Computer simulation of the stochastic transport equation

Trabalho apresentado no 37th Conference on Stochastic Processes and their Applications - July 28 - August 01, 2014 -Universidad de Buenos Aires

SPH simulations of clumps formation by dissipative collisions of molecular clouds - II. Magnetic case

We performed computer simulations of interstellar cloud-cloud collisions using the three-dimensional smoothed particle magnetohydrodynamics method. In order to study the role of the magnetic field on the process of collision-triggered fragmentation, we focused our attention on head-on supersonic collisions between two identical spherical molecular-clouds. Two extreme configurations of the magnetic field were adopted: parallel and perpendicular to the initial clouds motion. The initial magnetic field strength was approximately 12.0 muG. In the parallel case, much more of the collision debris were retained in the shocking region than in the non-magnetic case where gas escaped freely throughout the symmetry plane. Differently from the non-magnetic case, eddy-like vortices were formed. The regions of highest vorticity and the the regions of highest density are offset. We found clumps formation only in the parallel case, however, they were larger, hotter and less dense than in the analogous non-magnetic case. In the perpendicular case, the compressed field works as a magnetic wall, preventing a stronger compression of the colliding clouds. This last effect inhibits direct contact of the two clouds. In both cases, we found that the field lines show a chaotic aspect in large scales. Also, the field magnitude is considerably amplified in the shock layer. However, the field distribution is almost coherent in the higher density regions.

A critical investigation of the Tanford-Kirkwood scheme by means of Monte Carlo simulations

Monte Carlo simulations are used to assess the adequacy of the Tanford-Kirkwood prescription for electrostatic interactions in macromolecules. Within a continuum dielectric framework, the approach accurately describes salt screening of electrostatic interactions for moderately charged systems consistent with common proteins at physiological conditions. The limitations of the Debye-Huckel theory, which forms the statistical mechanical basis for the Tanford-Kirkwood result, become apparent for highly charged systems. It is shown, both by an analysis of the Debye-Huckel theory and by numerical simulations, that the difference in dielectric permittivity between macromolecule and surrounding solvent does not play a significant role for salt effects if the macromolecule is highly charged. By comparison to experimental data, the continuum dielectric model (combined with either an approximate effective Hamiltonian as in the Tanford-Kirkwood treatment or with exact Monte Carlo simulations) satisfactorily predicts the effects of charge mutation on metal ion binding constants, but only if the macromolecule and solvent are assigned the same or similar permittivities.

Computer intensive methods for controlling bias in a generalized species diversity index

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

FINITE ELEMENT SIMULATIONS FOR THE COMPREHENSION OF PHYSICAL PHENOMENA INVOLVED IN ELECTRIC IMPEDANCE TOMOGRAPHY OF MASONRY STRUCTURES

The paper describes the preliminary studies of University of Minho on the use of Electric Impedance/Resistance Tomography to assess masonry structures. The study is focused on the analysis of values of current and voltage resulting from the use of an electrical source with voltage and frequency values from a distribution network. The analysis is made from results obtained through computer simulations, using a three-dimensional model of the idealized masonry structures. A finite element program was used for the simulations. Three types of electrodes were used in simulations, and the analysis of the results led to significant conclusions. Later masonry specimens were built and a series of preliminary tests were carried out in the laboratory. The comparative analysis of simulated and experimental results allowed identifying the factors that have influence on the physical results.

Computer simulation of ordering and dynamics in liquid crystals in the bulk and close to the surface

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.

Simulations of charge transport in organic compounds

To aid the design of organic semiconductors, we study the charge transport properties of organic liquid crystals, i.e. hexabenzocoronene and carbazole macrocycle, and single crystals, i.e. rubrene, indolocarbazole and benzothiophene derivatives (BTBT, BBBT). The aim is to find structure-property relationships linking the chemical structure as well as the morphology with the bulk charge carrier mobility of the compounds. To this end, molecular dynamics (MD) simulations are performed yielding realistic equilibrated morphologies. Partial charges and molecular orbitals are calculated based on single molecules in vacuum using quantum chemical methods. The molecular orbitals are then mapped onto the molecular positions and orientations, which allows calculation of the transfer integrals between nearest neighbors using the molecular orbital overlap method. Thus we obtain realistic transfer integral distributions and their autocorrelations. In case of organic crystals the differences between two descriptions of charge transport, namely semi-classical dynamics (SCD) in the small polaron limit and kinetic Monte Carlo (KMC) based on Marcus rates, are studied. The liquid crystals are investigated solely in the hopping limit. To simulate the charge dynamics using KMC, the centers of mass of the molecules are mapped onto lattice sites and the transfer integrals are used to compute the hopping rates. In the small polaron limit, where the electronic wave function is spread over a limited number of neighboring molecules, the Schroedinger equation is solved numerically using a semi-classical approach. The results are compared for the different compounds and methods and, where available, with experimental data. The carbazole macrocycles form columnar structures arranged on a hexagonal lattice with side chains facing inwards, so columns can closely approach each other allowing inter-columnar and thus three-dimensional transport. When taking only intra-columnar transport into account, the mobility is orders of magnitude lower than in the three-dimensional case. BTBT is a promising material for solution-processed organic field-effect transistors. We are able to show that, on the time-scales of charge transport, static disorder due to slow side chain motions is the main factor determining the mobility. The resulting broad transfer integral distributions modify the connectivity of the system but sufficiently many fast percolation paths remain for the charges. Rubrene, indolocarbazole and BBBT are examples of crystals without significant static disorder. The high mobility of rubrene is explained by two main features: first, the shifted cofacial alignment of its molecules, and second, the high center of mass vibrational frequency. In comparsion to SCD, only KMC based on Marcus rates is capable of describing neighbors with low coupling and of taking static disorder into account three-dimensionally. Thus it is the method of choice for crystalline systems dominated by static disorder. However, it is inappropriate for the case of strong coupling and underestimates the mobility of well-ordered crystals. SCD, despite its one-dimensionality, is valuable for crystals with strong coupling and little disorder. It also allows correct treatment of dynamical effects, such as intermolecular vibrations of the molecules. Rate equations are incapable of this, because simulations are performed on static snapshots. We have thus shown strengths and weaknesses of two state of the art models used to study charge transport in organic compounds, partially developed a program to compute and visualize transfer integral distributions and other charge transport properties, and found structure-mobility relations for several promising organic semiconductors.

Modeling and simulations of nanoparticles in liquid crystalline systems

The aim of this work is to investigate, using extensive Monte Carlo computer simulations, composite materials consisting of liquid crystals doped with nanoparticles. These systems are currently of great interest as they offer the possibility of tuning the properties of liquid crystals used in displays and other devices as well as providing a way of obtaining regularly organized systems of nanoparticles exploiting the molecular organization of the liquid crystal medium. Surprisingly enough, there is however a lack of fundamental knowledge on the properties and phase behavior of these hybrid materials, making the route to their application an essentially empirical one. Here we wish to contribute to the much needed rationalization of these systems studying some basic effects induced by different nanoparticles on a liquid crystal host. We investigate in particular the effects of nanoparticle shape, size and polarity as well as of their affinity to the liquid crystal solvent on the stability of the system, monitoring phase transitions, order and molecular organizations. To do this we have proposed a coarse grained approach where nanoparticles are modelled as a suitably shaped (spherical, rod and disk like) collection of spherical Lennard-Jones beads, while the mesogens are represented with Gay-Berne particles. We find that the addition of apolar nanoparticles of different shape typically lowers the nematic–isotropic transition of a non-polar nematic, with the destabilization being greater for spherical nanoparticles. For polar mesogens we have studied the effect of solvent affinity of the nanoparticles showing that aggregation takes places for low solvation values. Interestingly, if the nanoparticles are polar the aggregates contribute to stabilizing the system, compensating the shape effect. We thus find the overall effects on stability to be a delicate balance of often contrasting contributions pointing to the relevance of simulations studies for understanding these complex systems.

Simulations of amphiphilic peptides at the air-water interface

Amphiphile Peptide, Pro-Glu-(Phe-Glu)n-Pro, Pro-Asp-(Phe-Asp)n-Pro, und Phe-Glu-(Phe-Glu)n-Phe, können so aus n alternierenden Sequenzen von hydrophoben und hydrophilen Aminosäuren konstruiert werden, dass sie sich in Monolagen an der Luft-Wasser Grenzfläche anordnen. In biologischen Systemen können Strukturen an der organisch-wässrigen Grenzfläche als Matrix für die Kristallisation von Hydroxyapatit dienen, ein Vorgang der für die Behandlung von Osteoporose verwendet werden kann. In der vorliegenden Arbeit wurden Computersimulationenrneingesetzt, um die Strukturen und die zugrunde liegenden Wechselwirkungen welche die Aggregation der Peptide auf mikroskopischer Ebene steuern, zu untersuchen. Atomistische Molekulardynamik-Simulationen von einzelnen Peptidsträngen zeigen, dass sie sich leicht an der Luft-Wasser Grenzfläche anordnen und die Fähigkeit haben, sich in β-Schleifen zu falten, selbst für relativ kurze Peptidlängen (n = 2). Seltene Ereignisse wie diese (i.e. Konformationsänderungen) erfordern den Einsatz fortgeschrittener Sampling-Techniken. Hier wurde “Replica Exchange” Molekulardynamik verwendet um den Einfluss der Peptidsequenzen zu untersuchen. Die Simulationsergebnisse zeigten, dass Peptide mit kürzeren azidischen Seitenketten (Asp vs. Glu) gestrecktere Konformationen aufwiesen als die mit längeren Seitenketten, die in der Lage waren die Prolin-Termini zu erreichen. Darüber hinaus zeigte sich, dass die Prolin-Termini (Pro vs. Phe) notwendig sind, um eine 2D-Ordnung innerhalb derrnAggregate zu erhalten. Das Peptid Pro-Asp-(Phe-Asp)n-Pro, das beide dieser Eigenschaften enthält, zeigt das geordnetste Verhalten, eine geringe Verdrehung der Hauptkette, und ist in der Lage die gebildeten Aggregate durch Wasserstoffbrücken zwischen den sauren Seitenketten zu stabilisieren. Somit ist dieses Peptid am besten zur Aggregation geeignet. Dies wurde auch durch die Beurteilung der Stabilität von experimentnah-aufgesetzten Peptidaggregaten, sowie der Neigung einzelner Peptide zur Selbstorganisation von anfänglich ungeordneten Konfigurationen unterstützt. Da atomistische Simulationen nur auf kleine Systemgrößen und relativ kurze Zeitskalen begrenzt sind, wird ein vergröbertes Modell entwickelt damit die Selbstorganisation auf einem größeren Maßstab studiert werden kann. Da die Selbstorganisation an der Grenzfläche vonrnInteresse ist, wurden existierenden Vergröberungsmethoden erweitert, um nicht-gebundene Potentiale für inhomogene Systeme zu bestimmen. Die entwickelte Methode ist analog zur iterativen Boltzmann Inversion, bildet aber das Update für das Interaktionspotential basierend auf der radialen Verteilungsfunktion in einer Slab-Geometrie und den Breiten des Slabs und der Grenzfläche. Somit kann ein Kompromiss zwischen der lokalen Flüssigketsstruktur und den thermodynamischen Eigenschaften der Grenzfläche erreicht werden. Die neue Methode wurde für einen Wasser- und einen Methanol-Slab im Vakuum demonstriert, sowie für ein einzelnes Benzolmolekül an der Vakuum-Wasser Grenzfläche, eine Anwendung die von besonderer Bedeutung in der Biologie ist, in der oft das thermodynamische/Grenzflächenpolymerisations-Verhalten zusätzlich der strukturellen Eigenschaften des Systems erhalten werden müssen. Daraufrnbasierend wurde ein vergröbertes Modell über einen Fragment-Ansatz parametrisiert und die Affinität des Peptids zur Vakuum-Wasser Grenzfläche getestet. Obwohl die einzelnen Fragmente sowohl die Struktur als auch die Wahrscheinlichkeitsverteilungen an der Grenzfläche reproduzierten, diffundierte das Peptid als Ganzes von der Grenzfläche weg. Jedoch führte eine Reparametrisierung der nicht-gebundenen Wechselwirkungen für eines der Fragmente der Hauptkette in einem Trimer dazu, dass das Peptid an der Grenzfläche blieb. Dies deutet darauf hin, dass die Kettenkonnektivität eine wichtige Rolle im Verhalten des Petpids an der Grenzfläche spielt.

Computer simulation methods to study interfacial tensions : from the Ising model to colloidal crystals

In condensed matter systems, the interfacial tension plays a central role for a multitude of phenomena. It is the driving force for nucleation processes, determines the shape and structure of crystalline structures and is important for industrial applications. Despite its importance, the interfacial tension is hard to determine in experiments and also in computer simulations. While for liquid-vapor interfacial tensions there exist sophisticated simulation methods to compute the interfacial tension, current methods for solid-liquid interfaces produce unsatisfactory results.rnrnAs a first approach to this topic, the influence of the interfacial tension on nuclei is studied within the three-dimensional Ising model. This model is well suited because despite its simplicity, one can learn much about nucleation of crystalline nuclei. Below the so-called roughening temperature, nuclei in the Ising model are not spherical anymore but become cubic because of the anisotropy of the interfacial tension. This is similar to crystalline nuclei, which are in general not spherical but more like a convex polyhedron with flat facets on the surface. In this context, the problem of distinguishing between the two bulk phases in the vicinity of the diffuse droplet surface is addressed. A new definition is found which correctly determines the volume of a droplet in a given configuration if compared to the volume predicted by simple macroscopic assumptions.rnrnTo compute the interfacial tension of solid-liquid interfaces, a new Monte Carlo method called ensemble switch method'' is presented which allows to compute the interfacial tension of liquid-vapor interfaces as well as solid-liquid interfaces with great accuracy. In the past, the dependence of the interfacial tension on the finite size and shape of the simulation box has often been neglected although there is a nontrivial dependence on the box dimensions. As a consequence, one needs to systematically increase the box size and extrapolate to infinite volume in order to accurately predict the interfacial tension. Therefore, a thorough finite-size scaling analysis is established in this thesis. Logarithmic corrections to the finite-size scaling are motivated and identified, which are of leading order and therefore must not be neglected. The astounding feature of these logarithmic corrections is that they do not depend at all on the model under consideration. Using the ensemble switch method, the validity of a finite-size scaling ansatz containing the aforementioned logarithmic corrections is carefully tested and confirmed. Combining the finite-size scaling theory with the ensemble switch method, the interfacial tension of several model systems, ranging from the Ising model to colloidal systems, is computed with great accuracy.

Molecular dynamics simulations of silicate and borate glasses and melts : structure, diffusion dynamics and vibrational properties

Molecular dynamics simulations of silicate and borate glasses and melts: Structure, diffusion dynamics and vibrational properties. In this work computer simulations of the model glass formers SiO2 and B2O3 are presented, using the techniques of classical molecular dynamics (MD) simulations and quantum mechanical calculations, based on density functional theory (DFT). The latter limits the system size to about 100−200 atoms. SiO2 and B2O3 are the two most important network formers for industrial applications of oxide glasses. Glass samples are generated by means of a quench from the melt with classical MD simulations and a subsequent structural relaxation with DFT forces. In addition, full ab initio quenches are carried out with a significantly faster cooling rate. In principle, the structural properties are in good agreement with experimental results from neutron and X-ray scattering, in all cases. A special focus is on the study of vibrational properties, as they give access to low-temperature thermodynamic properties. The vibrational spectra are calculated by the so-called ”frozen phonon” method. In all cases, the DFT curves show an acceptable agreement with experimental results of inelastic neutron scattering. In case of the model glass former B2O3, a new classical interaction potential is parametrized, based on the liquid trajectory of an ab initio MD simulation at 2300 K. In this course, a structural fitting routine is used. The inclusion of 3-body angular interactions leads to a significantly improved agreement of the liquid properties of the classical MD and ab initio MD simulations. However, the generated glass structures, in all cases, show a significantly lower fraction of 3-membered planar boroxol rings as predicted by experimental results (f=60%-80%). The largest boroxol ring fraction of f=15±5% is observed in the full ab initio quenches from 2300 K. In case of SiO2, the glass structures after the quantum mechanical relaxation are the basis for calculations of the linear thermal expansion coefficient αL(T), employing the quasi-harmonic approximation. The striking observation is a change change of sign of αL(T) going along with a temperature range of negative αL(T) at low temperatures, which is in good agreement with experimental results.

Is virtuality close enough to reality? A comparison of the effectiveness of simulations with traditional laboratory activities in a high school biology class

Some schools do not have ideal access to laboratory space and supplies. Computer simulations of laboratory activities can be a cost-effective way of presenting experiences to students, but are those simulations as effective at supplementing content concepts? This study compared the use of traditional lab activities illustrating the principles of cell respiration and photosynthesis in an introductory high school biology class with virtual simulations of the same activities. Additionally student results were analyzed to assess if student conceptual understanding was affected by the complexity of the simulation. Although all student groups posted average gain increases between the pre and post-tests coupled with positive effect sizes, students who completed the wet lab version of the activity consistently outperformed the students who completed the virtual simulation of the same activity. There was no significant difference between the use of more or less complex simulations. Students also tended to rate the wet lab experience higher on a motivation and interest inventory.

Why Monte Carlo Simulations are Inferences and not Experiments

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

Cerebellar mechanisms for motor learning: Testing predictions from a large-scale computer simulation

The cerebellum is the major brain structure that contributes to our ability to improve movements through learning and experience. We have combined computer simulations with behavioral and lesion studies to investigate how modification of synaptic strength at two different sites within the cerebellum contributes to a simple form of motor learning—Pavlovian conditioning of the eyelid response. These studies are based on the wealth of knowledge about the intrinsic circuitry and physiology of the cerebellum and the straightforward manner in which this circuitry is engaged during eyelid conditioning. Thus, our simulations are constrained by the well-characterized synaptic organization of the cerebellum and further, the activity of cerebellar inputs during simulated eyelid conditioning is based on existing recording data. These simulations have allowed us to make two important predictions regarding the mechanisms underlying cerebellar function, which we have tested and confirmed with behavioral studies. The first prediction describes the mechanisms by which one of the sites of synaptic modification, the granule to Purkinje cell synapses (gr → Pkj) of the cerebellar cortex, could generate two time-dependent properties of eyelid conditioning—response timing and the ISI function. An empirical test of this prediction using small, electrolytic lesions of the cerebellar cortex revealed the pattern of results predicted by the simulations. The second prediction made by the simulations is that modification of synaptic strength at the other site of plasticity, the mossy fiber to deep nuclei synapses (mf → nuc), is under the control of Purkinje cell activity. The analysis predicts that this property should confer mf → nuc synapses with resistance to extinction. Thus, while extinction processes erase plasticity at the first site, residual plasticity at mf → nuc synapses remains. The residual plasticity at the mf → nuc site confers the cerebellum with the capability for rapid relearning long after the learned behavior has been extinguished. We confirmed this prediction using a lesion technique that reversibly disconnected the cerebellar cortex at various stages during extinction and reacquisition of eyelid responses. The results of these studies represent significant progress toward a complete understanding of how the cerebellum contributes to motor learning. ^

Computer Simulation of Crowd Dynamics and Destructive Crowd Behavior

The social processes that lead to destructive behavior in celebratory crowds can be studied through an agent-based computer simulation. Riots are an increasingly common outcome of sports celebrations, and pose the potential for harm to participants, bystanders, property, and the reputation of the groups with whom participants are associated. Rioting cannot necessarily be attributed to the negative emotions of individuals, such as anger, rage, frustration and despair. For instance, the celebratory behavior (e.g., chanting, cheering, singing) during UConn’s “Spring Weekend” and after the 2004 NCAA Championships resulted in several small fires and overturned cars. Further, not every individual in the area of a riot engages in violence, and those who do, do not do so continuously. Instead, small groups carry out the majority of violent acts in relatively short-lived episodes. Agent-based computer simulations are an ideal method for modeling complex group-level social phenomena, such as celebratory gatherings and riots, which emerge from the interaction of relatively “simple” individuals. By making simple assumptions about individuals’ decision-making and behaviors and allowing actors to affect one another, behavioral patterns emerge that cannot be predicted by the characteristics of individuals. The computer simulation developed here models celebratory riot behavior by repeatedly evaluating a single algorithm for each individual, the inputs of which are affected by the characteristics of nearby actors. Specifically, the simulation assumes that (a) actors possess 1 of 5 distinct social identities (group memberships), (b) actors will congregate with actors who possess the same identity, (c) the degree of social cohesion generated in the social context determines the stability of relationships within groups, and (d) actors’ level of aggression is affected by the aggression of other group members. Not only does this simulation provide a systematic investigation of the effects of the initial distribution of aggression, social identification, and cohesiveness on riot outcomes, but also an analytic tool others may use to investigate, visualize and predict how various individual characteristics affect emergent crowd behavior.