Disorder and dissolution enhancement: Deposition of ibuprofen on to insoluble polymers

Microcrystalline cellulose (MCC) and cross-linked polyvinylpyrrolidone (PVP-CL) were examined as polymeric carriers to support amorphous ibuprofen (IB). Drug/cartier systems were prepared as physical mixes, and drug was loaded onto the polymers by hot mix and solvent deposition methods. The systems were examined using differential scanning calorimetry (DSC), X-ray powder diffractometry (XRD) and by dissolution testing. PVP-CL reduced drug crystallinity more than MCC and, surprisingly, even very simple mixing of ibuprofen with PVP-CL induced disordering of the drug. Increased ibuprofen dissolution rates were achieved with both polymers, in the order of solvent deposition > hot mixes > physical mixes. The increased dissolution rates could be attributed to a combination of faster dissolution from amorphous ibuprofen, microcrystalline drug deposition on carrier surfaces and polymer swelling. However, no clear relationship was observed between ibuprofen dissolution rates (using first order, Higuchi or Hixson-Crowell relationships) and drug crystallinity. (C) 2005 Elsevier B.V. All rights reserved.

Novel glycopolymer hydrogels as mucosa-mimetic materials to reduce animal testing

Glycopolymer hydrogels capable of mimicking mucosal tissue in mucoadhesion testing have been designed. Liquid formulations containing mucoadhesive polymers were found to be retained on these tissues to the same extent as ex vivo gastric mucosa, when using a dynamic method of assessing mucoadhesion.

Linear viscoelasticity from molecular dynamics simulation of entangled polymers

The linear viscoelastic (LVE) spectrum is one of the primary fingerprints of polymer solutions and melts, carrying information about most relaxation processes in the system. Many single chain theories and models start with predicting the LVE spectrum to validate their assumptions. However, until now, no reliable linear stress relaxation data were available from simulations of multichain systems. In this work, we propose a new efficient way to calculate a wide variety of correlation functions and mean-square displacements during simulations without significant additional CPU cost. Using this method, we calculate stress−stress autocorrelation functions for a simple bead−spring model of polymer melt for a wide range of chain lengths, densities, temperatures, and chain stiffnesses. The obtained stress−stress autocorrelation functions were compared with the single chain slip−spring model in order to obtain entanglement related parameters, such as the plateau modulus or the molecular weight between entanglements. Then, the dependence of the plateau modulus on the packing length is discussed. We have also identified three different contributions to the stress relaxation:  bond length relaxation, colloidal and polymeric. Their dependence on the density and the temperature is demonstrated for short unentangled systems without inertia.

Hierarchical modeling of entangled polymers

We demonstrate that it is possible to link multi-chain molecular dynamics simulations with the tube model using a single chain slip-links model as a bridge. This hierarchical approach allows significant speed up of simulations, permitting us to span the time scales relevant for a comparison with the tube theory. Fitting the mean-square displacement of individual monomers in molecular dynamics simulations with the slip-spring model, we show that it is possible to predict the stress relaxation. Then, we analyze the stress relaxation from slip-spring simulations in the framework of the tube theory. In the absence of constraint release, we establish that the relaxation modulus can be decomposed as the sum of contributions from fast and longitudinal Rouse modes, and tube survival. Finally, we discuss some open questions regarding possible future directions that could be profitable in rendering the tube model quantitative, even for mildly entangled polymers

Microscopic Mechanisms of Strain Hardening in Glassy Polymers

The mechanisms underlying the increase in stress for large mechanical strains of a polymer glass, quantified by the strain-hardening modulus, are still poorly understood. In the present paper we aim to elucidate this matter and present new mechanisms. Molecular-dynamics simulations of two polymers with very different strain-hardening moduli (polycarbonate and polystyrene) have been carried out. Nonaffine displacements occur because of steric hindrances and connectivity constraints. We argue that it is not necessary to introduce the concept of entanglements to understand strain hardening, but that hardening is rather coupled with the increase in the rate of nonaffine particle displacements. This rate increases faster for polycarbonate, which has the higher strain-hardening modulus. Also more nonaffine chain stretching is present for polycarbonate. It is shown that the inner distances of such a nonaffinely deformed chain can be well described by the inner distances of the worm-like chain, but with an effective stiffness length (equal to the Kuhn length for an infinite worm-like chain) that increases during deformation. It originates from the finite extensibility of the chain. In this way the increase in nonaffine particle displacement can be understood as resulting from an increase in the effective stiffness length of the perturbed chain during deformation, so that at larger strains a higher rate of plastic events in terms of nonaffine displacement is necessary, causing in turn the observed strain hardening in polymer glasses.

Testing the influence of small crystals on ice size spectra using Doppler lidar observations

Analysis of the vertical velocity of ice crystals observed with a 1.5micron Doppler lidar from a continuous sample of stratiform ice clouds over 17 months show that the distribution of Doppler velocity varies strongly with temperature, with mean velocities of 0.2m/s at -40C, increasing to 0.6m/s at -10C due to particle growth and broadening of the size spectrum. We examine the likely influence of crystals smaller than 60microns by forward modelling their effect on the area-weighted fall speed, and comparing the results to the lidar observations. The comparison strongly suggests that the concentration of small crystals in most clouds is much lower than measured in-situ by some cloud droplet probes. We argue that the discrepancy is likely due to shattering of large crystals on the probe inlet, and that numerous small particles should not be included in numerical weather and climate model parameterizations.

Why are some handaxes symmetrical? Testing the influence of handaxe morphology on butchery effectiveness

The morphology of Acheulean handaxes continues to be a subject of debate amongst Lower Palaeolithic archaeologists, with some arguing that many handaxes are over-engineered for a subsistence function alone. This study aims to provide an empirical foundation for these debates by testing the relationship between a range of morphological variables, including symmetry, and the effectiveness of handaxes for butchery. Sixty handaxes were used to butcher 30 fallow deer by both a professional and a non-professional butcher. Regression analysis on the resultant data set indicates that while frontal symmetry may explain a small amount of variance in the effectiveness of handaxes for butchery, a large percentage of variance remains unexplained by symmetry or any of the other morphological variables under consideration.

A simple model for predicting soil temperature in snow-covered and seasonally frozen soil: model description and testing

Microbial processes in soil are moisture, nutrient and temperature dependent and, consequently, accurate calculation of soil temperature is important for modelling nitrogen processes. Microbial activity in soil occurs even at sub-zero temperatures so that, in northern latitudes, a method to calculate soil temperature under snow cover and in frozen soils is required. This paper describes a new and simple model to calculate daily values for soil temperature at various depths in both frozen and unfrozen soils. The model requires four parameters average soil thermal conductivity, specific beat capacity of soil, specific heat capacity due to freezing and thawing and an empirical snow parameter. Precipitation, air temperature and snow depth (measured or calculated) are needed as input variables. The proposed model was applied to five sites in different parts of Finland representing different climates and soil types. Observed soil temperatures at depths of 20 and 50 cm (September 1981-August 1990) were used for model calibration. The calibrated model was then tested using observed soil temperatures from September 1990 to August 2001. R-2-values of the calibration period varied between 0.87 and 0.96 at a depth of 20 cm and between 0.78 and 0.97 at 50 cm. R-2 -values of the testing period were between 0.87 and 0.94 at a depth of 20cm. and between 0.80 and 0.98 at 50cm. Thus, despite the simplifications made, the model was able to simulate soil temperature at these study sites. This simple model simulates soil temperature well in the uppermost soil layers where most of the nitrogen processes occur. The small number of parameters required means, that the model is suitable for addition to catchment scale models.