Theoretical Study of Two Possible Side Reactions for Reductive Functionalization of 3d Metal–Methyl Complexes by Hydroxide Ion: Deprotonation and Metal–Methyl Bond Dissociation

Abstract

A DFT study of two possible competitive reactions for reductive functionalization (RF) of metal−methyl complexes ([M II (diimine) 2 (CH 3 )(Cl)], M II = V II through Cu II ) was performed to understand the factors that lower the selectivity of C−O bond forming reactions. One of the possible side reactions is deprotonation of the methyl group, which leads to formation of a methylene complex and water. The other possible side reaction is metal−methyl bond dissociation, which was assessed by calculating the bond dissociation free energies of M− CH 3 bonds. Deprotonation was found to be competitive kinetically for most of the first-row transition-metal−methyl complexes (except for Cr II , Mn II , and Cu II ) but less favorable thermodynamically in comparison to reductive functionalization for all of the studied first-row transition metals. Metal−carbon bond dissociation was found to be less favorable than the RF reactions for most 3d transition-metal complexes studied. Therefore, this study suggests that Earth-abundant catalysts for alkane oxidation should focus on chromium-triad metals. ■ INTRODUCTIONOxidation of light alkanes to their corresponding alcohols, especially methane to methanol, has attracted much attention recently. 1−14 Various computational studies have been done of the catalytic conversion of light alkanes to alcohols. 11−14 For example, in research by Periana and co-workers, the conversion of methane to methanol with a Hg II catalyst model (HgF + ) was studied by ab initio computational methods. 11 The efficiency of the reaction was high, and it was found to be improved by the high solvation energy of the proton. 11 In another computational study by Periana and co-workers, a catalytic mechanism was modeled for the functionalization of a metal−carbon bond. 12 The mechanism deduced from theory was similar to that previously reported by the same research group in which C−H activation occurs via an alkoxo complex (M−OR, M = Ir III ), producing M−R and the desired functionalized product, R− OH. In this mechanism, regeneration of M−OR from M−R took place with O atom donor ligands. Experimental and computational evidence was reported for facile oxygen atom transfer in the conversion of Re VII −R to Re VII −OR with nonperoxo oxygen atom donors. 12 A DFT study of rhodium− amidinate catalysts for methane to methanol conversion was reported by Gunnoe and co-workers. 14 In this study, quantum mechanical virtual screening was applied to select the optimum combination of ligand and solvent. The Rh(NN F ) complex, w h e r e N N F i s b i s ( N -p e n t a fl u o r o p h e n y l ) -pentafluorobenzylamidinate, was identified as a highly promising catalyst for methane to methanol conversion. The transition state barriers at 298 K for methane activation were found to be 27.6 kcal/mol in trifluoroacetic acid (TFAH) and 35.0 kcal/ mol in water; the barriers for functionalization were found to be 36.9 kcal/mol in TFAH and 31.7 kcal/mol in water. 13 In a study by Hush and co-workers, homogeneous conversion of methane to me...

Computational Study of 3d Metals and Their Influence on the Acidity of Methane C–H Bonds

“…In one study, Fallah and co-workers found that deprotonation of a methyl C–H bond was a competing side reaction to methane functionalization. 6 Thus, investigating the acid/base properties of aliphatic C–H bonds of both hydrocarbon and hydrocarbyl complexes within the coordination sphere of a transition metal is important in catalyst design.…”

Computation Sheds Insight into Iron Porphyrin Carbenes’ Electronic Structure, Formation, and N–H Insertion Reactivity

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Using Machine Learning to Predict the pKa of C–H Bonds. Relevance to Catalytic Methane Functionalization

“…5 Fallah et al likewise showed that deprotonation of methyl C-H bonds was a competing side-reaction to methyl-X functionalization, implying that the acid-base properties of hydrocarbyl C-H bonds impact catalyst selectivity. 6 More recent research by Grumbles and Cundari indicates that metal and supporting ligand effects on organometallic pKa(C-H) values of methyl ligands are commensurate with, if not greater than, traditional inductive and resonance effects for organic acids. 7 In all, six different machine learning models were tested in this research: neural network, support vector machine (SVM), k-nearest neighbors (kNN), Bayesian ridge regression, least squares linear regression, and random forest techniques.…”