A machine learning approach for predicting the nucleophilicity of organic molecules-Reference-Cited by-同舟云学术

A machine learning approach for predicting the nucleophilicity of organic molecules

Published:2022 Issue:3 Volume:24 Page:1821-1829
ISSN:1463-9076
Container-title:Physical Chemistry Chemical Physics
language:en
Short-container-title:Phys. Chem. Chem. Phys.

Author:

Saini Vaneet¹^ORCID,Sharma Aditya¹,Nivatia Dhruv²

Affiliation:

1. Department of Chemistry & Centre for Advanced Studies in Chemistry, Panjab University, Chandigarh 160014, India

2. IT Department, University Institute of Engineering & Technology, Panjab University, Chandigarh 160014, India

Abstract

A neural network model was found to efficiently predict the experimental nucleophilicity values using the quantum mechanical descriptors extracted from organic molecules.

Funder

Department of Science and Technology, Ministry of Science and Technology

Publisher

Royal Society of Chemistry (RSC)

Subject

Physical and Theoretical Chemistry,General Physics and Astronomy

Link

http://pubs.rsc.org/en/content/articlepdf/2022/CP/D1CP05072A

Reference64 articles.

1. Principles of an Electronic Theory of Organic Reactions.

2. K. A.Savin , in Writing Reaction Mechanisms in Organic Chemistry , ed. K. A. Savin , Academic Press , Boston , 3rd edn, 2014 , 10.1016/B978-0-12-411475-3.00001-4, pp. 1–53

3. The nucleophilicity N index in organic chemistry

4. Quantitative Correlation of Relative Rates. Comparison of Hydroxide Ion with Other Nucleophilic Reagents toward Alkyl Halides, Esters, Epoxides and Acyl Halides1

5. Correlation of Relative Rates and Equilibria with a Double Basicity Scale

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