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Molecular acidity: An accurate description with information‐theoretic approach in density functional reactivity theory
Author(s) -
Cao Xiaofang,
Rong Chunying,
Zhong Aiguo,
Lu Tian,
Liu Shubin
Publication year - 2018
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.25090
Subject(s) - information theory , universality (dynamical systems) , entropy (arrow of time) , density functional theory , chemistry , alkyl , benzoic acid , computational chemistry , rényi entropy , thermodynamics , statistical physics , computer science , mathematics , principle of maximum entropy , organic chemistry , physics , quantum mechanics , artificial intelligence , statistics
Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information‐theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh–Berkowitz–Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental p K a values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc.