scholarly journals Multisubstituted phthalonitriles for phthalocyanine synthesis

2004 ◽  
Vol 08 (11) ◽  
pp. 1293-1299 ◽  
Author(s):  
Jianghong Wang ◽  
Ashot Kh. Khanamiryan ◽  
Clifford C. Leznoff

3,4,5,6-tetrafluorophthalonitrile and 3,4,5,6-tetrachlorophthalonitrile were used as substrates with various phenoxides to prepare 3,4,6-trihalo-5-p-substitutedphenoxyphthalonitriles, containing four substituents other than hydrogen, by nucleophilic aromatic substitution reactions. Subsequent reactions with unsymmetrical catechols gave tetrasubstitutedphthalonitriles, having four different substituents. In one instance, attempts to displace the last remaining fluoro group by an octanoxide nucleophile led to substitution of a p-methylphenoxy group, showing that phenoxy substituents are also labile in nucleophilic aromatic substitution reactions on phthalonitriles. Alternatively, 4,5-dimethoxyphthalonitrile or 4,5-dineopentoxyphthalonitrile underwent electrophilic aromatic substitution reactions with dibromoisocyanuric acid to give their respective 3,6-dibromophthalonitriles. Coupling of these bromophthalonitriles with tri(n-butyl)phenylylethynyltin and tri(n-butyl)vinyltin in the presence of a nickel catalyst gave 4,5-dimethoxy-3,6-bisphenylethy nylphthalonitrile, 3-bromo-4,5-dimethoxy-6-phenylethynylphthalonitrile, 4,5-dineopentoxy-3,6-bisphenylethynylphthalonitrile, 3-bromo-4,5-dineopentoxy-6-phenylethynylphthalonitrile, 4,5-dimethoxy-3,6-vinylphthalonitrile and 3-bromo-4,5-dimethoxy-6-vinylphthalonitrile. Reductions in the coupling steps sometimes led to 4,5-dimethoxy-3-phenylethynylphthalonitrile and 4,5-dimethoxy-3-vinylphthalonitrile.

1996 ◽  
Vol 74 (3) ◽  
pp. 307-318 ◽  
Author(s):  
Clifford C. Leznoff ◽  
David M. Drew

Nucleophilic aromatic substitution reactions of 3-nitrophthalonitrile yield 3-hydroxyphthalonitrile and 3-neopentoxyphthalonitrile, the latter of which condensed to 1,8,15,22-tetraneopentoxyphthalocyanine as a mixture of isomers. Bisphthalonitriles such as 1,3-bis(2′,3′-dicyanophenoxy)-2,2-dipentylpropane, 1,3-bis(2′,3′-dicyanophenoxy)-2,2-diethylpropane, 1,3-bis(2′,3′-dicyanophenoxy)-2,2-dioctylpropane, and 1,3-bis(2′,3′-dicyanophenoxy)-2-methyl-2-trityloxymethylpropane all gave bis-crown-like 1,11,15,25-tetrasubstituted phthalocyanines as pure compounds when treated with lithium octoxide in 1-octanol at 196 °C. A host of nine other bisphthalonitriles including 1,5-bis(2′,3′-dicyanophenoxy)-3-oxapentane, 1,1-bis(2′,3′-dicyanophenoxymethyl)cyclohexane, 1,2-bis(2′,3′-dicyanophenoxymethyl)benzene, and 2,5-bis(2′,3′-dicyanophenoxymethyl)furan did not dimerize to mononuclear phthalocynaines. The "gem dimethyl" effect was suggested as a reason for the successful macrocyclizations. Key words: nucleophilic aromatic substitution, phthalonitriles, bisphthalonitriles, 1,11,15,25-tetrasubstituted phthalocyanines.


2021 ◽  
Author(s):  
Luis R. Domingo ◽  
Mar Ríos-Gutiérrez ◽  
María José Aurell

The origin of the meta regioselectivity in electrophilic aromatic substitution (EAS) reactions of deactivated benzene derivatives is herein analysed through Molecular Electron Density Theory (MEDT). To this end, the EAS...


2019 ◽  
Vol 15 ◽  
pp. 474-489 ◽  
Author(s):  
Andrejs Šišuļins ◽  
Jonas Bucevičius ◽  
Yu-Ting Tseng ◽  
Irina Novosjolova ◽  
Kaspars Traskovskis ◽  
...  

The synthesis of novel fluorescent N(9)-alkylated 2-amino-6-triazolylpurine and 7-deazapurine derivatives is described. A new C(2)-regioselectivity in the nucleophilic aromatic substitution reactions of 9-alkylated-2,6-diazidopurines and 7-deazapurines with secondary amines has been disclosed. The obtained intermediates, 9-alkylated-2-amino-6-azido-(7-deaza)purines, were transformed into the title compounds by CuAAC reaction. The designed compounds belong to the push–pull systems and possess promising fluorescence properties with quantum yields in the range from 28% to 60% in acetonitrile solution. Due to electron-withdrawing properties of purine and 7-deazapurine heterocycles, which were additionally extended by triazole moieties, the compounds with electron-donating groups showed intramolecular charge transfer character (ICT/TICT) of the excited states which was proved by solvatochromic dynamics and supported by DFT calculations. In the 7-deazapurine series this led to increased fluorescence quantum yield (74%) in THF solution. The compounds exhibit low cytotoxicity and as such are useful for the cell labelling studies in the future.


2021 ◽  
Author(s):  
Nicolai Ree ◽  
Andreas H. Göller ◽  
Jan H. Jensen

We present RegioML, an atom-based machine learning model for predicting the regioselectivities of electrophilic aromatic substitution reactions. The model relies on CM5 atomic charges computed using semiempirical tight binding (GFN1-xTB) combined with the ensemble decision tree variant light gradient boosting machine (LightGBM). The model is trained and tested on 21,201 bromination reactions with 101K reaction centers, which is split into a training, test, and out-of-sample datasets with 58K, 15K, and 27K reaction centers, respectively. The accuracy is 93% for the test set and 90% for the out-of-sample set, while the precision (the percentage of positive predictions that are correct) is 88% and 80%, respectively. The test-set performance is very similar to the graph-based WLN method developed by Struble et al. (React. Chem. Eng. 2020, 5, 896) though the comparison is complicated by the possibility that some of the test and out-of-sample molecules are used to train WLN. RegioML out-performs our physics-based RegioSQM20 method (J. Cheminform. 2021, 13:10) where the precision is only 75%. Even for the out-of-sample dataset, RegioML slightly outperforms RegioSQM20. The good performance of RegioML and WLN is in large part due to the large datasets available for this type of reaction. However, for reactions where there is little experimental data, physics-based approaches like RegioSQM20 can be used to generate synthetic data for model training. We demonstrate this by showing that the performance of RegioSQM20 can be reproduced by a ML-model trained on RegioSQM20-generated data.


1989 ◽  
Vol 30 (3) ◽  
pp. 305-308 ◽  
Author(s):  
Lawrence T. Scott ◽  
Chris A. Sumpter ◽  
Mitsunori Oda ◽  
Ihsan Erden

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