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Automatic generation of complementary auxiliary basis sets for explicitly correlated methods.

Emmanouil Semidalas1, Jan M L Martin1

  • 1Department of Molecular Chemistry and Materials Science, Weizmann Institute of Science, Reḥovot, Israel.

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|July 19, 2022
PubMed
Summary
This summary is machine-generated.

A new algorithm, autoCABS, simplifies explicitly correlated calculations by automatically generating complementary auxiliary basis sets (CABS). This method ensures high accuracy comparable to existing approaches, especially for larger basis sets.

Keywords:
automatic fitting basis set generationcomplementary auxiliary basis setexplicitly correlated methods

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Theoretical Chemistry

Background:

  • Explicitly correlated calculations require auxiliary basis sets like JK fitting, RI-MP2, and CABS.
  • Existing methods can auto-generate JK and RI-MP2 basis sets, but CABS generation is not automated.
  • This limitation hinders the application of explicitly correlated methods for specific systems.

Purpose of the Study:

  • To introduce a simple algorithm, autoCABS, for the automated generation of complementary auxiliary basis sets (CABS).
  • To provide a free software Python implementation of the autoCABS algorithm.
  • To assess the quality of autoCABS-generated CABS basis sets in explicitly correlated calculations.

Main Methods:

  • Development of a novel algorithm named autoCABS.
  • Implementation of autoCABS in Python, available under a free software license.
  • Testing autoCABS using cc-pVnZ-F12 basis sets, W4-08 thermochemical benchmark, and HFREQ2014 harmonic frequencies.

Main Results:

  • autoCABS successfully generates CABS basis sets for various systems.
  • The quality of autoCABS-generated CABS basis sets is comparable to literature OptRI basis sets.
  • Accuracy differences diminish as the size of the orbital basis set (n in cc-pVnZ-F12) increases.

Conclusions:

  • The autoCABS algorithm provides a reliable and accessible method for generating CABS basis sets.
  • This automation facilitates the wider application of explicitly correlated computational methods.
  • autoCABS-generated CABS basis sets offer a high-quality and increasingly accurate alternative for computational chemistry research.