BH9, a New Comprehensive Benchmark Data Set for Barrier Heights and Reaction Energies: Assessment of Density Functional Approximations and Basis Set Incompleteness Potentials

The
calculation of accurate reaction energies and barrier heights
is essential in computational studies of reaction mechanisms and thermochemistry.
To assess methods regarding their ability to predict these two properties,
high-quality benchmark sets are required that comprise a reasonably
large and diverse set of organic reactions. Due to the time-consuming
nature of both locating transition states and computing accurate reference
energies for reactions involving large molecules, previous benchmark
sets have been limited in scope, the number of reactions considered,
and the size of the reactant and product molecules. Recent advances
in coupled-cluster theory, in particular local correlation methods
like DLPNO-CCSD­(T), now allow the calculation of reaction energies
and barrier heights for relatively large systems. In this work, we
present a comprehensive and diverse benchmark set of barrier heights
and reaction energies based on DLPNO-CCSD­(T)/CBS called BH9. BH9 comprises
449 chemical reactions belonging to nine types common in organic chemistry
and biochemistry. We examine the accuracy of DLPNO-CCSD­(T) vis-a-vis
canonical CCSD­(T) for a subset of BH9 and conclude that, although
there is a penalty in using the DLPNO approximation, the reference
data are accurate enough to serve as a benchmark for density functional
theory (DFT) methods. We then present two applications of the BH9
set. First, we examine the performance of several density functional
approximations commonly used in thermochemical and mechanistic studies.
Second, we assess our basis set incompleteness potentials regarding
their ability to mitigate basis set incompleteness errors. The number
of data points, the diversity of the reactions considered, and the
relatively large size of the reactant molecules make BH9 the most
comprehensive thermochemical benchmark set to date and a useful tool
for the development and assessment of computational methods.