Acceleration of Diffusion in Ab Initio Nanoreactor\nMolecular Dynamics and Application to Hydrogen Sulfide Oxidation

The computational\ndescription of chemical reactivity can become\nextremely complex when multiple different reaction products and intermediates\ncome into play, forming a chemical reaction network. Therefore, computational\nmethods for the automated construction of chemical reaction networks\nhave been developed in the last decades. One of these methods, ab\ninitio nanoreactor molecular dynamics (NMD), is based on external\nforces enhancing reactivity by e.g., periodically compressing the\nsystem and allowing it to relax. However, during the relaxation process,\na significant simulation time is required to allow energy to dissipate\nand molecules to diffuse, making this part of the NMD simulation computationally\nintensive. This work aims to improve NMD by accelerating the diffusion\nprocess in the relaxation phase. We systematically investigate the\nspeedup of reaction discovery gained by diffusion acceleration, leading\nto a factor of up to 28 in discovery frequency. Diffusion-accelerated\nnanoreactor molecular dynamics (DA-NMD) is then used to construct\na reaction network of hydrogen sulfide oxidation under atmospheric\nconditions, where reactions are automatically detected by a change\nin the bond order and bond distance. A reaction network of 108 molecular\nspecies and 399 elementary reactions was constructed starting from\nhydrogen sulfide, hydroxy radicals, and molecular oxygen covering\na broad variety of sulfur–oxygen chemistry and oxidation states\nof the sulfur atom ranging from −II to +VI.