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This summary is machine-generated.

We developed a faster method for calculating random phase approximation (RPA) energies, improving water cluster structure analysis. The RPA+rSE correction accurately predicts binding energies, rivaling double hybrid functionals.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Accurate prediction of molecular structures and energies is crucial in chemistry.
  • Random Phase Approximation (RPA) is a powerful method for electron correlation, but computationally intensive.
  • Water clusters are fundamental systems for understanding hydrogen bonding and solvation.

Purpose of the Study:

  • To present an efficient implementation for analytical gradients of RPA electron-correlation energy.
  • To investigate the structures and energy orderings of small to medium-sized water clusters.
  • To assess the accuracy of RPA and its corrections for binding energies.

Main Methods:

  • Improved analytical gradients for RPA using atomic orbitals and localized resolution of the identity.
  • Structure relaxation of water clusters (H2O)n, n=21, 22, 25.
  • Basis set convergence studies and comparison with double hybrid functionals.

Main Results:

  • Efficient RPA force calculations enabled structure relaxation of water clusters.
  • RPA energy ordering of low-energy isomers is sensitive to basis set choice.
  • RPA underbinds water clusters, exacerbated at the complete basis set (CBS) limit.
  • Renormalized single excitation (rSE) correction mitigates underbinding, showing overbinding at finite basis sets.
  • RPA+rSE achieves accuracy comparable to double hybrid functionals near the CBS limit for binding energies.

Conclusions:

  • The improved RPA implementation allows for efficient structural analysis of water clusters.
  • Basis set choice significantly impacts the predicted energy landscape of water clusters.
  • RPA+rSE offers a computationally viable and accurate method for predicting binding energies, especially relevant for systems like water clusters.