Identification of petroleum distillates from fire debris using multidimensional gas chromatography

Summary A method for identifying petroleum distillates (accelerants) in fire debris samples by dynamic headspace analysis and multidimensional gas chromatography is described. The method relies on the separation of target compounds characteristic of different petroleum distillate classes from interfering co-eluting and matrix components. A relatively nonpolar column is used to characterize the volatility distribution of the sample and heartcutting to a second polar column of certain fractions to separate target compounds from interferences unresolved on the first column. The method is demonstrated for the identification of gasoline, kerosene, charcoal lighter fluid, and paint thinners in simulated arson samples.     

Directed self‐assembly of single quantum dots for telecommunication wavelength optical devices

The ability to control the nucleation site of a single quantum dot will have a profound effect on the development of quantum dot‐based photonic devices. The deterministic approach will provide a truly scalable technology that can take full advantage of conventional semiconductor processing for device fabrication. In this review, we discuss the progress towards the integration of deterministically nucleated single quantum dots with top‐down quantum optical devices targeting telecommunication wavelengths. Advances in site‐controlled quantum dot nucleation using selective‐area epitaxy now makes it possible to position quantum dots at predetermined positions on a substrate in registry with alignment markers. This, in turn, has allowed for devices fabricated in subsequent processing steps to be aligned to individual quantum dots. The specific devices being targeted are gated‐single dots and coupled dot‐cavity systems which are key components of efficient sources of single photons and entangled photon pairs.     

Acceleration of the Smith–Waterman algorithm using single and multiple graphics processors

Finding regions of similarity between two very long data streams is a computationally intensive problem referred to as sequence alignment. Alignment algorithms must allow for imperfect sequence matching with different starting locations and some gaps and errors between the two data sequences. Perhaps the most well known application of sequence matching is the testing of DNA or protein sequences against genome databases. The Smith–Waterman algorithm is a method for precisely characterizing how well two sequences can be aligned and for determining the optimal alignment of those two sequences. Like many applications in computational science, the Smith–Waterman algorithm is constrained by the memory access speed and can be accelerated significantly by using graphics processors (GPUs) as the compute engine. In this work we show that effective use of the GPU requires a novel reformulation of the Smith–Waterman algorithm. The performance of this new version of the algorithm is demonstrated using the SSCA#1 (Bioinformatics) benchmark running on one GPU and on up to four GPUs executing in parallel. The results indicate that for large problems a single GPU is up to 45 times faster than a CPU for this application, and the parallel implementation shows linear speed up on up to 4 GPUs.     

Geoacoustic inversion by mode amplitude perturbation

This paper introduces a perturbative inversion algorithm for determining sea floor acoustic properties, which uses modal amplitudes as input data. Perturbative inverse methods have been used in the past to estimate bottom acoustic properties in sediments, but up to this point these methods have used only the modal eigenvalues as input data. As with previous perturbative inversion methods, the one developed in this paper solves the nonlinear inverse problem using a series of approximate, linear steps. Examples of the method applied to synthetic and experimental data are provided to demonstrate the method's feasibility. Finally, it is shown that modal eigenvalue and amplitude perturbation can be combined into a single inversion algorithm that uses all of the potentially available modal data.     

Factors Affecting the Interpretation of Selectivity on Synergi Reversed-Phase Columns

The solvation parameter model is used to establish the contribution of cohesion, dipole-type, and hydrogen-bonding interactions to the retention mechanism on Synergi Hydro-RP, Fusion-RP, and Polar-RP reversed-phase columns with methanol–water mobile phases containing from 10–70% (v/v) methanol. Large changes in relative retention on the compared columns can result from steric resistance, differences in the phase ratios, and from dewetting at low methanol compositions while changes in intermolecular interactions are responsible for smaller changes at a fixed mobile phase composition. For Synergi Hydro-RP and Polar-RP changing methanol for acetonirile is more powerful for affecting changes in retention order than changing the stationary phase. The three Synergi columns show useful selectivity differences for method development when compared with 13 other modern reversed-phase columns representing a selection of different stationary phase chemistries. The results from this study indicate the limitations of classifying reversed-phase columns by the retention of prototypical compounds to define specific retention mechanisms.     

Mixturelike behavior near a liquid-liquid phase transition in simulations of supercooled water

In simulations of a waterlike model (ST2) that exhibits a liquid-liquid phase transition, we test for the occurrence of a thermodynamic region in which the liquid can be modeled as a two-component mixture. We assign each molecule to one of two species based on the distance to its fifth-nearest neighbor, and evaluate the concentration of each species over a wide range of temperature and density. Our concentration data compare well with mixture-model predictions in a region between the liquid-liquid critical temperature and the temperature of maximum density. Fits of the model to the data in this region yield accurate estimates for the location of the critical point. We also show that the liquid outside the region of density anomalies is poorly modeled as a simple mixture.     

Continuous development HPTLC and sequential wavelength scanning for the simultaneous determination of nine clinically important β-blocking drugs

High performance thin-layer chromatography was used for the separation of nine therapeutically important and structurally similar β-adrenoceptor blocking drugs on silica gel plates. In situ scanning of the plate in the reflectance mode gave detection limits in the low nanogram range depending on the individual drug and the wavelength selected for its determination. Scanning the HPTLC plate at several wavelengths can be used to aid the identification of partially resolved components. Continuous development and continuous multiple development techniques are compared for the simultaneous separation of the drug mixture.     

Isolation and determination of toxic congeners of polychlorinated biphenyls in environmental samples

A Method has been developed for the separation and enrichemen of there non-ortho, eight mono-ortho, and di-ortho substituted polychlorinated biphenyls (PCBs) from Aroclor formulations and environmental samples. The fractionation is accomplished using high performance liquid chromatography (HPLC) with a 2-(1-pyrenyl)ethyldimethylsilysily silca column. GC-MSD with an optimized temperature program was used for quantitation, Hexane, pentane, cyclohexane, iso-octane, and 2-propanol were tested as a mobile phase for the isolation of the thirteen target PCBs in a Aroclor 1242, 1254, and 1260 (1:1:1) misture, Pentane at room temperature with a slow rate of 0.7 ml/min is the condition of choice. The average recovery of thirteen target PCBs spiked in the Aroclor mixture is 99.5% with an average relative standard deviation of 4.5%. The average method detection limit is 8pg/μl. Targer PCBs in the reference solis, incinarator ash, and sediment samples were measured.