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A simple model for calculating atomic charges in molecules.

Alexander A Voityuk1, Anton J Stasyuk, Sergei F Vyboishchikov

  • 1Institució Catalana de Recerca i Estudis Avançats (ICREA), Passeig de Lluís Companys, 23, 08010 Barcelona, Spain. alexander.voityuk@gmail.com.

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|September 4, 2018
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Summary

We introduce the adjusted charge partitioning (ACP) scheme for analyzing atomic charges in molecules. This method accurately reproduces experimental dipole moments and provides chemically consistent atomic charges, proving robust across different computational bases.

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Area of Science:

  • Quantum Chemistry
  • Computational Chemistry
  • Materials Science

Background:

  • Accurate atomic charge calculation is crucial for understanding molecular properties and reactivity.
  • Existing atomic charge analysis methods have limitations in accuracy, consistency, and basis set dependency.

Purpose of the Study:

  • To develop and validate a novel atomic charge analysis method, the adjusted charge partitioning (ACP) scheme.
  • To assess the performance of the ACP scheme against established methods using a diverse set of molecules.

Main Methods:

  • The adjusted charge partitioning (ACP) scheme utilizes weighting factors cAr^(2n-2)exp(-αAr) with atomic parameters cA and αA.
  • Extensive numerical tests were conducted on 540 molecules across 17 main-group elements.
  • Atomic charges and dipole moments were compared with results from Mulliken, Löwdin, Hirshfeld, CM5, ESP, NPA, and QTAIM methods.

Main Results:

  • The ACP scheme demonstrates insensitivity to the choice of basis sets used in calculations.
  • Generated atomic charges are chemically consistent and reliable.
  • The method accurately reproduces experimental dipole moments for the tested molecules.

Conclusions:

  • The adjusted charge partitioning (ACP) scheme offers a robust and accurate approach for atomic charge analysis.
  • ACP provides a valuable alternative to existing methods, particularly for its basis set independence and chemical consistency.
  • This method enhances the predictive power of computational chemistry for molecular properties.