Investigation by Combined Solid-State NMR and SAXS Methods of the Morphology and Domain Size in Polystyrene-b-Polyethylene Oxide-b-Polystyrene Triblock Copolymers

The microphase structure of a series of polystyrene-b-polyethylene oxide-b-polystyrene (SEOS) triblock copolymers with different compositions and molecular weights has been studied by solid-state NMR, DSC, wide and small angle X-ray scattering (WAXS and SAXS). WAXS and DSC measurements were used to detect the presence of crystalline domains of polyethyleneoxide (PEO) blocks at room temperature as a function of the copolymer chemical composition. Furthermore, DSC experiments allowed the determination of the melting temperatures of the crystalline part of the PEO blocks. SAXS measurements, performed above and below the melting temperature of the PEO blocks, revealed the formation of periodic structures, but the absence or the weakness of high order reflections peaks did not allow a clear assessment of the morphological structure of the copolymers. This information was inferred by combining the results obtained by SAXS and (1)H NMR spin diffusion experiments, which also provided an estimation of the size of the dispersed phases of the nanostructured copolymers. (C) 2009 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 48:55-64,2010

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

Monodisperse lignin fractions as standards in size-exclusion analysis Comparison with polystyrene standards

The difficulty of preparing monodisperse lignin fractions on a large scale is a limiting factor in many applications. The present paper addresses this problem by examining the properties and size-exclusion behavior of lignin isolated by the acetosolv pulping process from post-extraction crushed sugarcane bagasse. The isolated lignin was subjected to a solvent pretreatment, followed by preparative gel permeation chromatography fractionation. The fractions were analyzed by high-performance size-exclusion chromatography (HPSEC) and these samples showed a great decrease in polydispersity, compared to the original acetosolv lignin. Several fractions of very low polydispersity, close to unity, were employed as calibration curve standards in HPSEC analysis. This original analytical approach allowed calibration with these lignin fractions to be compared with the polystyrene standards that are universally employed for lignin molecular mass determination. This led to a noteworthy result, namely that the lignin fractions and polystyrene standards showed very similar behavior over a large range of molecular masses in a typical HPSEC analysis of acetosolv lignin. (C) 2009 Elsevier B.V. All rights reserved.

Biosurfactants as Agents to Reduce Adhesion of Pathogenic Bacteria to Polystyrene Surfaces: Effect of Temperature and Hydrophobicity

Polystyrene surfaces were conditioned with surfactin and rhamnolipid biosurfactants and then assessed regarding the attachment of Staphylococcus aureus, Listeria monocytogenes, and Micrococcus lute us. The effect of different temperatures (35, 25, and 4 degrees C) on the anti-adhesive activity was also studied. Microbial adhesion to solvents and contact angle measurements were performed to characterize bacteria and material surfaces. The results showed that surfactin was able to inhibit bacterial adhesion in all the conditions analyzed, giving a 63-66% adhesion reduction in the bacterial strains at 4 degrees C. Rhamnolipid promoted a slight decrease in the attachment of S. aureus. The anti-adhesive activity of surfactin increased with the decrease in temperature, showing that this is an important parameter to be considered in surface conditioning tests. Surfactin showed good potential as an anti-adhesive compound that can be explored to protect surfaces from microbial contamination.