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Assessment of the performance of six indices in predicating the aromaticity of planar porphyrinoids.

Authors :
Ding, Wenjing
Zhang, Zhan
Chen, Xi
Zhan, Chang-guo
Source :
Journal of Molecular Modeling. Mar2023, Vol. 29 Issue 3, p1-10. 10p.
Publication Year :
2023

Abstract

Context and results: Aromaticity is a fundamental chemical concept that has been widely used in explaining the reactivity, stability, structure, and magnetic properties of many molecules such as conjugated macrocycles, metal heterocyclic compounds, and certain metal clusters. Porphyrinoids (including porphyrin) are of particular interest in terms of diverse aromaticity. Various indices therefore have been used to predict the aromaticity of porphyrin-like macrocycles. However, the reliability of these indices for porphyinoids is always questionable. In order to assess the performance of the indices, we have selected six representative indices to predict the aromaticity of 35 porphyrinoids. The calculated values were then compared with the corresponding results obtained from experiments. Our studies suggest that the theoretical prediction by nucleus independent chemical shifts (NICS), topology of the induced magnetic field (TIMF), anisotropy of the induced current density (AICD), and gauge including magnetically induced current method (GIMIC) are essentially consistent with experimental evidence in all 35 cases and thus are preferred indices. Computational and theoretical techniques: Based on density functional theory, the performance of the NICS, TIMF, AICD, GIMIC, harmonic oscillator model of aromaticity (HOMA), and multicenter bond order (MCBO) indices were evaluated theoretically. Molecular geometries were optimized at the M06-2X/6-311G** level. NMR calculations using GIAO or CGST method were performed at the M06-2X/6-311G** level. The above calculations were carried out using Gaussian16 suite. The TIMF, GIMIC, HOMA, and MCBO indices were obtained using the Multiwfn program. The AICD outputs were visualized using the POV-Ray software. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16102940
Volume :
29
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Molecular Modeling
Publication Type :
Academic Journal
Accession number :
162586462
Full Text :
https://doi.org/10.1007/s00894-023-05485-9