Pyrolysis of Liulin Coal Simulated by GPU-Based ReaxFF MD with Cheminformatics Analysis

In this study, the first GPU-enabled
ReaxFF MD program with significantly
improved performance, surpassing CPU implementations, was employed
to explore the initial chemical mechanisms and product distributions
in pyrolysis of Liulin coal, a bituminous coal from Shanxi, PRC. The
largest coal model ever used in simulation via ReaxFF MD, the Liulin
coal molecular model consisting of 28 351 atoms was constructed
based on a combination of experiments and classical coal models. The
ReaxFF MD simulations at temperatures of 1000–2600 K were performed
for 250 ps to investigate the temperature effects on the product profile
and the initial chemical reactions of the Liulin coal model pyrolysis.
The generation rates of C14–C40 compounds
and gas tend to equilibrate within 150–250 ps, indicating that
the simulation should allow most of the thermal decomposition reactions
complete and the simulated product profiles are reasonable for understanding
the chemical reactions of the Liulin coal pyrolysis. The product (gas,
tar, and char) evolution tendencies with time and temperature observed
in the simulations are fairly in agreement with the experimental tendency
reported in the literature. In particular, the evolution trends of
three representative products (naphthalene, methyl-naphthalene and
dimethyl-naphthalene) with temperature are very consistent with Py-GC/MS
experiments. The detailed chemical reactions of the pyrolysis simulation
have been generated using VARMD (Visualization and Analysis of Reactive
Molecular Dynamics), which was newly created to examine the complexity
of the chemical reaction network in ReaxFF MD simulation. The generation
and consumption of HO· and H3C· radicals with time and temperature are reasonable and consistent
both with the evolution of H2O and CH4, and
with the detailed chemical reactions obtained as well. The amount
of six-membered ring structures was observed to decrease with time
and temperature, because of their conversion into 5-membered rings
or 7–9-membered rings or even-larger-membered ring structures
that will further open and decompose into small fragments. This work
demonstrates a new methodology for investigating coal pyrolysis mechanism
by combining GPU-enabled high-performance computing with cheminformatics
analysis in ReaxFF MD.