Nanoscale compositional analysis of NiTi shape memory alloy films deposited by DC magnetron sputtering

The formation of surface oxide layer as well as compositional changes along the thickness for NiTi shape memory alloy thin films deposited by direct current magnetron sputtering at substrate temperature of 300 degrees C in the as-deposited condition as well as in the postannealed (at 600 degrees C) condition have been thoroughly studied by using secondary ion mass spectroscopy, x-ray photoelectron spectroscopy, and scanning transmission electron microscopy-energy dispersive x-ray spectroscopy techniques. Formation of titanium oxide (predominantly titanium dioxide) layer was observed in both as-deposited and postannealed NiTi films, although the oxide layer was much thinner (8 nm) in as-deposited condition. The depletion of Ti and enrichment of Ni below the oxide layer in postannealed films also resulted in the formation of a graded microstructure consisting of titanium oxide, Ni3Ti, and B2 NiTi. A uniform composition of B2 NiTi was obtained in the postannealed film only below a depth of 200-250 nm from the surface. Postannealed film also exhibited formation of a ternary silicide (NixTiySi) at the film-substrate interface, whereas no silicide was seen in the as-deposited film. The formation of silicide also caused a depletion of Ni in the film in a region similar to 250-300 nm just above the film substrate interface. (C) 2013 American Vacuum Society.

Experimental analysis of shape deformation of evaporating droplet using Legendre polynomials

Experiments involving heating of liquid droplets which are acoustically levitated, reveal specific modes of oscillations. For a given radiation flux, certain fluid droplets undergo distortion leading to catastrophic bag type breakup. The voltage of the acoustic levitator has been kept constant to operate at a nominal acoustic pressure intensity, throughout the experiments. Thus the droplet shape instabilities are primarily a consequence of droplet heating through vapor pressure, surface tension and viscosity. A novel approach is used by employing Legendre polynomials for the mode shape approximation to describe the thermally induced instabilities. The two dominant Legendre modes essentially reflect (a) the droplet size reduction due to evaporation, and (b) the deformation around the equilibrium shape. Dissipation and inter-coupling of modal energy lead to stable droplet shape while accumulation of the same ultimately results in droplet breakup. (C) 2013 Elsevier B.V. All rights reserved.

WormSizer: high-throughput analysis of nematode size and shape.

The fundamental phenotypes of growth rate, size and morphology are the result of complex interactions between genotype and environment. We developed a high-throughput software application, WormSizer, which computes size and shape of nematodes from brightfield images. Existing methods for estimating volume either coarsely model the nematode as a cylinder or assume the worm shape or opacity is invariant. Our estimate is more robust to changes in morphology or optical density as it only assumes radial symmetry. This open source software is written as a plugin for the well-known image-processing framework Fiji/ImageJ. It may therefore be extended easily. We evaluated the technical performance of this framework, and we used it to analyze growth and shape of several canonical Caenorhabditis elegans mutants in a developmental time series. We confirm quantitatively that a Dumpy (Dpy) mutant is short and fat and that a Long (Lon) mutant is long and thin. We show that daf-2 insulin-like receptor mutants are larger than wild-type upon hatching but grow slow, and WormSizer can distinguish dauer larvae from normal larvae. We also show that a Small (Sma) mutant is actually smaller than wild-type at all stages of larval development. WormSizer works with Uncoordinated (Unc) and Roller (Rol) mutants as well, indicating that it can be used with mutants despite behavioral phenotypes. We used our complete data set to perform a power analysis, giving users a sense of how many images are needed to detect different effect sizes. Our analysis confirms and extends on existing phenotypic characterization of well-characterized mutants, demonstrating the utility and robustness of WormSizer.