Metallic phase–free Zn-Al mixed oxide dual function materials enable high CO selectivity in reactive carbon capture from dilute CO2 streams
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Engineering topics
Publications and source records attributed to Ruddy, Daniel A. (ORCID:0000000326543778).
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Active site occlusion by carbon species, often referred to as coke, is a common deactivation mechanism for heterogeneous catalysts. While it is known that transition metals can lower the temperature required for oxidative coke removal, the roles of ionic species and metal nanoparticles in coke removal are not well understood. This work aims to differentiate how ionic and nanoparticle Cu sites catalyze oxidative regeneration of a coked beta (BEA) zeolite catalyst. This was accomplished by synthesizing catalysts containing exclusively CuOx nanoparticles (NPs) or Cu2+ ions supported on BEA, physically mixing Cu/BEA with a coked BEA catalyst, and monitoring coke removal using in situ spectroscopy. Our results point to an improved combustion activity for CuOx NPs relative to Cu2+ ions, especially in the combustion of graphitic-type coke species. This improved understanding of coke combustion in transition metal containing catalysts informs strategies to improve catalyst regeneration, thereby increasing operational lifetimes.
As the world endures environmental crises associated with climate change and the rise of atmospheric CO2 concentrations from anthropogenic CO2 emission, carbon capture and utilization (CCU) technologies are increasingly necessary. Reactive carbon capture (RCC) technologies, in which capture and conversion of CO2 occur in a single reactor, are more energetically and economically attractive by avoiding the need to purify, compress, and transport the captured CO2. To this end, dual function materials (DFMs) - composed of sorbents and catalysts co-dispersed on the same high surface area carrier - have been developed. The sorbent component allows for selective capture of CO2 from a gas stream and the catalyst component subsequently performs the in-situ conversion of the adsorbed CO2 upon introduction of a reactive gas (typically H2). The end product of the most established DFM, comprised of Ru and/or Ni with an alkaline sorbent, is methane via the CO2 methanation reaction. While renewable methane would be an excellent transition fuel, fossil methane is inexpensive (averaging $2.57/MMBTU in pre-pandemic 2019) and the economics of renewable methane utilization are noncompetitive. This requires the design and investigation of DFMs that enable CO2 capture and conversion to more valuable and more useful C1 products like CO or methanol (average price of methanol was $20.61/MMBTU in pre-pandemic 2019). These products can then be further upgraded to high energy density synthetic fuels, and related carbonaceous products, for more sustainable alternatives in industries that are difficult to decarbonize, specifically heavy duty vehicles and aviation. Herein, we report various sorbent + catalyst combinations to achieve the production of useful C1 products through reactive capture of CO2.
Transition metal carbides (TMCs) have attracted significant attention because of their applications toward a wide range of catalytic transformations. However, the practicality of their synthesis is still limited because of the harsh conditions in which most TMCs are prepared. Recently, a solution-phase synthesis of phase-pure a-MoC1-x nanoparticles was presented. While this synthetic route yielded nanoparticles with exceptional catalytic performance, the reaction parameter space was not explored, and catalyst throughput was not optimized for scale-up. Continuous flow platforms coupled with statistical design of experiments (DoE) can provide a powerful method for understanding the reaction parameter space for optimizations. Here, we demonstrate the use of statistical DoE in tandem with response surface methodology for a parametric screening analysis to optimize the throughput of a MoC1-x nanoparticle synthesis utilizing a millifluidic flow reactor. A full factorial design was implemented to evaluate four input variables (reaction temperature, flow rate, solvent fraction of oleylamine, and precursor concentration) that carry statistically significant effects on three responses (throughput, residence time, and isolated yield). A Doehlert matrix was implemented to investigate each significant variable at a higher number of levels to optimize throughput. Our results give a nonintuitive set of experimental conditions that resulted in an optimized throughput of 2.2 g h-1. This translates to a 50-fold increase in throughput compared to the previously reported batch method. The catalytic performance of the MoC1-x nanoparticles produced under optimized throughput was demonstrated in the CO2 hydrogenation reaction. This DoE screening analysis and throughput optimization of MoC1-x synthesis open the door to an increased feasibility for scale-up.