| Title |
Conceptual DFT analysis of the regioselectivity of 1,3-dipolar cycloadditions: nitrones as a case of study
|
|---|---|
| Published in |
Journal of Molecular Modeling, July 2017
|
| DOI | 10.1007/s00894-017-3382-0 |
| Pubmed ID | |
| Authors |
Ramón Alain Miranda-Quintana, Marco Martínez González, David Hernández-Castillo, Luis A. Montero-Cabrera, Paul W. Ayers, Christophe Morell |
| Abstract |
The regioselectivity of the 1,3-dipolar cycloaddition of a model nitrone with a set of dipolarophiles, presenting diverse electronic effects, is analyzed using conceptual density functional theory (DFT) methods. We deviate from standard approaches based on frontier molecular orbitals and formulations of the local hard/soft acid/base principle and use instead the dual descriptor. A detailed analysis is carried out to determine the influence of the way to calculate the dual descriptor, the computational procedure, basis set and choice of method to condensate the values of this descriptor. We show that the qualitative regioselectivity predictions depend on the choice of "computational conditions", something that indicates the danger of using black-box computational set-ups in conceptual DFT studies. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 32% |
| Student > Ph. D. Student | 3 | 16% |
| Researcher | 2 | 11% |
| Professor | 2 | 11% |
| Student > Doctoral Student | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 13 | 68% |
| Social Sciences | 1 | 5% |
| Unknown | 5 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 July 2017.
All research outputs
#18,562,247
of 22,990,068 outputs
Outputs from Journal of Molecular Modeling
#529
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#242,146
of 315,953 outputs
Outputs of similar age from Journal of Molecular Modeling
#12
of 18 outputs
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