Equilibrium swelling measurements of network and semicrystalline polymers in supercritical carbon dioxide using high-pressure NMR

The extent of swelling of cross-linked poly(dimethylsiloxane) and linear low-density poly(ethylene) in supercritical CO2 has been investigated using high-pressure NMR spectroscopy and microscopy. Poly(dimethylsiloxane) was cross-linked to four different cross-link densities and swollen in supercritical CO2. The Flory-Huggins interaction parameter, x, was found to be 0.62 at 300 bar and 45 degrees C, indicating that supercritical CO2 is a relatively poor solvent compared to toluene or benzene. Linear low-density poly(ethylene) was shown to exhibit negligible swelling upon exposure to supercritical CO2 up to 300 bar. The effect Of CO2 pressure on the amorphous region of the poly(ethylene) was investigated by observing changes in the H-1 T-2 relaxation times of the polymer. These relaxation times decreased with increasing pressure, which was attributed to a decrease in mobility of the polymer chains as a result of compressive pressure.

A bayesian artificial neural network method to characterise laminar defects using dynamic measurements

This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.

Physical outcome measurements via the Internet: reliability at two Internet speeds

We have developed a software application to enable interactive rehabilitation via the Internet. The reliability of the telemedicine application was examined by comparing it with face-to-face assessment. The physical outcome measures assessed were knee range of motion, quadriceps muscle strength, limb girth and an assessment of gait. One therapist performed both in-person and Internet-based measurements of all outcome measures on 20 normal subjects. There was good agreement between the two techniques (the 95% limits of agreement included zero for all the variables studied). Internet assessments were conducted at two bandwidths: ISDN at 128 kbit/s and the telephone network at 17 kbit/s. Bandwidth had no significant influence on any of the measures. This study suggests that Internet-based physiotherapy interventions delivered to the home are suitable for further development.

Use of liquid phase adsorption for characterizing pore network connectivity in activated carbon

A simple percolation theory-based method for determination of the pore network connectivity using liquid phase adsorption isotherm data combined with a density functional theory (DFT)-based pore size distribution is presented in this article. The liquid phase adsorption experiments have been performed using eight different esters as adsorbates and microporous-mesoporous activated carbons Filtrasorb-400, Norit ROW 0.8 and Norit ROX 0.8 as adsorbents. The density functional theory (DFT)-based pore size distributions of the carbons were obtained using DFT analysis of argon adsorption data. The mean micropore network coordination numbers, Z, of the carbons were determined based on DR characteristic plots and fitted saturation capacities using percolation theory. Based on this method, the critical molecular sizes of the model compounds used in this study were also obtained. The incorporation of percolation concepts in the prediction of multicomponent adsorption equilibria is also investigated, and found to improve the performance of the ideal adsorbed solution theory (IAST) model for the large molecules utilized in this study. (C) 2002 Elsevier Science B.V. All rights reserved.

Effect of pore-network connectivity on multicomponent adsorption of large molecules

The effect of pore-network connectivity on binary liquid-phase adsorption equilibria using the ideal adsorbed solution theory (LAST) was studied. The liquid-phase binary adsorption experiments used ethyl propionate, ethyl butyrate, and ethyl isovalerate as the adsorbates and commercial activated carbons Filtrasorb-400 and Norit ROW 0.8 as adsorbents. As the single-component isotherm, a modified Dubinin-Radushkevich equation was used. A comparison with experimental data shows that incorporating the connectivity of the pore network and considering percolation processes associated with different molecular sizes of the adsorptives in the mixture, as well as their different corresponding accessibility, can improve the prediction of binary adsorption equilibria using the LAST Selectivity of adsorption for the larger molecule in binary systems increases with an increase in the pore-network coordination number, as well with an increase in the mean pore width and in the spread of the pore-size distribution.