Reactive molecular dynamics simulations of the initial stage of brown coal oxidation at high temperatures

Yan, Guochao; Zhang, Zhiqiang; Yan, Kefeng

doi:10.1080/00268976.2012.708443

Cited by 48 publications

(18 citation statements)

References 24 publications

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“…The intermediate species are generated with the consumption of reactants, and the concentration profiles converge to values corresponding to chemical equilibrium. This kind of cursory analysis is commonly performed by almost all ReaxFF simulation studies …”

Section: Resultsmentioning

confidence: 99%

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Extracting the mechanisms and kinetic models of complex reactions from atomistic simulation data

Sun

et al. 2019

J Comput Chem

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Determining reaction mechanisms and kinetic models, which can be used for chemical reaction engineering and design, from atomistic simulation is highly challenging. In this study, we develop a novel methodology to solve this problem. Our approach has three components: (1) a procedure for precisely identifying chemical species and elementary reactions and statistically calculating the reaction rate constants; (2) a reduction method to simplify the complex reaction network into a skeletal network which can be used directly for kinetic modeling; and (3) a deterministic method for validating the derived full and skeletal kinetic models. The methodology is demonstrated by analyzing simulation data of hydrogen combustion. The full reaction network comprises 69 species and 256 reactions, which is reduced into a skeletal network of 9 species and 30 reactions. The kinetic models of both the full and skeletal networks represent the simulation data well. In addition, the essential elementary reactions and their rate constants agree favorably with those obtained experimentally. © 2019 Wiley Periodicals, Inc.

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Section: Resultsmentioning

confidence: 99%

“…Despite the advances in identifying reaction species and rates from simulation data, there is no established method for obtaining reaction mechanisms that can be used directly for engineering (kinetic) modeling. In a recent work by Döntgen et al, a method for identifying reaction species and elementary reactions was proposed.…”

Section: Introductionmentioning

confidence: 99%

Extracting the mechanisms and kinetic models of complex reactions from atomistic simulation data

Sun

et al. 2019

J Comput Chem

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“…Liu et al 25 studied the pyrolysis process of perfluorinated ketones at different temperatures (300–5000 K) by using ReaxFF. Salmon et al, 26 Yan et al, 27 and Chen et al 28 used ReaxFF to study the pyrolysis and oxidation of lignite. Xu et al 29 used the ReaxFF-MD simulation method to study the characteristics of lignite pyrolysis products, main element transformation behavior, and pyrolysis mechanism from the perspective of clean utilization at 1600–3000 K. Zheng et al 30 used the ReaxFF molecular dynamic method to study the product distribution and initial chemical reaction of Liulin coal during pyrolysis at 1000–2600 K. Gao et al 31 discussed the dynamic migration mechanism of organic oxygen in the coal pyrolysis process by the ReaxFF molecular dynamic method.…”

Section: Introductionmentioning

confidence: 99%

Study on the Formation Mechanism of the Pyrolysis Products of Lignite at Different Temperatures Based on ReaxFF-MD

Zhu

Huo

et al. 2021

ACS Omega

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The internal part of coal that is not in contact with oxygen will undergo pyrolysis reaction due to heat conduction, and the active groups generated can reverse-aggravate the degree of coal spontaneous combustion. At present, a few studies have been conducted on the pyrolysis mechanism of coal at different temperatures by using mutually validated experimental and simulation methods, resulting in the mismatch between the microscopic mechanism and macroscopic characteristics. In this paper, DH lignite is taken as the research object, and its macromolecular model is established. The pyrolysis reaction of lignite is studied by the experimental methods of coal pyrolysis index gas collection and detection experimental and thermogravimetric analyses and the simulation method of ReaxFF-MD. The influence of temperature on lignite pyrolysis is explored by analyzing the distribution of products at different temperatures and the formation mechanism of typical products, so as revealing the microscopic mechanism of lignite pyrolysis. The results show that 110–500 K of experimental temperature corresponds to 1400–2400 K of simulation temperature. CO 2 and C 2 H 4 are the main gas products during pyrolysis simulation. Carboxyl and ester groups are the main source of CO 2 , which gradually increases with the rise of temperature. Since CO 2 can be reduced to produce CO, H 2 O, and C 2 H 2 O at high temperatures, the yield decreases when the temperature is higher than 2000 K. C 2 H 4 is derived from the decomposition of long-chain aliphatic hydrocarbons, and its yield fluctuation rises with the rise of temperature. The formation of H 2 O and H 2 mainly occurs in the secondary pyrolysis stage. When 1400 K < T < 2100 K, the primary pyrolysis is the main reaction, where the weak bridge bonds and macromolecular structure undergo cleavage to form gas products and tar free radical fragments. When T > 2100 K, the secondary pyrolysis reactions were significant. Tar free radicals and char undergo decomposition, hydrogenation, and polymerization reaction, gas products and tar free radicals increase, and the char yield decreases compared with the primary pyrolysis stage, so 2100 K is the key temperature of the pyrolysis reaction. The research is of great importance in improving the accurate control of coal spontaneous combustion.

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“…With the development of force field (e.g., ReaxFF, firstly carried out by van Duin [13]) and software (e.g., Material studio, VASP, Gaussian), the molecular simulation methods have frequently been used to obtain the reaction mechanism of chemical substances pyrolysis, such as triglyceride [14,15], ndodecane [16], coal pyrolysis [17][18][19], which is an approach closer to real world process. ReaxFF MD simulation has been affirmed successfully to describe the molecular process underlying the kinetics in pyrolysis.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, Zhang et al [30], reported the reaction mechanism of coal pyrolysis and hydrogen production, and concluded that the water clusters in SCW weaken the C-C bonds in aromatic rings. Yan et al [19], investigated the initial stage of brown coal oxidation at high temperature by reactive MD simulation and showed oxidation and pyrolysis of aromatic ring. The early maturation processes in Morwell Brown coal were reported by Salmon et al [31], using ReaxFF MD simulation.…”

Section: Introductionmentioning

confidence: 99%

Molecular model and ReaxFF molecular dynamics simulation of coal vitrinite pyrolysis

Zhu

Wang

et al. 2015

J Mol Model

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Vitrinite in coal, the mainly generating methane maceral, plays an important role in hydrocarbon generation of coal. This study aims at obtaining products formation mechanism of vitrinite pyrolysis, and hence determining the chemical bond, molecular liquefaction activity, and reactions mechanism of methane and C2-4 during pyrolysis. The ReaxFF molecular dynamics (MD) simulation was carried out at temperature of 1500 K in order to investigate the mechanism of vitrinite pyrolysis. Initially, a minimum energy conformational structure model was constrained by a combination of elemental and carbon-13 nuclear magnetic resonance ((13)C NMR) literature data. The model analysis shows the chemical and physical parameters of vitrinite pyrolysis are broadly consistent with the experimental data. Based on the molecular model, ReaxFF MD simulations further provide information of unimolecule such as bond length, and chemical shift, and hence the total population and energy of main products. Molecules bond and pyrolysis fragments, based on active bond analyzed, revealed pyrolysis products of single vitrinite molecule with aliphatic C-C bond, especially ring and chain aliphatic as liquefaction activity. The molecular cell whose density is 0.9 g/cm(3) with lowest energy accords with the experimental density 1.33 g/cm(3). The content of main products after pyrolysis, classifying as CH4, H2O, and H2, was changed along with the increasing temperature. The gas molecule, fragments and generation pathways of CO2, H2, CH4, and C2H6 were also elucidated. These results show agreement with experimental observations, implying that MD simulation can provide reasonable explanation for the reaction processes involved in coal vitrinite pyrolysis. Thus the mechanism of coal hydrocarbon generation was revealed at the molecular level.

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Reactive molecular dynamics simulations of the initial stage of brown coal oxidation at high temperatures

Cited by 48 publications

References 24 publications

Extracting the mechanisms and kinetic models of complex reactions from atomistic simulation data

Extracting the mechanisms and kinetic models of complex reactions from atomistic simulation data

Study on the Formation Mechanism of the Pyrolysis Products of Lignite at Different Temperatures Based on ReaxFF-MD

Molecular model and ReaxFF molecular dynamics simulation of coal vitrinite pyrolysis

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