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.