77 research outputs found
Potential Energy Landscape of CO Adsorbates on NaCl(100) and Implications in Isomerization of Vibrationally Excited CO
Several full-dimensional potential energy surfaces (PESs) are reported for
vibrating CO adsorbates at two coverages on a rigid NaCl(100) surface based on
first principles calculations. These PESs reveal a rather flat energy landscape
for physisorption of vibrationless CO on NaCl(100), evidenced by various C-down
adsorption patterns within a small energy range. Agreement with available
experimental results is satisfactory, although quantitative differences exist.
These PESs are used to explore isomerization pathways between the C-down and
higher energy O-down configurations, which reveal a significant isomerization
barrier. As CO vibration is excited, however, the energy order of the two
isomer changes, which helps to explain the experimental observed flipping of
vibrationally excited CO adsorbates
Synthesis and characterization of core-shell structure silica-coated Fe29.5Ni70.5 nanoparticles
In view of potential applications of magnetic particles in biomedicine and
electromagnetic devices, we made use of the classical Stober method
base-catalysed hydrolysis and condensation of tetraethoxysilane (TEOS) to
encapsulate FeNi nanoparticles within a silica shell. An original stirring
system under high power ultrasounds made possible to disperse the otherwise
agglomerated particles. Sonication guaranteed particles to remain dispersed
during the Stober synthesis and also improved the efficiency of the method. The
coated particles are characterized by electron microscopy (TEM) and
spectroscopy (EDX) showing a core-shell structure with a uniform layer of
silica. Silica-coating does not affect the core magnetic properties. Indeed,
all samples are ferromagnetic at 77 K and room temperature and the Curie point
remains unchanged. Only the coercive force shows an unexpected non-monotonous
dependence on silica layer thickness.Comment: Regular paper submited to international peer-reveiwed journa
Differing climate and landscape effects on regional dryland vegetation responses during wet periods allude to future patterns
Forecasting Ozone Levels and Analyzing Their Dynamics by a Bayesian Multilayer Perceptron Model for Two Air-Monitoring Sites in Hong Kong
Potential Energy Landscape of CO Adsorbates on NaCl(100) and Implications in Isomerization of Vibrationally Excited CO
Statistical methods for characterizing diversity of microbial communities by analysis of terminal restriction fragment length polymorphisms of 16S rRNA genes
The analysis of terminal restriction fragment length polymorphisms (T-RFLP) of 16S rRNA genes has proven to be a facile means to compare microbial communities and presumptively identify abundant members. The method provides data that can be used to compare different communities based on similarity or distance measures. Once communities have been clustered into groups, clone libraries can be prepared from sample(s) that are representative of each group in order to determine the phylogeny of the numerically abundant populations in a community. In this paper methods are introduced for the statistical analysis of T-RFLP data that include objective methods for (i) determining a baseline so that 'true' peaks in electropherograms can be identified; (ii) a means to compare electropherograms and bin fragments of similar size; (iii) clustering algorithms that can be used to identify communities that are similar to one another; and (iv) a means to select samples that are representative of a cluster that can be used to construct 16S rRNA gene clone libraries. The methods for data analysis were tested using simulated data with assumptions and parameters that corresponded to actual data. The simulation results demonstrated the usefulness of these methods in their ability to recover the true microbial community structure generated under the assumptions made. Software for implementing these methods is available at http://www.ibest.uidaho.edu/tools/trflp_stats/index.php.Zaid Abdo, Ursel M.E. SchĂĽette, Stephen J. Bent, Christopher J. Williams, Larry J. Forney and Paul Joyc
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