Towards a Realistic Theoretical Electronic ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
Titre :
Towards a Realistic Theoretical Electronic Spectra of Metal Aqua Ions in Solution: The Case of Ce(H<sub>2</sub>O)<sub>n</sub><sup>3+</sup> Using Statistical Methods and Quantum ChemistryCalculation
Auteur(s) :
Raposo-Hernández, Gema [Auteur]
Pappalardo, Rafael [Auteur]
Réal, Florent [Auteur]
Laboratoire de Physique des Lasers, Atomes et Molécules - UMR 8523 [PhLAM]
Vallet, Valérie [Auteur]
Physico-Chimie Moléculaire Théorique [PCMT]
Sánchez Marcos, Enrique [Auteur correspondant]
Pappalardo, Rafael [Auteur]
Réal, Florent [Auteur]
Laboratoire de Physique des Lasers, Atomes et Molécules - UMR 8523 [PhLAM]
Vallet, Valérie [Auteur]
Physico-Chimie Moléculaire Théorique [PCMT]
Sánchez Marcos, Enrique [Auteur correspondant]
Titre de la revue :
The Journal of Chemical Physics
Pagination :
144109
Éditeur :
American Institute of Physics
Date de publication :
2024-10-14
ISSN :
0021-9606
Mot(s)-clé(s) en anglais :
numbers: Valid appear here Ce 3+ hydrate classical interaction potentials MD NEVPT2 electronic transitions statistical average of transitions line broadening procedures
numbers: Valid appear here Ce 3+ hydrate
classical interaction potentials
MD
NEVPT2
electronic transitions
statistical average of transitions
line broadening procedures
numbers: Valid appear here Ce 3+ hydrate
classical interaction potentials
MD
NEVPT2
electronic transitions
statistical average of transitions
line broadening procedures
Discipline(s) HAL :
Chimie/Chimie théorique et/ou physique
Physique [physics]/Physique [physics]/Chimie-Physique [physics.chem-ph]
Physique [physics]/Physique [physics]/Chimie-Physique [physics.chem-ph]
Résumé en anglais : [en]
Ce(III) UV-vis spectrum<p>Accurately predicting spectra for heavy elements, often open-shell systems, is a significant challenge typically addressed using a single cluster approach with a fixed coordination number. Developing ...
Lire la suite >Ce(III) UV-vis spectrum<p>Accurately predicting spectra for heavy elements, often open-shell systems, is a significant challenge typically addressed using a single cluster approach with a fixed coordination number. Developing a realistic model that accounts for temperature effects, variable coordination numbers, and interprets experimental data is even more demanding due to the strong solute-solvent interactions present in solutions of heavy metal cations. This study addresses these challenges by combining multiple methodologies to accurately predict realistic spectra for highly-charged metal cations in aqueous media, with a focus on the electronic absorption spectrum of Ce<sup>3+</sup> in water. Utilizing highly correlated relativistic quantum mechanical (QM) wavefunctions and structures from molecular dynamics (MD) simulations, we show that the convolution of individual vertical transitions yields an excellent agreement with experimental results without the introduction of empirical broadening. The good results are obtained for both the normalized spectrum and that of absolute intensity. The study incorporates a statistical machine learning algorithm, Gaussian Mixture Models-Nuclear Ensemble Approach (GMM-NEA), to convolute individual spectra. The microscopic distribution provided by MD simulations allows us to examine the contributions of the octa-and ennea-hydrate of Ce<sup>3+</sup> in water to the final spectrum. Additionally, the temperature dependence of the spectrum is theoretically captured by observing the changing population of these hydrate forms with temperature. We also explore an alternative method for obtaining statistically representative structures in a less demanding manner than MD simulations, derived from QM Wigner distributions.The combination of Wigner-sampling and GMM-NEA broadening shows promise for wide application in spectroscopic analysis and predictions, offering a computationally efficient alternative to traditional methods.</p>Lire moins >
Lire la suite >Ce(III) UV-vis spectrum<p>Accurately predicting spectra for heavy elements, often open-shell systems, is a significant challenge typically addressed using a single cluster approach with a fixed coordination number. Developing a realistic model that accounts for temperature effects, variable coordination numbers, and interprets experimental data is even more demanding due to the strong solute-solvent interactions present in solutions of heavy metal cations. This study addresses these challenges by combining multiple methodologies to accurately predict realistic spectra for highly-charged metal cations in aqueous media, with a focus on the electronic absorption spectrum of Ce<sup>3+</sup> in water. Utilizing highly correlated relativistic quantum mechanical (QM) wavefunctions and structures from molecular dynamics (MD) simulations, we show that the convolution of individual vertical transitions yields an excellent agreement with experimental results without the introduction of empirical broadening. The good results are obtained for both the normalized spectrum and that of absolute intensity. The study incorporates a statistical machine learning algorithm, Gaussian Mixture Models-Nuclear Ensemble Approach (GMM-NEA), to convolute individual spectra. The microscopic distribution provided by MD simulations allows us to examine the contributions of the octa-and ennea-hydrate of Ce<sup>3+</sup> in water to the final spectrum. Additionally, the temperature dependence of the spectrum is theoretically captured by observing the changing population of these hydrate forms with temperature. We also explore an alternative method for obtaining statistically representative structures in a less demanding manner than MD simulations, derived from QM Wigner distributions.The combination of Wigner-sampling and GMM-NEA broadening shows promise for wide application in spectroscopic analysis and predictions, offering a computationally efficient alternative to traditional methods.</p>Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet ANR :
Source :
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