETs) in use today. Several new transistor designs, some designed and built here at Michigan Tech, involve electrons tunneling their way through arrays of nanoparticles. We use a multi-scale approach to model these devices and study their behavior. For investigating the tunneling characteristics of the individual junctions, we use a first-principles approach to model conduction between sub-nanometer gold particles. To estimate the change in energy due to the movement of individual electrons, we use the finite element method to calculate electrostatic capacitances. The kinetic Monte Carlo method allows us to use our knowledge of these details to simulate the dynamics of an entire device— sometimes consisting of hundreds of individual particles—and watch as a device ‘turns on’ and starts conducting an electric current. Scanning tunneling microscopy (STM) and the closely related scanning tunneling spectroscopy (STS) are a family of powerful experimental techniques that allow for the probing and imaging of surfaces and molecules at atomic resolution. However, interpretation of the results often requires comparison with theoretical and computational models. We have developed a new method for calculating STM topographs and STS spectra. This method combines an established method for approximating the geometric variation of the electronic density of states, with a modern method for calculating spin-dependent tunneling currents, offering a unique balance between accuracy and accessibility.

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Much of the research in the field of participatory modeling (PM) has focused on the developed world. Few cases are focused on developing regions, and even fewer on Latin American developing countries. The work that has been done in Latin America has often involved water management, often specifically involving water users, and has not focused on the decision making stage of the policy cycle. Little work has been done to measure the effect PM may have on the perceptions and beliefs of decision makers. In fact, throughout the field of PM, very few attempts have been made to quantitatively measure changes in participant beliefs and perceptions following participation. Of the very few exceptions, none have attempted to measure the long-term change in perceptions and beliefs. This research fills that gap. As part of a participatory modeling project in Sonora, Mexico, a region with water quantity and quality problems, I measured the change in beliefs among participants about water models: ability to use and understand them, their usefulness, and their accuracy. I also measured changes in beliefs about climate change, and about water quantity problems, specifically the causes, solutions, and impacts. I also assessed participant satisfaction with the process and outputs from the participatory modeling workshops. Participants were from water agencies, academic institutions, NGOs, and independent consulting firms. Results indicated that participant comfort and self-efficacy with water models, their beliefs in the usefulness of water models, and their beliefs about the impact of water quantity problems changed significantly as a result of the workshops. I present my findings and discuss the results.

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