Material properties of nanoclay PVC composites

Nanocomposites of poly(vinyl chloride) have been prepared using both hectorite- and bentonite-based organically-modified clays. The organic modification used is tallow-triethanol-ammonium ion. The morphology of the systems was investigated using X-ray diffraction and transmission electron microscopy and these systems show that true nanocomposites, both intercalated and exfoliated systems, are produced. The mechanical properties have been evaluated and the modulus increases upon nanocomposite formation without a significant decrease in tensile strength or elongation at break. Thermal analysis studies using thermogravimetric analysis, differential scanning calorimetry, and dynamic mechanical analysis were conducted. Thermal stability of the PVC systems was assessed using a standard thermal process evaluating the evolution of hydrogen chloride and by color development through the yellowness index. Cone calorimetry was used to measure the fire properties and especially to evaluate smoke evolution. The addition of an appropriately-modified bentonite or hectorite nanoclay leads to both a reduction in the total smoke that is evolved, and an increase in the length of time over which smoke is evolved. Along with this, a reduction in the peak heat release rate is seen. It is likely that the presence of the clay in some way interferes with the cyclization of the conjugated system formed upon HCl loss

Systematically missing confounders in individual participant data meta-analysis of observational cohort studies.

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohort