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Poisoning density functional theory with benchmark sets of difficult systems.

Tim Gould1, Stephen G Dale1

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New benchmark sets identify challenging systems for density functional approximations (DFAs). These

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • Large benchmark sets like GMTKN55 assess density functional theory (DFT) performance across diverse chemical systems.
  • Broad assessments may overlook specific, difficult cases where DFT approximations fail significantly.

Purpose of the Study:

  • Introduce novel 'poison' benchmark sets (P30-5, P30-10, P30-20) to identify challenging systems for DFT.
  • Provide targeted datasets for developing and refining DFT approximations.

Main Methods:

  • Created 'poison' benchmark sets (P30-5, P30-10, P30-20) from the most difficult systems within GMTKN55.
  • These sets include systems with 5, 10, and 20 atoms, respectively.

Main Results:

  • The P30 sets isolate particularly challenging instances for current DFT methods.
  • These datasets highlight specific weaknesses in existing density functional approximations (DFAs).

Conclusions:

  • The P30 benchmark sets are crucial for developing improved DFAs.
  • They aid in selecting appropriate DFAs for complex computational studies, including catalysis.