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"Mindless" DFT Benchmarking.

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Summary
This summary is machine-generated.

This study introduces artificial molecules (AMs) for creating diverse thermochemical benchmark sets, enabling robust density functional testing. Double-hybrid functionals demonstrated the best performance in accurately predicting relative energies for these challenging chemical systems.

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Area of Science:

  • Computational chemistry
  • Quantum chemistry
  • Theoretical chemistry

Background:

  • Accurate thermochemical data is crucial for developing reliable computational chemistry methods.
  • Existing benchmark sets often lack structural diversity and can be biased by chemical intuition.
  • There is a need for systematically generated, diverse molecular test sets to rigorously evaluate theoretical models.

Purpose of the Study:

  • To present a diversity-oriented approach for generating thermochemical benchmark sets using artificial molecules (AMs).
  • To open up the narrow structural space of chemical intuition by creating unforeseeable, electronically challenging cases.
  • To provide highly accurate reference energies for benchmarking a wide range of density functionals.

Main Methods:

  • Generation of "artificial molecules" (AMs) with systematic constraints, avoiding uncontrolled chemical biases.
  • Decomposition of AMs into small molecules (hydrides and diatomics) for calculating chemically meaningful relative energies.
  • Calculation of reference energies using high-accuracy all-electron coupled cluster singles, doubles, and perturbative triples (CCSD(T))/complete basis set methods.
  • Benchmarking of various density functionals, including local density approximation (LDA), generalized gradient approximation (GGA), meta-GGA, hybrid, and double-hybrid functionals, with and without empirical dispersion corrections (DFT-D).

Main Results:

  • Two diverse test sets of eight-atom, main group AMs were generated, featuring unusual structures.
  • Statistical analysis of the MB08-165 set (165 entries) showed a clear trend aligning with "Jacob's ladder" of density functional theory (DFT) complexity.
  • Mean absolute deviations (MAD) decreased from LDA (20 kcal/mol) to GGAs (approx. 10 kcal/mol) and hybrid-GGAs (approx. 6-8 kcal/mol).
  • The best performance (MAD of 4.1-4.2 kcal/mol) was achieved by double-hybrid functionals (B2-PLYP-D, B2GP-PLYP-D), followed by M06-2X (MAD of 4.8 kcal/mol).

Conclusions:

  • The proposed diversity-oriented approach effectively generates challenging benchmark sets for robust computational chemistry method evaluation.
  • The results confirm the hierarchical improvement in accuracy predicted by "Jacob's ladder" for DFT functionals.
  • Double-hybrid functionals represent the current state-of-the-art for thermochemical accuracy among the tested DFT methods for these diverse systems.