Publications

Passive SCR systems, which employ both a three-way catalyst and SCR catalyst, are effective for the reduction of nitrogen oxide (NOx) emissions from lean burn gasoline engines. However, questions remain regarding the effect of three-way catalyst formulations on their performance in these systems. Here, Pd/CeOx/Al2O3 catalysts with variable CeOx loading were synthesized, characterized, and evaluated to determine the effects of CeOx on catalyst performance. While a small amount of ceria was beneficial for promoting essential reactions, excess ceria was detrimental due to the increase in oxygen storage capacity. Additionally, insights into potential reaction pathways for NH3 production were determined.

Coke formation and catalytic performance under various conditions, such as reaction period, temperature, presence of carrier gas and organic sulfur compounds in the feed, were investigated for JP-8 cracking over HZSM-5 catalysts. The spent HZSM-5 catalysts were characterized by N2 adsorption/desorption, X-ray powder diffraction (XRD), Fourier-transform infrared spectroscope (FT-IR), Temperature programmed oxidation (TPO), and X-ray photoelectron spectroscopy (XPS). A significant loss of surface area and pore volume appeared in the initial period of the cracking reaction, owing to coke formation. Complex, aromatic structured coke formed and deposited on the surface the HZSM-5 catalyst. This resulted in high carbon content, carbon burn-off at higher temperatures, and a change in morphology to less well-defined shapes. As the reaction temperature increased, the aromaticity of the coke species increased, thereby resulting in the coke species having more carbon content and a lower H/C ratio. Furthermore, the absence of a carrier gas gave rise to faster catalyst deactivation and lower LPG yield. Surrogate JP-8 fuel experiments revealed that the aromatic sulfur compounds in the feed do not degrade the catalytic activity by sulfur poisoning, but rather by accelerated coke formation.

High throughput experimentation in heterogeneous catalysis provides an efficient solution to the generation of large datasets under reproducible conditions. Knowledge extraction from these datasets has mostly been performed using statistical methods, targeting the optimization of catalyst formulations. The combination of advanced machine learning methodologies with high-throughput experimentation has enormous potential to accelerate the predictive discovery of novel catalyst formulations that do not exist with current statistical design of experiments. This perspective describes selective examples ranging from statistical design of experiments for catalyst synthesis to genetic algorithms applied to catalyst optimization, and finally random forest machine learning using experimental data for the discovery of novel catalysts. Lastly, this perspective also provides an outlook on advanced machine learning methodologies as applied to experimental data for materials discovery.

Heterogeneously catalyzed deoxydehydration (DODH) ordinarily occurs over relatively costly oxide supported ReOx sites and is an effective process for the removal of vicinal OH groups that are common in biomass-derived chemicals. Here, through first-principles calculations, we investigate the DODH of 1,4-anhydroerythritol over anatase TiO2(101)-supported ReOx and MoOx. The atomistic structures of ReOx and MoOx under typical reaction conditions were identified with constrained thermodynamics calculations as ReO2(2O)/6H–TiO2 and MoO(2O)/3H–TiO2, respectively. The calculated energy profile and developed microkinetic reaction model suggest that both ReO2(2O)/6H–TiO2 and MoO(2O)/3H–TiO2 exhibit a relatively low DODH activity at 413 K. However, at higher temperatures such as 473 K, MoO(2O)/TiO2(101) was found to exhibit a reasonably high catalytic activity similar to ReO2(2O)/6H–TiO2, consistent with a recent experimental study. Mechanistically, the first O–H bond cleavage of 1,4-anhydroerythritol and the dihydrofuran extrusion were found to be the rate-controlling steps for the reaction over ReO2(2O)/6H–TiO2 and MoO(2O)/3H–TiO2, respectively. Thus, this study clarifies the mechanism of the DODH over oxide-supported catalysts and provides meaningful insight into the design of low-cost DODH catalysts.

Fast pyrolysis, in combination with torrefaction pretreatment, was used to convert tobacco residues to value-added bio-fuels and chemicals. Tobacco plant residues were torrefied at 220, 260, and 300 °C, before being pyrolyzed at 450, 500, 550, and 600 °C in a rotating blade ablative reactor under vacuum conditions to test the effects on product yields. With torrefaction, tobacco residues thermally decomposed 20–25% w/w at low temperatures. Torrefaction and pyrolysis temperatures were found to markedly affect pyrolytic product yields of bio-chars and bio-oils, while having no effect on gas-phase products. Bio-oil yields exhibited a direct relation with pyrolysis temperature and an inverse relation with torrefaction temperature. Bio-oils produced were separated into light and heavy oils and analyzed by GC-MS, and 1H and 13C NMR. Nicotine was found to be the main compound in the light and heavy oils along with several phenols and cresols in the heavy oil.

Abstract Heterogeneous catalysts generally have a variety of active-site structures due to the innate heterogeneity of the surface, resulting in complicated correlations between activity and active-site structure. Single site heterogeneous cobalt catalysts with a uniform catalytic surface were utilized as a platform to probe surface sensitive reactions; in this case CO2 hydrogenation. It was found that atomically isolated cobalt single sites, which exist solely in the tetrahedral Co2+ coordination, exclusively form CO under typical CO2 methanation conditions, while cobalt clusters yielded the highest rate of CO2 reaction and began to form methane. Utilizing the principles of Ostwald Ripening to probe the ensemble effects for CO2 hydrogenation, the transition from atomic isolation to small clusters of atoms to nanoparticles was explored. The chemical structure of the cobalt was elucidated primarily via X-Ray Absorption Spectroscopy (XANES/EXAFS) and X-Ray Photoelectron Spectroscopy (XPS).

High throughput experimentation has the capability to generate massive, multidimensional datasets, allowing for the discovery of novel catalytic materials. Here, we show the synthesis and catalytic screening of over 100 unique Ru-Metal-K based bimetallic catalysts for low temperature ammonia decomposition, with a Ru loading between 1–3 wt% Ru and a fixed K loading of 12 wt% K, supported on γ-Al2O3. Bimetallic catalysts containing Sc, Sr, Hf, Y, Mg, Zr, Ta, or Ca in addition to Ru were found to have excellent ammonia decomposition activity when compared to state-of-the-art catalysts in literature. Furthermore, the Ru content could be reduced to 1 wt% Ru, a factor of four decrease, with the addition of Sr, Y, Zr, or Hf, where these secondary metals have not been previously explored for ammonia decomposition. The bimetallic interactions between Ru and the secondary metal, specifically RuSrK and RuFeK, were investigated in detail to elucidate the reaction kinetics and surface properties of both high and low performing catalysts. The RuSrK catalyst had a turnover frequency of 1.78 s−1, while RuFeK had a turnover frequency of only 0.28 s−1 under identical operating conditions. Based on their apparent activation energies and number of surface sites, the RuSrK had a factor of two lower activation energy than the RuFeK, while also possessing an equivalent number of surface sites, which suggests that the Sr promotes ammonia decomposition in the presence of Ru by modifying the active sites of Ru.