ChemInform Abstract: Efficient Synthesis of N,N-Disubstituted 5-Aminothiophene-2-carboxaldehydes by Nucleophilic Aromatic Substitution in Water.

ChemInform ◽  
2010 ◽  
Vol 29 (28) ◽  
pp. no-no
Author(s):  
D. PRIM ◽  
G. KIRSCH ◽  
J.-F. NICOUD
Keyword(s):  
Nucleophilic Aromatic Substitution ◽  
Aromatic Substitution ◽  
Efficient Synthesis

The Versatility of the Aryne–Imine–Aryne Coupling for the ­Synthesis of Acridinium Photocatalysts

Synlett ◽  
2021 ◽  
Author(s):  
Christof Sparr ◽  
Valeriia Hutskalova
Keyword(s):  
Substitution Reaction ◽  
Precious Metal ◽  
Photophysical Properties ◽  
Cation Radical ◽  
Coupling Reaction ◽  
Nucleophilic Aromatic Substitution ◽  
The Novel ◽  
Aromatic Substitution ◽  
Efficient Synthesis

AbstractThe increasing use of acridinium photocatalysts as sustainable alternative to precious metal-based counterparts encourages the design and efficient synthesis of distinct catalyst structures. Herein, we report our exploration of the scope of the aryne–imine–aryne coupling reaction combined with a subsequent acridane oxidation for a short two-step approach towards various acridinium salts. The photophysical properties of the novel photocatalysts were investigated and the practical value was demonstrated by a cation-radical accelerated nucleophilic aromatic substitution reaction.

Efficient Synthesis of 3,4-Disubstituted 7-Azaindoles Employing SEM as a Dual Protecting–Activating Group

Synlett ◽  
2019 ◽  
Vol 30 (20) ◽  
pp. 2273-2278 ◽  
Author(s):  
Piroska Gyárfás ◽  
János Gerencsér ◽  
Warren S. Wade ◽  
László Ürögdi ◽  
Zoltán Novák ◽  
...  
Keyword(s):  
Functional Groups ◽  
Efficient Method ◽  
Reaction Times ◽  
Nucleophilic Aromatic Substitution ◽  
Aromatic Substitution ◽  
Efficient Synthesis ◽  
Mild Conditions

An efficient method for nucleophilic aromatic substitution on 7-azaindoles has been developed. The reaction is facilitated by the unique dual influence of SEM as both protecting and activating group, permitting mild conditions and short reaction times that are compatible with sensitive functional groups. The method is suitable for the synthesis of a broad range of products, most notably ethers.

scholarly journals Exploring chemical diversity via a modular reaction pairing strategy

2012 ◽  
Vol 8 ◽  
pp. 1293-1302 ◽  
Author(s):  
Joanna K Loh ◽  
Sun Young Yoon ◽  
Thiwanka B Samarakoon ◽  
Alan Rolfe ◽  
Patrick Porubsky ◽  
...  
Keyword(s):  
Amino Alcohol ◽  
Building Blocks ◽  
Chemical Diversity ◽  
Nucleophilic Aromatic Substitution ◽  
Mitsunobu Reaction ◽  
Aromatic Substitution ◽  
Efficient Synthesis ◽  
Microwave Assisted ◽  
Computational Analyses ◽  
Pairing Protocol

The efficient synthesis of an 80-member library of unique benzoxathiazocine 1,1-dioxides by a microwave-assisted, intermolecular nucleophilic aromatic substitution (SNAr) diversification pathway is reported. Eight benzofused sultam cores were generated by means of a sulfonylation/SNAr/Mitsunobu reaction pairing protocol, and subsequently diversified by intermolecular SNAr with ten chiral, non-racemic amine/amino alcohol building blocks. Computational analyses were employed to explore and evaluate the chemical diversity of the library.

Efficient Synthesis of Arylenedioxy‐Bridged Porphyrin Dimers through Catalyst‐Free Nucleophilic Aromatic Substitution

ChemPlusChem ◽  
2020 ◽  
Vol 85 (1) ◽  
pp. 217-226
Author(s):  
Ken‐ichi Yamashita ◽  
Narumi Kuramochi ◽  
Hang Pham Qui Van ◽  
Kazuhiro Furutani ◽  
Takuji Ogawa ◽  
...  
Keyword(s):  
Nucleophilic Aromatic Substitution ◽  
Aromatic Substitution ◽  
Efficient Synthesis ◽  
Catalyst Free ◽  
Porphyrin Dimers

scholarly journals Machine learning meets mechanistic modelling for accurate prediction of experimental activation energies

2021 ◽  
Author(s):  
Kjell Jorner ◽  
Tore Brinck ◽  
Per-Ola Norrby ◽  
David Buttar
Keyword(s):  
Machine Learning ◽  
Activation Energies ◽  
Accurate Prediction ◽  
Nucleophilic Aromatic Substitution ◽  
Aromatic Substitution ◽  
Mechanistic Modelling

Hybrid reactivity models, combining mechanistic calculations and machine learning with descriptors, are used to predict barriers for nucleophilic aromatic substitution.

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