HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation
A large number of PAH molecules is collected from recent literature. The HOMO-LUMO gap value of PAHs was computed at the level of B3LYP/6-311+G (d,p). The gap values lie in the range of 0.64–6.59 eV. It is found that the gap values of all PAH molecules exhibit a size dependency to some extent. Howev...
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2021
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oai:doaj.org-article:9619ee2306554d76a2ab1a8985ed59222021-11-17T09:59:46ZHOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation2297-307910.3389/fmech.2021.744001https://doaj.org/article/9619ee2306554d76a2ab1a8985ed59222021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmech.2021.744001/fullhttps://doaj.org/toc/2297-3079A large number of PAH molecules is collected from recent literature. The HOMO-LUMO gap value of PAHs was computed at the level of B3LYP/6-311+G (d,p). The gap values lie in the range of 0.64–6.59 eV. It is found that the gap values of all PAH molecules exhibit a size dependency to some extent. However, the gap values may show a big variation even at the same size due to the complexity in the molecular structure. All collected PAHs are further classified into seven groups according to features in the structures, including the types of functional groups and the molecular planarity. The impact of functional groups, including –OH, –CHO, –COOH, =O, –O– and –CnHm on the bandgap is discussed in detail. The substitution of ketone group has the greatest reduction on the HOMO-LUMO gap of PAH molecules. Besides functional groups, we found that both local structure and the position of five-member rings make critical impacts on the bandgap via a detailed analysis of featured PAHs with unexpected low and high gap values. Among all these factors, the five-member rings forming nonplanar PAHs impact the gap most. Furthermore, we developed a machine learning model to predict the HOMO-LUMO gaps of PAHs, and the average absolute error is only 0.19 eV compared with the DFT calculations. The excellent performance of the machine learning model provides us an accurate and efficient way to explore the band information of PAHs in soot formation.Yabei XuQingzhao ChuDongping ChenAndrés FuentesFrontiers Media S.A.articlePAHHOMO-LUMO gapfunctional groupfive-member ringmachine learningMechanical engineering and machineryTJ1-1570ENFrontiers in Mechanical Engineering, Vol 7 (2021) |
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PAH HOMO-LUMO gap functional group five-member ring machine learning Mechanical engineering and machinery TJ1-1570 |
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PAH HOMO-LUMO gap functional group five-member ring machine learning Mechanical engineering and machinery TJ1-1570 Yabei Xu Qingzhao Chu Dongping Chen Andrés Fuentes HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
description |
A large number of PAH molecules is collected from recent literature. The HOMO-LUMO gap value of PAHs was computed at the level of B3LYP/6-311+G (d,p). The gap values lie in the range of 0.64–6.59 eV. It is found that the gap values of all PAH molecules exhibit a size dependency to some extent. However, the gap values may show a big variation even at the same size due to the complexity in the molecular structure. All collected PAHs are further classified into seven groups according to features in the structures, including the types of functional groups and the molecular planarity. The impact of functional groups, including –OH, –CHO, –COOH, =O, –O– and –CnHm on the bandgap is discussed in detail. The substitution of ketone group has the greatest reduction on the HOMO-LUMO gap of PAH molecules. Besides functional groups, we found that both local structure and the position of five-member rings make critical impacts on the bandgap via a detailed analysis of featured PAHs with unexpected low and high gap values. Among all these factors, the five-member rings forming nonplanar PAHs impact the gap most. Furthermore, we developed a machine learning model to predict the HOMO-LUMO gaps of PAHs, and the average absolute error is only 0.19 eV compared with the DFT calculations. The excellent performance of the machine learning model provides us an accurate and efficient way to explore the band information of PAHs in soot formation. |
format |
article |
author |
Yabei Xu Qingzhao Chu Dongping Chen Andrés Fuentes |
author_facet |
Yabei Xu Qingzhao Chu Dongping Chen Andrés Fuentes |
author_sort |
Yabei Xu |
title |
HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
title_short |
HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
title_full |
HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
title_fullStr |
HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
title_full_unstemmed |
HOMO–LUMO Gaps and Molecular Structures of Polycyclic Aromatic Hydrocarbons in Soot Formation |
title_sort |
homo–lumo gaps and molecular structures of polycyclic aromatic hydrocarbons in soot formation |
publisher |
Frontiers Media S.A. |
publishDate |
2021 |
url |
https://doaj.org/article/9619ee2306554d76a2ab1a8985ed5922 |
work_keys_str_mv |
AT yabeixu homolumogapsandmolecularstructuresofpolycyclicaromatichydrocarbonsinsootformation AT qingzhaochu homolumogapsandmolecularstructuresofpolycyclicaromatichydrocarbonsinsootformation AT dongpingchen homolumogapsandmolecularstructuresofpolycyclicaromatichydrocarbonsinsootformation AT andresfuentes homolumogapsandmolecularstructuresofpolycyclicaromatichydrocarbonsinsootformation |
_version_ |
1718425626085425152 |