Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

Effects of iron additions on filament growth and productivity of the cyanobacterium Lyngbya majuscula

The bioavailability of iron, in combination with essential macronutrients such as phosphorus, has been hypothesised to be linked to nuisance blooms of the toxic cyanobacterium Lyngbya majuscula. The present laboratory study used two biological assay techniques to test whether various concentrations of added iron (inorganic and organically chelated) enhanced L. majuscula filament growth and productivity (C-14-bicarbonate uptake rate). Organically chelated iron (FeEDTA) with adequate background concentrations of phosphorus and molybdenum caused the largest increases (up to 4.5 times the control) in L. majuscula productivity and filament growth. The addition of inorganic iron (without added phosphorus or molybdenum) also stimulated L. majuscula filament growth. However, overall the FeEDTA was substantially and significantly more effective in promoting L. majuscula growth than inorganic iron (FeCl3). The organic chelator (EDTA) alone and molybdenum alone also enhanced L. majuscula growth but to a lesser extent than the chelated iron. The results of the present laboratory study support the hypothesis that iron and chelating organic compounds may be important in promoting blooms of L. majuscula in coastal waters of Queensland, Australia.

Effects of combined additions of Sr and AlTiB grain refiners in hypoeutectic Al-Si foundry alloys

Strontium is the most widely used and a very effective element for modifying the morphology of eutectic silicon, while Ti and B are commonly present in the commercial grain refiners used for Al-Si alloys. Systematic studies on the effects of combined additions of Sr and different AlTiB grain refiners on the Al + Si eutectic and primary aluminium solidification have been performed. While slight coarsening of both eutectic Si and primary aluminium grains occurs during holding, no obvious interactions are observed between Sr and AlTiB grain refiners when the addition level of grain refiners is low. As a result, a well-modified and grain refined structure was obtained. However, strong negative interactions between Sr and Al1.5Ti1.5B3 were observed as the addition level of the grain refiner increases. It was found that these interactions have a much more profound impact on the eutectic solidification than the primary Al solidification. The melt treated with combined additions of Sr and Al1.5Ti1.5B still shows good grain refinement efficiency even after losing its modification completely. The mechanism responsible for such negative interactions is further discussed. (c) 2006 Elsevier B.V. All rights reserved.

Heuristic algorithm for computing reversal distance with multigene families via binary integer programming

Hannenhalli and Pevzner developed the first polynomial-time algorithm for the combinatorial problem of sorting of signed genomic data. Their algorithm solves the minimum number of reversals required for rearranging a genome to another when gene duplication is nonexisting. In this paper, we show how to extend the Hannenhalli-Pevzner approach to genomes with multigene families. We propose a new heuristic algorithm to compute the reversal distance between two genomes with multigene families via the concept of binary integer programming without removing gene duplicates. The experimental results on simulated and real biological data demonstrate that the proposed algorithm is able to find the reversal distance accurately. ©2005 IEEE

Efficient spatial clustering algorithm using binary tree

In this paper we present an efficient k-Means clustering algorithm for two dimensional data. The proposed algorithm re-organizes dataset into a form of nested binary tree*. Data items are compared at each node with only two nearest means with respect to each dimension and assigned to the one that has the closer mean. The main intuition of our research is as follows: We build the nested binary tree. Then we scan the data in raster order by in-order traversal of the tree. Lastly we compare data item at each node to the only two nearest means to assign the value to the intendant cluster. In this way we are able to save the computational cost significantly by reducing the number of comparisons with means and also by the least use to Euclidian distance formula. Our results showed that our method can perform clustering operation much faster than the classical ones. © Springer-Verlag Berlin Heidelberg 2005