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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Revisiting the negative dipole moment derivatives of HNgX molecules

Full text
Author(s):
Richter, Wagner E. [1] ; Duarte, Leonardo J. [2] ; da Silva, Arnaldo F. [3] ; Bruns, Roy E. [2]
Total Authors: 4
Affiliation:
[1] Technol Fed Univ Parana, Dept Chem Engn, Rua Doutor Washington Subtil Chueire 330 Jardim C, BR-8401722 Ponta Grossa, PR - Brazil
[2] Univ Estadual Campinas, Inst Chem, Campinas, SP - Brazil
[3] Univ Nottingham, Sch Chem, Nottingham - England
Total Affiliations: 3
Document type: Journal article
Source: THEORETICAL CHEMISTRY ACCOUNTS; v. 139, n. 3 MAR 23 2020.
Web of Science Citations: 0
Abstract

The negative dipole moment derivatives of the HNgX molecules (Ng=Ar,Kr \& x37e;X=F,Cl) are revisited in order to evaluate novel aspects arised through the decade after the original investigation by SAC McDowell. The present work also makes a double-parallel comparison between different models of analyzing vibrational band intensities: the CCFDF and CCTDP models, each of them obtained with CHELPG and QTAIM charges. The CHELPG charges are in better agreement with QTAIM charges than the CHELPG atomic dipoles with the respective QTAIM ones. Moreover, within the two models, the CCFDF and CCTDP parameters follow more closely our expected elementary chemical trends when obtained using QTAIM instead CHELPG charges. The differences are more pronounced for the CCFDF than for the CCTDP model, making the latter more suitable for interpretation of infrared intensities in terms of electronic structure parameters. It is preferred to handle QTAIM/CCTDP calculations whenever possible, but CHELPG/CCTDP is an option when the former is not feasible or available. (AU)

FAPESP's process: 18/08861-9 - Application of the QTAIM / CCTDP model and machine learning for the forecast of chemical reactivities
Grantee:Roy Edward Bruns
Support Opportunities: Regular Research Grants
FAPESP's process: 18/24844-7 - Using atomic polar tensors and QCT parameters to train a machine learning model and predict Hammett constants.
Grantee:Leonardo José Duarte
Support Opportunities: Scholarships abroad - Research Internship - Doctorate (Direct)