Observation of the Q(3/2) Λ-doublet transitions for X2Π3/2 OD in helium nanodroplets

The deuteroxyl radical (OD) has been isolated in superfluid helium nanodroplets and characterised by infrared depletion spectroscopy. Two resolved Q(3/2) lines are observed, with a separation that is 4.88 (10) times larger than in the gas phase. This is similar to that previously reported for He-solvated OH (5.30 (2)), for which it was shown that the splitting could be reproduced by a model that assumes a small parity dependence of the rotor's effective moment of inertia [P.L. Raston, T. Liang, and G.E. Douberly, J. Phys. Chem. A (2013). DOI:10.1021/jp312335q]. With this model, the OD Λ-doublet splitting in liquid He is reproduced with B^e and B^f rotational constants that differ by ≈0.24%.     

Multifunctional mesoporous silica nanoparticles in poly(ethylene‐co‐vinyl acetate) for transparent heat retention films

Transparent inorganic‐polymer nanocomposite films are of tremendous current interest inemerging solar coverings including photovoltaic encapsulants and commercial greenhouse plastics, but suffer from significant radiative heat loss. This work provides a new and simple approach for controlling this heat loss by using mesoporous silica/quantum dot nanoparticles in poly(ethylene‐co‐vinyl acetate) (EVA) films. Mesoporous silica shells were grown on CdS‐ZnS quantum dot (QDs) cores using a reverse microemulsion technique, controlling the shell thickness. These mesoporous silica nanoparticles (MSNs) were then melt‐mixed with EVA pellets using a mini twin‐screw extruder and pressed into thin films of concentration variable controlled thickness. The results demonstrate that the experimental MSNs showed improved infrared and thermal wavebands retention in the EVA transparent films compared to commercial silica additives, even at lower concentrations. It was also found MSNs enhanced the quantum yield and photostability of the QDs, providing high visible light transmission and blocking of UV transmission of interest for next generation solar coatings. © 2015 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2015 , 53, 851–859     

A backbone based TSP heuristic for large instances

We introduce a reduction technique for large instances of the traveling salesman problem (TSP). This approach is based on the observation that tours with good quality are likely to share many edges. We exploit this observation by neglecting the less important tour space defined by the shared edges, and searching the important tour subspace in more depth. More precisely, by using a basic TSP heuristic, we obtain a set of starting tours. We call the set of edges which are contained in each of these starting tours as pseudo-backbone edges. Then we compute the maximal paths consisting only of pseudo-backbone edges, and transform the TSP instance to another one with smaller size by contracting each such path to a single edge. This reduced TSP instance can be investigated more intensively, and each tour of the reduced instance can be expanded to a tour of the original instance. Combining our reduction technique with the currently leading TSP heuristic of Helsgaun, we experimentally investigate 32 difficult VLSI instances from the well-known TSP homepage. In our experimental results we set world records for seven VLSI instances, i.e., find better tours than the best tours known so far (two of these world records have since been improved upon by Keld Helsgaun and Yuichi Nagata, respectively). For the remaining instances we find tours that are equally good or only slightly worse than the world record tours.     

Automated determination of size and morphology information from soot transmission electron microscope (TEM)-generated images

The thermophoretic sampling of particulates from hot media, coupled with transmission electron microscope (TEM) imaging, is a combined approach that is widely used to derive morphological information. The identification and the measurement of the particulates, however, can be complex when the TEM images are of low contrast, noisy, and have non-uniform background signal level. The image processing method can also be challenging and time consuming, when the samples collected have large variability in shape and size, or have some degree of overlapping. In this work, a three-stage image processing sequence is presented to facilitate time-efficient automated identification and measurement of particulates from the TEM grids. The proposed processing sequence is first applied to soot samples that were thermophoretically sampled from a laminar non-premixed ethylene-air flame. The parameter values that are required to be set to facilitate the automated process are identified, and sensitivity of the results to these parameters is assessed. The same analysis process is also applied to soot samples that were acquired from an externally irradiated laminar non-premixed ethylene-air flame, which have different geometrical characteristics, to assess the morphological dependence of the proposed image processing sequence. Using the optimized parameter values, statistical assessments of the automated results reveal that the largest discrepancies that are associated with the estimated values of primary particle diameter, fractal dimension, and prefactor values of the aggregates for the tested cases, are approximately 3, 1, and 10 %, respectively, when compared with the manual measurements.