The analysis of first-passage time statistics in soft-matter systems, such as water near amino-acid crystals explored in [1], can be vital in understanding the dynamical complexity of their chemical and geometrical properties. From the first-passage time statistics of water molecules, it was shown in [1, 2] that it is possible to infer space-dependent diffusion coefficients in directions normal to various phase boundaries.
The analysis developed in [1, 2] is highly-nontrivial, computationally expensive, and system-dependent. Here, in an interdisciplinary collaboration between statistical physics and atomistic simulations, we aim to develop a generic computational methodology which will allow us to extract and analyse trajectories, obtained from molecular dynamics simulations by programs such as GROMACS or LAMMPS, to determine first passage times and spatially resolved diffusion coefficients. We perform exhaustive high-performance-computing benchmarks of our algorithm in various
aqueous systems, and develop a user-friendly interface that we will make available to researchers as an open-source toolbox, working on in-silico studies of natural products.
