Quantifying ligand effects in high-oxidation-state metal catalysis

Abstract

Catalysis by high-valent metals such as titanium(IV) impacts our lives daily through reactions like olefin polymerization. In any catalysis, optimization involves a careful choice of not just the metal but also the ancillary ligands. Because these choices dramatically impact the electronic structure of the system and, in turn, catalyst performance, new tools for catalyst development are needed. Understanding ancillary ligand effects is arguably one of the most critical aspects of catalyst optimization and, while parameters for phosphines have been used for decades with low-valent systems, a comparable system does not exist for high-valent metals. A new electronic parameter for ligand donation, derived from experiments on a high-valent chromium species, is now available. Here, we show that the new parameters enable quantitative determination of ancillary ligand effects on catalysis rate and, in some cases, even provide mechanistic information. Analysing reactions in this way can be used to design better catalyst architectures and paves the way for the use of such parameters in a host of high-valent processes.

Metal–oxygen decoordination stabilizes anion redox in Li-rich oxides

“…45,46 Given the stabilizing effect of cation migration demonstrated here, the relative reactivity of these materials towards the electrolyte and oxygen evolution in the absence of cation migration will be an interesting avenue of further study. Our results reveal a clear strategy for designing materials for applications beyond energy storage where low valence electron counts (high oxidation states) need to be reversibly accessed, such as catalysts for reactions including oxygen evolution, 20,47,48 olefin polymerization, 49 and methane 489 hydroxylation. 50 We used the TOPAS software package (Academic v6, Bruker) for Rietveld refinement.…”

Towards the online computer-aided design of catalytic pockets

“…Because the buried volume focuses on space occupation around the metal, rather than on specific features of a given class of ligands, it can be used to build property-structure relationships for any class of catalysts and ligands. For example, this parameter has been used to quantify the steric effects of ligands in high-oxidation-state metal catalysis 26 and, together with the Tolman cone angle, to explain the enhancement of nickel catalysis in crosscoupling reactions via remote steric effects 27 . Nevertheless, most of the proposed descriptors are limited by condensing the features of a given catalyst to single numbers, while the chemical behaviour is often more complex, because it is related to the three-dimensional (3D) shape of the catalytic pocket.…”

Computational Ligand Descriptors for Catalyst Design

“…Large database of simple descriptors (topology, size, elements, electronegativity), pruned for high correlation with redox potentials. 15,23,190,191 Bidentate pyrrolide, indolide, aryloxide, and bis(thiolate) ligands (12), applied to analysis of titanium-catalysed hydroamination %Vbur, natural ligand donor parameter (LDP) developed by Odom's group, 192,193 ligand properties derived from simplified, monodentate ligands X on [NCr(NiPr2)2X] 194 Cyclopentadienyl ligands (22) in Rh(III)catalysed C-H activations NMR, CO stretching, redox potential, charges, cone angles, Sterimol parameters 195 P,N-donor and Cp/Cp* ligands (11), coordinated to Ruthenium catalysts for alkene isomerisaton, study of selectivity and activity Initial calculation of 308 descriptors, reduced through further analysis to 6 key descriptors, analysis discussed in section 3.2 below. 196 Asymmetric bidentate ligands (19) with range of donor groups coupled via orthophenylene bridge, coordination to Rh(CO)2 fragments.…”