An automated multi-scale approach to predict self-diffusion from a potential energy field

A. K. Mace, S. D. Barthel, and B. Smit, An automated multi-scale approach to predict self-diffusion from a potential energy field J. Chem. Theory Comput.  (2019) 15 (4), 2127–2141  http://dx.doi.org/10.1021/acs.jctc.8b01255


Abstract: For large-scale screening studies there is a need to estimate the diffusion of gas molecules in nanoporous materials more efficiently than (brute force) molecular dynamics. In particular for systems with low diffusion coefficients molecular dynamics can be prohibitory expensive. An alternative is to compute the hoping rates between adsorption sites using transition state theory. For large-scale screening this requires the automatic detection of the transition states between the adsorption sites along the different diffusion paths.

Here an algorithm is presented that analyses energy grids for the moving particles. It detects the energies at which diffusion paths are formed, together with their direction. This allows to easily identify non-diffusive systems. For diffusive systems, it partitions the grid coordinates assigned to energy basins and transitions states, permitting a transition state theory based analysis of the diffusion.

We test our method on methane diffusion in zeolites, using a standard kinetic Monte Carlo simulation based on the output of our grid analysis. We find that it is accurate, fast, and rigorous without limitations to the geometries of the diffusion tunnels or transition states.

© Berend Smit 2019