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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Quantifying the error of the core-valence separation approximation.

Michael F Herbst1, Thomas Fransson2

  • 1CERMICS, École des Ponts ParisTech, 6-8 Avenue Blaise Pascal, 77455 Marne-la-Vallée, France; Inria Paris, 75589 Paris Cedex 12, France; and Sorbonne Universitée, Institut des Sciences du Calcul et des Données, ISCD, 75005 Paris, France.

The Journal of Chemical Physics
|August 11, 2020
PubMed
Summary
This summary is machine-generated.

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We developed a post-processing method to eliminate errors in core-valence separation (CVS) calculations for X-ray absorption spectroscopy. This improves the accuracy of predicting core-excited states, crucial for understanding electronic structures.

Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Spectroscopy

Background:

  • Core-valence separation (CVS) is essential for calculating core-excited states in X-ray absorption spectroscopy.
  • The CVS scheme, while specific, introduces inherent errors in these calculations.

Purpose of the Study:

  • To implement a post-processing step to remove errors from CVS excitations.
  • To analyze the accuracy and error sources within the CVS scheme.
  • To investigate the impact of basis set selection on CVS accuracy.

Main Methods:

  • Algebraic-diagrammatic construction scheme for the polarization propagator.
  • Post-processing of CVS excitations.
  • Systematic analysis of error contributions and basis set effects.

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Main Results:

  • A novel post-processing method successfully eliminates CVS errors.
  • CVS accuracy is limited by the balance of neglected core-valence and core-core excitations.
  • Basis set choice, particularly tight polarizing functions, is critical for error balance.
  • CVS error is system-independent and element-specific (±0.02 eV for K-edge).

Conclusions:

  • The developed post-processing method enhances the reliability of CVS calculations.
  • Understanding error sources provides insights into improving theoretical models for spectroscopy.
  • Basis set optimization is key to achieving accurate core-excited state predictions.