Peering through the Narrow Window of Optimal Performance

Some reactions, such as the oxidation of alkanes to alcohols, demand the utilization of catalysts that can selectively convert reactants into the desired products, particularly when the undesired products are energetically more favorable. Specially, n-butane oxidation to 1-butanol, is one of such, but very important reaction. In such a reaction, one of the basic techniques to control selectivity is by utilizing a catalysts capable of promoting reactions in the pathway to the alcohol and inhibiting reactions in the pathways to all other possible products. To this regard, metal nano particle (NP) catalysts encapsulated by metal organic frameworks (MOF), have shown promising attributes. Specifically, the NP@MOF catalyst Pt@ZIF-8 has shown capability to restrict catalytic activation to the terminal carbon of a linear hydrocarbon due to the steric constraints supplied by the ZIF-8 encapsulation.

To this note, Professor Rachel Getman and her graduate student Jiazhou Zhu from the Department of Chemical and Biomolecular Engineering at Clemson University conducted a study to identify design parameters for the nanoparticle component of the catalyst that control activity and selectivity toward a terminal alcohol in the n-butane →1-butanol reaction. In addition, they intended to learn the features of transition-metal nano particle catalysts that promote activity and selectivity for alkane selective oxidations. Their work is currently published in the research journal, Industrial & Engineering Chemistry Research.

The research method employed commenced with the utilization of a combination of density functional theory and micro-kinetic modeling to calculate the thermodynamics and kinetics of reactions likely to be involved in the dominant reaction pathway for n-butane oxidation to 1-butanol, using molecular oxygen and water as oxidants. Next, they calculated the values on the various metal nanoparticles after which they evaluated the descriptors of catalytic activity and constructed linear scaling relationships that could be used to write catalytic thermodynamic and kinetic values as continuous functions of the descriptor values. Lastly, they performed a degree of rate control analysis so as to reveal the catalytic intermediates and transition states that had the greatest influence on the rate.

The authors observed that, amongst the metal nano particles assessed, Cu3Pd(111) and Ag3Pd(111) surfaces were found to be the most active for n-butane oxidation to 1-butanol, with Cu3Pd additionally exhibiting high selectivity for 1-butanol. Additionally, they noted that the catalytic affinity for C* had a substantial impact on selectivity toward 1-butanol, since the formation energy of C* on catalyst surfaces was found to correlate to catalytic ability to break C−H bonds.

In summary, Rachel Getman-Jiazhou Zhu study presented the successful utilization of a combination of density functional theory calculations and microkinetic modeling to study reactions of n-butane over sterically constrained metal (111) surfaces, for the purpose of identifying catalyst characteristics that lead to the active and selective production of 1-butanol. In general, the two researchers observed that there exists a very small window where it is possible to achieve high selectivity and activity for 1-butanol, which very finely balances catalytic affinity for C* and OH*. Altogether, their findings on catalytic descriptors, reaction mechanisms, optimal operating conditions and relative surface coverages have potential to be widely useful in the quest to design active and selective catalysts for alkane oxidation to alcohols. “Designing a catalytic process to selectively produce desired products from specified reactants requires a pretty deep understanding of molecular-level thermodynamic and kinetic behaviors. Molecular simulations can help to provide this understanding and also identify catalyst properties and reaction conditions that will lead to optimized performance.” Said Professor Rachel Getman.