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Title: Predicting Sooting Tendencies from Chemical Structure with Experimental and Theoretical Insight

Abstract

Particulate matter (PM) emissions from internal combustion engines negatively impact public health and global climate. These problems are exacerbated by newer gasoline direct injection engines, which are more fuel-efficient, but also produce more soot than traditional spark ignited engines. Reducing soot formation is therefore of paramount importance in the development of new fuels. A fuel's sooting tendency is a quantitative parameter that describes the sooting behavior of a pure compound or fuel mixture. The yield sooting index (YSI), developed by McEnally and Pfefferle, accurately measures sooting tendencies using small sample quantities. Using an experimental sooting tendency database, we have developed a predictive model for sooting behavior from a quantitative structure-activity relationship (QSAR). It was developed so that input molecules are first decomposed into individual carbon-type fragments for which the sooting tendency contribution can be assigned based on a Bayesian linear regression against the experimental database. The model's predictive accuracy is comparable to its training performance using leave-one-out cross-validation. We have used this model to provide quantitative insights into the effects of chemical structure on soot formation, but excitingly, we have also been able to readily identify the presence of more complicated kinetic sooting mechanisms for structures which are extreme outliers.more » Oxygenated aromatics can be produced readily from biomass as renewable sources and oxygenated aromatics with very similar structures tend to have a much lower sooting tendency, for example methoxybenzene (anisole, 107), 2-methylphenol (m-cresol, 103), 2-ethylphenol (120), 3-ethylphenol (138) and 1-phenylethanol (142). Thus, the presence of just one oxygen atom in an aromatic compound can drastically alter the reaction pathways leading to soot precursors. We have applied density functional theory (DFT) calculations and flow reactor experiments to examine how oxygenation alters reaction pathways in a combustion environment. This study has allowed us to gain understanding on how the location of an oxygenated functional group influences soot formation. Our work provides a blueprint for the design of oxygenated fuels from biomass, which minimize the production of soot in low oxygen environments.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [1];  [2];  [3];  [3]; ORCiD logo [1];  [4]; ORCiD logo [1]; ORCiD logo [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Pennsylvania State University, University Park, Pennsylvania
  3. Yale University, New Haven, Connecticut
  4. Colorado State University, Fort Collins, Colorado
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)
OSTI Identifier:
1567041
Report Number(s):
NREL/PR-2700-74915
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 23rd Annual Green Chemistry & Engineering Conference, 11-13 June 2019, Reston, Virginia
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; biomass; oxygenated aromatics; biofuels; spark ignited engines; soot; direct injection engines; emissions

Citation Formats

St. John, Peter C, Fioroni, Gina M, Huq, Nabila A, Huo, Xiangchen, Etz, Brian D, Xuan, Yuan, McEnally, Charles S., Pfefferle, Lisa, Vardon, Derek R, Paton, Robert S., McCormick, Robert L, and Kim, Seon Ah. Predicting Sooting Tendencies from Chemical Structure with Experimental and Theoretical Insight. United States: N. p., 2019. Web.
St. John, Peter C, Fioroni, Gina M, Huq, Nabila A, Huo, Xiangchen, Etz, Brian D, Xuan, Yuan, McEnally, Charles S., Pfefferle, Lisa, Vardon, Derek R, Paton, Robert S., McCormick, Robert L, & Kim, Seon Ah. Predicting Sooting Tendencies from Chemical Structure with Experimental and Theoretical Insight. United States.
St. John, Peter C, Fioroni, Gina M, Huq, Nabila A, Huo, Xiangchen, Etz, Brian D, Xuan, Yuan, McEnally, Charles S., Pfefferle, Lisa, Vardon, Derek R, Paton, Robert S., McCormick, Robert L, and Kim, Seon Ah. Mon . "Predicting Sooting Tendencies from Chemical Structure with Experimental and Theoretical Insight". United States. https://www.osti.gov/servlets/purl/1567041.
@article{osti_1567041,
title = {Predicting Sooting Tendencies from Chemical Structure with Experimental and Theoretical Insight},
author = {St. John, Peter C and Fioroni, Gina M and Huq, Nabila A and Huo, Xiangchen and Etz, Brian D and Xuan, Yuan and McEnally, Charles S. and Pfefferle, Lisa and Vardon, Derek R and Paton, Robert S. and McCormick, Robert L and Kim, Seon Ah},
abstractNote = {Particulate matter (PM) emissions from internal combustion engines negatively impact public health and global climate. These problems are exacerbated by newer gasoline direct injection engines, which are more fuel-efficient, but also produce more soot than traditional spark ignited engines. Reducing soot formation is therefore of paramount importance in the development of new fuels. A fuel's sooting tendency is a quantitative parameter that describes the sooting behavior of a pure compound or fuel mixture. The yield sooting index (YSI), developed by McEnally and Pfefferle, accurately measures sooting tendencies using small sample quantities. Using an experimental sooting tendency database, we have developed a predictive model for sooting behavior from a quantitative structure-activity relationship (QSAR). It was developed so that input molecules are first decomposed into individual carbon-type fragments for which the sooting tendency contribution can be assigned based on a Bayesian linear regression against the experimental database. The model's predictive accuracy is comparable to its training performance using leave-one-out cross-validation. We have used this model to provide quantitative insights into the effects of chemical structure on soot formation, but excitingly, we have also been able to readily identify the presence of more complicated kinetic sooting mechanisms for structures which are extreme outliers. Oxygenated aromatics can be produced readily from biomass as renewable sources and oxygenated aromatics with very similar structures tend to have a much lower sooting tendency, for example methoxybenzene (anisole, 107), 2-methylphenol (m-cresol, 103), 2-ethylphenol (120), 3-ethylphenol (138) and 1-phenylethanol (142). Thus, the presence of just one oxygen atom in an aromatic compound can drastically alter the reaction pathways leading to soot precursors. We have applied density functional theory (DFT) calculations and flow reactor experiments to examine how oxygenation alters reaction pathways in a combustion environment. This study has allowed us to gain understanding on how the location of an oxygenated functional group influences soot formation. Our work provides a blueprint for the design of oxygenated fuels from biomass, which minimize the production of soot in low oxygen environments.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {9}
}

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