Simón Bolívar University

About: Simón Bolívar University is a education organization based out in Caracas, Venezuela. It is known for research contribution in the topics: Population & Crystallization. The organization has 5912 authors who have published 8294 publications receiving 126152 citations.

Homogeneous nucleation of the dispersed crystallisable component of immiscible polymer blends

Abstract: Immiscible melt mixed blends of a crystallisable polyolefin (isotactic polypropylene, PP) and atactic polystyrene (PS) were prepared in a wide composition range. It was found that when PP is the major component in the blend its crystallisation behaviour is not affected by blending it with PS. However if PP is the minor component, it will be dispersed in the immiscible PS matrix, hence the nucleation mechanism changes from predominantly heterogeneous to predominantly homogeneous as long as the size of the dispersed PP droplets is below a critical value (of the order of 1–2 μm).

Isotropization and change of complexity by gravitational decoupling

Abstract: We employ the gravitational decoupling approach for static and spherically symmetric systems to develop a simple and powerful method in order to (a) continuously isotropize any anisotropic solution of the Einstein field equations, and (b) generate new solutions for self-gravitating distributions with the same or vanishing complexity factor. A few working examples are given for illustrative purposes.

Closed‐form formulas for Kirchhoff index

Abstract: We find closed-form expressions for the resistance, or Kirchhoff index, of certain connected graphs using Foster's theorems, random walks, and the superposition principle. © 2001 John Wiley & Sons, Inc. Int J Quant Chem 81: 135–140, 2001

Sequential approximate optimization using variable fidelity response surface approximations

Abstract: The dimensionality and complexity of typical multidisciplinary systems hinders the use of formal optimization techniques in application to this class of problems. The use of approximations to represent the system design metrics and constraints has become vital for achieving good performance in many multidisciplinary design optimization (MDO) algorithms. This paper reports recent research efforts on the use of variable fidelity response surface approximations (RSA) to drive the convergence of MDO problems using a trust region model management algorithm. The present study focuses on a comparative study of different response sampling strategies based on design of experiment (DOE) approaches within the disciplines to generate the zero order data to build the RSAs. Two MDO test problems that have complex coupling between disciplines are used to benchmark the performance of each sampling strategy. The results show that these types of variable fidelity RSAs can be effectively managed by the trust region model management strategy to drive convergence of MDO problems. It is observed that the efficiency of the optimization algorithm depends on the sampling strategy used. A comparison of the DOE approaches with those obtained using a optimization based sampling strategy (i.e. concurrent subspace optimization --- CSSO) shows the DOE methodologies to be competitive with the CSSO based sampling methodology in some cases. However, the CSSO based sampling strategy was found to be, in general, more efficient in driving the optimization.

Self-Nucleation of Crystalline Phases Within Homopolymers, Polymer Blends, Copolymers, and Nanocomposites

Abstract: Self-nucleation (SN) is a special nucleation process triggered by self-seeds or self-nuclei that are generated in a given polymeric material by specific thermal protocols or by inducing chain orientation in the molten or partially molten state. SN increases the nucleation density of polymers by several orders of magnitude, producing significant modifications to their morphology and overall crystallization kinetics. In fact, SN can be used as a tool for investigating the overall isothermal crystallization kinetics of slow-crystallizing materials by accelerating the primary nucleation stage in a previous SN step. Additionally, SN can facilitate the formation of one particular crystalline phase in polymorphic materials. The SN behavior of a given polymer is influenced by its molecular weight, molecular topology, and chemical structure, among other intrinsic and extrinsic characteristics. This review paper focuses on the applications of DSC-based SN techniques to study the nucleation, crystallization, and morphology of different types of polymers, blends, copolymers, and nanocomposites.