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A set of empirical potentials based upon two and three body interactions were constructed for the Li+-C system and structural optimizations for various assemblages containing Li+ ions and graphene sheets were conducted using some emerging evolutionary and genetic algorithms, differential evolution, and particle swarm optimization in particular. Some limited molecular dynamics calculations were also performed. The results are discussed and analyzed with reference to the lithium ion batteries, where the graphite-Li+ assemblages traditionally constitute the negative electrode, for which the present results are highly pertinent. [ABSTRACT FROM AUTHOR]

An inverse modeling approach was taken up in this work to model the process of recrystallization using cellular automata (CA). Using this method after formulating a CA model of recrystallization, differential evaluation (DE), a real-coded variant of genetic algorithms, was used to search for the value of nucleation rate, providing an acceptable matching between the theoretical and experimentally observed values of fraction-recrystallized (X). Initially, the inverse modeling was attempted with a simple CA strategy, in which each of the CA cells had an equal probability of becoming nucleated. DE searched for the value of the nucleation rate yielding the best results for single-crystal iron at 550 °C. A good match could not be simultaneously achieved this way for the early stages of recrystallization as well as for the later stages. To overcome this difficulty, the CA grid was divided into two zones, having lower and higher probabilities of nucleation. This resulted in good correspondence between the predicted and experimental values of X for the entire duration of recrystallization. The introduction of a distribution in the probability of nucleation made the model even closer to the actual process, in which the probability of nucleation is often nonuniform due to nonuniformity in dislocation density as well as the presence of grain/interface boundaries. [ABSTRACT FROM AUTHOR]

The efficacy of biologically inspired genetic algorithms for optimization is now well established. This article discusses the scope of using such an algorithm as an equation solver and presents detailed calculations on the Pb-S-O vapor system containing a total of 20 species as a paradigm case. This further increases the scope of applications of this evolutionary methodology in the domain of phase equilibria research, and this methodology is expected to be more advantageous than many other conventional techniques. [ABSTRACT FROM AUTHOR]

Energy minimization studies were carried out for a number of Cu clusters using binary and Gray-coded genetic algorithms along with real coded differential evolution, and their optimized ground state geometries are presented. The potential energy function is constructed using a two-body interaction methodology, involving both attractive and repulsive pair-potential terms. The results obtained through the evolutionary algorithms are compared against those obtained earlier using a Monte Carlo technique. [ABSTRACT FROM AUTHOR]

The mold region of the Continuous Caster was studied using a heat transfer formulation coupled with an optimization scheme. The pertinent transport equations were solved using a finite volume approach and the optimization calculations were conducted using biologically inspired Genetic Algorithms. The results are compared with the data available in the literature and significant improvements in terms of the casting velocity and the solidified shell thickness are observed and reported. [ABSTRACT FROM AUTHOR]

Energy minimization studies were carried out for a number of hydrogenated silicon clusters of the type SinH2m using a Tight-Binding model coupled with the biologically inspired optimizer, genetic algorithms (GAs). The results are compared with a previously published report on these clusters where the ground state geometry optimizations were not carried out. The optimized results fully resolved the cluster configurations in three dimensions, which are often different from the un-optimized configurations reported earlier. [ABSTRACT FROM AUTHOR]

A nonorthogonal tight-binding model has been developed for the system containing Si and H, where the energy functional included the contributions of both electronic and pairwise interaction between the atoms. In order to calculate the ground state structures of various clusters, energy minimization was carried out using Differential Evolution: a very recently developed biologically inspired computing technique, belonging, in general, to the family of Genetic Algorithms (GAs), but having a number of advantages over its conventional forms. [ABSTRACT FROM AUTHOR]

A mathematical model has been developed for the flow and mass-transfer processes associated with the nonspherical, deformed bubbles in a copper converter. The case of an isolated reacting bubble has been studied numerically by solving the pertinent transport equations with Galerkin finite element modeling (FEM) technique. The continuous change in bubble shape and size has been handled through an adaptive grid generation technique based upon a transfinite inter-polation scheme. Some of the results have shown a significant difference from the earlier analysis of spherical bubbles. The numerical predictions are well in accord with the existing theory and measurements. [ABSTRACT FROM AUTHOR]

Existing thermodynamic data for the Fe-As-S-0 system were evaluted and predominance area diagrams for that system were constructed at 798 and 973 K. Isopleths for the As/S and As/O atomic ratios in the vapor phase have been added to the diagrams by solving the complex equilibria. These modified diagrams were used to evaluate the results of roasting both natural and synthetic arsenopyrite (FeAsS) in inert, reducing, and oxidizing atmospheres at 798 and 873 K. Conditions leading to the retention of As as AsO(s) and FeAsO(s) were also reviewed. The experimental results indicate that both reducing and oxidizing atmospheres are more effective in the removal of As than an inert atmosphere. In a reducing atmosphere arsenic sulfides are evolved and the percentage of As removal increases with decreasing P The greatest percent of As removal occurred with highly oxidizing atmospheres which generated AsO vapor. [ABSTRACT FROM AUTHOR]