Quantitative Electrophilicity Measures

作     者：GONZáLEZ Marco Martínez CáRDENAS Carlos RODRíGUEZ Juan I. LIU Shubin HEIDAR-ZADEH Farnaz MIRANDA-QUINTANA Ramón Alain AYERS Paul W. 

作者机构：Laboratory of Computational and Theoretical Chemistry Faculty of Chemistry University of Havana Havana 10400 Cuba. Departamento de Quimica and Centro de Quimica Universidade de Coimbra 3004-535 Coimbra Portugal. Departamento de Fisica Fac 

出 版 物：《物理化学学报》 (Acta Physico-Chimica Sinica)

年 卷 期：2018年第34卷第6期

页      面：662-674页

核心收录：

学科分类：081704[工学-应用化学] 08[工学] 0817[工学-化学工程与技术] 

基　　金：CC acknowledges support by FONDECYT (1140313), Financiamiento Basal para Centros Cientificos y Tecnoldgicos de Excelencia-FB0807, and project RC-130006 CIL[S Chile. PWA acknowledges support from NSERC, the Canada Research Chairs, and Compute Canada: Cana 

主　　题：Electrophilicity Conceptual density functional theory Symbolic regression Genetic programming Grammatical evolution 

摘      要：Quantitative correlation of several theoretical electrophilicity measures over different families of organic compounds are examined relative to the experimental values of Mayr et ***,the ability to predict these values accurately will help to elucidate the reactivity and selectivity trends observed in charge-transfer reactions.A crucial advantage of this theoretical approach is that itprovides this information without the need of experiments,which are often demanding and ***,two different types of electrophilicity measures were ***,models derived from conceptual density functional theory(c-DFT),including Parr s original proposal and further generalizations of this index,are *** instance,the approaches of Gázquez et *** Chamorro et *** considered,whereby it is possible to distinguish between processes in which a molecule gains or loses ***,we also explored two novel electrophilicity *** one hand,the potential of environmental perturbations to affect electron incorporation into a system is analyzed in terms of recent developments in *** studies highlight the importance of considering the molecular surroundings when a consistent description of chemical reactivity is *** the other hand,we test a new definition of electrophilicity that is free from inconsistencies(so-called thermodynamic electrophilicity).This approach is based on Parr s pioneering insights,though it corrects issues present in the standard working expression for the calculation of ***,we use machine-learning tools(i.e.,symbolic regression) to identify the models that best fit the experimental *** this way,the best possible description of the electrophilicity values in terms of different electronic structure quantities is ***,this straightforward approach enables one to obtain good correlations between the theoretical and experimental quantities by using the simple,yet p