Physical properties of giant planets

The chemical identification and physical nature of giant planets are discussed. The phase equilibria of H2-He mixture is briefly described for these large planets

Chemical Identification of the Radioelements Produced from Carbon and Boron by Deuteron Bombardment

Chemical experiments were made on the radioactive substances resulting from the bombardment of carbon and boron by deuterons. Carbon is shown to yield an isotope of nitrogen and boron an isotope of carbon. The nitrogen so formed has a half-life of 10.5 minutes while that found by Curie and Joliot on bombardment of boron with alpha-particles has a half-life of 14 minutes. These facts are discussed

Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level precision. This progress has been accompanied by an exponential increase in the size and quality of datasets produced by microscopic and spectroscopic experimental techniques. These developments necessitate adequate methods for extracting relevant physical and chemical information from the large datasets, for which a priori information on the structures of various atomic configurations and lattice defects is limited or absent. Here we demonstrate an application of deep neural networks to extract information from atomically resolved images including location of the atomic species and type of defects. We develop a 'weakly-supervised' approach that uses information on the coordinates of all atomic species in the image, extracted via a deep neural network, to identify a rich variety of defects that are not part of an initial training set. We further apply our approach to interpret complex atomic and defect transformation, including switching between different coordination of silicon dopants in graphene as a function of time, formation of peculiar silicon dimer with mixed 3-fold and 4-fold coordination, and the motion of molecular 'rotor'. This deep learning based approach resembles logic of a human operator, but can be scaled leading to significant shift in the way of extracting and analyzing information from raw experimental data

Chemical identification of chlorophenylpiperazine in seized tablets

Designer drug is a term used to describe psychoactive drugs of abuse which are usually synthesized by modifying the molecular structures of existing drugs of abuse. The term gained widespread popularity when MDMA (ecstasy) experienced a popularity boom in the mid 1980´s. In Brazil, designer drugs seizures have increased in the last few years, and actually tablets with unknown psychoactive compounds began to be forwarded to the Forensic Laboratories. This work describes the analytical assays that were performed to identify the chlorophenylpiperazine, a psychoactive substance first time identified in seized tablets in Sao Paulo state

Semiochemicals in merino ewes : field effects and chemical identification

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Tuning localized plasmons in nanostructured substrates for surface-enhanced Raman scattering

Comprehensive reflectivity mapping of the angular dispersion of nanostructured arrays comprising of inverted pyramidal pits is demonstrated. By comparing equivalently structured dielectric and metallic arrays, diffraction and plasmonic features are readily distinguished. While the diffraction features match expected theory, localised plasmons are also observed with severely flattened energy dispersions. Using pit arrays with identical pitch, but graded pit dimensions, energy scaling of the localised plasmon is observed. These localised plasmons are found to match a simple model which confines surface plasmons onto the pit sidewalls thus allowing an intuitive picture of the plasmons to be developed. This model agrees well with a 2D finite-difference time-domain simulation which shows the same dependence on pit dimensions. We believe these tuneable plasmons are responsible for the surface-enhancement of the Raman scattering (SERS) of an attached layer of benzenethiol molecules. Such SERS substrates have a wide range of applications both in security, chemical identification, environmental monitoring and healthcare

Active Wavelength Selection for Chemical Identification Using Tunable Spectroscopy

Spectrometers are the cornerstone of analytical chemistry. Recent advances in microoptics manufacturing provide lightweight and portable alternatives to traditional spectrometers. In this dissertation, we developed a spectrometer based on Fabry-Perot interferometers (FPIs). A FPI is a tunable (it can only scan one wavelength at a time) optical filter. However, compared to its traditional counterparts such as FTIR (Fourier transform infrared spectroscopy), FPIs provide lower resolution and lower signal-noiseratio (SNR). Wavelength selection can help alleviate these drawbacks. Eliminating uninformative wavelengths not only speeds up the sensing process but also helps improve accuracy by avoiding nonlinearity and noise. Traditional wavelength selection algorithms follow a training-validation process, and thus they are only optimal for the target analyte. However, for chemical identification, the identities are unknown. To address the above issue, this dissertation proposes active sensing algorithms that select wavelengths online while sensing. These algorithms are able to generate analytedependent wavelengths. We envision this algorithm deployed on a portable chemical gas platform that has low-cost sensors and limited computation resources. We develop three algorithms focusing on three different aspects of the chemical identification problems. First, we consider the problem of single chemical identification. We formulate the problem as a typical classification problem where each chemical is considered as a distinct class. We use Bayesian risk as the utility function for wavelength selection, which calculates the misclassification cost between classes (chemicals), and we select the wavelength with the maximum reduction in the risk. We evaluate this approach on both synthesized and experimental data. The results suggest that active sensing outperforms the passive method, especially in a noisy environment. Second, we consider the problem of chemical mixture identification. Since the number of potential chemical mixtures grows exponentially as the number of components increases, it is intractable to formulate all potential mixtures as classes. To circumvent combinatorial explosion, we developed a multi-modal non-negative least squares (MMNNLS) method that searches multiple near-optimal solutions as an approximation of all the solutions. We project the solutions onto spectral space, calculate the variance of the projected spectra at each wavelength, and select the next wavelength using the variance as the guidance. We validate this approach on synthesized and experimental data. The results suggest that active approaches are superior to their passive counterparts especially when the condition number of the mixture grows larger (the analytes consist of more components, or the constituent spectra are very similar to each other). Third, we consider improving the computational speed for chemical mixture identification. MM-NNLS scales poorly as the chemical mixture becomes more complex. Therefore, we develop a wavelength selection method based on Gaussian process regression (GPR). GPR aims to reconstruct the spectrum rather than solving the mixture problem, thus, its computational cost is a function of the number of wavelengths. We evaluate the approach on both synthesized and experimental data. The results again demonstrate more accurate and robust performance in contrast to passive algorithms

Performance metrics for the evaluation of hyperspectral chemical identification systems

Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume’s chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.United States. Defense Threat Reduction Agency (Air Force contract FA8721-05-C-0002

\u3cem\u3eIn Vitro\u3c/em\u3e Biosynthesis and Chemical Identification of UDP-\u3cem\u3eN\u3c/em\u3e-acetyl-d-quinovosamine (UDP-d-QuiNAc)

N-acetyl-d-quinovosamine (2-acetamido-2,6-dideoxy-d-glucose, QuiNAc) occurs in the polysaccharide structures of many Gram-negative bacteria. In the biosynthesis of QuiNAc-containing polysaccharides, UDP-QuiNAc is the hypothetical donor of the QuiNAc residue. Biosynthesis of UDP-QuiNAc has been proposed to occur by 4,6-dehydration of UDP-N-acetyl-d-glucosamine (UDP-GlcNAc) to UDP-2-acetamido-2,6-dideoxy-d-xylo-4-hexulose followed by reduction of this 4-keto intermediate to UDP-QuiNAc. Several specific dehydratases are known to catalyze the first proposed step. A specific reductase for the last step has not been demonstrated in vitro, but previous mutant analysis suggested that Rhizobium etli gene wreQ might encode this reductase. Therefore, this gene was cloned and expressed in Escherichia coli, and the resulting His6-tagged WreQ protein was purified. It was tested for 4-reductase activity by adding it and NAD(P)H to reaction mixtures in which 4,6-dehydratase WbpM had acted on the precursor substrate UDP-GlcNAc. Thin layer chromatography of the nucleotide sugars in the mixture at various stages of the reaction showed that WbpM converted UDP-GlcNAc completely to what was shown to be its 4-keto-6-deoxy derivative by NMR and that addition of WreQ and NADH led to formation of a third compound. Combined gas chromatography-mass spectrometry analysis of acid hydrolysates of the final reaction mixture showed that a quinovosamine moiety had been synthesized after WreQ addition. The two-step reaction progress also was monitored in real time by NMR. The final UDP-sugar product after WreQ addition was purified and determined to be UDP-d-QuiNAc by one-dimensional and two-dimensional NMR experiments. These results confirmed that WreQ has UDP-2-acetamido-2,6-dideoxy-d-xylo-4-hexulose 4-reductase activity, completing a pathway for UDP-d-QuiNAc synthesis in vitro