High-resolution Keck I spectroscopy of Galactic halo post-asymptotic giant branch stars

Absolute and differential abundance analyses have been performed from high-resolution, high signal-to-noise ratio optical (Keck I) spectra for three evolved Galactic halo stars, namely PG 1704 + 222, HD 341617 and LSIV -0401. Their derived atmospheric parameters indicate that all three objects are undergoing a post-asymptotic giant branch (post-AGB) phase of evolution. A differential abundance analysis reveals HD 341617 as having a mild carbon deficiency of 0.74 dex, possibly due to the star having evolved off the AGB before the onset of the third dredge-up. Although such carbon underabundances are typical of hot post-AGB objects, the same trend is not observed in PG 1704 + 222, where the carbon abundance is found to be consistent with those derived for nitrogen and oxygen. Hence, a dredge-up scenario need not be invoked to explain the chemical composition of PG 1704 + 222. For LSIV -0401 no iron deficiency is apparent relative to magnesium and silicon, and hence a gas- dust separation event in the AGB progenitor need not be invoked for this star.

TIME-RESOLVED RESONANCE RAMAN-SPECTROSCOPY OF TRIPLET-STATE METALATED AND FREE-BASE TETRAARYLPORPHYRINS

Resonance Raman spectra of the T-1 excited states of Zn and free-base tetra-4-sulfonatophenylporphyrin (TPPS) have been recorded at room temperature in aqueous solution using two-colour time-resolved methods. The spectra of both sulfonated molecules are very similar to their tetraphenylporphyrin (TPP) analogues, which have been recorded in THF solution using the same pump-probe conditions, but they have higher signal-to-noise ratios because interference from strong solvent bands is reduced. Although two different T-1 spectra of Zn(TPP) have been reported these spectra differ slightly from each other and from the spectrum reported here, which has band positions very close (+/-6 cm(-1)) to those of Zn(TPPS). The high S/N ratios obtainable for the water-soluble porphyrins have allowed reliable polarization data to be recorded for their S-0 and T-1 states. This data set allows a realistic comparison of the changes in bonding associated with excitation of both free-base and Zn tetraarylporphyrins to the T-1 state.

Label-free detection of nanomolar unmodified single- and double-stranded dna by using surface-enhanced raman spectroscopy on Ag and Au colloids

Unlabelled single- and double-stranded DNA (ssDNA and dsDNA, respectively) has been detected at concentrations =10-9?M by surface-enhanced Raman spectroscopy. Under appropriate conditions the sequences spontaneously adsorbed to the surface of both Ag and Au colloids through their nucleobases; this allowed highly reproducible spectra with good signal-to-noise ratios to be recorded on completely unmodified samples. This eliminated the need to promote absorption by introducing external linkers, such as thiols. The spectra of model ssDNA sequences contained bands of all the bases present and showed systematic changes when the overall base composition was altered. Initial tests also showed that small but reproducible changes could be detected between oligonucleotides with the same bases arranged in a different order. The spectra of five ssDNA sequences that correspond to different strains of the Escherichia coli bacterium were found to be sufficiently composition-dependent so that they could be differentiated without the need for any advanced multivariate data analysis techniques.

Max separation clustering for feature extraction from Optical Emission Spectroscopy Data

This paper proposes max separation clustering (MSC), a new non-hierarchical clustering method used for feature extraction from optical emission spectroscopy (OES) data for plasma etch process control applications. OES data is high dimensional and inherently highly redundant with the result that it is difficult if not impossible to recognize useful features and key variables by direct visualization. MSC is developed for clustering variables with distinctive patterns and providing effective pattern representation by a small number of representative variables. The relationship between signal-to-noise ratio (SNR) and clustering performance is highlighted, leading to a requirement that low SNR signals be removed before applying MSC. Experimental results on industrial OES data show that MSC with low SNR signal removal produces effective summarization of the dominant patterns in the data.