Excited state properties from ground state DFT descriptors : A QSPR approach for dyes

Guillaume Fayet 1, 2 Denis Jacquemin 3 Valérie Wathelet 3 Eric A. Perpete 3 Patricia Rotureau 2 Carlo Adamo 1
1 LECIME - Laboratoire d'Electrochimie, Chimie des Interfaces et Modélisation pour l'Energie (LECIME - UMR 7575)
2 INERIS - Institut National de l'Environnement Industriel et des Risques
3 Laboratoire de Chimie Théorique Appliquée
Abstract : This work presents a quantitative structure-property relationship (QSPR)-based approach allowing an accurate prediction of the excited-state properties of organic dyes (anthraquinones and azobenzenes) from ground-state molecular descriptors, obtained within the (conceptual) density functional theory (DFT) framework. The ab initio computation of the descriptors was achieved at several levels of theory, so that the influence of the basis set size as well as of the modeling of environmental effects could be statistically quantified. It turns out that, for the entire data set, a statistically-robust four-variable multiple linear regression based on PCM-PBE0/6-31G calculations delivers a R-adj(2) of 0.93 associated to predictive errors allowing for rapid and efficient dye design. All the selected desc ri ptors are independent of the dye's family, an advantage over previously designed QSPR schemes. On top of that, the obtained accuracy is comparable to the one of the today's reference methods while exceeding the one of hardness-based fittings. QSPR relationships specific to both families of dyes have also been built up. This work paves the way towards reliable and computationally affordable color design for organic dye.
Keywords : QSPR DFT EXCITED STATE
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Journal articles
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Submitted on : Friday, March 21, 2014 - 2:18:39 PM
Last modification on : Wednesday, September 28, 2016 - 4:15:32 PM

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Guillaume Fayet, Denis Jacquemin, Valérie Wathelet, Eric A. Perpete, Patricia Rotureau, et al.. Excited state properties from ground state DFT descriptors : A QSPR approach for dyes. Journal of Molecular Graphics and Modelling, Elsevier, 2010, 28 (6), pp.465-471. ⟨10.1016/j.jmgm.2009.11.001⟩. ⟨ineris-00963222⟩

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