Reactivity and Selectivity in Olefin Metathesis

Technical advances have been accompanied by an ever-increasing demand for new (functional) materials with predefined properties. For example, synthetic fibers have been developed with high temperature stability and flame resistance for protective clothing or sporting goods. Chemistry has emerged as the discipline of choice to create novel materials or molecules and to convert cheap starting material into valuable products. In these chemical reactions, two aspects are essential: (i) to selectively create only the desired product thereby reducing waste and (ii) to use as little energy as possible to make the product thereby being sustainable. To fulfill these requirements, often so-called catalysts are used that aid the chemical transformation. These catalysts increase the selectivity, that is, the reaction to the desired product over the reaction to any unwanted byproducts, while also reducing the required energy. Catalysts are spectators; hence, they are not consumed in the reaction but are regenerated after one reaction cycle to be available for the conversion of the next molecule. The catalysts available today often have severe issues: they may contain metal atoms that are scarce or toxic for humans, they may be prone to deactivation and loss of functionality or they can only convert specific starting material thus limiting the variety of products that can be made. The discovery of new catalysts that are selective, efficient, stable, and based on abundant and nontoxic metals is therefore of utmost importance for a sustainable development. Until today, experimental chemists have synthesized a plethora of catalysts some of them are of such industrial importance that they got awarded the Nobel prize, for example, catalysts that provide access to polymers with tunable properties. Despite the vast progress in the field, the development often builds on previous experience and chemical intuition. For a rational design of efficient catalysts, however, the entire reaction process and the factors that make a good catalyst need to be understood in-depth. In addition to experimental work, computer models can be used to study these processes and factors on a molecular level. They can provide information that is not easily assessable in experiment by systematic variation of (reaction) parameters. In this project, we use methodologies routed in quantum mechanics to simulate the catalyst and the reaction in computer models. The smallest particles in our calculations are electrons and atomic nuclei. Our aim is to identify features that make an efficient and selective catalyst to produce tailor-made polymers that are used as novel materials. We intend to suggest novel catalysts to be made in the laboratory that are superior to presently available ones.

As technology advances, the demand for new materials with tailored, high-performance properties continues to rise. Chemistry is at the heart of creating these materials by transforming inexpensive raw compounds into valuable products. Two key goals drive this transformation: maximizing selectivity to reduce waste, and minimizing energy input for sustainable production. Catalysts are essential tools in achieving these goals. They accelerate chemical reactions, improve selectivity, and lower energy demands, without being consumed in the process. However, many existing catalysts face challenges: they rely on rare or toxic metals, degrade quickly, or are effective only for a limited range of reactions or substrates. Developing catalysts that are selective, efficient, stable, and made from Earth-abundant, non-toxic elements is vital for sustainable innovation. This project focused on improving our understanding of catalytic reactions through computational chemistry, focussing on olefin metathesis - a reaction to redistribute alkyl fragments and allowing for (stereospecific) oligomierization of the substrate. Using quantum mechanical methods, we uncovered the stereospecific pathway responsible for the high E-selectivity of a molybdenum-based olefin metathesis catalyst. Beyond existing systems, we also proposed new catalyst designs based on abundant 3d transition metals, such as manganese, and assessed their potential before attempting synthesis. We soon realized that conventional computational models were often inadequate, especially for predicting catalyst activity in flexible systems or in solution. To overcome these limitations, we developed new tools and methods that better reflect realistic experimental conditions, including explicit solvation and molecular flexibility. These advances brought theoretical models closer to experimental practice. This allowed us to explore a new class of catalysts, supramolecular Cu-calix[8]arene complexes, which showed improved performance in C-X coupling reactions where traditional copper catalysts had limited success. We demonstrated how supramolecular encapsulation enables the effective use of Earth-abundant copper investigated C-N coupling dynamics under experimental temperature, pressure, and in explicit solvent. To capture statistical relevance of the bond formation step, we generated a large dataset and applied advanced statistical and machine learning techniques to extract chemical insight. Through this work, we advanced both the theoretical foundations and practical tools needed for the rational design of next-generation catalysts that are not only effective but also sustainable.