Research interests

The main goal of most of our ongoing research projects is to develop new and improved transition-metal-based catalysts. Molecular-level computational chemistry is an important tool in order to reach this goal. The initial role of theory in these projects usually is to provide mechanistic information, meaning that the most efficient catalyst development should be based on a clear understanding of the underlying factors governing the activity or selectivity. However, theory can provide more than just the mechanism: Due to decades of development in both computational methodology and hardware, it has become cost-efficient to move large portions of the catalyst screening-work from the lab to the computer, and integration of computational chemistry into catalyst development is an important part of our work. The predicted new catalysts are subsequently synthesized and tested, either in our own lab or in the labs of collaborating groups.

Depending on the chemical problem in question, the methods used in the computational parts of these projects range from molecular mechanics through semi-empiry and density functional theory to high level, wave function-correlated ab initio methods. The use of more approximate methods is routinely preceded by validation against experimental data or results from higher level calculations.

Main current research

Industrial catalysis

Most of our activity is within the downstream application of natural gas, with a particular focus on the use of olefins as the main substrate in a range of refinement processes:

Olefin metathesis Examples:
Development of Z-selective catalysts	Description of project, Occhipinti et al. J. Am. Chem. Soc. 2013, 135, 3331-3334
Design of more active catalysts	Occhipinti et al. J. Am. Chem. Soc. 2006, 128, 6952-6964
Detailed mechanistic insight	Minenkov et al. Eur. J. Inorg. Chem. 2012, 17, 1507-1516
Validation of computational methods	Minenkov et al. J. Phys. Chem. A 2009, 113, 11833-11844 and Minenkov et al. Dalton Trans. 2012, 41, 5526-5541
Olefin oligomerization and polymerization Examples:
Functional group tolerance versus insertion barriers in late-transition-metal-catalyzed co-polymerization	Heyndrickx et al. Organometallics 2012, 31, 6022-6031
Mechanistic insight and design of new ethylene oligomerization and polymerizatioin catalysts	Heyndrickx et al. Chem. Eur. J. 2011, 17, 14628-14642, Döhring et al. et al. Organometallics 2001, 20, 2234-2245, and Jensen et al. Organometallics 2001, 20, 4852-4862
Prediction of stereoselectivity of zirconocenes	Angermund et al. Macromol. Rapid Commun. 2000, 21, 91-97 and Angermund et al. Chem. Rev. 2000, 100, 1457-14707
Hydroformylation Example:
Mechanistic insight and design of new catalysts	Sparta et al. J. Am. Chem. Soc. 2007, 129, 8487-8499

Method development

We develop methods and approaches for design and development of catalysts and other functional transition-metal compounds. We have, for example, worked on incorporating chemically intuitive and meaningful molecular descriptors, such as measures of ligand-to-metal donation, metal-to-ligand back-donation, and steric repulsion, into quantitative structure-activity relationship (QSAR) models. The result has been powerful and very predictive models from which it is also straightforward to extract chemical information and understanding. The limitation of this approach is that it is manual in the sense that a human being still has to suggest, build and subject the candidate catalyst structure to calculations to obtain a computational measure of its suitability as a catalyst. We are thus, together with the group of Prof. Bjørn K. Alsberg, NTNU-Trondheim, working to automate the procedure of designing new catalysts and other functional transition-metal compounds. We develop a de novo in silico design method based on an evolutionary algorithm in which the fitness (or cost function) is obtained from quantum chemical or other molecular-level calculations.

Overview of the development of the approaches and methods towards design:

Manual in silico design and descriptor development Examples:
Ligand-to-metal donation and back-donation	Occhipinti et al. J. Am. Chem. Soc. 2006, 128, 6952-6964
Tolman electronic and steric parameters	Sparta et al. J. Am. Chem. Soc. 2007, 129, 8487-8499
Automated in silico design Example:
de novo evolutionary algorithm for design of functional transition metal complexes	Chu et al. J. Am. Chem. Soc. 2012,134, 8885-8895.