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May 7, 2026Journal of Chemical Theory and Computation0 citations

Double-Hybrid, but Not Double-Cost: GPU-Accelerated DHDFT for the COMPAS-3 Data Set of Polybenzenoid Hydrocarbons

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RSRyan StocksEPElise PalethorpeAKAmir Karton

Key Points

  • This research focuses on enhancing computational efficiency in the study of polybenzenoid hydrocarbons using GPU-accelerated DHDFT methods.
  • Conducted revDSD-PBEP86-D4(noFC)/def2-QZVPP calculations on 39,000 hydrocarbon isomers.
  • Utilized the Perlmutter supercomputer for computational analysis.
  • Benchmarked various LDA, GGA, and MGGA functionals against isomer energies.
  • The SVWN5 LDA functional provides a mean absolute deviation (MAD) of 4.47 kJ/mol, outperforming other functionals without dispersion corrections.
  • With dispersion corrections, M06-L-D4 achieves a MAD of 3.82 kJ/mol, outperforming other functionals.

Abstract

angular momentum. We demonstrate revDSD-PBEP86-D4(noFC)/def2-QZVPP calculations on the entire COMPAS-3x data set of ∼39,000 peri-condensed polybenzenoid hydrocarbon isomer geometries (up to 68 atoms) using just 900 node-hours on the Perlmutter supercomputer. For medium-sized organic molecules (up to ∼3k basis functions), the PT2 component adds minimal cost relative to the initial SCF step. This demonstrates that efficient GPU acceleration reduces the practical computational requirements of DHDFT comparable to conventional hybrid DFT. We additionally benchmark a range of LDA, GGA, and MGGA functionals against the revDSD-PBEP86-D4(noFC) isomerization energies. Without dispersion corrections, the SVWN5 LDA functional (MAD 4.47 kJ/mol) outperforms all tested GGAs and MGGAs. With dispersion corrections, only two MGGAs, led by M06-L-D4 (MAD 3.82 kJ/mol), are able to surpass the SVWN5 results.

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Cite This Study

Stocks et al. (2026) studied this question.

synapsesocial.com/papers/69fbe3ca164b5133a91a3023https://doi.org/10.1021/acs.jctc.6c00175
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