TY - JOUR
T1 - Numerical simulations of yield-based sooting tendencies of aromatic fuels using ReaxFF molecular dynamics
AU - Kwon, Hyunguk
AU - Shabnam, Sharmin
AU - van Duin, Adri C.T.
AU - Xuan, Yuan
N1 - Funding Information:
This research was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Bioenergy Technologies Office (BETO) and Vehicle Technologies Office (VTO) Program Award Number DE-EE0007983. ACTvD acknowledges funding form U.S. Department of Energy grant #DE-EE008195. SS acknowledges funding from AFOSR grant FA9550-17-1-0173.
Funding Information:
This research was funded by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Bioenergy Technologies Office (BETO) and Vehicle Technologies Office (VTO) Program Award Number DE-EE0007983. ACTvD acknowledges funding form U.S. Department of Energy grant #DE-EE008195. SS acknowledges funding from AFOSR grant FA9550-17-1-0173.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/2/15
Y1 - 2020/2/15
N2 - We present the first ReaxFF Molecular Dynamics (MD) simulations to quantitatively predict the sooting tendencies of various fuels. The specific sooting tendency metric used in this work is the Yield Sooting Index (YSI), which quantifies the effects of fuel molecular structure on soot yield. YSI has been experimentally measured and numerically simulated using computational fluid dynamics for a large range of fuels, but there is no existing reactive MD framework for YSI simulations. To adopt the experimental YSI concept, a multi-stage simulation procedure is designed using ReaxFF. As a proof-of-concept, toluene and phenol are selected as test fuels, since both have relatively well-understood reaction pathways. The ReaxFF YSI simulations are shown to capture key reaction events for both fuels selected that are consistent with existing chemical kinetic understanding. Toluene is shown to mostly retain its original aromatic ring structure and directly grow to larger aromatic compounds with multiple rings. On the other hand, the aromatic growth process from phenol is accompanied by carbon-loss reactions with CO release. In addition, a quantitative YSI formulation is also derived in ReaxFF and the ReaxFF-predicted YSI values are compared with measurement data and reasonably good agreement is achieved. The results reported in this work demonstrates that the ReaxFF-based framework can potentially be used to quantitatively predict the relative sooting tendencies, especially for fuels with unknown or poorly-known chemistry, to understand their sooting properties and in search for soot relevant reaction pathways from these fuels.
AB - We present the first ReaxFF Molecular Dynamics (MD) simulations to quantitatively predict the sooting tendencies of various fuels. The specific sooting tendency metric used in this work is the Yield Sooting Index (YSI), which quantifies the effects of fuel molecular structure on soot yield. YSI has been experimentally measured and numerically simulated using computational fluid dynamics for a large range of fuels, but there is no existing reactive MD framework for YSI simulations. To adopt the experimental YSI concept, a multi-stage simulation procedure is designed using ReaxFF. As a proof-of-concept, toluene and phenol are selected as test fuels, since both have relatively well-understood reaction pathways. The ReaxFF YSI simulations are shown to capture key reaction events for both fuels selected that are consistent with existing chemical kinetic understanding. Toluene is shown to mostly retain its original aromatic ring structure and directly grow to larger aromatic compounds with multiple rings. On the other hand, the aromatic growth process from phenol is accompanied by carbon-loss reactions with CO release. In addition, a quantitative YSI formulation is also derived in ReaxFF and the ReaxFF-predicted YSI values are compared with measurement data and reasonably good agreement is achieved. The results reported in this work demonstrates that the ReaxFF-based framework can potentially be used to quantitatively predict the relative sooting tendencies, especially for fuels with unknown or poorly-known chemistry, to understand their sooting properties and in search for soot relevant reaction pathways from these fuels.
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U2 - 10.1016/j.fuel.2019.116545
DO - 10.1016/j.fuel.2019.116545
M3 - Article
AN - SCOPUS:85075428619
VL - 262
JO - Fuel
JF - Fuel
SN - 0016-2361
M1 - 116545
ER -