Dyes and Pigments, volume 204, pages 110470
Meso-carbazole substituted porphyrin complexes: Synthesis and spectral properties according to experiment, DFT calculations and the prediction by machine learning methods
Publication type: Journal Article
Publication date: 2022-08-01
Journal:
Dyes and Pigments
Quartile SCImago
Q1
Quartile WOS
Q1
Impact factor: 4.5
ISSN: 01437208, 18733743
General Chemical Engineering
Process Chemistry and Technology
Abstract
In this work, two porphyrins bearing [3,6-di-tert-butyl-carbazol-9-yl-benzoyloxy)]- (1) and [3,6-bis(3′,6′-di( tert -butyl)-9′H-carbazol)-9H-carbazolbenzoyloxy]phenyl (2) groups and their zinc (1Zn, 2Zn)/cobalt (1Co, 2Co) complexes were synthesized and studied by experimental and theoretical methods. The spectral parameters (UV–vis absorption/femtosecond transient absorption/fluorescence, IR, 1H NMR, mass spectra) of the compounds were observed. Their structure was also examined by the DFT method. The comparative study of the UV–vis spectra by the DFT/TDDFT calculation, and by the prediction of the Soret band maximum using machine learning methods , namely the consensus models based on the data of over 10000 porphyrin free bases and their complexes with metals was performed. The absorption maximum wavelength (Soret band) of porphyrins predicted with machine learning methods showed better agreement with the experimental data compared to the DFT/TDDFT calculation. The final consensus model is freely available at https://ochem.eu/article/145340 and can be used by the other researchers to obtain new functionalized porphyrins with desired optical properties. • New meso-carbazole substituted porphyrin complexes were synthesized. • They were characterized by UV–visible, infrared, fluorescence, transient absorption spectroscopy, and mass spectrometry. • Prediction of the Soret band maximum by DFT calculations and machine learning methods.
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- We do not take into account publications that without a DOI.
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- Statistics recalculated weekly.
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Bichan N. G. et al. Meso-carbazole substituted porphyrin complexes: Synthesis and spectral properties according to experiment, DFT calculations and the prediction by machine learning methods // Dyes and Pigments. 2022. Vol. 204. p. 110470.
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Bichan N. G., Ovchenkova E. N., Ksenofontov A. A., Mozgova V. A., Gruzdev M. S., Chervonova U. V., Shelaev I. V., Lomova T. N. Meso-carbazole substituted porphyrin complexes: Synthesis and spectral properties according to experiment, DFT calculations and the prediction by machine learning methods // Dyes and Pigments. 2022. Vol. 204. p. 110470.
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TY - JOUR
DO - 10.1016/j.dyepig.2022.110470
UR - https://doi.org/10.1016%2Fj.dyepig.2022.110470
TI - Meso-carbazole substituted porphyrin complexes: Synthesis and spectral properties according to experiment, DFT calculations and the prediction by machine learning methods
T2 - Dyes and Pigments
AU - Bichan, Nataliya G
AU - Ovchenkova, Ekaterina N
AU - Ksenofontov, Alexander A
AU - Mozgova, V A
AU - Gruzdev, Matvey S
AU - Chervonova, U V
AU - Shelaev, Ivan V
AU - Lomova, Tatyana N.
PY - 2022
DA - 2022/08/01 00:00:00
PB - Elsevier
SP - 110470
VL - 204
SN - 0143-7208
SN - 1873-3743
ER -
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@article{2022_Bichan,
author = {Nataliya G Bichan and Ekaterina N Ovchenkova and Alexander A Ksenofontov and V A Mozgova and Matvey S Gruzdev and U V Chervonova and Ivan V Shelaev and Tatyana N. Lomova},
title = {Meso-carbazole substituted porphyrin complexes: Synthesis and spectral properties according to experiment, DFT calculations and the prediction by machine learning methods},
journal = {Dyes and Pigments},
year = {2022},
volume = {204},
publisher = {Elsevier},
month = {aug},
url = {https://doi.org/10.1016%2Fj.dyepig.2022.110470},
pages = {110470},
doi = {10.1016/j.dyepig.2022.110470}
}