(617gh) Kinetic Monte Carlo Simulation of Propylene Epoxidation with Au/TiO2/SiO2 Catalysts

Propylene oxide is currently produced using three different types of commercial processes: (1) chlorohydrin process; (2) propylene oxide â?? styrene monomer (PO-SM) process; and (3) BASF-Dow hydrogen peroxide (HPPO) process. The first two processes pose significant environmental challenges, due to the production of either chlorinated or peroxycarboxylic acid waste. The BASF-Dow process uses hydrogen peroxide as the oxidant and TS-1 (titanium silicalite-1) as the catalyst. This process allows for a selectivity as high as 95%. However, on a molar basis, propylene oxide and hydrogen peroxide have similar market values, and the production of H₂O₂ is associated with environmental risks. Therefore, direct oxidation of propylene by oxygen has received considerable attention. Using supported gold-based nano-catalyst to produce propylene oxide directly from propylene using molecular oxygen as the oxidant provides an alternative, clean, and potentially more efficient route (compared to the current methods). For some time, it has been recognized that Au supported by titanium silicalite (TS-1) zeolite has the ability to catalyze propylene epoxidation. When propylene, oxygen, and hydrogen are co-fed, hydrogen peroxide can be readily formed on the surface of gold, and in turn, selectively oxidizes propylene molecules that are adsorbed on TiO₂ to propylene oxide. Isolated Ti active sites are preferred for high selectivity towards propylene oxide, since propylene oxide molecules that adsorb on adjacent Ti sites lead to catalyst deactivation and the formation of unwanted byproducts. Although the selectivity is very high (>90%), even the best catalysts found to date still suffer from multiple challenges, including low propylene conversion (<10%), poor stability, and inefficient usage of H₂ (<50%). Therefore, significant improvement with regard to these issues is necessary.

We are currently exploring the use of Au-based bimetallic catalysts on oxide supports for direct propylene epoxidation (with H₂ and O₂) in order to achieve higher conversion, while maintaining selectivity. In order to do this, we are pursuing a combined computational and experimental investigation to clearly understand the structure/performance relationships of the catalyst material. The will allow us to identify the kinetically important steps in the propylene oxide formation mechanism, and consequently, the key step(s) involved in controlling product selectivity, stability, and overall activity.

Based on our on-going experimental work, a comprehensive atomistic model has been developed to quantify the underlying mechanisms which dictate the observed performance characteristics. The model is based on the kinetic Monte Carlo (KMC) simulation technique, which is well-grounded in the energetic and kinetic parameters extracted from DFT calculations. However, the kinetic rate parameters governing the steps in the reaction mechanism differ by several orders-of-magnitude, leading to stiffness in the traditional stochastic KMC approach. Thus, a multi-scale KMC technique is implemented, which is based on a quasi-steady state assumption of the fast system events. This allows rapid system propagation through time, and we are able to reach experimental time scales (while atomistic resolution is still preserved). Thus, we are able to make direction connections between the catalyst details (metal nanoparticle size, catalyst loading, etc.) and operating variables (temperature, partial pressure of gasses, etc.) and the resulting turnover frequency (TOF) of the catalyst for propylene epoxidation.