Molecular modeling is applied to a representative array of kerogens for the purpose of obtaining quantitative predictions of thermodynamic properties from quantum mechanics and volumetric properties from molecular dynamics. The kerogen model units (175–260 carbon atoms) have been built in the MedeA environment from the sole consideration of the elemental analysis and functional group analysis documented in the work of Exxon and IFP-EN scientists [Kelemen, S. R., et al., Energy Fuels, 2007, 21 (3), pp 1548–1561]. The density results are in good agreement with the well-documented trends of kerogen density with thermal maturity and organic type. The heat capacity in the ideal gas state is predicted to increase as a function of temperature, as obtained from quantum mechanics at the semiempirical level (MOPAC-PM7). This result is in quantitative agreement with experimental heat capacity data on type I kerogen and on coal. This behavior appears clearly as a nonclassical feature, because of the quantization of e...

Molecular Modeling of the Volumetric and Thermodynamic Properties of Kerogen: Influence of Organic Type and Maturity

Valorization of disposable COVID-19 mask through the thermo-chemical process

A detailed insight of key reactive events related to oxidation and pyrolysis of hydrocarbon fuels further enhances our understanding of combustion chemistry. Though comprehensive kinetic models are available for smaller hydrocarbons (typically C3 or lower), developing and validating reaction mechanisms for larger hydrocarbons is a daunting task, due to the complexity of their reaction networks. The ReaxFF method provides an attractive computational method to obtain reaction kinetics for complex fuel and fuel mixtures, providing an accuracy approaching ab-initio-based methods but with a significantly lower computational expense. The development of the first ReaxFF combustion force field by Chenoweth et al. (CHO-2008 parameter set) in 2008 has opened new avenues for researchers to investigate combustion chemistry from the atomistic level. In this article, we seek to address two issues with the CHO-2008 ReaxFF description. While the CHO-2008 description has achieved significant popularity for studying large ...

Extension of the ReaxFF Combustion Force Field toward Syngas Combustion and Initial Oxidation Kinetics

Initial reaction mechanisms of cellulose pyrolysis revealed by ReaxFF molecular dynamics

Combustion is a complex chemical system which involves thousands of chemical reactions and generates hundreds of molecular species and radicals during the process. In this work, a neural network-based molecular dynamics (MD) simulation is carried out to simulate the benchmark combustion of methane. During MD simulation, detailed reaction processes leading to the creation of specific molecular species including various intermediate radicals and the products are intimately revealed and characterized. Overall, a total of 798 different chemical reactions were recorded and some new chemical reaction pathways were discovered. We believe that the present work heralds the dawn of a new era in which neural network-based reactive MD simulation can be practically applied to simulating important complex reaction systems at ab initio level, which provides atomic-level understanding of chemical reaction processes as well as discovery of new reaction pathways at an unprecedented level of detail beyond what laboratory experiments could accomplish. Gaining insights into combustion processes is challenging due to the complex reactions involved. The present work proposes a neural network potential model trained to ab initio data that enables to simulate the combustion of methane by predicting reactants, products and reaction intermediates.

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Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation.

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 C-14-C-40 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 center dot 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.

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

Study of high density polyethylene (HDPE) pyrolysis with reactive molecular dynamics

Efficient degradation of tetracycline by persulfate activation with Fe, Co and O co−doped g−C3N4: Performance, mechanism and toxicity

Tar compositions from pyrolysis of three ranks of Chinese coals of Hailaer lignite, Fugu sub-bituminous coal, and Liulin bituminous coal under different temperatures and pressures were analyzed via a pyrolyer combined with gas chromatography/mass spectrometry (Py-GC/MS). A nuclear magnetic resonance (NMR) analysis was performed to characterize the coals. It was found that the relative content of polycyclic aromatic hydrocarbons (PAHs) is not as sensitive to temperature as monocyclic aromatic hydrocarbons (MAHs), which increased with increasing the pyrolysis temperature. A decreasing trend of the content of acids/esters was observed for all three ranks of coals. However, the three coals exhibited quite different trends with the temperature in terms of the relative content of aliphatic hydrocarbons. MAHs and PAHs were predominant components in the tar from Liulin bituminous coal. The tars from Hailaer lignite and Fugu sub-bituminous coal were rich in phenolics, which can be detected at a low temperature of 400 degrees C. In contrast, the phenolics were much less in the tar from Liulin bituminous coal and can merely remarkably be detected at a higher temperature of 600 degrees C. The contents of phenolics and aliphatic hydrocarbons decreased with increasing the pressure for all three coals, and the contents of MAHs and PAHs showed inverse trends with the pressure. This could result from the enhanced reactions of cydizations of aliphatics and scissions of the C-OH bond in phenolics by elevated pressure. C-19 alkane and p-cresol as model compounds of aliphatics and phenolics were pyrolyzed under high pressures to verify this point. For a larger particle size of Fugu sub-bituminous and Liulin bituminous coals, the contents of aliphatics decreased remarkably, while the contents of MAHs and PAHs were distinctly augmented. This could be attributed to the intraparticle secondary reactions.

Xiaomin Gong

Papers

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

Study of high density polyethylene (HDPE) pyrolysis with reactive molecular dynamics

Efficient degradation of tetracycline by persulfate activation with Fe, Co and O co−doped g−C3N4: Performance, mechanism and toxicity

Impact of the Temperature, Pressure, and Particle Size on Tar Composition from Pyrolysis of Three Ranks of Chinese Coals

Principles, synthesis and applications of dual Z-scheme photocatalysts