Dynamic weighting in Monte Carlo and optimization

Dynamic importance weighting is proposed as a Monte Carlo method that has the capability to sample relevant parts of the configuration space even in the presence of many steep energy minima. The method relies on an additional dynamic variable (the importance weight) to help the system overcome steep barriers. A non-Metropolis theory is developed for the construction of such weighted samplers. Algorithms based on this method are designed for simulation and global optimization tasks arising from multimodal sampling, neural network training, and the traveling salesman problem. Numerical tests on these problems confirm the effectiveness of the method.

How optimization of potential functions affects protein folding.

The relationship between the optimization of the potential function and the foldability of theoretical protein models is studied based on investigations of a 27-mer cubic-lattice protein model and a more realistic lattice model for the protein crambin. In both the simple and the more complicated systems, optimization of the energy parameters achieves significant improvements in the statistical-mechanical characteristics of the systems and leads to foldable protein models in simulation experiments. The foldability of the protein models is characterized by their statistical-mechanical properties--e.g., by the density of states and by Monte Carlo folding simulations of the models. With optimized energy parameters, a high level of consistency exists among different interactions in the native structures of the protein models, as revealed by a correlation function between the optimized energy parameters and the native structure of the model proteins. The results of this work are relevant to the design of a general potential function for folding proteins by theoretical simulations.

Progress toward chemical accuracy in the computer simulation of condensed phase reactions.

We describe a procedure for the generation of chemically accurate computer-simulation models to study chemical reactions in the condensed phase. The process involves (i) the use of a coupled semiempirical quantum and classical molecular mechanics method to represent solutes and solvent, respectively; (ii) the optimization of semiempirical quantum mechanics (QM) parameters to produce a computationally efficient and chemically accurate QM model; (iii) the calibration of a quantum/classical microsolvation model using ab initio quantum theory; and (iv) the use of statistical mechanical principles and methods to simulate, on massively parallel computers, the thermodynamic properties of chemical reactions in aqueous solution. The utility of this process is demonstrated by the calculation of the enthalpy of reaction in vacuum and free energy change in aqueous solution for a proton transfer involving methanol, methoxide, imidazole, and imidazolium, which are functional groups involved with proton transfers in many biochemical systems. An optimized semiempirical QM model is produced, which results in the calculation of heats of formation of the above chemical species to within 1.0 kcal/mol (1 kcal = 4.18 kJ) of experimental values. The use of the calibrated QM and microsolvation QM/MM (molecular mechanics) models for the simulation of a proton transfer in aqueous solution gives a calculated free energy that is within 1.0 kcal/mol (12.2 calculated vs. 12.8 experimental) of a value estimated from experimental pKa values of the reacting species.

Identification of the mRNA targets of tRNA-­specific regulation using genome-­wide simulation of translation

FUNDING Biotechnology and Biological Sciences Research Council (BBSRC) [BB/I020926/1 to I.S.]; BBSRC PhD studentship award [C103817D to I.S. and M.C.R.]; Scottish Universities Life Science Alliance PhD studentship award (to M.C.R. and I.S.]. Funding for open access charge: BBSRC. Conflict of interest statement. None declared.

Simulação e modelagem computacional de dados de espalhamento à baixos ângulos - enfoque em estruturas de alta simetria

Esta tese apresenta uma abordagem para a criação rápida de modelos em diferentes geometrias (complexas ou de alta simetria) com objetivo de calcular a correspondente intensidade espalhada, podendo esta ser utilizada na descrição de experimentos de es- palhamento à baixos ângulos. A modelagem pode ser realizada com mais de 100 geome- trias catalogadas em um Banco de Dados, além da possibilidade de construir estruturas a partir de posições aleatórias distribuídas na superfície de uma esfera. Em todos os casos os modelos são gerados por meio do método de elementos finitos compondo uma única geometria, ou ainda, compondo diferentes geometrias, combinadas entre si a partir de um número baixo de parâmetros. Para realizar essa tarefa foi desenvolvido um programa em Fortran, chamado de Polygen, que permite modelar geometrias convexas em diferentes formas, como sólidos, cascas, ou ainda com esferas ou estruturas do tipo DNA nas arestas, além de usar esses modelos para simular a curva de intensidade espalhada para sistemas orientados e aleatoriamente orientados. A curva de intensidade de espalhamento é calculada por meio da equação de Debye e os parâmetros que compõe cada um dos modelos, podem ser otimizados pelo ajuste contra dados experimentais, por meio de métodos de minimização baseados em simulated annealing, Levenberg-Marquardt e algorítmicos genéticos. A minimização permite ajustar os parâmetros do modelo (ou composição de modelos) como tamanho, densidade eletrônica, raio das subunidades, entre outros, contribuindo para fornecer uma nova ferramenta para modelagem e análise de dados de espalhamento. Em outra etapa desta tese, é apresentado o design de modelos atomísticos e a sua respectiva simulação por Dinâmica Molecular. A geometria de dois sistemas auto-organizado de DNA na forma de octaedro truncado, um com linkers de 7 Adeninas e outro com linkers de ATATATA, foram escolhidas para realizar a modelagem atomística e a simulação por Dinâmica Molecular. Para este sistema são apresentados os resultados de Root Mean Square Deviations (RMSD), Root Mean Square Fluctuations (RMSF), raio de giro, torção das hélices duplas de DNA além da avaliação das ligações de Hidrogênio, todos obtidos por meio da análise de uma trajetória de 50 ns.

Solução rasterizada para o problema de empacotamento de fita irregular utilizando a Montanha Voronoi.

O empacotamento irregular de fita é um grupo de problemas na área de corte e empacotamento, cuja aplicação é observada nas indústrias têxtil, moveleira e construção naval. O problema consiste em definir uma configuração de itens irregulares de modo que o comprimento do contêiner retangular que contém o leiaute seja minimizado. A solução deve ser válida, isto é, não deve haver sobreposição entre os itens, que não devem extrapolar as paredes do contêiner. Devido a aspectos práticos, são admitidas até quatro orientações para o item. O volume de material desperdiçado está diretamente relacionado à qualidade do leiaute obtido e, por este motivo, uma solução eficiente pressupõe uma vantagem econômica e resulta em um menor impacto ambiental. O objetivo deste trabalho consiste na geração automática de leiautes de modo a obter níveis de compactação e tempo de processamento compatíveis com outras soluções na literatura. A fim de atingir este objetivo, são realizadas duas propostas de solução. A primeira consiste no posicionamento sequencial dos itens de modo a maximizar a ocorrência de posições de encaixe, que estão relacionadas à restrição de movimento de um item no leiaute. Em linhas gerais, várias sequências de posicionamentos são exploradas com o objetivo de encontrar a solução mais compacta. Na segunda abordagem, que consiste na principal proposta deste trabalho, métodos rasterizados são aplicados para movimentar itens de acordo com uma grade de posicionamento, admitindo sobreposição. O método é baseado na estratégia de minimização de sobreposição, cujo objetivo é a eliminação da sobreposição em um contêiner fechado. Ambos os algoritmos foram testados utilizando o mesmo conjunto de problemas de referência da literatura. Foi verificado que a primeira estratégia não foi capaz de obter soluções satisfatórias, apesar de fornecer informações importantes sobre as propriedades das posições de encaixe. Por outro lado, a segunda abordagem obteve resultados competitivos. O desempenho do algoritmo também foi compatível com outras soluções, inclusive em casos nos quais o volume de dados era alto. Ademais, como trabalho futuro, o algoritmo pode ser estendido de modo a possibilitar a entrada de itens de geometria genérica, o que pode se tornar o grande diferencial da proposta.

Oxide Semiconductors For Organic Opto-electronic Devices

Development of transparent oxide semiconductors (TOS) from Earth-abundant materials is of great interest for cost-effective thin film device applications, such as solar cells, light emitting diodes (LEDs), touch-sensitive displays, electronic paper, and transparent thin film transistors. The need of inexpensive or high performance electrode might be even greater for organic photovoltaic (OPV), with the goal to harvest renewable energy with inexpensive, lightweight, and cost competitive materials. The natural abundance of zinc and the wide bandgap ($sim$3.3 eV) of its oxide make it an ideal candidate. In this dissertation, I have introduced various concepts on the modulations of various surface, interface and bulk opto-electronic properties of ZnO based semiconductor for charge transport, charge selectivity and optimal device performance. I have categorized transparent semiconductors into two sub groups depending upon their role in a device. Electrodes, usually 200 to 500 nm thick, optimized for good transparency and transporting the charges to the external circuit. Here, the electrical conductivity in parallel direction to thin film, i.e bulk conductivity is important. And contacts, usually 5 to 50 nm thick, are optimized in case of solar cells for providing charge selectivity and asymmetry to manipulate the built in field inside the device for charge separation and collection. Whereas in Organic LEDs (OLEDs), contacts provide optimum energy level alignment at organic oxide interface for improved charge injections. For an optimal solar cell performance, transparent electrodes are designed with maximum transparency in the region of interest to maximize the light to pass through to the absorber layer for photo-generation, plus they are designed for minimum sheet resistance for efficient charge collection and transport. As such there is need for material with high conductivity and transparency. Doping ZnO with some common elements such as B, Al, Ga, In, Ge, Si, and F result in n-type doping with increase in carriers resulting in high conductivity electrode, with better or comparable opto-electronic properties compared to current industry-standard indium tin oxide (ITO). Furthermore, improvement in mobility due to improvement on crystallographic structure also provide alternative path for high conductivity ZnO TCOs. Implementing these two aspects, various studies were done on gallium doped zinc oxide (GZO) transparent electrode, a very promising indium free electrode. The dynamics of the superimposed RF and DC power sputtering was utilized to improve the microstructure during the thin films growth, resulting in GZO electrode with conductivity greater than 4000 S/cm and transparency greater than 90 %. Similarly, various studies on research and development of Indium Zinc Tin Oxide and Indium Zinc Oxide thin films which can be applied to flexible substrates for next generation solar cells application is presented. In these new TCO systems, understanding the role of crystallographic structure ranging from poly-crystalline to amorphous phase and the influence on the charge transport and optical transparency as well as important surface passivation and surface charge transport properties. Implementation of these electrode based on ZnO on opto-electronics devices such as OLED and OPV is complicated due to chemical interaction over time with the organic layer or with ambient. The problem of inefficient charge collection/injection due to poor understanding of interface and/or bulk property of oxide electrode exists at several oxide-organic interfaces. The surface conductivity, the work function, the formation of dipoles and the band-bending at the interfacial sites can positively or negatively impact the device performance. Detailed characterization of the surface composition both before and after various chemicals treatment of various oxide electrode can therefore provide insight into optimization of device performance. Some of the work related to controlling the interfacial chemistry associated with charge transport of transparent electrodes are discussed. Thus, the role of various pre-treatment on poly-crystalline GZO electrode and amorphous indium zinc oxide (IZO) electrode is compared and contrasted. From the study, we have found that removal of defects and self passivating defects caused by accumulation of hydroxides in the surface of both poly-crystalline GZO and amorphous IZO, are critical for improving the surface conductivity and charge transport. Further insight on how these insulating and self-passivating defects cause charge accumulation and recombination in an device is discussed. With recent rapid development of bulk-heterojunction organic photovoltaics active materials, devices employing ZnO and ZnO based electrode provide air stable and cost-competitive alternatives to traditional inorganic photovoltaics. The organic light emitting diodes (OLEDs) have already been commercialized, thus to follow in the footsteps of this technology, OPV devices need further improvement in power conversion efficiency and stable materials resulting in long device lifetimes. Use of low work function metals such as Ca/Al in standard geometry do provide good electrode for electron collection, but serious problems using low work-function metal electrodes originates from the formation of non-conductive metal oxide due to oxidation resulting in rapid device failure. Hence, using low work-function, air stable, conductive metal oxides such as ZnO as electrons collecting electrode and high work-function, air stable metals such as silver for harvesting holes, has been on the rise. Devices with degenerately doped ZnO functioning as transparent conductive electrode, or as charge selective layer in a polymer/fullerene based heterojunction, present useful device structures for investigating the functional mechanisms within OPV devices and a possible pathway towards improved air-stable high efficiency devices. Furthermore, analysis of the physical properties of the ZnO layers with varying thickness, crystallographic structure, surface chemistry and grain size deposited via various techniques such as atomic layer deposition, sputtering and solution-processed ZnO with their respective OPV device performance is discussed. We find similarity and differences in electrode property for good charge injection in OLEDs and good charge collection in OPV devices very insightful in understanding physics behind device failures and successes. In general, self-passivating surface of amorphous TCOs IZO, ZTO and IZTO forms insulating layer that hinders the charge collection. Similarly, we find modulation of the carrier concentration and the mobility in electron transport layer, namely zinc oxide thin films, very important for optimizing device performance.

Models and methods for the direct simulation of rough and micropatterned surfaces

Friction in hydrodynamic bearings are a major source of losses in car engines ([69]). The extreme loading conditions in those bearings lead to contact between the matching surfaces. In such conditions not only the overall geometry of the bearing is relevant, but also the small-scale topography of the surface determines the bearing performance. The possibility of shaping the surface of lubricated bearings down to the micrometer ([57]) opened the question of whether friction can be reduced by mean of micro-textures, with mixed results. This work focuses in the development of efficient numerical methods to solve thin film (lubrication) problems down to the roughness scale of measured surfaces. Due to the high velocities and the convergent-divergent geometries of hydrodynamic bearings, cavitation takes place. To treat cavitation in the lubrication problem the Elrod- Adams model is used, a mass-conserving model which has proven in careful numerical ([12]) and experimental ([119]) tests to be essential to obtain physically meaningful results. Another relevant aspect of the modeling is that the bearing inertial effects are considered, which is necessary to correctly simulate moving textures. As an application, the effects of micro-texturing the moving surface of the bearing were studied. Realistic values are assumed for the physical parameters defining the problems. Extensive fundamental studies were carried out in the hydrodynamic lubrication regime. Mesh-converged simulations considering the topography of real measured surfaces were also run, and the validity of the lubrication approximation was assessed for such rough surfaces.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

The influence of magnetic field geometry on magnetars X-ray spectra

Nowadays, the analysis of the X-ray spectra of magnetically powered neutron stars or magnetars is one of the most valuable tools to gain insight into the physical processes occurring in their interiors and magnetospheres. In particular, the magnetospheric plasma leaves a strong imprint on the observed X-ray spectrum by means of Compton up-scattering of the thermal radiation coming from the star surface. Motivated by the increased quality of the observational data, much theoretical work has been devoted to develop Monte Carlo (MC) codes that incorporate the effects of resonant Compton scattering (RCS) in the modeling of radiative transfer of photons through the magnetosphere. The two key ingredients in this simulations are the kinetic plasma properties and the magnetic field (MF) configuration. The MF geometry is expected to be complex, but up to now only mathematically simple solutions (self-similar solutions) have been employed. In this work, we discuss the effects of new, more realistic, MF geometries on synthetic spectra. We use new force-free solutions [14] in a previously developed MC code [9] to assess the influence of MF geometry on the emerging spectra. Our main result is that the shape of the final spectrum is mostly sensitive to uncertain parameters of the magnetospheric plasma, but the MF geometry plays an important role on the angle-dependence of the spectra.

Multi-objective optimization of environmentally conscious chemical supply chains under demand uncertainty

In this work, we analyze the effect of demand uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear program (MILP) with the unique feature of incorporating explicitly the demand uncertainty using scenarios with given probability of occurrence. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact.

Water adsorption in hydrophilic zeolites: experiment and simulation

We have measured experimental adsorption isotherms of water in zeolite LTA4A, and studied the regeneration process by performing subsequent adsorption cycles after degassing at different temperatures. We observed incomplete desorption at low temperatures, and cation rearrangement at successive adsorption cycles. We also developed a new molecular simulation force field able to reproduce experimental adsorption isotherms in the range of temperatures between 273 K and 374 K. Small deviations observed at high pressures are attributed to the change in the water dipole moment at high loadings. The force field correctly describes the preferential adsorption sites of water at different pressures. We tested the influence of the zeolite structure, framework flexibility, and cation mobility when considering adsorption and diffusion of water. Finally, we performed checks on force field transferability between different hydrophilic zeolite types, concluding that classical, non-polarizable water force fields are not transferable.

Coupled Biomechanical Response of the Cornea Assessed by Non-Contact Tonometry. A Simulation Study

The mechanical response of the cornea subjected to a non-contact air-jet tonometry diagnostic test represents an interplay between its geometry, the corneal material behavior and the loading. The objective is to study this interplay to better understand and interpret the results obtained with a non-contact tonometry test. A patient-specific finite element model of a healthy eye, accounting for the load free configuration, was used. The corneal tissue was modeled as an anisotropic hyperelastic material with two preferential directions. Three different sets of parameters within the human experimental range obtained from inflation tests were considered. The influence of the IOP was studied by considering four pressure levels (10–28 mmHg) whereas the influence of corneal thickness was studied by inducing a uniform variation (300–600 microns). A Computer Fluid Dynamics (CFD) air-jet simulation determined pressure loading exerted on the anterior corneal surface. The maximum apex displacement showed a linear variation with IOP for all materials examined. On the contrary, the maximum apex displacement followed a cubic relation with corneal thickness. In addition, a significant sensitivity of the apical displacement to the corneal stiffness was also obtained. Explanation to this behavior was found in the fact that the cornea experiences bending when subjected to an air-puff loading, causing the anterior surface to work in compression whereas the posterior surface works in tension. Hence, collagen fibers located at the anterior surface do not contribute to load bearing. Non-contact tonometry devices give useful information that could be misleading since the corneal deformation is the result of the interaction between the mechanical properties, IOP, and geometry. Therefore, a non-contact tonometry test is not sufficient to evaluate their individual contribution and a complete in-vivo characterization would require more than one test to independently determine the membrane and bending corneal behavior.

Earth’s Rotation: A Challenging Problem in Mathematics and Physics

A suitable knowledge of the orientation and motion of the Earth in space is a common need in various fields. That knowledge has been ever necessary to carry out astronomical observations, but with the advent of the space age, it became essential for making observations of satellites and predicting and determining their orbits, and for observing the Earth from space as well. Given the relevant role it plays in Space Geodesy, Earth rotation is considered as one of the three pillars of Geodesy, the other two being geometry and gravity. Besides, research on Earth rotation has fostered advances in many fields, such as Mathematics, Astronomy and Geophysics, for centuries. One remarkable feature of the problem is in the extreme requirements of accuracy that must be fulfilled in the near future, about a millimetre on the tangent plane to the planet surface, roughly speaking. That challenges all of the theories that have been devised and used to-date; the paper makes a short review of some of the most relevant methods, which can be envisaged as milestones in Earth rotation research, emphasizing the Hamiltonian approach developed by the authors. Some contemporary problems are presented, as well as the main lines of future research prospected by the International Astronomical Union/International Association of Geodesy Joint Working Group on Theory of Earth Rotation, created in 2013.

Controlled rippling of graphene via irradiation and applied strain modify its mechanical properties: a nanoindentation simulation study

Ripples, present in free standing graphene, have an important influence in the mechanical behavior of this two-dimensional material. In this work we show through nanoindentation simulations, how out-of-plane displacements can be modified by strain resulting in softening of the membrane under compression and stiffening under tension. Irradiation also induces changes in the mechanical properties of graphene. Interestingly, compressed samples, irradiated at low doses are stiffened by the irradiation while samples under tensile strain do not show significant changes in their mechanical properties. These simulations indicate that vacancies, produced by the energetic ions, cannot be the ones directly responsible for this behavior. However, changes in roughness induced by the momentum transferred from the energetic ions to the membrane, can explain these differences. These results provide an alternative explanation to recent experimental observations of stiffening of graphene under low dose irradiation, as well as paths to tailor the mechanical properties of this material via applied strain and irradiation.