references.bib

@Article{Ren_Fuel_2024_v375_p132623,
    author =   {Xuan Ren and Ruining He and Xinhui Wang and Fang Wang and Xinpeng
             Zhang and Dingcheng Wang and Shuyuan Liu and Henry J. Curran and Jinhu
             Liang and Yang Li},
    title =    {{A comprehensive experimental and theoretical study of thermal response
             mechanisms of TKX-50 and HMX}},
    journal =  {Fuel},
    year =     2024,
    volume =   375,
    pages =    132623,
    doi =      {10.1016/j.fuel.2024.132623},
}

@Article{Song_Fuel_2024_v375_p132603,
    author =   {Liang Song and Tian-Cheng Zhang and Yong Zhang and Bo-Cong Chen and
             Jing Ye and Fang-Chao Hou and Jing Sun and Su-Qin Zhou},
    title =    {{Thermal decomposition behaviors of adamantane and 1-methyladamantane
             in oxygen atmosphere: ReaxFF molecular dynamics simulation}},
    journal =  {Fuel},
    year =     2024,
    volume =   375,
    pages =    132603,
    doi =      {10.1016/j.fuel.2024.132603},
}

@Article{Yu_ChemEngJ_2024_v498_p155320,
    author =   {Xiaozhen Yu and Xiangbao Meng and Jihe Chen and Yujian Zhu and Yadi Li
             and Zhao Qin and Jianxu Ding and Shizemin Song},
    title =    {{Macroscopic behavior and kinetic mechanism of ammonium dihydrogen
             phosphate for suppressing polyethylene dust deflagration}},
    journal =  {Chem. Eng. J.},
    year =     2024,
    volume =   498,
    pages =    155320,
    doi =      {10.1016/j.cej.2024.155320},
}

@Article{Hassanloo_Fuel_2024_v374_p132486,
    author =   {Hamidreza Hassanloo and Xinyan Wang},
    title =    {{Combustion mechanism of nanobubbled dodecane: A reactive molecular
             study}},
    journal =  {Fuel},
    year =     2024,
    volume =   374,
    pages =    132486,
    doi =      {10.1016/j.fuel.2024.132486},
}

@Article{Wang_Fuel_2024_v374_p132418,
    author =   {Yutong Wang and Junhao Guo and Guozhu Liu},
    title =    {{Molecular simulation on inhomogeneous microaggregation and pyrolysis
             mechanics of supercritical methylcyclohexane}},
    journal =  {Fuel},
    year =     2024,
    volume =   374,
    pages =    132418,
    doi =      {10.1016/j.fuel.2024.132418},
}

@Article{Zhang_JHazardMater_2024_v478_p135488,
    author =   {Peng Zhang and Xinbao Xu and Xiaoming Luo},
    title =    {{Degradation pathways and product formation mechanisms of asphaltene in
             supercritical water}},
    journal =  {J. Hazard. Mater.},
    year =     2024,
    volume =   478,
    pages =    135488,
    doi =      {10.1016/j.jhazmat.2024.135488},
    abstract = {Asphaltene is the compound with the most complex structure and the
             most difficult degradation in oily sludge, which is the key to limit
             the efficiency of supercritical water oxidation treatment of oily
             sludge. In this paper, the supercritical water oxidation process of
             asphaltene was investigated in terms of free radical reaction,
             degradation pathway, and product generation mechanism using ReaxFF
             molecular dynamics simulation method. The results showed that
             increasing temperature, increasing O2, and increasing H2O have
             different effects on HO2{\textperiodcentered}generation. Benzene rings
             undergo fusion and condensation through hydrogenation abstraction and
             oxygen addition reactions, subsequently breaking down into long-chain
             alkanes. Increasing O2 can effectively promote the ring-opening of
             nitrogen-containing heterocycles. -COOH is the most important
             intermediate fragment for CO and CO2 generation, and there is a
             reaction competition with -CHO3 and -CO3. When the number of oxygen
             molecules increases from 300 to 700, the reaction frequency of -CHO3
             and -CO3 to generate CO and CO2 increases by 17.14{~}{\%} and
             12.77{~}{\%}{\textperiodcentered}H2O determines the production of H2
             by controlling the number of H{\textperiodcentered}radicals present.
             As the amount of H2O increases from 500 to 1500, the product ratio of
             H2 increases from 12.73{~}{\%} to 21.31{~}{\%}. ENVIRONMENTAL
             IMPLICATION: Asphaltene is the most structurally complex organic
             matter in oily sludge, and its presence makes it difficult for oily
             sludge to be completely degraded by conventional treatment methods
             such as pyrolysis and incineration. Polycyclic aromatic hydrocarbons
             (PAHs) represented by asphaltene increase the carcinogenicity and
             mutagenicity of oily sludge, and even irreversibly pollute soil and
             groundwater. Supercritical water oxidation, as an efficient organic
             waste treatment technology, can realize harmlessness in a green and
             efficient way. So the study on the mechanism of supercritical water
             oxidation of asphaltene is of great significance for environmental
             protection.},
}

@Article{Yu_Energy_2024_v303_p131990,
    author =   {Xiaozhen Yu and Jihe Chen and Xiangbao Meng and Yujian Zhu and Yadi Li
             and Zhao Qin and Yang Wu and Ke Yan and Shizemin Song},
    title =    {{Polyethylene deflagration characterization and kinetic mechanism
             analysis}},
    journal =  {Energy},
    year =     2024,
    volume =   303,
    pages =    131990,
    doi =      {10.1016/j.energy.2024.131990},
}

@Article{Mao_JPhysDApplPhys_2024_v57_p355501,
    author =   {Yijin Mao and Yuwen Zhang},
    title =    {{Quantifying reaction rates in methane oxidation: atomistic simulations
             at high temperature}},
    journal =  {J. Phys. D: Appl. Phys.},
    year =     2024,
    volume =   57,
    number =   35,
    pages =    355501,
    doi =      {10.1088/1361-6463/ad5217},
    abstract = {{\ensuremath{<}}jats:title<sub>Abstract{\ensuremath{<}}/jat
             s:title<sub>
             {\ensuremath{<}}jats:p<sub>This study presents a
             comprehensive analysis of methane oxidation at high temperatures (2500
             K{\textendash}3500 K){\textemdash}a critical process in atmospheric
             chemistry and energy production. Employing reactive molecular dynamics
             simulations, the research bridges the knowledge gap in understanding
             the complex reaction networks at these elevated temperatures. Key
             features include the identification of intermediate species and the
             simplification of the reaction networks through advanced simulation
             and post-processing techniques. Another focus of the study is on
             employing the Arrhenius equation for nonlinear curve fitting to
             determine activation energy and pre-exponential factors for various
             reactions. The analysis reveals that, despite temperature variations,
             there are 121 common reactions among the reduced reaction systems.
             This discovery revealed the underlying consistency in methane
             oxidation pathways across a range of high temperatures. The results of
             this research are vital for enhancing current models of methane
             oxidation, particularly in the context of improving combustion
             processes and deepening our understanding of atmospheric dynamics
             involving methane.{\ensuremath{<}}/jats:p<sub>},
}

@Article{Wang_IntJRefrig_2024_v165_p360,
    author =   {Xueyan Wang and Hua Tian and Gequn Shu and Zhao Yang},
    title =    {{Effect of H2O on macroscopic flame behaviors and combustion reaction
             mechanism of 1,1-difluoroethane (R152a)}},
    journal =  {Int. J. Refrig.},
    year =     2024,
    volume =   165,
    pages =    {360--374},
    doi =      {10.1016/j.ijrefrig.2024.05.013},
}

@Article{Schmalz_IntJChemKinet_2024_v56_p501,
    author =   {Felix Schmalz and Wassja A. Kopp and Eirini Goudeli and Kai Leonhard},
    title =    {{Reaction path identification and validation from molecular dynamics
             simulations of hydrocarbon pyrolysis}},
    journal =  {Int J Chem. Kinet.},
    year =     2024,
    volume =   56,
    number =   9,
    pages =    {501--512},
    doi =      {10.1002/kin.21719},
    abstract = {{\ensuremath{<}}jats:title<sub>Abstract{\ensuremath{<}}/jat
             s:title<sub>{\ensuremath{<}}jats:p<sub>Creation
             of complex chemical mechanisms for hydrocarbon pyrolysis and
             combustion is challenging due to the large number of species and
             reactions involved. Reactive molecular dynamics (RMD) enables the
             simulation of thousands of reactions and the discovery of previously
             unknown components of the reaction network. However, due to the
             inherent imprecision of reactive force fields, it is necessary to
             verify RMD{-}obtained reaction paths using more accurate methods such
             as Density Functional Theory (DFT). We demonstrate a method for
             identification and confirmation of reaction pathways from RMD that
             supplement an established mechanism, using the example of benzene
             formation from {\ensuremath{<}}jats:italic<sub>n{\ensuremat
             h{<}}/jats:italic<sub>{-}heptane and {\ensuremath{<}}jats:i
             talic<sub>iso{\ensuremath{<}}/jats:italic<sub>{-
             }octane pyrolysis. We establish a validation workflow to extract
             reaction geometries from RMD and optimize transition states using the
             Nudged{-}Elastic{-}Band method on semi{-}empirical and quantum
             mechanical levels of theory. Our findings demonstrate that the widely
             recognized ReaxFF parameterization, CHO2016, can identify known
             pathways from a established soot formation mechanism while also
             indicating new ones. We also show that CHO2016 underestimates hydrogen
             migration barriers by up to  as compared to DFT and can lower
             activation barriers significantly for spin{-}forbidden reactions. This
             highlights the necessity for validation or potentially even
             reparametrization of{~}CHO2016.{\ensuremath{<}}/jats:p<sub>},
}

@Article{Ma_AngewChemInternationalEngl_2024_v63_pe202403614,
    author =   {Lunliang Ma and Tao Wang},
    title =    {{Rational Understanding Hydroxide Diffusion Mechanism in Anion Exchange
             Membranes during Electrochemical Processes with RDAnalyzer}},
    journal =  {Angew. Chem. (International, Engl.)},
    year =     2024,
    volume =   63,
    number =   34,
    pages =    {e202403614},
    doi =      {10.1002/anie.202403614},
    abstract = {Enhancing the understanding of hydroxide transport mechanisms in anion
             exchange membranes (AEMs) is beneficial for the rational design of
             high-performance AEMs in the renewable energy system. However, the
             high complexity and lack of adequate analytic tools make it
             challenging to clarify different mechanisms unambiguously. Herein, we
             developed an in-house toolkit, the Reactive Diffusion Analyzer
             (RDAnalyzer), to conduct an effective analysis of hydroxide diffusion
             mechanisms from ReaxFF molecular dynamic simulations. Using the
             experimentally well-synthesized T20NC6NC5N as a model system, we
             successfully decoupled the hydroxide diffusion mechanisms into free
             Vehicular and free Grotthuss, as well as associated Vehicular and
             associated Grotthuss, which was not yet achieved previously.
             Meanwhile, RDAnalyzer managed to specifically identify the drift
             length of hydroxide species for each mechanism under the electric
             field, which worked as a useful variable for calculating the
             conductivity of AEMs. Our theoretically predicted conductivity for
             T20NC6NC5N agrees reasonably with experimental results, indicating the
             reliability of RDAnalyzer. This work not only provides a rational
             understanding of the complex hydroxide diffusion mechanisms in AEMs
             but also holds the potential to guide the rational design of high-
             performance AEMs with computations.},
}

@Article{Xing_IntJHydrogEnergy_2024_v77_p126,
    author =   {Zhihao Xing and Xi Jiang and Roger F. Cracknell},
    title =    {{Investigation of the chemical mechanism of pollutant formation in co-
             firing of ammonia and biomass lignin}},
    journal =  {Int. J. Hydrog. Energy},
    year =     2024,
    volume =   77,
    pages =    {126--137},
    doi =      {10.1016/j.ijhydene.2024.06.171},
}

@Article{Lv_MaterTodayCommun_2024_v40_p109624,
    author =   {Meiheng Lv and Yifan Zhang and Runze Liu and Yinhua Ma and Li Liu and
             Wenze Li and Huaxin Liu and Jianyong Liu},
    title =    {{Exploring the thermal decomposition mechanism of nitromethane via a
             neural network potential}},
    journal =  {Mater. Today Commun.},
    year =     2024,
    volume =   40,
    pages =    109624,
    doi =      {10.1016/j.mtcomm.2024.109624},
}

@Article{Deng_JEnergyInst_2024_v115_p101676,
    author =   {Bingxin Deng and Xiaoya Chang and Yongjin Wang and Qingzhao Chu and
             Dongping Chen},
    title =    {{Pyrolysis mechanism of a highly branched bio-derived fuel and its
             blends with aviation kerosene (RP-3)}},
    journal =  {J. Energy Inst.},
    year =     2024,
    volume =   115,
    pages =    101676,
    doi =      {10.1016/j.joei.2024.101676},
}

@Article{Wei_Energies_2024_v17_p3536,
    author =   {Yu Wei and Xiaohui Zhang and Shan Qing and Hua Wang},
    title =    {{Reaction Mechanism of Pyrolysis and Combustion of Methyl Oleate: A
             ReaxFF-MD Analysis}},
    journal =  {Energies},
    year =     2024,
    volume =   17,
    number =   14,
    pages =    3536,
    doi =      {10.3390/en17143536},
    abstract = {{\ensuremath{<}}jats:p<sub>As an emerging environmentally
             friendly fuel, biodiesel has excellent fuel properties comparable to
             those of petrochemical diesel. Oleic acid methyl ester, as the main
             component of biodiesel, has the characteristics of high cetane number
             and low emission rate of harmful gases. However, the comprehensive
             chemical conversion pathway of oleic acid methyl ester is not clear.
             In this paper, the reactive force field molecular dynamics simulation
             (ReaxFF-MD) method is used to construct a model of oleic acid methyl
             ester pyrolysis and combustion system. Further, the chemical
             conversion kinetics process at high temperatures (2500
             K{\textendash}3500 K) was studied, and a chemical reaction network was
             drawn. The research results show that the density of the system has
             almost no effect on the decomposition activation energy of oleic acid
             methyl ester, and the activation energies of its pyrolysis and
             combustion processes are 190.02 kJ/mol and 144.89 kJ/mol,
             respectively. Ethylene, water and carbon dioxide are the dominant and
             most accumulated products. From the specific reaction mechanism, the
             main pyrolysis path of oleic acid methyl ester is the breakage of the
             C-C bond to produce small molecule intermediates, and subsequent
             transformation of the ester group radical into carbon oxides. The
             combustion path is the evolution of long-chain alkanes into short-
             carbon-chain gaseous products, and these species are further burned to
             form stable CO2 and H2O. This study further discusses the microscopic
             combustion kinetics of biodiesel, providing a reference for the
             construction of biodiesel combustion models. Based on this theoretical
             study, the understanding of free radicals, intermediates, and products
             in the pyrolysis and combustion of biomass can be
             deepened.{\ensuremath{<}}/jats:p<sub>},
}

@Article{Li_SciTotalEnviron_2024_v931_p172921,
    author =   {Haotian Li and Fuping Zeng and Xinnuo Guo and Kexin Zhu and Ju Tang},
    title =    {{Thermal degradation of greenhouse gas SF6 at realistic temperatures:
             Insights from atomic-scale CVHD simulations}},
    journal =  {Sci. Total. Environ.},
    year =     2024,
    volume =   931,
    pages =    172921,
    doi =      {10.1016/j.scitotenv.2024.172921},
    abstract = {Sulfur hexafluoride (SF6), recognized as a potent greenhouse gas with
             significant contributions to climate change, presents challenges in
             understanding its degradation processes. Molecular dynamics
             simulations are valuable tools for understanding modes of
             decomposition while the traditional approaches face limitations in
             time scale and require unrealistically high temperatures. The
             collective variable-driven hyperdynamics (CVHD) approach has been
             introduced to directly depict the pyrolysis process for SF6 gas at
             practical application temperatures, as low as 1600{~}K for the first
             time. Achieving an unprecedented acceleration factor of up to 107, the
             method extends the simulation time scale to milliseconds and beyond
             while maintaining consistency with experimental and theoretical
             models. The differences in the reaction process between simulations
             conducted at actual and elevated temperatures have been noted,
             providing insights into SF6 degradation pathways. The work provides a
             basis for the further studies on the thermal degradation of
             pollutants.},
}

@Article{Xing_ChemEngJ_2024_v489_p151492,
    author =   {Zhihao Xing and Xi Jiang},
    title =    {{Neural network potential-based molecular investigation of pollutant
             formation of ammonia and ammonia-hydrogen combustion}},
    journal =  {Chem. Eng. J.},
    year =     2024,
    volume =   489,
    pages =    151492,
    doi =      {10.1016/j.cej.2024.151492},
}

@Article{Yang_FireSafJ_2024_v146_p104157,
    author =   {Zhihui Yang and Yinan Qiu and Wei Chen},
    title =    {{Inhibition mechanism of CHF3 on hydrogen{\textendash}oxygen
             combustion: Insights from reactive force field molecular dynamics
             simulations}},
    journal =  {Fire Saf. J.},
    year =     2024,
    volume =   146,
    pages =    104157,
    doi =      {10.1016/j.firesaf.2024.104157},
}

@Article{Yang_Energy_2024_v295_p131013,
    author =   {Yu Yang and Reo Kai and Hiroaki Watanabe},
    title =    {{Reaction mechanism and light gas conversion in pyrolysis and oxidation
             of dimethyl ether (DME): A ReaxFF molecular dynamics study}},
    journal =  {Energy},
    year =     2024,
    volume =   295,
    pages =    131013,
    doi =      {10.1016/j.energy.2024.131013},
}

@Article{Cao_JPhysDApplPhys_2024_v57_p195204,
    author =   {Weidong Cao and Xingwen Li and Yanfeng Zhang and Qian Wang and Renjie
             Yu and Zhenyi Chen and Tao Zhuang},
    title =    {{Atomic-scale insight into arc plasma radiation-induced gassing
             materials ablation: photothermal decomposition behavior}},
    journal =  {J. Phys. D: Appl. Phys.},
    year =     2024,
    volume =   57,
    number =   19,
    pages =    195204,
    doi =      {10.1088/1361-6463/ad2562},
    abstract = {{\ensuremath{<}}jats:title<sub>Abstract{\ensuremath{<}}/jat
             s:title<sub>
             {\ensuremath{<}}jats:p<sub>In this study, we present a
             novel computational atomistic study of the photothermal decomposition
             behavior of arc plasma on radiation-induced gassing materials
             ablation, studying a polyamide 66 (PA66) system using reactive force
             field (ReaxFF) molecular dynamics (MD). We determine the infrared (IR)
             vibrational frequency of the PA66 permanent molecular dipole using MD
             and then computationally impose an electric field at the same
             frequency to simulate photothermal decomposition by IR, verifying our
             observations with gas chromatography-mass spectrometry (GCMS) of
             experimental decomposition. MD indicates that photothermal
             decomposition reaction is dominated by either cleavage at low
             temperature or cyclization at high temperature. At low temperature,
             initial chain scission takes place at the two amide C{\textendash}N,
             and the remaining chains break down into a variety of molecular
             fragments and free radicals. Further increasing the temperature
             stabilizes a variety of branched chain structures via cyclization,
             debranching and polymerization, with further cleavage forming
             hydrocarbons and volatile small molecule gases. Overall, H{\ensuremath
             {<}}jats:sub<sub>2{\ensuremath{<}}/jats:sub<sub>
             , CO, H{\ensuremath{<}}jats:sub<sub>2{\ensuremath{<}}/jats:
             sub<sub>O, alkanes and alkenes are the main gaseous
             products and cyclic structures (especially nitrogen-containing three-
             membered ring) are the main solid products during the photothermal
             decomposition of PA66, and their formation results from a variety of
             complex chemical reactions. The results of MD cover the experimental
             observations of GCMS, demonstrating that this computational
             methodology helps us understand the molecular breakdown mechanisms of
             arc plasma radiation-induced gassing materials. We also discuss the
             physical mechanism by which the main gas can accelerate arc quenching,
             and the importance and necessity of using electric fields to simulate
             IR photothermal decomposition of arc-induced
             ablation.{\ensuremath{<}}/jats:p<sub>},
}

@Article{Xiao_BioresourTechnol_2024_v399_p130590,
    author =   {Yuqin Xiao and Yuxin Yan and Hainam Do and Richard Rankin and Haitao
             Zhao and Ping Qian and Keke Song and Tao Wu and Cheng Heng Pang},
    title =    {{Understanding cellulose pyrolysis via ab initio deep learning
             potential field}},
    journal =  {Bioresour. Technol.},
    year =     2024,
    volume =   399,
    pages =    130590,
    doi =      {10.1016/j.biortech.2024.130590},
    abstract = {Comprehensive and dynamic studies of cellulose pyrolysis reaction
             mechanisms are crucial in designing experiments and processes with
             enhanced safety, efficiency, and sustainability. The details of the
             pyrolysis mechanism are not readily available from experiments but can
             be better described via molecular dynamics (MD) simulations. However,
             the large size of cellulose molecules challenges accurate ab initio MD
             simulations, while existing reactive force field parameters lack
             precision. In this work, precise ab initio deep learning potentials
             field (DPLF) are developed and applied in MD simulations to facilitate
             the study of cellulose pyrolysis mechanisms. The formation mechanism
             and production rate of both valuable and greenhouse products from
             cellulose at temperatures larger than 1073{~}K are comprehensively
             described. This study underscores the critical role of advanced
             simulation techniques, particularly DLPF, in achieving efficient and
             accurate understanding of cellulose pyrolysis mechanisms, thus
             promoting wider industrial applications.},
}

@Article{Guo_AcsCatal_2024_v14_p5720,
    author =   {Hui Guo and Hong Zhu and Gao-Yong Liu and Zhao-Xu Chen},
    title =    {{General Reaction Network Exploration Scheme Based on Graph Theory
             Representation and Depth First Search Applied to CO
             <sub>2</sub> Hydrogenation on
             Pd<sub>2</sub>Cu Catalyst}},
    journal =  {Acs Catal.},
    year =     2024,
    volume =   14,
    number =   8,
    pages =    {5720--5734},
    doi =      {10.1021/acscatal.4c00067},
}

@Article{She_IntJHydrogEnergy_2024_v63_p1197,
    author =   {Chongchong She and Manman Wang and Jiaming Gao and Zhi Wang and
             Shaohua Jin and Minglei Chen and Liang Song and Pengwan Chen and Kun
             Chen},
    title =    {{Study on combustion mechanism of methanol/nitromethane based on
             reactive molecular dynamics simulation}},
    journal =  {Int. J. Hydrog. Energy},
    year =     2024,
    volume =   63,
    pages =    {1197--1211},
    doi =      {10.1016/j.ijhydene.2024.03.185},
}

@Article{Liu_ChemEngSci_2024_v287_p119709,
    author =   {Chunjing Liu and Dikun Hong and Wenchang Zhao and Fei Zheng and Weiran
             Lyu and Jianyi Lu},
    title =    {{Transformation simulation of N-containing functional groups in coal
             pyrolysis and combustion processes by using ReaxFF}},
    journal =  {Chem. Eng. Sci.},
    year =     2024,
    volume =   287,
    pages =    119709,
    doi =      {10.1016/j.ces.2024.119709},
}

@Article{Ruan_TribolInt_2024_v192_p109291,
    author =   {Xiaopeng Ruan and Xiaomei Wang and Rui Zhou and Yang Zhao and Luyao
             Bao and Feng Zhou and Zhibin Lu},
    title =    {{Dynamic chemisorption and tribochemistry of
             {\ensuremath{\alpha}}-lipoic-acid-ester on ferrous surfaces}},
    journal =  {Tribol. Int.},
    year =     2024,
    volume =   192,
    pages =    109291,
    doi =      {10.1016/j.triboint.2024.109291},
}

@Article{Wang_Fuel_2024_v361_p130522,
    author =   {Huijuan Wang and Wei Xia and Huimin Yu and Hua Chen and Yongli Pan and
             Yingxin Sun and Shengtao Li and Sheng Han},
    title =    {{A theoretical investigation on the transformer oil pyrolysis mechanism
             and the effect of the small molecule acid in oils}},
    journal =  {Fuel},
    year =     2024,
    volume =   361,
    pages =    130522,
    doi =      {10.1016/j.fuel.2023.130522},
}

@Article{Xiao_PhysChemChemPhys_2024_v26_p11867,
    author =   {Hang Xiao and Bin Yang},
    title =    {{A neural network potential energy surface assisted molecular dynamics
             study on the pyrolysis behavior of two spiro-hydrocarbons}},
    journal =  {Phys. Chem. Chem. Phys.},
    year =     2024,
    volume =   26,
    number =   15,
    pages =    {11867--11879},
    doi =      {10.1039/d3cp05425j},
    abstract = {Spiro-hydrocarbons are potentially a type of novel alternative jet
             fuel due to their high density and net heat of combustion. In this
             work, the pyrolysis study of two spiro-hydrocarbons
             (spiro[cyclopropane-1,6'-tricyclo[3.2.1.02,4]octane] (C10H14) as Fuel
             1 and spiro[bicyclo[2.2.1]heptane-2,1'-cyclopropane] (C9H14) as Fuel
             2) is performed via molecular dynamics (MD) simulations, with a neural
             network potential energy surface (NNPES), deep potential (DP) model,
             adopted. The data set for the DP model of each fuel is constructed
             after 31 and 27 iterations, respectively. The high precision of the DP
             model is demonstrated, and the temperature transferability of each
             model is observed. The overall pyrolysis performance is evaluated with
             the fuel decomposition rate, showing that both fuels have comparable
             gas-reactivity to commercial aviation fuels, such as JP-10. The
             reaction networks of initial pyrolysis for Fuels 1 and 2 are
             constructed, and the contribution of each pathway is discussed. Fuel 1
             tends to form an unsaturated six-membered ring structure, while Fuel 2
             generates unsaturated open-chain hydrocarbons. Further analyses of the
             MD results provide time-evolution information on each component in the
             pyrolysis species pool. Compared to Fuel 1, the initial pyrolysis of
             Fuel 2 leads to more hydrogen, alkenes, and alkanes, as well as fewer
             monocyclic aromatic hydrocarbons (MAHs), demonstrating a reduced
             tendency for afterward coking. This work might contribute to the
             development of the mechanism of the two spiro-hydrocarbons and guide
             the research of other similar structural fuels.},
}

@Article{Pang_PhysChemChemPhys_2024_v26_p11545,
    author =   {Kehui Pang and Mingjie Wen and Xiaoya Chang and Yabei Xu and Qingzhao
             Chu and Dongping Chen},
    title =    {{The thermal decomposition mechanism of RDX/AP composites: ab initio
             neural network MD simulations}},
    journal =  {Phys. Chem. Chem. Phys.},
    year =     2024,
    volume =   26,
    number =   15,
    pages =    {11545--11557},
    doi =      {10.1039/d3cp05709g},
    abstract = {A neural network potential (NNP) is developed to investigate the
             decomposition mechanism of RDX, AP, and their composites. Utilizing an
             ab initio dataset, the NNP is evaluated in terms of atomic energy and
             forces, demonstrating strong agreement with ab initio calculations.
             Numerical stability tests across a range of timesteps reveal excellent
             stability compared to the state-of-the-art ReaxFF models. Then the
             thermal decomposition of pure RDX, AP, and RDX/AP composites is
             performed using NNP to explore the coupling effect between RDX and AP.
             The results highlight a dual interaction between RDX and AP, i.e., AP
             accelerates RDX decomposition, particularly at low temperatures, and
             RDX promotes AP decomposition. Analyzing RDX trajectories at the
             RDX/AP interface unveils a three-part decomposition mechanism
             involving N-N bond cleavage, H transfer with AP to form Cl-containing
             acid, and chain-breaking reactions generating small molecules such as
             N2, CO, and CO2. The presence of AP enhances H transfer reactions,
             contributing to its role in promoting RDX decomposition. This work
             studies the reaction kinetics of RDX/AP composites from the atomic
             point of view, and can be widely used in the establishment of reaction
             kinetics models of composite systems with energetic materials.},
}

@Article{Liu_JPhysChemA_2024_v128_p1656,
    author =   {Ziyi Liu and An-Hui Lu and Dongqi Wang},
    title =    {{Deep Potential Molecular Dynamics Study of Propane Oxidative
             Dehydrogenation}},
    journal =  {J. Phys. Chem., A},
    year =     2024,
    volume =   128,
    number =   9,
    pages =    {1656--1664},
    doi =      {10.1021/acs.jpca.3c07859},
    abstract = {Oxidative dehydrogenation (ODH) of light alkanes is a key process in
             the oxidative conversion of alkanes to alkenes, oxygenated
             hydrocarbons, and COx (x = 1,2). Understanding the underlying
             mechanisms extensively is crucial to keep the ODH under control for
             target products, e.g., alkenes rather than COx, with minimal energy
             consumption, e.g., during the alkene production or maximal energy
             release, e.g., during combustion. In this work, deep potential (DP), a
             neural network atomic potential developed in recent years, was
             employed to conduct large-scale accurate reactive dynamic simulations.
             The model was trained on a sufficient data set obtained at the density
             functional theory level. The intricate reaction network was elucidated
             and organized in the form of a hierarchical network to demonstrate the
             key features of the ODH mechanisms, including the activation of
             propane and oxygen, the influence of propyl reaction pathways on the
             propene selectivity, and the role of rapid H2O2 decomposition for
             sustainable and efficient ODH reactions. The results indicate the more
             complex reaction mechanism of propane ODH than that of ethane ODH and
             are expected to provide insights in the ODH catalyst optimization. In
             addition, this work represents the first application of deep potential
             in the ODH mechanistic study and demonstrates the ample advantages of
             DP in the study of mechanism and dynamics of complex systems.},
}

@Article{Wang_IndEngChemRes_2024_v63_p3554,
    author =   {Ruikun Wang and Hongbao Zhang and Dikun Hong and Shiteng Tan and
             Zhenghui Zhao and Lichao Ge},
    title =    {{Interphase Migration of Nitrogen and the Evolution Mechanism of
             Nitrogen-Containing Functional Groups in Char during Sludge Pyrolysis}},
    journal =  {Ind. Eng. Chem. Res.},
    year =     2024,
    volume =   63,
    number =   8,
    pages =    {3554--3562},
    doi =      {10.1021/acs.iecr.3c04052},
}

@Article{Jiang_JMolLiq_2024_v396_p124040,
    author =   {Jun Jiang and Si-Yu Xu and Feng-Qi Zhao and Xue-Hai Ju},
    title =    {{New insights into the degradation mechanism of TNT in supercritical
             water: Combining density functional theory with the reactive force
             field}},
    journal =  {J. Mol. Liq.},
    year =     2024,
    volume =   396,
    pages =    124040,
    doi =      {10.1016/j.molliq.2024.124040},
}

@Article{Li_ChemEngSci_2024_v284_p119528,
    author =   {Jifan Li and Xiaohui Zhang and Aimin Zhang and Hua Wang},
    title =    {{ReaxFF based molecular dynamics simulation of ethyl butyrate in
             pyrolysis and combustion}},
    journal =  {Chem. Eng. Sci.},
    year =     2024,
    volume =   284,
    pages =    119528,
    doi =      {10.1016/j.ces.2023.119528},
}

@Article{Xiao_ProcCombustInst_2024_v40_p105525,
    author =   {Hang Xiao and Zhaohan Chu and Changyang Wang and Jinghui Lu and Long
             Zhao and Bin Yang},
    title =    {{Revealing the initial pyrolysis behavior of decalin in an experimental
             study coupled with neural network-assisted molecular dynamics}},
    journal =  {Proc. Combust. Inst.},
    year =     2024,
    volume =   40,
    number =   {1-4},
    pages =    105525,
    doi =      {10.1016/j.proci.2024.105525},
}

@Article{Wen_PhysChemChemPhys_2024_v26_p9984,
    author =   {Mingjie Wen and Xiaoya Chang and Yabei Xu and Dongping Chen and
             Qingzhao Chu},
    title =    {{Determining the mechanical and decomposition properties of high
             energetic materials ({\ensuremath{\alpha}}-RDX,
             {\ensuremath{\beta}}-HMX, and {\ensuremath{\varepsilon}}-CL-20) using
             a neural network potential}},
    journal =  {Phys. Chem. Chem. Phys.},
    year =     2024,
    volume =   26,
    number =   13,
    pages =    {9984--9997},
    doi =      {10.1039/d4cp00017j},
    abstract = {Molecular simulations of high energetic materials (HEMs) are limited
             by efficiency and accuracy. Recently, neural network potential (NNP)
             models have achieved molecular simulations of millions of atoms while
             maintaining the accuracy of density functional theory (DFT) levels.
             Herein, an NNP model covering typical HEMs containing C, H, N, and O
             elements is developed. The mechanical and decomposition properties of
             1,3,5-trinitroperhydro-1,3,5-triazine (RDX),
             hexahydro-1,3,5-trinitro-1,3,5-triazine (HMX), and
             2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20) are determined by
             employing the molecular dynamics (MD) simulations based on the NNP
             model. The calculated results show that the mechanical properties of
             {\ensuremath{\alpha}}-RDX, {\ensuremath{\beta}}-HMX, and
             {\ensuremath{\varepsilon}}-CL-20 agree with previous experiments and
             theoretical results, including cell parameters, equations of state,
             and elastic constants. In the thermal decomposition simulations, it is
             also found that the initial decomposition reactions of the three
             crystals are N-NO2 homolysis, corresponding radical intermediates
             formation, and NO2-induced reactions. This decomposition trajectory is
             mainly divided into two stages separating from the peak of NO2:
             pyrolysis and oxidation. Overall, the NNP model for C/H/N/O elements
             in this work is an alternative reactive force field for RDX, HMX, and
             CL-20 HEMs, and it opens up new potential for future kinetic study of
             nitramine explosives.},
}

@Article{Sun_MolBaselSwitz_2023_v29_p56,
    author =   {Zijian Sun and Jincheng Ji and Weihua Zhu},
    title =    {{Effects of Nanoparticle Size on the Thermal Decomposition Mechanisms
             of 3,5-Diamino-6-hydroxy-2-oxide-4-nitropyrimidone through ReaxFF
             Large-Scale Molecular Dynamics Simulations}},
    journal =  {Mol. (Basel Switz.)},
    year =     2023,
    volume =   29,
    number =   1,
    pages =    56,
    doi =      {10.3390/molecules29010056},
    abstract = {ReaxFF-lg molecular dynamics method was employed to simulate the
             decomposition processes of IHEM-1 nanoparticles at high temperatures.
             The findings indicate that the initial decomposition paths of the
             nanoparticles with different sizes at varying temperatures are
             similar, where the bimolecular polymerization reaction occurred first.
             Particle size has little effect on the initial decomposition pathway,
             whereas there are differences in the numbers of the species during the
             decomposition and their evolution trends. The formation of the
             hydroxyl radicals is the dominant decomposition mechanism with the
             highest reaction frequency. The degradation rate of the IHEM-1
             molecules gradually increases with the increasing temperature. The
             IHEM-1 nanoparticles with smaller sizes exhibit greater decomposition
             rate constants. The activation energies for the decomposition are
             lower than the reported experimental values of bulk explosives, which
             suggests a higher sensitivity.},
}

@Article{Sun_ComputTheorChem_2024_v1231_p114446,
    author =   {Haoshan Sun and Xiaohui Zhang and Hongxi Liu and Jifan Li and Hua Wang},
    title =    {{Pyrolysis and combustion reaction mechanisms of methyl palmitate with
             ReaxFF-MD method}},
    journal =  {Comput. Theor. Chem.},
    year =     2024,
    volume =   1231,
    pages =    114446,
    doi =      {10.1016/j.comptc.2023.114446},
}

@Article{Li_IntJGreenEnergy_2024_v21_p2117,
    author =   {Yunlong Li and Yinan Qiu and Zheng Wang and Wei Chen},
    title =    {{Molecular dynamics simulation of the inhibition effects of inert gases
             (Ar/He/N<sub>2</sub>) on hydrogen oxidation}},
    journal =  {Int. J. Green Energy},
    year =     2024,
    volume =   21,
    number =   9,
    pages =    {2117--2127},
    doi =      {10.1080/15435075.2023.2297766},
    abstract = {ABSTRACT In this paper, the inhibition effects of Ar/He/N2 on the
             H2-O2 system near the extended second explosion limit were
             investigated by ReaxFF simulations. It was found that all three inert
             gases can inhibit the reactions, delaying the initiation reaction, and
             prolonging ignition delay since the generation and consumption of free
             radicals such as HO2 and OH were suppressed. Further, the inhibitory
             effect has the correlation of Ar <sub> He <sub>
             N2. The inhibitory effect of Ar is more pronounced compared to He due
             to the bigger effective radius and physical mass. Moreover, the
             addition of N2 introduced extra initiation reaction (H2{\,}+{\,}N2
             {\textrightarrow} NNH{\,}+{\,}H) and generated additional intermediate
             products such as NNH and N2OH, which result in the weakest inhibitory
             effect. Compared to diatomic inhibitors (e.g., N2), the monatomic
             inhibitors such as Ar and He exhibit stronger inhibitory effects on
             the hydroxide reaction under high pressure.},
}

@Article{She_Fuel_2025_v379_p132982,
    author =   {Chongchong She and Tiancheng Zhang and Jiaming Gao and Zhi Wang and
             Shaohua Jin and Lijie Li and Junfeng Wang and Liang Song and Pengwan
             Chen and Kun Chen},
    title =    {{Insights into the combustion mechanisms of turpentine oil based on
             ReaxFF molecular dynamics simulations}},
    journal =  {Fuel},
    year =     2025,
    volume =   379,
    pages =    132982,
    doi =      {10.1016/j.fuel.2024.132982},
}