聚甲基丙烯酸甲酯/(苯乙烯-丙烯腈)共聚物混合体系的早期分离

本文用激光光散射技术研究了高分子混合体系聚甲基丙烯酸甲酯/(苯乙烯-丙烯腈)共聚物(PMMA/PSAN)不稳相分离(Spinodal decomposition)过程,结果指出,相分离前期符合Cahn理论预言的结果;首次用光散射技术在高分子混合体系相分离研究中得到了不稳相分离增长速率最大值R(q_m);只(q)的实验结果与理论值相吻合;证实了界面自由能对相分离增长速率的影响是不可忽略的。

An Investigation into the Role of Polymeric Carriers on Crystal Growth within Amorphous Solid Dispersion Systems

Using phase diagrams derived from Flory–Huggins theory, we defined the thermodynamic state of amorphous felodipine within three different polymeric carriers. Variation in the solubility and miscibility of felodipine within different polymeric materials (using F–H theory) has been identified and used to select the most suitable polymeric carriers for the production of amorphous drug–polymer solid dispersions. With this information, amorphous felodipine solid dispersions were manufactured using three different polymeric materials (HPMCAS-HF, Soluplus, and PVPK15) at predefined drug loadings, and the crystal growth rates of felodipine from these solid dispersions were investigated. Crystallization of amorphous felodipine was studied using Raman spectral imaging and polarized light microscopy. Using this data, we examined the correlation among several characteristics of solid dispersions to the crystal growth rate of felodipine. An exponential relationship was found to exist between drug loading and crystal growth rate. Moreover, crystal growth within all selected amorphous drug–polymer solid dispersion systems were viscosity dependent (η–ξ). The exponent, ξ, was estimated to be 1.36 at a temperature of 80 °C. Values of ξ exceeding 1 may indicate strong viscosity dependent crystal growth in the amorphous drug–polymer solid dispersion systems. We argue that the elevated exponent value (ξ > 1) is a result of drug–polymer mixing which leads to a less fragile amorphous drug–polymer solid dispersion system. All systems investigated displayed an upper critical solution temperature, and the solid–liquid boundary was always higher than the spinodal decomposition curve. Furthermore, for PVP–FD amorphous dispersions at drug loadings exceeding 0.6 volume ratio, the mechanism of phase separation within the metastable zone was found to be driven by nucleation and growth rather than liquid–liquid separation.

Properties of self-assembled diluted magnetic semiconductor nanostructures

Este trabalho centra-se na investigação da possibilidade de se conseguir um semicondutor magnético diluído (SMD) baseado em ZnO. Foi levado a cabo um estudo detalhado das propriedades magnéticas e estruturais de estruturas de ZnO, nomeadamente nanofios (NFs), nanocristais (NCs) e filmes finos, dopadas com metais de transição (MTs). Foram usadas várias técnicas experimentais para caracterizar estas estruturas, designadamente difracção de raios-X, microscopia electrónica de varrimento, ressonância magnética, SQUID, e medidas de transporte. Foram incorporados substitucionalmente nos sítios do Zn iões de Mn2+ e Co2+ em ambos os NFs e NCs de ZnO. Revelou-se para ambos os iões dopantes, que a incorporação é heterogénea, uma vez que parte do sinal de ressonância paramagnética electrónica (RPE) vem de iões de MTs em ambientes distorcidos ou enriquecidos com MTs. A partir das intensidades relativas dos espectros de RPE e de modificações da superfície, demonstra-se ainda que os NCs exibem uma estrutura core-shell. Os resultados, evidenciam que, com o aumento da concentração de MTs, a dimensão dos NCs diminui e aumentam as distorções da rede. Finalmente, no caso dos NCs dopados com Mn, obteve-se o resultado singular de que a espessura da shell é da ordem de 0.3 nm e de que existe uma acumulação de Mn na mesma. Com o objectivo de esclarecer o papel dos portadores de carga na medição das interacções ferromagnéticas, foram co-dopados filmes de ZnO com Mn e Al ou com Co e Al. Os filmes dopados com Mn, revelaram-se simplesmente paramagnéticos, com os iões de Mn substitucionais nos sítios do Zn. Por outro lado, os filmes dopados com Co exibem ferromagnetismo fraco não intrínseco, provavelmente devido a decomposição spinodal. Foram ainda efectuados estudos comparativos com filmes de ligas de Zn1-xFexO. Como era de esperar, detectaram-se segundas fases de espinela e de óxido de ferro nestas ligas; todas as amostras exibiam curvas de histerese a 300 K. Estes resultados suportam a hipótese de que as segundas fases são responsáveis pelo comportamento magnético observado em muitos sistemas baseados em ZnO. Não se observou nenhuma evidência de ferromagnetismo mediado por portadores de carga. As experiências mostram que a análise de RPE permite demonstrar directamente se e onde estão incorporados os iões de MTs e evidenciam a importância dos efeitos de superfície para dimensões menores que ~15 nm, para as quais se formam estruturas core-shell. As investigações realizadas no âmbito desta tese demonstram que nenhuma das amostras de ZnO estudadas exibiram propriedades de um SMD intrínseco e que, no futuro, são necessários estudos teóricos e experimentais detalhados das interacções de troca entre os iões de MTs e os átomos do ZnO para determinar a origem das propriedades magnéticas observadas.

Incorporating memory effects in phase separation processes

We consider the modification of the Cahn-Hilliard equation when a time delay process through a memory function is taken into account. We then study the process of spinodal decomposition in fast phase transitions associated with a conserved order parameter. Finite-time memory effects are seen to affect the dynamics of phase transition at short times and have the effect of delaying, in a significant way, the process of rapid growth of the order parameter that follows a quench into the spinodal region. These effects are important in several systems characterized by fast processes, like non-equilibrium dynamics in the early universe and in relativistic heavy-ion collisions. (C) 2006 Elsevier B.V. All rights reserved.

Numerical approximation of the Ginzburg-Landau equation with memory effects in the dynamics of phase transitions

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Langevin dynamics of the deconfinement transition for pure gauge theory

We investigate the effects of dissipation in the deconfinement transition for pure SU(2) and SU(3) gauge theories. Using an effective theory for the order parameter, we study its Langevin evolution numerically. Noise effects are included for the case of SU(2). We find that both dissipation and noise have dramatic effects on the spinodal decomposition of the order parameter and delay considerably its thermalization. For SU(3) the effects of dissipation are even larger than for SU(2).

The aggregation process in tetraethoxysilane-derived sonogels as an analogy to the critical phenomenon

The structural evolution in silica sols prepared from tetraethoxysilane (TEOS) sonohydrolysis was studied 'in situ' using small-angle x-ray scattering (SAXS). The structure of the gelling system can be reasonably well described by a correlation function given by gamma(r) similar to (1/R(2))(1/r) exp(- r/xi), where xi is the structure correlation length and R is a chain persistence length, as an analogy to the Ornstein-Zernike theory in describing critical phenomenon. This approach is also expected for the scattering from some linear and branched molecules as polydisperse coils of linear chains and random f-functional branched polycondensates. The characteristic length. grows following an approximate power law with time t as xi similar to t(1) (with the exponent quite close to 1) while R remains undetermined but with a constant value, except at the beginning of the process in which the growth of. is slower and R increases by only about 15% with respect to the value of the initial sol. The structural evolution with time is compatible with an aggregation process by a phase separation by coarsening. The mechanism of growth seems to be faster than those typically observed for pure diffusion controlled cluster-cluster aggregation. This suggests that physical forces (hydrothermal forces) could be actuating together with diffusion in the gelling process of this system. The data apparently do not support a spinodal decomposition mechanism, at least when starting from the initial stable acid sol studied here.

Interface morphology snapshots of vertically segregated thin films of semiconducting polymer/polystyrene blends

We present atomic force microscopic images of the interphase morphology of vertically segregated thin films spin coated from two-component mixtures of poly[2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenylene-vinylene] (MEH-PPV) and polystyrene (PS). We investigate the mechanism leading to the formation of wetting layers and lateral structures during spin coating using different PS molecular weights, solvents and blend compositions. Spinodal decomposition competes with the formation of surface enrichment layers. The spinodal wavelength as a function of PS molecular weight follows a power-law similar to bulk-like spinodal decomposition. Our experimental results indicate that length scales of interface topographical features can be adjusted from the nanometer to micrometer range. The importance of controlled arrangement of semiconducting polymers in thin film geometries for organic optoelectronic device applications is discussed. (c) 2007 Elsevier Ltd. All rights reserved.

Uso de métodos químicos para obtener polvos cerámicos del sistema (Sn, Ti)O2

The (Sn,Ti)O2, system has a great interest due to its technological applications such as gas sensor and varistor. Although the thermodynamic properties and the kinetics of spinoidal decomposition in this system have been extensively studied, the general properties and applications of SnO2 - TiO2 binary compositions have been not investigated yet in depth. On the other hand, little work has been done to optimize the synthesis methods to obtain (Sn,Ti)O2 cerallmic powders, with pre - determinate physical and chemical characteristics. In this work the ceramic powders has been obtained by coprecipitation and polymeric precursor (Pechini) methods. The different physical chemistry phenomena that occurred during the synthesis were discussed. The (Sn,Ti)O2, ceramic powders were characterized with X- ray diffraction (XRD), thermal analysis (DTA/TG) and scanning electron microscopy (SEM). The knowledge about of steps and variables of synthesis process acquired with development of this work, we permited to obtain (Sn, Ti)O2, nanometers particles to low temperatures: to 450°C for coprecipitation method and to 600°C for Pechini method. The spinodal decomposition that ocurr to 900°C was discussed also.

Zusammenhang zwischen der Einzelkettendynamik und der Dynamik von Konzentrationsfluktuationen in mehrkomponentigen Polymersystemen

Zusammmenfassung:Um Phasenseparation in binären Polymermischungen zuuntersuchen, werden zwei dynamische Erweiterungen der selbstkonsistenten Feldtheorie (SCFT)entwickelt. Die erste Methode benutzt eine zeitliche Entwicklung der Dichten und wird dynamische selbstkonsistente Feldtheorie (DSCFT) genannt, während die zweite Methode die zeitliche Propagation der effektiven äußeren Felder der SCFT ausnutzt. Diese Methode wird mit External Potential Dynamics (EPD) bezeichnet. Für DSCFT werden kinetische Koeffizienten verwendet, die entweder die lokale Dynamik von Punktteilchen oder die nichtlokale Dynamik von Rouse'schen Polymeren nachbilden. Die EPD-Methode erzeugt mit einem konstanten kinetischen Koeffizienten die Dynamik von Rouse'schen Ketten und benötigt weniger Rechenzeit als DSCFT. Diese Methoden werden für verschiedene Systeme angewendet.Zuerst wird spinodale Entmischung im Volumen untersucht,wobei der Unterschied zwischen lokaler und nichtlokalerDynamik im Mittelpunkt steht. Um die Gültigkeit derErgebnisse zu überprüfen, werden Monte-Carlo-Simulationen durchgeführt. In Polymermischungen, die von zwei Wänden, die beide die gleiche Sorte Polymere bevorzugen, eingeschränkt werden, wird die Bildung von Anreicherungsschichten an den Wänden untersucht. Für dünne Polymerfilme zwischen antisymmetrischen Wänden, d.h. jede Wand bevorzugt eine andere Polymerspezies, wird die Spannung einer parallel zu den Wänden gebildeten Grenzfläche analysiert und der Phasenübergang von einer anfänglich homogenen Mischung zur lokalisierten Phase betrachtet. Des Weiteren wird die Dynamik von Kapillarwellenmoden untersucht.

Use of Eutectic Mixtures for Preparation of Monolithic Carbons with CO2-Adsorption and Gas-Separation Capabilities

With global warming becoming one of the main problems our society is facing nowadays, there is an urgent demand to develop materials suitable for CO2 storage as well as for gas separation. Within this context, hierarchical porous structures are of great interest for in-flow applications because of the desirable combination of an extensive internal reactive surface along narrow nanopores with facile molecular transport through broad “highways” leading to and from these pores. Deep eutectic solvents (DESs) have been recently used in the synthesis of carbon monoliths exhibiting a bicontinuous porous structure composed of continuous macroporous channels and a continuous carbon network that contains a certain microporosity and provides considerable surface area. In this work, we have prepared two DESs for the preparation of two hierarchical carbon monoliths with different compositions (e.g., either nitrogen-doped or not) and structure. It is worth noting that DESs played a capital role in the synthesis of hierarchical carbon monoliths not only promoting the spinodal decomposition that governs the formation of the bicontinuous porous structure but also providing the precursors required to tailor the composition and the molecular sieve structure of the resulting carbons. We have studied the performance of these two carbons for CO2, N2, and CH4 adsorption in both monolithic and powdered form. We have also studied the selective adsorption of CO2 versus CH4 in equilibrium and dynamic conditions. We found that these materials combined a high CO2-sorption capacity besides an excellent CO2/N2 and CO2/CH4 selectivity and, interestingly, this performance was preserved when processed in both monolithic and powdered form.

Combinatorial logic synthesis using technology directed decomposition

The aim of logic synthesis is to produce circuits which satisfy the given boolean function while meeting timing constraints and requiring the minimum silicon area. Logic synthesis involves two steps namely logic decomposition and technology mapping. Existing methods treat the two as separate operation. The traditional approach is to minimize the number of literals without considering the target technology during the decomposition phase. The decomposed expressions are then mapped on to the target technology to optimize the area, Timing optimization is carried out subsequently, A new approach which treats logic decomposition and technology maping as a single operation is presented. The logic decomposition is based on the parameters of the target technology. The area and timing optimization is carried out during logic decomposition phase itself. Results using MCNC circuits are presented to show that this method produces circuits which are 38% faster while requiring 14% increase in area.

Strong Connectivity in Directed Hypergraphs and its Application to the Atomic Decomposition of Ontologies

Los hipergrafos dirigidos se han empleado en problemas relacionados con lógica proposicional, bases de datos relacionales, linguística computacional y aprendizaje automático. Los hipergrafos dirigidos han sido también utilizados como alternativa a los grafos (bipartitos) dirigidos para facilitar el estudio de las interacciones entre componentes de sistemas complejos que no pueden ser fácilmente modelados usando exclusivamente relaciones binarias. En este contexto, este tipo de representación es conocida como hiper-redes. Un hipergrafo dirigido es una generalización de un grafo dirigido especialmente adecuado para la representación de relaciones de muchos a muchos. Mientras que una arista en un grafo dirigido define una relación entre dos de sus nodos, una hiperarista en un hipergrafo dirigido define una relación entre dos conjuntos de sus nodos. La conexión fuerte es una relación de equivalencia que divide el conjunto de nodos de un hipergrafo dirigido en particiones y cada partición define una clase de equivalencia conocida como componente fuertemente conexo. El estudio de los componentes fuertemente conexos de un hipergrafo dirigido puede ayudar a conseguir una mejor comprensión de la estructura de este tipo de hipergrafos cuando su tamaño es considerable. En el caso de grafo dirigidos, existen algoritmos muy eficientes para el cálculo de los componentes fuertemente conexos en grafos de gran tamaño. Gracias a estos algoritmos, se ha podido averiguar que la estructura de la WWW tiene forma de “pajarita”, donde más del 70% del los nodos están distribuidos en tres grandes conjuntos y uno de ellos es un componente fuertemente conexo. Este tipo de estructura ha sido también observada en redes complejas en otras áreas como la biología. Estudios de naturaleza similar no han podido ser realizados en hipergrafos dirigidos porque no existe algoritmos capaces de calcular los componentes fuertemente conexos de este tipo de hipergrafos. En esta tesis doctoral, hemos investigado como calcular los componentes fuertemente conexos de un hipergrafo dirigido. En concreto, hemos desarrollado dos algoritmos para este problema y hemos determinado que son correctos y cuál es su complejidad computacional. Ambos algoritmos han sido evaluados empíricamente para comparar sus tiempos de ejecución. Para la evaluación, hemos producido una selección de hipergrafos dirigidos generados de forma aleatoria inspirados en modelos muy conocidos de grafos aleatorios como Erdos-Renyi, Newman-Watts-Strogatz and Barabasi-Albert. Varias optimizaciones para ambos algoritmos han sido implementadas y analizadas en la tesis. En concreto, colapsar los componentes fuertemente conexos del grafo dirigido que se puede construir eliminando ciertas hiperaristas complejas del hipergrafo dirigido original, mejora notablemente los tiempos de ejecucion de los algoritmos para varios de los hipergrafos utilizados en la evaluación. Aparte de los ejemplos de aplicación mencionados anteriormente, los hipergrafos dirigidos han sido también empleados en el área de representación de conocimiento. En concreto, este tipo de hipergrafos se han usado para el cálculo de módulos de ontologías. Una ontología puede ser definida como un conjunto de axiomas que especifican formalmente un conjunto de símbolos y sus relaciones, mientras que un modulo puede ser entendido como un subconjunto de axiomas de la ontología que recoge todo el conocimiento que almacena la ontología sobre un conjunto especifico de símbolos y sus relaciones. En la tesis nos hemos centrado solamente en módulos que han sido calculados usando la técnica de localidad sintáctica. Debido a que las ontologías pueden ser muy grandes, el cálculo de módulos puede facilitar las tareas de re-utilización y mantenimiento de dichas ontologías. Sin embargo, analizar todos los posibles módulos de una ontología es, en general, muy costoso porque el numero de módulos crece de forma exponencial con respecto al número de símbolos y de axiomas de la ontología. Afortunadamente, los axiomas de una ontología pueden ser divididos en particiones conocidas como átomos. Cada átomo representa un conjunto máximo de axiomas que siempre aparecen juntos en un modulo. La decomposición atómica de una ontología es definida como un grafo dirigido de tal forma que cada nodo del grafo corresponde con un átomo y cada arista define una dependencia entre una pareja de átomos. En esta tesis introducimos el concepto de“axiom dependency hypergraph” que generaliza el concepto de descomposición atómica de una ontología. Un modulo en una ontología correspondería con un componente conexo en este tipo de hipergrafos y un átomo de una ontología con un componente fuertemente conexo. Hemos adaptado la implementación de nuestros algoritmos para que funcionen también con axiom dependency hypergraphs y poder de esa forma calcular los átomos de una ontología. Para demostrar la viabilidad de esta idea, hemos incorporado nuestros algoritmos en una aplicación que hemos desarrollado para la extracción de módulos y la descomposición atómica de ontologías. A la aplicación la hemos llamado HyS y hemos estudiado sus tiempos de ejecución usando una selección de ontologías muy conocidas del área biomédica, la mayoría disponibles en el portal de Internet NCBO. Los resultados de la evaluación muestran que los tiempos de ejecución de HyS son mucho mejores que las aplicaciones más rápidas conocidas. ABSTRACT Directed hypergraphs are an intuitive modelling formalism that have been used in problems related to propositional logic, relational databases, computational linguistic and machine learning. Directed hypergraphs are also presented as an alternative to directed (bipartite) graphs to facilitate the study of the interactions between components of complex systems that cannot naturally be modelled as binary relations. In this context, they are known as hyper-networks. A directed hypergraph is a generalization of a directed graph suitable for representing many-to-many relationships. While an edge in a directed graph defines a relation between two nodes of the graph, a hyperedge in a directed hypergraph defines a relation between two sets of nodes. Strong-connectivity is an equivalence relation that induces a partition of the set of nodes of a directed hypergraph into strongly-connected components. These components can be collapsed into single nodes. As result, the size of the original hypergraph can significantly be reduced if the strongly-connected components have many nodes. This approach might contribute to better understand how the nodes of a hypergraph are connected, in particular when the hypergraphs are large. In the case of directed graphs, there are efficient algorithms that can be used to compute the strongly-connected components of large graphs. For instance, it has been shown that the macroscopic structure of the World Wide Web can be represented as a “bow-tie” diagram where more than 70% of the nodes are distributed into three large sets and one of these sets is a large strongly-connected component. This particular structure has been also observed in complex networks in other fields such as, e.g., biology. Similar studies cannot be conducted in a directed hypergraph because there does not exist any algorithm for computing the strongly-connected components of the hypergraph. In this thesis, we investigate ways to compute the strongly-connected components of directed hypergraphs. We present two new algorithms and we show their correctness and computational complexity. One of these algorithms is inspired by Tarjan’s algorithm for directed graphs. The second algorithm follows a simple approach to compute the stronglyconnected components. This approach is based on the fact that two nodes of a graph that are strongly-connected can also reach the same nodes. In other words, the connected component of each node is the same. Both algorithms are empirically evaluated to compare their performances. To this end, we have produced a selection of random directed hypergraphs inspired by existent and well-known random graphs models like Erd˝os-Renyi and Newman-Watts-Strogatz. Besides the application examples that we mentioned earlier, directed hypergraphs have also been employed in the field of knowledge representation. In particular, they have been used to compute the modules of an ontology. An ontology is defined as a collection of axioms that provides a formal specification of a set of terms and their relationships; and a module is a subset of an ontology that completely captures the meaning of certain terms as defined in the ontology. In particular, we focus on the modules computed using the notion of syntactic locality. As ontologies can be very large, the computation of modules facilitates the reuse and maintenance of these ontologies. Analysing all modules of an ontology, however, is in general not feasible as the number of modules grows exponentially in the number of terms and axioms of the ontology. Nevertheless, the modules can succinctly be represented using the Atomic Decomposition of an ontology. Using this representation, an ontology can be partitioned into atoms, which are maximal sets of axioms that co-occur in every module. The Atomic Decomposition is then defined as a directed graph such that each node correspond to an atom and each edge represents a dependency relation between two atoms. In this thesis, we introduce the notion of an axiom dependency hypergraph which is a generalization of the atomic decomposition of an ontology. A module in the ontology corresponds to a connected component in the hypergraph, and the atoms of the ontology to the strongly-connected components. We apply our algorithms for directed hypergraphs to axiom dependency hypergraphs and in this manner, we compute the atoms of an ontology. To demonstrate the viability of this approach, we have implemented the algorithms in the application HyS which computes the modules of ontologies and calculate their atomic decomposition. In the thesis, we provide an experimental evaluation of HyS with a selection of large and prominent biomedical ontologies, most of which are available in the NCBO Bioportal. HyS outperforms state-of-the-art implementations in the tasks of extracting modules and computing the atomic decomposition of these ontologies.

DYNAMIC SCALING AND FRACTAL BEHAVIOR OF SPINODAL PHASE-SEPARATION IN POLYMER MIXTURES OF POLY(METHYL METHACRYLATE) WITH POLY(STYRENE-CO-ACRYLONITRILE)

Dynamic scaling and fractal behaviour of spinodal phase separation is studied in a binary polymer mixture of poly(methyl methacrylate) (PMMA) and poly(styrene-co-acrylonitrile) (SAN). In the later stages of spinodal phase separation, a simple dynamic scaling law was found for the scattering function S(q,t):S(q,t) approximately q(m)-3S approximately (q/q(m)). The possibility of using fractal theory to describe the complex morphology of spinodal phase separation is discussed. In phase separation, morphology exhibits strong self-similarity. The two-dimensional image obtained by optical microscopy can be analysed within the framework of fractal concepts. The results give a fractal dimension of 1.64. This implies that the fractal structure may be the reason for the dynamic scaling behaviour of the structure function.

Dependency Directed Reasoning for Complex Program Understanding

Artificial Intelligence research involves the creation of extremely complex programs which must possess the capability to introspect, learn, and improve their expertise. Any truly intelligent program must be able to create procedures and to modify them as it gathers information from its experience. [Sussman, 1975] produced such a system for a 'mini-world'; but truly intelligent programs must be considerably more complex. A crucial stepping stone in AI research is the development of a system which can understand complex programs well enough to modify them. There is also a complexity barrier in the world of commercial software which is making the cost of software production and maintenance prohibitive. Here too a system which is capable of understanding complex programs is a necessary step. The Programmer's Apprentice Project [Rich and Shrobe, 76] is attempting to develop an interactive programming tool which will help expert programmers deal with the complexity involved in engineering a large software system. This report describes REASON, the deductive component of the programmer's apprentice. REASON is intended to help expert programmers in the process of evolutionary program design. REASON utilizes the engineering techniques of modelling, decomposition, and analysis by inspection to determine how modules interact to achieve the desired overall behavior of a program. REASON coordinates its various sources of knowledge by using a dependency-directed structure which records the justification for each deduction it makes. Once a program has been analyzed these justifications can be summarized into a teleological structure called a plan which helps the system understand the impact of a proposed program modification.