2 resultados para surface size

em DigitalCommons@University of Nebraska - Lincoln


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Anionic surface-initiated polymerization of ethylene oxide and styrene has been performed using multiwalled carbon nanotubes (MWNTs) functionalized with anionic initiators. The surface of MWNTs was modified via covalent attachment of precursor anions such as 4-hydroxyethyl benzocyclobutene (BCBEO) and 1-benzocyclobutene-1′-phenylethylene (BCB-PE) through Diels-Alder cycloaddition at 235 °C. Surface-functionalized MWNTs-g-(BCB-EO) n and MWNTs-g-(BCB-PE) n with 23 and 54 wt % precursor initiators, respectively, were used for the polymerizations. Alkoxide anion on the surface of MWNTs-g-(BCB-EO) n was generated through reaction with potassium triphenylmethane for the polymerization of ethylene oxide in tetrahydrofuran and phenyl substituted alkyllithium was generated from the surface of MWNTs-g-(BCB-PE) n using sec-butyllithium for the polymerization of styrene in benzene. In both cases, the initiation was found to be very slow because of the heterogeneous reaction medium. However, the MWNTs gradually dispersed in the reaction medium during the polymerization. A pale green color was noticed in the case of ethylene oxide polymerization and the color of initiator as well as the propagating anions was not discernible visually in styrene polymerization. Polymer grafted nanocomposites, MWNTs-g-(BCB-PEO) n and MWNTs-g-(BCB-PS) n containing a very high percentage of hairy polymer with a small fraction of MWNTs (<1 wt %) were obtained. The conversion of ethylene oxide and the weight percent of PEO on the surface of the MWNTs increased with increasing reaction time indicating a controlled polymerization. The polymer-grafted MWNTs were characterized using FTIR, 1H NMR, Raman spectroscopy, differential scanning calorimetry, thermogravimetric analysis, and transmission electron microscopy (TEM). Size exclusion chromatography of the polymer grafted MWNTs revealed broad molecular weight distributions (1.3 < Mw/Mn < 1.8) indicating the presence of different sizes of polymer nanocomposites. The TEM images showed the presence of thick layers of polymer up to 30 nm around the MWNTs. The living nature of the growing polystyryllithium was used to produce diblock copolymer grafts using sequential polymerization of isoprene on the surface of MWNTs.

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1. Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance. 2. We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use. 3. Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated. 4. A first step in analysis of distance sampling data is modeling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark–recapture distance sampling, which relaxes the assumption of certain detection at zero distance. 5. All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap. 6. Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modeling analysis engine for spatial and habitat-modeling, and information about accessing the analysis engines directly from other software. 7. Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of- the-art software that implements these methods is described that makes the methods accessible to practicing ecologists.