A generalized novel group contribution kinetic modeling approach to linear alkene metathesis.

Abstract

Traditional modeling approaches for linear metathesis systems involve the use of complicated approaches – This paper proposes a generalized novel kinetic modeling technique, in which the substituent (alkyl) groups on the transition states are postulated to have a unique effect on the rate at which the controlling step (transition state dissociation) occurs. Metathesis involves the redistribution of the carbon-carbon double bond across constituents, to create longer chain hydrocarbons, which significantly enhances product value in an industrial context. This work proceeds by unpacking the mechanics of the 1-Hexene (linear) metathesis pathway and utilizes this as a basis for developing a group contribution kinetic modeling approach. The substituent (alkyl) groups present in the forming transition state complexes were used to define (identify) rate constants that would potentially control the rate of formation of the various transition state complexes. A key assumption in this work was that the largest externally attaching substituent, and the substituent existing in the metallacyclobutane complex, be selected as the groups that define the formation of the respective transition state complexes. These observations resulted in a system of 25 uniquely defined (identified) rate parameters that were derived based on the defining groups observed within the mechanisms and are sufficient to describe the metathesis system under investigation. Literature experimental data, at a range of temperatures (420℃ – 460℃) was readily available and was used for the purpose of fitting the identified rate parameters, by simultaneously solving the system of differential equations that result from this system. Given the system size (25 parameters), and complexity of the interactions in the system, evolutionary and swarm optimization techniques were found to be fit for this purpose. It was found that combination between a genetic algorithm (GA) and particle swarm optimization (PSO) approach yielded identified parameters that minimized the overall error of the prediction. Kinetic parameters were identified, and Arrhenius plots were developed – These allowed for the activation energies (𝐸𝑎) and pre-exponential factors (𝐴𝑜) to be determined for each parameter. This was tested using literature experimental datasets, and predictions were found to present with a modified fitness value between 1.968 and 50.55. This illustrates that the novel group contribution kinetic modeling approach was suitable to define the interactions in the system. Further research is required to generalize this result over other alkene metathesis systems; however, this work proves that the approach is viable. Extending this work to ring closing metathesis (RCM), is a future area of research that is of particular importance, as pharmaceutical intermediates result from these processes, and represents the unique opportunity to create a synergistic industrial landscape.