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Quantitative Computational Thermochemistry of Transition Metal Species

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DeYonker, Nathan J., Peterson, Kirk A., Steyl, Gideon, Wilson, Angela K., Cundari, Thomas R.·2007·The Journal of Physical Chemistry A

Abstract

The correlation consistent Composite Approach (ccCA), which has been shown to achieve chemical accuracy (+/-1 kcal mol-1) for a large benchmark set of main group and s-block metal compounds, is used to compute enthalpies of formation for a set of 17 3d transition metal species. The training set includes a variety of metals, ligands, and bonding types. Using the correlation consistent basis sets for the 3d transition metals, we find that gas-phase enthalpies of formation can be efficiently calculated for inorganic and organometallic molecules with ccCA. However, until the reliability of gas-phase transition metal thermochemistry is improved, both experimentally and theoretically, a large experimental training set where uncertainties are near +/-1 kcal mol-1 (akin to commonly used main group benchmarking sets) remains an ambitious goal. For now, an average deviation of +/-3 kcal mol-1 appears to be the initial goal of "chemical accuracy" for ab initio transition metal model chemistries. The ccCA is also compared to a more robust but relatively expensive composite approach primarily utilizing large basis set coupled cluster computations. For a smaller training set of eight molecules, ccCA has a mean absolute deviation (MAD) of 3.4 kcal mol-1 versus the large basis set coupled-cluster-based model chemistry, which has a MAD of 3.1 kcal mol-1. However, the agreement for transition metal complexes is more system dependent than observed in previous benchmark studies of composite methods and main group compounds.

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Authors
DeYonker, N. J., Peterson, K. A., Steyl, G., Wilson, A. K., & Cundari, T. R.
Venue
The Journal of Physical Chemistry A
Published
2007-05-15
Volume
111
Issue
44
Pages
11269-11277
ISSN
  • 1089-5639 (ISSN-L)
  • 1520-5215
OpenAlex
W2080868911
Cited by
187
References
0
FWCI
6.72
Type
journal article
Language
en
Open access
green

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