Recent progress in methodology with DFT methods has allowed tackling of increasingly challenging tasks in terms of understanding mechanisms and making predictions on small molecule activation by biological metal centers. The potential practical applications of such investigations cannot be overstated: fields like proton activation for molecular hydrogen production, water splitting, molecular nitrogen activation, or carbon dioxide fixation still have unexplored facets, with computa-tional methods able to provide key input for generating robust economically feasible catalysts. On a different note, species that may be too short lived to be observed experimentally are facile targets for DFT predictions. Also, recent years have seen a focus on allowing predictions on spectroscopic parameters [92–95].
One important component is, however, the responsibility of the researcher to properly assess the predictive value of the DFT results. The times where a single method would be applied on a small set of models, concluding that “theory confirms experiment,” have long passed. We have given here examples of how some of the mainstream functionals can easily lead to opposing conclusions on key aspects of the topic investigated; in our experience these differences between functionals may amount to as high as 30 kcal/mol in terms of spin state preferences, and not much lower for activation barrier differences; these values are much larger than the 1–5 kcal/mol commonly assumed in past years. From this point of view, methodo-logical contributions such as reference [3] will in our opinion prove to be by far among the most useful for the future development of the field.
Acknowledgment Funding from the Romanian Ministry for Education and Research project PCCE 140/2008 is gratefully acknowledged.
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DOI: 10.1007/978-3-642-32750-6_4
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