Molecular modelling of polymers 17. Simulation and QSPR analyses of transport behavior in amorphous polymeric materials

Quantitative structure-property relationships (QSPRs) were constructed to predict O 2 , N 2 and CO 2 diffusion in amorphous polymers. The major polymer property governing diffusion in these QSPR models is bulk modulus. Oxygen permeation and solubility QSPR models were also constructed. Cohesive energy of the polymer matrix is the polymer property most highly correlated to permeation. Oxygen solubility appears to be about equally dependent on polymer density, bulk modulus or cohesive energy. A limited QSPR exploration of aqueous diffusion in polymer matrices indicates that cohesive energy of the polymeric material governs aqueous diffusion. The QSPR models can be used to efficiently predict transport properties from molecular dynamics simulations since only bulk modulus and/or cohesive energy need to be determined from a simulation in order to estimate a transport property using the appropriate QSPR model. An original computational technique to generate close-to-equilibrium dense polymeric structures is proposed. Diffusion of small gases are studied on the equilibrated structures using massively parallel molecular dynamics simulations running on the Intel Teraflops (9200 Pentium Pro processors) and Intel Paragon (1840 processors). Compared to the current state-of-the-art equilibration methods, the new technique appears to be faster by some orders of magnitude. The main advantage of the technique is that one can circumvent the bottlenecks in configuration space that inhibit relaxation in molecular dynamics simulations. The technique is based on the fact that tetravalent atoms (such as carbon and silicon) fit in the centre of a regular tetrahedron and that regular tetrahedrons can be used to mesh three-dimensional space. Thus, the problem of polymer equilibration described by continuous equations in molecular dynamics is reduced to a discrete representation where solutions are approximated by simple algorithms.