992 resultados para LATTICE-DYNAMICAL PROPERTIES


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In this work we study the behavior of the falling motion of neodymium magnets, inside conductive a metallic duct made of copper, aluminum, brass and bronze. We obtain, analyze and present results involving relationships between material and dynamical properties of falling neodymium magnets with the mechanical and electrical properties of conductive materials, such as mass, electrical resistivity, electrical conductivity, length and external diameter

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Pós-graduação em Física - IGCE

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pulmonary surfactant is a very important product in the medical treatment of the syndrome of insufficiency respiratory in neonates. The synthesis of this surfactant in labs need to optimize the rate of spreading in the alveolar interstitial liquid obtaining a monolayer of the phospholipids membrane base capable to maintains several of the dynamical properties of the respiratory system during breathing. The recover of theses mechanical properties has to be archived using the minimal quantities of product and with the optimal proteins composition (SP-B in special). In this paper we show our results of obtaining and process speckle pattern images of the spreading of phospholipids membrane composed the matrix of this product (DPPC) when physiologic interstitial liquid are presented.

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In this work, we have used a combined of atomistic simulation methods to explore the effects of confinement of water molecules between silica surfaces. Firstly, the mechanical properties of water severe confined (~3A) between two silica alpha-quartz was determined based on first principles calculations within the density functional theory (DFT). Simulated annealing methods were employed due to the complex potential energry surface, and the difficulties to avoid local minima. Our results suggest that much of the stiffness of the material (46%) remains, even after the insertion of a water monolayer in the silica. Secondly, in order to access typical time scales for confined systems, classical molecular dynamics was used to determine the dynamical properties of water confined in silica cylindrical pores, with diameters varying from 10 to 40A. in this case we have varied the passivation of the silica surface, from 13% to 100% of SiOH, and the other terminations being SiOH2 and SiOH3, the distribution of the different terminations was obtained with a Monte Carlo simulation. The simulations indicates a lowering of the diffusion coefficientes as the diameter decreases, due to the structuration of hydrogen bonds of water molecules; we have also obtained the density profiles of the confined water and the interfacial tension.

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The comprehensive control of morphology and structure is of extreme importance in semiconducting polymers when used as active layers in optoelectronic devices. In the work reported here, a systematic investigation of the structural and dynamical properties of poly(9,9-di-n-octyl-fluorene-alt-benzothiadiazole), known as F8BT, and their correlation with electrical properties is presented when the material is used as an active layer in optoelectronic devices. By means of X-ray diffraction, one observes that in thick layer films (thickness of about 4 μm) grown by drop-cast deposition, a solvent induced crystalline phase exists which evolves to a stable phase as the temperature is raised. This was not observed in thin films (thickness of about 250 nm) prepared by spin-coating within the investigated temperature range. By modeling the current-voltages characteristics of both thick and thin film devices, important information on the influence of crystallization on the trapping states could be drawn. Furthermore, the temperature dependence of the charge carrier mobility was found to be closely related to that of the molecular relaxation processes. The understanding of the nature of such molecular relaxations, measured by solid-state nuclear magnetic resonance methods, allows one to understand the importance of molecular relaxations and microstructure changes on the trap states of the system.

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The aim of this PhD thesis is to investigate the orientational and dynamical properties of liquid crystalline systems, at molecular level and using atomistic computer simulations, to reach a better understanding of material behavior from a microscopic point view. In perspective this should allow to clarify the relation between the micro and macroscopic properties with the objective of predicting or confirming experimental results on these systems. In this context, we developed four different lines of work in the thesis. The first one concerns the orientational order and alignment mechanism of rigid solutes of small dimensions dissolved in a nematic phase formed by the 4-pentyl,4 cyanobiphenyl (5CB) nematic liquid crystal. The orientational distribution of solutes have been obtained with Molecular Dynamics Simulation (MD) and have been compared with experimental data reported in literature. we have also verified the agreement between order parameters and dipolar coupling values measured in NMR experiments. The MD determined effective orientational potentials have been compared with the predictions of Maier­Saupe and Surface tensor models. The second line concerns the development of a correct parametrization able to reproduce the phase transition properties of a prototype of the oligothiophene semiconductor family: sexithiophene (T6). T6 forms two crystalline polymorphs largely studied, and possesses liquid crystalline phases still not well characterized, From simulations we detected a phase transition from crystal to liquid crystal at about 580 K, in agreement with available experiments, and in particular we found two LC phases, smectic and nematic. The crystal­smectic transition is associated to a relevant density variation and to strong conformational changes of T6, namely the molecules in the liquid crystal phase easily assume a bent shape, deviating from the planar structure typical of the crystal. The third line explores a new approach for calculating the viscosity in a nematic through a virtual exper- iment resembling the classical falling sphere experiment. The falling sphere is replaced by an hydrogenated silicon nanoparticle of spherical shape suspended in 5CB, and gravity effects are replaced by a constant force applied to the nanoparticle in a selected direction. Once the nanoparticle reaches a constant velocity, the viscosity of the medium can be evaluated using Stokes' law. With this method we successfully reproduced experimental viscosities and viscosity anisotropy for the solvent 5CB. The last line deals with the study of order induction on nematic molecules by an hydrogenated silicon surface. Gaining predicting power for the anchoring behavior of liquid crystals at surfaces will be a very desirable capability, as many properties related to devices depend on molecular organization close to surfaces. Here we studied, by means of atomistic MD simulations, the flat interface between an hydrogenated (001) silicon surface in contact with a sample of 5CB molecules. We found a planar anchoring of the first layers of 5CB where surface interactions are dominating with respect to the mesogen intermolecular interactions. We also analyzed the interface 5CB­vacuum, finding a homeotropic orientation of the nematic at this interface.

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Ziel der vorliegenden Arbeit ist die Aufklärung von Struktur und Dynamik komplexer supramolekularer Systeme mittels Festkörper NMR Spektroskopie. Die Untersuchung von pi-pi Wechselwirkungen, welche einen entscheidenden Einfluss auf die strukturellen und dynamischen Eigenschaften supra- molekularer Systeme haben, hilft dabei, die Selbst- organisationsprozesse dieser komplexen Materialien besser zu verstehen. Mit dipolaren 1H-1H and 1H-13C Wiedereinkopplungs NMR Methoden unter schnellem MAS können sowohl 1H chemische Verschiebungen als auch dipolare 1H-1H und 1H-13C Kopplungen untersucht werden, ohne dass eine Isotopenmarkierung erforderlich ist. So erhält man detaillierte Informationen über die Struktur und die Beweglichkeit einzelner Molekül- segmente. In Verbindung mit sogenannten nucleus independent chemical shift (NICS) maps (berechnet mit ab-initio Methoden) lassen sich Abstände von Protonen relativ zu pi-Elektronensystemen bestimmen und so Strukturvorschläge ableiten. Mit Hilfe von homo- und heteronuklearen dipolaren Rotationsseitenbandenmustern könnenaußerdem Ordnungs- parameter für verschiedene Molekülsegmente bestimmt werden. Die auf diese Weise gewonnenen Informationen über die strukturellen und dynamischen Eigenschaften supramolekularer Systeme tragen dazu bei, strukturbestimmende Molekül- einheiten und Hauptordnungsphänomene zu identifizieren sowie lokale Wechselwirkungen zu quantifizieren, um so den Vorgang der Selbstorganisation besser zu verstehen.

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Granular matter, also known as bulk solids, consists of discrete particles with sizes between micrometers and meters. They are present in many industrial applications as well as daily life, like in food processing, pharmaceutics or in the oil and mining industry. When handling granular matter the bulk solids are stored, mixed, conveyed or filtered. These techniques are based on observations in macroscopic experiments, i.e. rheological examinations of the bulk properties. Despite the amply investigations of bulk mechanics, the relation between single particle motion and macroscopic behavior is still not well understood. For exploring the microscopic properties on a single particle level, 3D imaging techniques are required.rnThe objective of this work was the investigation of single particle motions in a bulk system in 3D under an external mechanical load, i.e. compression and shear. During the mechanical load the structural and dynamical properties of these systems were examined with confocal microscopy. Therefor new granular model systems in the wet and dry state were designed and prepared. As the particles are solid bodies, their motion is described by six degrees of freedom. To explore their entire motion with all degrees of freedom, a technique to visualize the rotation of spherical micrometer sized particles in 3D was developed. rnOne of the foci during this dissertation was a model system for dry cohesive granular matter. In such systems the particle motion during a compression of the granular matter was investigated. In general the rotation of single particles was the more sensitive parameter compared to the translation. In regions with large structural changes the rotation had an earlier onset than the translation. In granular systems under shear, shear dilatation and shear zone formation were observed. Globally the granular sediments showed a shear behavior, which was known already from classical shear experiments, for example with Jenike cells. Locally the shear zone formation was enhanced, when near the applied load a pre-diluted region existed. In regions with constant volume fraction a mixing between the different particle layers occurred. In particular an exchange of particles between the current flowing region and the non-flowing region was observed. rnThe second focus was on model systems for wet granular matter, where an additional binding liquid is added to the particle suspension. To examine the 3D structure of the binding liquid on the micrometer scale independently from the particles, a second illumination and detection beam path was implemented. In shear and compression experiments of wet clusters and bulk systems completely different dynamics compared to dry cohesive models systems occured. In a Pickering emulsion-like system large structural changes predominantly occurred in the local environment of binding liquid droplets. These large local structural changes were due to an energy interplay between the energy stored in the binding droplet during its deformation and the binding energy of particles at the droplet interface. rnConfocal microscopy in combination with nanoindentation gave new insights into the single particle motions and dynamics of granular systems under a mechanical load. These novel experimental results can help to improve the understanding of the relationship between bulk properties of granular matter, such as volume fraction or yield stress and the dynamics on a single particle level.rnrn

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In der vorliegenden Forschungsarbeit wird die Konkurrenz von Kristallisation und Verglasung in metastabilen kolloidalen Hart-Kugel(HK)-Modellsystemen mit dynamischer und zeitaufgelöster statischer Lichtstreuung untersucht. Durch gleichzeitige Messungen mit beiden Methoden an derselben Probe gelang es, mit hoher Genauigkeit und aussagekräftiger Statistik nachzuweisen, dass in beiden Systemklassen eine starke Korrelation der strukturellen und dynamischen Eigenschaften vorliegt und diese Korrelation zu quantifizieren. Ein zentraler Teil der Arbeit bestand in dem Aufbau einer geeigneten Lichtstreuanlage mit der erstmalig Messungen der Dynamik und der Struktur simultan an derselben nicht-ergodischen Probe durchgeführt werden konnten. Für die dynamische Lichtstreuung wurde ein Flächendetektor (CCD-Kamera) verwendet. In Kombination mit einer speziellen Detektionsoptik ermöglicht dies, die gleichzeitige Detektion von Streulicht aus unterschiedlichen Probenbereichen (Subensembles). Damit kann gleichzeitig die Dynamik in unterschiedlichen Subensembles mit einer Auflösung von 15,8x15,8µm2 untersucht werden. Die Lichtstreuanlage wurde ausführlich charakterisiert und ihre korrekte Funktionsweise mithilfe von Vergleichsmessungen an etablierten Lichtstreuanlagen bestätigt. Die zeitliche Entwicklung der Dynamik und der Struktur von metastabilen Proben wurde unterhalb, am und oberhalb des Glasübergangs quantifiziert. Dabei zeigte das untersuchte kolloidale HK-Modellsystem alle typischen Eigenschaften eines HK-Systems. Die kristallisierenden Proben zeigten das etablierte zweistufige Kristallisationsszenario mit entsprechender Kristallisationskinetik und die Glasproben zeigten das erwartete Alterungsverhalten. Bei dem zweistufigen Kristallisationsszenario kommt es zuerst zur Nukleation einer metastabilen Zwischenphase von sogenannten Precursorn. In einer zweiten Stufe bilden sich Kristallite innerhalb dieser Precursor. Durch Vergleich zwischen kristallisierenden und verglasenden Proben konnte auch während der Verglasung die Bildung von Precursorn beobachtet werden. Die Korrelation zwischen der Anzahl an Precursorn und der Partikeldynamik legt die Vermutung nahe, dass das immer noch unverstandene Phänomen der Alterung von Gläsern mit der Bildung von Precursorn zusammenhängt. Verhinderte Kristallisation führt zu einer starken Verlangsamung der Partikeldynamik. Die Partikeldynamik einer Probe am Glasübergang zeigt, dass die Probe vor Einsetzen der Kristallisation eine glasartige Dynamik aufwies. Dies legt die Vermutung nahe, dass einkomponentige kolloidale HK-Gläser den Gleichgewichtszustand (Kristall) auf langen Zeitskalen erreichen können. Durch die Untersuchung der Partikeldynamik von metastabilen Proben in einzelnen Subensembles konnte eine heterogene Verteilung der Partikeldynamik nachgewiesen werden. Es existieren Bereiche, in denen die Partikeldynamik schneller oder langsamer ist als in anderen Bereichen. Gleichzeitig zeigen die Messungen der strukturellen Eigenschaften, dass metastabile Proben auch heterogen bezüglich ihrer Struktur sind. Mithilfe dieser Messungen konnte die zeitliche Entwicklung des Anteils an langsamen Partikeln und des Anteils an Partikeln innerhalb von Objekten höherer Ordnung (Precursor/Kristallite) bestimmt werden. Es zeigte sich eine direkte Korrelation zwischen dem Anteil an langsamen Partikeln und dem Anteil an Partikeln in Objekten höherer Ordnung. Die Untersuchung der Dynamik und der Struktur in einzelnen Subensembles lieferte einen weiteren Hinweis darauf, dass Subensembles, in denen eine stärker ausgeprägte strukturelle Ordnung vorliegt, auch bevorzugt eine langsamere Partikeldynamik aufweisen.

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Hot Jupiters, due to the proximity to their parent stars, are subjected to a strong irradiating flux that governs their radiative and dynamical properties. We compute a suite of three-dimensional circulation models with dual-band radiative transfer, exploring a relevant range of irradiation temperatures, both with and without temperature inversions. We find that, for irradiation temperatures T irr lsim 2000 K, heat redistribution is very efficient, producing comparable dayside and nightside fluxes. For T irr ≈ 2200-2400 K, the redistribution starts to break down, resulting in a high day-night flux contrast. Our simulations indicate that the efficiency of redistribution is primarily governed by the ratio of advective to radiative timescales. Models with temperature inversions display a higher day-night contrast due to the deposition of starlight at higher altitudes, but we find this opacity-driven effect to be secondary compared to the effects of irradiation. The hotspot offset from the substellar point is large when insolation is weak and redistribution is efficient, and decreases as redistribution breaks down. The atmospheric flow can be potentially subjected to the Kelvin-Helmholtz instability (as indicated by the Richardson number) only in the uppermost layers, with a depth that penetrates down to pressures of a few millibars at most. Shocks penetrate deeper, down to several bars in the hottest model. Ohmic dissipation generally occurs down to deeper levels than shock dissipation (to tens of bars), but the penetration depth varies with the atmospheric opacity. The total dissipated Ohmic power increases steeply with the strength of the irradiating flux and the dissipation depth recedes into the atmosphere, favoring radius inflation in the most irradiated objects. A survey of the existing data, as well as the inferences made from them, reveals that our results are broadly consistent with the observational trends.

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El cerebro humano es probablemente uno de los sistemas más complejos a los que nos enfrentamos en la actualidad, si bien es también uno de los más fascinantes. Sin embargo, la compresión de cómo el cerebro organiza su actividad para llevar a cabo tareas complejas es un problema plagado de restos y obstáculos. En sus inicios la neuroimagen y la electrofisiología tenían como objetivo la identificación de regiones asociadas a activaciones relacionadas con tareas especificas, o con patrones locales que variaban en el tiempo dada cierta actividad. Sin embargo, actualmente existe un consenso acerca de que la actividad cerebral tiene un carácter temporal multiescala y espacialmente extendido, lo que lleva a considerar el cerebro como una gran red de áreas cerebrales coordinadas, cuyas conexiones funcionales son continuamente creadas y destruidas. Hasta hace poco, el énfasis de los estudios de la actividad cerebral funcional se han centrado en la identidad de los nodos particulares que forman estas redes, y en la caracterización de métricas de conectividad entre ellos: la hipótesis subyacente es que cada nodo, que es una representación mas bien aproximada de una región cerebral dada, ofrece a una única contribución al total de la red. Por tanto, la neuroimagen funcional integra los dos ingredientes básicos de la neuropsicología: la localización de la función cognitiva en módulos cerebrales especializados y el rol de las fibras de conexión en la integración de dichos módulos. Sin embargo, recientemente, la estructura y la función cerebral han empezado a ser investigadas mediante la Ciencia de la Redes, una interpretación mecánico-estadística de una antigua rama de las matemáticas: La teoría de grafos. La Ciencia de las Redes permite dotar a las redes funcionales de una gran cantidad de propiedades cuantitativas (robustez, centralidad, eficiencia, ...), y así enriquecer el conjunto de elementos que describen objetivamente la estructura y la función cerebral a disposición de los neurocientíficos. La conexión entre la Ciencia de las Redes y la Neurociencia ha aportado nuevos puntos de vista en la comprensión de la intrincada anatomía del cerebro, y de cómo las patrones de actividad cerebral se pueden sincronizar para generar las denominadas redes funcionales cerebrales, el principal objeto de estudio de esta Tesis Doctoral. Dentro de este contexto, la complejidad emerge como el puente entre las propiedades topológicas y dinámicas de los sistemas biológicos y, específicamente, en la relación entre la organización y la dinámica de las redes funcionales cerebrales. Esta Tesis Doctoral es, en términos generales, un estudio de cómo la actividad cerebral puede ser entendida como el resultado de una red de un sistema dinámico íntimamente relacionado con los procesos que ocurren en el cerebro. Con este fin, he realizado cinco estudios que tienen en cuenta ambos aspectos de dichas redes funcionales: el topológico y el dinámico. De esta manera, la Tesis está dividida en tres grandes partes: Introducción, Resultados y Discusión. En la primera parte, que comprende los Capítulos 1, 2 y 3, se hace un resumen de los conceptos más importantes de la Ciencia de las Redes relacionados al análisis de imágenes cerebrales. Concretamente, el Capitulo 1 está dedicado a introducir al lector en el mundo de la complejidad, en especial, a la complejidad topológica y dinámica de sistemas acoplados en red. El Capítulo 2 tiene como objetivo desarrollar los fundamentos biológicos, estructurales y funcionales del cerebro, cuando éste es interpretado como una red compleja. En el Capítulo 3, se resumen los objetivos esenciales y tareas que serán desarrolladas a lo largo de la segunda parte de la Tesis. La segunda parte es el núcleo de la Tesis, ya que contiene los resultados obtenidos a lo largo de los últimos cuatro años. Esta parte está dividida en cinco Capítulos, que contienen una versión detallada de las publicaciones llevadas a cabo durante esta Tesis. El Capítulo 4 está relacionado con la topología de las redes funcionales y, específicamente, con la detección y cuantificación de los nodos mas importantes: aquellos denominados “hubs” de la red. En el Capítulo 5 se muestra como las redes funcionales cerebrales pueden ser vistas no como una única red, sino más bien como una red-de-redes donde sus componentes tienen que coexistir en una situación de balance funcional. De esta forma, se investiga cómo los hemisferios cerebrales compiten para adquirir centralidad en la red-de-redes, y cómo esta interacción se mantiene (o no) cuando se introducen fallos deliberadamente en la red funcional. El Capítulo 6 va un paso mas allá al considerar las redes funcionales como sistemas vivos. En este Capítulo se muestra cómo al analizar la evolución de la topología de las redes, en vez de tratarlas como si estas fueran un sistema estático, podemos caracterizar mejor su estructura. Este hecho es especialmente relevante cuando se quiere tratar de encontrar diferencias entre grupos que desempeñan una tarea de memoria, en la que las redes funcionales tienen fuertes fluctuaciones. En el Capítulo 7 defino cómo crear redes parenclíticas a partir de bases de datos de actividad cerebral. Este nuevo tipo de redes, recientemente introducido para estudiar las anormalidades entre grupos de control y grupos anómalos, no ha sido implementado nunca en datos cerebrales y, en este Capítulo explico cómo hacerlo cuando se quiere evaluar la consistencia de la dinámica cerebral. Para concluir esta parte de la Tesis, el Capítulo 8 se centra en la relación entre las propiedades topológicas de los nodos dentro de una red y sus características dinámicas. Como mostraré más adelante, existe una relación entre ellas que revela que la posición de un nodo dentro una red está íntimamente correlacionada con sus propiedades dinámicas. Finalmente, la última parte de esta Tesis Doctoral está compuesta únicamente por el Capítulo 9, el cual contiene las conclusiones y perspectivas futuras que pueden surgir de los trabajos expuestos. En vista de todo lo anterior, espero que esta Tesis aporte una perspectiva complementaria sobre uno de los más extraordinarios sistemas complejos frente a los que nos encontramos: El cerebro humano. ABSTRACT The human brain is probably one of the most complex systems we are facing, thus being a timely and fascinating object of study. Characterizing how the brain organizes its activity to carry out complex tasks is highly non-trivial. While early neuroimaging and electrophysiological studies typically aimed at identifying patches of task-specific activations or local time-varying patterns of activity, there has now been consensus that task-related brain activity has a temporally multiscale, spatially extended character, as networks of coordinated brain areas are continuously formed and destroyed. Up until recently, though, the emphasis of functional brain activity studies has been on the identity of the particular nodes forming these networks, and on the characterization of connectivity metrics between them, the underlying covert hypothesis being that each node, constituting a coarse-grained representation of a given brain region, provides a unique contribution to the whole. Thus, functional neuroimaging initially integrated the two basic ingredients of early neuropsychology: localization of cognitive function into specialized brain modules and the role of connection fibres in the integration of various modules. Lately, brain structure and function have started being investigated using Network Science, a statistical mechanics understanding of an old branch of pure mathematics: graph theory. Network Science allows endowing networks with a great number of quantitative properties, thus vastly enriching the set of objective descriptors of brain structure and function at neuroscientists’ disposal. The link between Network Science and Neuroscience has shed light about how the entangled anatomy of the brain is, and how cortical activations may synchronize to generate the so-called functional brain networks, the principal object under study along this PhD Thesis. Within this context, complexity appears to be the bridge between the topological and dynamical properties of biological systems and, more specifically, the interplay between the organization and dynamics of functional brain networks. This PhD Thesis is, in general terms, a study of how cortical activations can be understood as the output of a network of dynamical systems that are intimately related with the processes occurring in the brain. In order to do that, I performed five studies that encompass both the topological and the dynamical aspects of such functional brain networks. In this way, the Thesis is divided into three major parts: Introduction, Results and Discussion. In the first part, comprising Chapters 1, 2 and 3, I make an overview of the main concepts of Network Science related to the analysis of brain imaging. More specifically, Chapter 1 is devoted to introducing the reader to the world of complexity, specially to the topological and dynamical complexity of networked systems. Chapter 2 aims to develop the biological, topological and functional fundamentals of the brain when it is seen as a complex network. Next, Chapter 3 summarizes the main objectives and tasks that will be developed along the forthcoming Chapters. The second part of the Thesis is, in turn, its core, since it contains the results obtained along these last four years. This part is divided into five Chapters, containing a detailed version of the publications carried out during the Thesis. Chapter 4 is related to the topology of functional networks and, more specifically, to the detection and quantification of the leading nodes of the network: the hubs. In Chapter 5 I will show that functional brain networks can be viewed not as a single network, but as a network-of-networks, where its components have to co-exist in a trade-off situation. In this way, I investigate how the brain hemispheres compete for acquiring the centrality of the network-of-networks and how this interplay is maintained (or not) when failures are introduced in the functional network. Chapter 6 goes one step beyond by considering functional networks as living systems. In this Chapter I show how analyzing the evolution of the network topology instead of treating it as a static system allows to better characterize functional networks. This fact is especially relevant when trying to find differences between groups performing certain memory tasks, where functional networks have strong fluctuations. In Chapter 7 I define how to create parenclitic networks from brain imaging datasets. This new kind of networks, recently introduced to study abnormalities between control and anomalous groups, have not been implemented with brain datasets and I explain in this Chapter how to do it when evaluating the consistency of brain dynamics. To conclude with this part of the Thesis, Chapter 8 is devoted to the interplay between the topological properties of the nodes within a network and their dynamical features. As I will show, there is an interplay between them which reveals that the position of a node in a network is intimately related with its dynamical properties. Finally, the last part of this PhD Thesis is composed only by Chapter 9, which contains the conclusions and future perspectives that may arise from the exposed results. In view of all, I hope that reading this Thesis will give a complementary perspective of one of the most extraordinary complex systems: The human brain.

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The purpose of this Project is, first and foremost, to disclose the topic of nonlinear vibrations and oscillations in mechanical systems and, namely, nonlinear normal modes NNMs to a greater audience of researchers and technicians. To do so, first of all, the dynamical behavior and properties of nonlinear mechanical systems is outlined from the analysis of a pair of exemplary models with the harmonic balanced method. The conclusions drawn are contrasted with the Linear Vibration Theory. Then, it is argued how the nonlinear normal modes could, in spite of their limitations, predict the frequency response of a mechanical system. After discussing those introductory concepts, I present a Matlab package called 'NNMcont' developed by a group of researchers from the University of Liege. This package allows the analysis of nonlinear normal modes of vibration in a range of mechanical systems as extensions of the linear modes. This package relies on numerical methods and a 'continuation algorithm' for the computation of the nonlinear normal modes of a conservative mechanical system. In order to prove its functionality, a two degrees of freedom mechanical system with elastic nonlinearities is analized. This model comprises a mass suspended on a foundation by means of a spring-viscous damper mechanism -analogous to a very simplified model of most suspended structures and machines- that has attached a mass damper as a passive vibration control system. The results of the computation are displayed on frequency energy plots showing the NNMs branches along with modal curves and time-series plots for each normal mode. Finally, a critical analysis of the results obtained is carried out with an eye on devising what they can tell the researcher about the dynamical properties of the system.

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Using molecular dynamics (MD) simulations, we explore the structural and dynamical properties of siRNA within the intercalated environment of a Mg:Al 2:1 Layered Double Hydroxide (LDH) nanoparticle. An ab initio force field (Condensed-phase Optimized Molecular Potentials for Atomistic Simulation Studies: COMPASS) is used for the MD simulations of the hybrid organic-inorganic systems. The structure, arrangement, mobility, close contacts and hydrogen bonds associated with the intercalated RNA are examined and contrasted with those of the isolated RNA. Computed powder X-ray diffraction patterns are also compared with related LDH-DNA experiments. As a method of probing whether the intercalated environment approximates the crystalline or rather the aqueous state, we explore the stability of the principle parameters (e.g., the major groove width) that differentiate both A- and A'- crystalline forms of siRNA and contrast this with recent findings for the same siRNA simulated in water. We find the crystalline forms remain structurally distinct when intercalated, whereas this is not the case in water. Implications for the stability of hybrid LDH-RNA systems are discussed.

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This thesis presents a two-dimensional water model investigation and development of a multiscale method for the modelling of large systems, such as virus in water or peptide immersed in the solvent. We have implemented a two-dimensional ‘Mercedes Benz’ (MB) or BN2D water model using Molecular Dynamics. We have studied its dynamical and structural properties dependence on the model’s parameters. For the first time we derived formulas to calculate thermodynamic properties of the MB model in the microcanonical (NVE) ensemble. We also derived equations of motion in the isothermal–isobaric (NPT) ensemble. We have analysed the rotational degree of freedom of the model in both ensembles. We have developed and implemented a self-consistent multiscale method, which is able to communicate micro- and macro- scales. This multiscale method assumes, that matter consists of the two phases. One phase is related to micro- and the other to macroscale. We simulate the macro scale using Landau Lifshitz-Fluctuating Hydrodynamics, while we describe the microscale using Molecular Dynamics. We have demonstrated that the communication between the disparate scales is possible without introduction of fictitious interface or approximations which reduce the accuracy of the information exchange between the scales. We have investigated control parameters, which were introduced to control the contribution of each phases to the matter behaviour. We have shown, that microscales inherit dynamical properties of the macroscales and vice versa, depending on the concentration of each phase. We have shown, that Radial Distribution Function is not altered and velocity autocorrelation functions are gradually transformed, from Molecular Dynamics to Fluctuating Hydrodynamics description, when phase balance is changed. In this work we test our multiscale method for the liquid argon, BN2D and SPC/E water models. For the SPC/E water model we investigate microscale fluctuations which are computed using advanced mapping technique of the small scales to the large scales, which was developed by Voulgarakisand et. al.