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Nuclear electronic orbital density functional theory (NEO-DFT) accurately predicts proton affinities by including nuclear quantum effects. CAM-B3LYP functional and def2-QZVP basis set show optimal performance, outperforming traditional DFT methods.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Theoretical Chemistry

Background:

  • Traditional Density Functional Theory (DFT) treats nuclei classically, limiting accuracy in proton affinity predictions.
  • Nuclear Quantum Effects (NQEs) significantly influence protonation processes and require advanced computational methods.
  • The Nuclear Electronic Orbital DFT (NEO-DFT) method offers a framework to incorporate NQEs for protons.

Purpose of the Study:

  • To benchmark the NEO-DFT method for proton affinity predictions across an expanded molecular dataset.
  • To evaluate the impact of various computational parameters, including exchange-correlation functionals and basis sets, on NEO-DFT accuracy.
  • To compare the performance of NEO-DFT with traditional DFT for proton affinity calculations.

Main Methods:

  • A comprehensive benchmark of NEO-DFT was performed using a test set of 72 molecules with experimental proton affinities.
  • Various exchange-correlation functionals (e.g., B3LYP-based, CAM-B3LYP) and electron-proton correlation (epc) functionals (e.g., epc17-2, epc19) were assessed.
  • Different electronic basis sets (def2-SVP, def2-TZVP, def2-QZVP) and nuclear basis sets were systematically investigated.

Main Results:

  • B3LYP-based functionals, particularly CAM-B3LYP, demonstrated the highest accuracy for proton affinity predictions (MAD = 6.2 kJ/mol).
  • NEO-DFT with electron-proton correlation included significantly improved accuracy over traditional DFT (MAD = 31.6 kJ/mol).
  • The def2-QZVP electronic basis set provided the best accuracy (MAD = 5.0 kJ/mol), while nuclear basis sets had minimal impact.

Conclusions:

  • NEO-DFT is an effective method for accurately predicting proton affinities by incorporating nuclear quantum effects.
  • Optimal parameter choices, including the CAM-B3LYP functional and def2-QZVP basis set, enhance NEO-DFT performance.
  • This study provides valuable guidance for selecting computational parameters in future NEO-DFT applications.