Migration of crystals during the filling of semi-solid castings

In cold-chamber high-pressure die castings (HPDC), the microstructure consists of coarse externally solidified crystals (ESCs) that are commonly observed in the central region of cross sections. In the present work, controlled laboratory scale casting experiments have been conducted with particular emphasis on the flow and solidification conditions. An A356 aluminum alloy was used to produce castings by pouring semi-solid metal through a steel die. Microstructures similar to those encountered in HPDC have been produced and the resulting microstructure is found to depend on the melt and die temperature: (1) the fraction of ESCs determines the extent of migration to the central region; (2) a maximum packing determines the area fraction of ESCs in the center; and (3) the die temperature affects the position of the ESCs-a higher die temperature can induce a displaced ESC distribution. It is found that the n-figration of crystals to the central region requires a flow, which is constrained at all melt/die interfaces. Furthermore, potential lift mechanisms are discussed. An assessment of the Saffman lift force on individual particles shows it has no significant effect on the migration of ESCs.

Single patient (n-of-1) trials with binary treatment preference

The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.

Post-crystallization treatments for improving diffraction quality of protein crystals

X-ray crystallography is the most powerful method for determining the three-dimensional structure of biological macromolecules. One of the major obstacles in the process is the production of high-quality crystals for structure determination. All too often, crystals are produced that are of poor quality and are unsuitable for diffraction studies. This review provides a compilation of post-crystallization methods that can convert poorly diffracting crystals into data-quality crystals. Protocols for annealing, dehydration, soaking and cross-linking are outlined and examples of some spectacular changes in crystal quality are provided. The protocols are easily incorporated into the structure-determination pipeline and a practical guide is provided that shows how and when to use the different post-crystallization treatments for improving crystal quality.

Quil A-lipid powder formulations releasing ISCOMs and related colloidal stuctures upon hydration

The aim of the present study was to prepare solid Quil A-cholesterol-phospholid formulations (as powder mixtures or compressed to pellets) by physical mixing or by freeze-drying of aqueous dispersions of these components in ratios that allow spontaneous formation of ISCOMs and other colloidal stuctures upon hydration. The effect of addition of excess cholesterol to the lipid mixtures on the release of a model antigen (PE-FITC-OVA) from the pellets was also investigated. Physical properties were evaluated by X-ray powder diffractometry (XPRD), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and polarized light microscopy (PLM). Characterization of aqueous colloidal dispersions was performed by negative staining transmission electron microscopy (TEM). Physically mixed powders (with or without PE-FITC-OVA) and pellets prepared from the same powders did not spontaneously form ISCOM matrices and related colloidal structures such as worm-like micelles, ring-like micelles, lipidic/layered structures and lamellae (hexagonal array of ring-like micelles) upon hydration as expected from the pseudo-temary diagram for aqueous mixtures of Quil A, cholesterol and phospholipid. In contrast, spontaneous formation of the expected colloids was demonstrated for the freeze-dried lipid mixtures. Pellets prepared by compression of freeze-dried powders released PE-FITC-OVA slower than those prepared from physically mixed powders. TEM investigations revealed that the antigen was released in the form of colloidal particles (ISCOMs) from pellets prepared by compression of freeze-dried powders. The addition of excess cholesterol slowed down the release of antigen. The findings obtained in this study are important for the formulation of solid Quil A-containing lipid articles as controlled particulate adjuvant containing antigen delivery systems. (c) 2004 Elsevier B.V. All rights reserved.

Surface morphology dependent photoluminescence from colloidal silicon nanocrystals

Monodisperse 1-2 nm silicon nanocrystals are synthesized in reverse micelles and have their surfaces capped with either allylamine or 1-heptene to produce either hydrophilic or hydrophobic silicon nanocrystals. Optical characterization (absorption, PL, and time-resolved PL) is performed on colloidal solutions with the two types of surface-capped silicon nanocrystals with identical size distributions. Direct evidence is obtained for the modification of the optical properties of silicon nanocrystals by the surface-capping molecule. The two different surface-capped silicon nanocrystals show remarkably different optical properties.

W/O microemulsions for ocular delivery: Evaluation of ocular irritation and precorneal retention

Water-in-oil microemulsions (w/o ME) capable of undergoing a phase-transition to lamellar liquid crystals (LC) or bicontinuous ME upon aqueous dilution were formulated using Crodarnol EO, Crill 1 and Crillet 4, an alkanol or alkanediol as cosurfactant and water. The hypothesis that phase-transition of ME to LC may be induced by tears and serve to prolong precomeal retention was tested. The ocular irritation potential of components and formulations was assessed using a modified hen's egg chorioallantoic membrane test (HET-CAM) and the preocular retention of selected formulations was investigated in rabbit eye using gamma scintigraphy. Results showed that Crill 1, Crillet 4 and Crodamol EO were non-irritant. However, all other cosurfactants investigated were irritant and their irritation was dependent on their carbon chain length. A w/o ME formulated without cosurfactant showed a protective effect when a strong irritant (0.1 M NaOH) was used as the aqueous phase. Precorneal clearance studies revealed that the retention of colloidal and coarse dispersed systems was significantly greater than an aqueous solution with no significant difference between ME systems (containing 5% and 10% water) as well as o/w emulsion containing 85% water. Conversely, a LC system formulated without cosurfactant displayed a significantly greater retention compared to other formulations. (c) 2005 Elsevier B.V. All rights reserved.

The effect of aluminium content on the mechanical properties and microstructure of die cast binary magnesium-aluminium alloys

This paper investigates the relationship between mechanical properties and microstructure in high pressure die cast binary Mg-Al alloys. As-cast test bars produced using high pressure die casting have been tested in tension in order to determine the properties for castings produced using this technique. It has been shown that increasing aluminium levels results in increases in yield strength and a decrease in ductility for these alloys. Higher aluminium levels also result in a decrease in creep rate at 150 degrees C. It has also been shown that an increase in aluminium levels results in an increase in the volume fraction of eutectic Mg17Al12 in the microstructure.

Dynamic binary translation using run-time feedbacks

Dynamic binary translation is the process of translating, modifying and rewriting executable (binary) code from one machine to another at run-time. This process of low-level re-engineering consists of a reverse engineering phase followed by a forward engineering phase. UQDBT, the University of Queensland Dynamic Binary Translator, is a machine-adaptable translator. Adaptability is provided through the specification of properties of machines and their instruction sets, allowing the support of different pairs of source and target machines. Most binary translators are closely bound to a pair of machines, making analyses and code hard to reuse. Like most virtual machines, UQDBT performs generic optimizations that apply to a variety of machines. Frequently executed code is translated to native code by the use of edge weight instrumentation, which makes UQDBT converge more quickly than systems based on instruction speculation. In this paper, we describe the architecture and run-time feedback optimizations performed by the UQDBT system, and provide results obtained in the x86 and SPARC® platforms.

Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture

Computer modelling promises to. be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The 'spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/- 50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations. (c) 2006 Published by Elsevier B.V.

Simulation of binary mixture adsorption of methane and CO2 at supercritical conditions in carbons

Knowledge of the adsorption behavior of coal-bed gases, mainly under supercritical high-pressure conditions, is important for optimum design of production processes to recover coal-bed methane and to sequester CO2 in coal-beds. Here, we compare the two most rigorous adsorption methods based on the statistical mechanics approach, which are Density Functional Theory (DFT) and Grand Canonical Monte Carlo (GCMC) simulation, for single and binary mixtures of methane and carbon dioxide in slit-shaped pores ranging from around 0.75 to 7.5 nm in width, for pressure up to 300 bar, and temperature range of 308-348 K, as a preliminary study for the CO2 sequestration problem. For single component adsorption, the isotherms generated by DFT, especially for CO2, do not match well with GCMC calculation, and simulation is subsequently pursued here to investigate the binary mixture adsorption. For binary adsorption, upon increase of pressure, the selectivity of carbon dioxide relative to methane in a binary mixture initially increases to a maximum value, and subsequently drops before attaining a constant value at pressures higher than 300 bar. While the selectivity increases with temperature in the initial pressure-sensitive region, the constant high-pressure value is also temperature independent. Optimum selectivity at any temperature is attained at a pressure of 90-100 bar at low bulk mole fraction of CO2, decreasing to approximately 35 bar at high bulk mole fractions. (c) 2005 American Institute of Chemical Engineers.

Tailoring surface properties to build colloidal diagnostic devices: Controlling interparticle associations

The ability to control the surface properties and subsequent colloidal stability of dispersed particles has widespread applicability in many fields. Sub-micrometer fluorescent silica particles (reporters) can be used to actively encode the combinatorial synthesis of peptide libraries through interparticle association. To achieve these associations, the surface chemistry of the small fluorescent silica reporters is tailored to encourage robust adhesion to large silica microparticles onto which the peptides are synthesized. The interparticle association must withstand a harsh solvent environment multiple synthetic and washing procedures, and biological screening buffers. The encoded support beads were exposed to different solvents used for peptide synthesis, and different solutions used for biological screening including phosphate buffered saline (PBS), 2-[N-morpholino]ethane sulfonic acid (VIES) and a mixture of MES and N-(3-dimethyl-aminopropyl)-N'-ethylcarbodiimide (EDC). The number of reporters remaining adhered to the support bead was quantified after each step. The nature of the associations were explored and tested to optimize the efficiency of these phenomena. Results presented illustrate the influence of the surface functionality and polyelectrolyte modification of the reporters. These parameters were investigated through zeta potential and X-ray photoelectron spectroscopy.

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.

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

Growth of crystals in optical tweezers

We report here on the use of optical tweezers in the growth and manipulation of protein and inorganic crystals. Sodium chloride and hen egg-white lysozyme crystals were grown in a batch process, and then seeds from the solution were introduced into the optical tweezers. The regular and controllable shape and the known optical birefringence in these structures allowed a detailed study of the orientation effects in the beam due to both polarization and gradient forces. Additionally, we determined that the laser tweezers could be used to suspend a crystal for three-dimensional growth under varying conditions. Studies included increasing the protein concentration, thermal cycling, and a diffusion-induced increase in precipitant concentration. Preliminary studies on the use of the tweezers to create a localized seed for growth from polyethylene oxide solutions are also reported.