Conformational Energy Benchmark for Longer n-Alkane Chains.

Area of Science:

• Computational Chemistry
• Molecular Modeling
• Physical Chemistry

Background:

• Unbranched alkanes are fundamental in nature and biology.
• Accurate calculation of their properties is crucial for advanced modeling.
• Existing methods require comprehensive evaluation for conformational energy prediction.

Purpose of the Study:

• To establish the ACONFL benchmark dataset for conformational energies of long n-alkane chains.
• To evaluate the performance of various computational chemistry methods for these systems.
• To identify accurate and efficient methods for modeling alkane chain conformations.

Main Methods:

• Generation of highly accurate reference data using DLPNO-CCSD(T1)/CBS.
• Comprehensive assessment of density functional theory (DFT) methods, including dispersion-corrected functionals.
• Evaluation of wave function methods, semiempirical methods, and force fields.

Main Results:

• The r2SCAN-V functional demonstrates excellent performance, comparable to composite DFT methods.
• GFN-FF force field shows outstanding accuracy for conformational energies.
• MP2/CBS unexpectedly underperforms compared to D4 dispersion-corrected Hartree-Fock.

Conclusions:

• ACONFL serves as a valuable benchmark for developing and validating computational methods.
• Modern DFT functionals and specific force fields offer improved accuracy for alkane systems.
• The study provides guidance for selecting appropriate methods in molecular modeling and simulations.