Analysis and measurement of candle flame shapes

A combined analytical and experimental study was performed to determine the length and width of a candle flame. Measurements were made of laminar steady flames from photographs of straight-wick candles composed of n-tetracosane and normal paraffin waxes. The wicks studied ranged in diameter from about 1 to 9 mm, and in height from about 2 to 10 mm, with aspect ratios (diameter to length) of 0.1 to 2. The flame length from the pool surface and the flame width at the top of the wick were found. It was also noted and recorded that the flame attachment point along the vertical wick varied. The attachment point was found to depend on the aspect ratio of the wick. A model based on stagnant layer burning for a finite cylinder was used, along with the Roper laminar burner model for flame height. With slight adjustment to a constant, the width of the flame was well predicted, and the prediction for the flame height was about 60% too high and offset. In addition, the model gave insight to produce an accurate simple correlation for flame height in terms of wick aspect ratio and Rayleigh number.     

Manifold preprocessing for laser‐induced breakdown spectroscopy under Mars conditions

Laser‐induced breakdown spectroscopy (LIBS) is currently being used onboard the Mars Science Laboratory rover Curiosity to predict elemental abundances in dust, rocks, and soils using a partial least squares regression model developed by the ChemCam team. Accuracy of that model is constrained by the number of samples needed in the calibration, which grows exponentially with the dimensionality of the data, a phenomenon known as the curse of dimensionality. LIBS data are very high dimensional, and the number of ground‐truth samples (i.e., standards) recorded with the ChemCam before departing for Mars was small compared with the dimensionality, so strategies to optimize prediction accuracy are needed. In this study, we first use an existing machine learning algorithm, locally linear embedding (LLE), to combat the curse of dimensionality by embedding the data into a low‐dimensional manifold subspace before regressing. LLE constructs its embedding by maintaining local neighborhood distances and discarding large global geodesic distances between samples, in an attempt to preserve the underlying geometric structure of the data. We also introduce a novel supervised version, LLE for regression (LLER), which takes into account the known chemical composition of the training data when embedding. LLER is shown to outperform traditional LLE when predicting most major elements. We show the effectiveness of both algorithms using three different LIBS datasets recorded under Mars‐like conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

Do columnar defects produce bulk pinning?

From magneto-optical imaging performed on heavy-ion-irradiated YBa(2)Cu(3)O(7-delta) single crystals, it is found that at fields and temperatures where strong single vortex pinning by individual irradiation-induced amorphous columnar defects is to be expected, vortex motion is limited by the nucleation of vortex kinks at the specimen surface. In the material bulk, vortex motion occurs through (easy) kink sliding. Depinning in the bulk determines the screening current only at fields comparable to or larger than the matching field, at which the majority of vortices is not trapped by an ion track.     

Single-turnover intermolecular reaction between a Fe(III)-superoxide-Cu(I) cytochrome c oxidase model and exogeneous Tyr244 mimics

An Fe(III)-superoxide-Cu(I) cytochrome c oxidase model reacts intermolecularly with hindered phenols leading to phenoxyl radicals, as was observed in the enzyme and evidence for the formation of an Fe(IV)-oxo is presented.