Publications

The CuxRh_3–x(BTC)₂ catalyst (abbreviated CuRhBTC, BTC^3– = benzene tricarboxylate) provides excellent dispersion of active metal sites coupled with well-defined, robust structures for propylene hydrogenation reactions. This material therefore serves as a unique prototype for understanding catalytic activity in metal organic frameworks (MOFs). The mechanism of gas-phase hydrogenation at the bimetallic metal nodes of a MOF has been investigated in detail for the first time using in situ spectroscopy and diffraction experiments combined with density functional theory (DFT) calculations. The reaction occurs via a cooperative process in which the metal and linker sites play complementary roles; specifically, H₂ is dissociated at a Rh²⁺ site with a missing Rh–O bond, while protonation of the decoordinated carboxylate linker stabilizes the active sites and promotes H2 dissociation. In situ X-ray diffraction experiments show that the crystalline structure of the MOF is retained under reaction conditions at 20–100 °C. In situ Raman spectroscopy and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) experiments demonstrate that propylene adsorbs at both Rh²⁺ and Cu²⁺ sites via π bonding. Cu²⁺ is catalytically inactive, but at Rh²⁺ sites, a propyl intermediate is observed when H2 is introduced into the propylene feed. Furthermore, the appearance of the O–H stretch of COOH at ∼3690 cm^–1 in the DRIFT spectra is characteristic of defects consisting of missing Rh–O bonds. These experimental results are in general agreement with a reaction mechanism proposed by DFT, in which the decoordinated carboxylate linker is protonated, and the active Rh²⁺ site remains available for readsorption of reactants in the subsequent catalytic cycle.

In this review, we highlight how design of experiments and machine learning can be utilized in catalysis to help optimize reaction conditions, catalysts, and predict new catalyst formulations. An overview of how the techniques work is presented, and the advantages and disadvantages of the techniques are discussed. We showcase the ability to extract meaningful knowledge utilizing small experimental data sets and the recent advancements in the use of machine learning in catalysis. We conclude the review by presenting a potential method to combine the benefits of both machine learning and design of experiments to help accelerate catalyst discovery and optimization.

Torrefaction is a treatment process for converting biomass to high-quality solid fuels. The investigation and interpretation of this process on highly dimensional, non-linear relationships as large datasets are limited. In this work, machine learning (ML) in combination with collaborative game theory (Shapley additive explanation, SHAP) was applied to develop an interpretable model in predicting solid yields (SY) and higher heating values (HHV) of solid products from biomass torrefaction using 18 independent input features from operating conditions, feedstock characteristics and torrefaction reactor properties. Three novel ML algorithms were evaluated, based on 10-fold cross-validation, with 5 different sets of input features. A gradient tree boosting (GTB) model was found to have the highest prediction accuracy R² of 0.93 with root mean square error (RMSE) of 0.06 for SY while about 0.91 R² with 0.79 RMSE for HHV. With the powerful SHAP algorithm, a new framework was proposed to interpret/explain the GTB model performance and highlight the highly influential features for the system of biomass torrefaction in both local and global points of view. Interactions for any pair of the features on the GTB model can be achieved. This application of ML with SHAP is a useful tool for researchers on biomass conversion.

Selective removal of oxygen from biomass-derived polyols is critical toward bridging the gap between biomass feedstocks and the production of commodity chemicals. In this work, we show that earth-abundant molybdenum oxide based heterogeneous catalysts are active, selective, and stable for the cleavage of vicinal C–O bonds in biomass-derived polyols. Catalyst characterization (Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS)) shows that partially reduced MoO_x centers are responsible for C–O bond cleavage and are generated in situ by hydrogen dissociated atoms over palladium (Pd) nanoparticles. We find that the support, TiO₂, facilitates communication between the hydrogen dissociating metal and dispersed MoO_x sites through hydrogen spillover. Reactivity studies using a biomass-derived model substrate (1,4-anhydroerythritol) show the effective removal of vicinal hydroxyls over MoO_x-Pd/TiO₂ producing tetrahydrofuran with >98% selectivity at 29% conversion. Catalyst stability is demonstrated upon cycling. These studies are critical toward the development of low-cost heterogeneous catalysts for sustainable hydrodeoxygenation of biobased polyols to platform chemicals.

The efficient delivery of reactive and toxic gaseous reagents to organic reactions was studied using metal-organic frameworks (MOFs). The simultaneous cargo vehicle and catalytic capabilities of several MOFs were probed for the first time using the examples of aromatization, aminocarbonylation, and carbonylative Suzuki–Miyaura coupling reactions. These reactions highlight that MOFs can serve a dual role as a gas cargo vehicle and a catalyst, leading to product formation with yields similar to reactions employing pure gases. Furthermore, the MOFs can be recycled without sacrificing product yield, while simultaneously maintaining crystallinity. The reported findings were supported crystallographically and spectroscopically (e.g., diffuse reflectance infrared Fourier transform spectroscopy), foreshadowing a pathway for the development of multifunctional MOF-based reagent-catalyst cargo vessels for reactive gas reagents as an attractive alternative to the use of toxic pure gases or gas generators.

Hydrothermal synthesis of ZSM-5 zeolites with different Si/Al ratios was conducted by using a microwave-assisted heating method. Their characteristics, such as morphology, porosity, acidity, and the catalytic performance for the cracking reaction of military jet fuel JP-8, were compared with ZSM-5 zeolites obtained via a conventional heating synthesis method. The microwave-assisted heating method contributed to bigger crystal sizes of the ZSM-5 zeolite as well as broader mesopore size distribution in the zeolite crystal with the same Si/Al ratio. Acidity analysis revealed ZSM-5 zeolites with similar acid properties could be produced with both heating methods. As the different heating methods attributed to different crystal sizes and roughness of the synthesized ZSM-5 zeolite, which are influenced by the fast crystal growth and consumption of silicon and aluminum precursor during the hydrothermal synthesis, different petroleum gas yields, and paraffinic product selectivity were observed from the ZSM-5 zeolite produced via microwave-assisted heating method.

Commercial aircraft fuel tanks require sealants applied at contact points to prevent leakage or moisture contamination, but cure times for conventional sealants range from hours to days. Thiol-ene ultraviolet (UV) curable sealants have been a proposed material for these applications. However, selecting proper monomers and optimizing synthesis conditions for a figure of merit is an arduous process. Therefore, modeling the adhesive strength of a thiol-ene sealant was performed using a response surface design of experiment (DoE). Two separate crosslinking alkenes were separately combined with a thiol monomer, and a 6 mm thick polymer was synthesized at different cure temperatures, cure times, and with various solid filler material on an aluminum substrate according to a response surface design. The samples were then peeled off the substrate at a 180° angle, and peel strength was measured. The DoE utilized the peel data to derive a multivariable numeric function for the peel strength. Resulting contour data shows the system has not been fully optimized, but trends in the data show that future experiments should lean toward higher cure times and temperatures to maximize peel strength. Additionally, the resulting model equation can predict adhesive strengths near the studied conditions.

The effect of the addition of a Cu/Al₂O₃ catalyst on the product distribution of gas-phase products during torrefaction of pelletized corn residues was investigated at temperatures between 220 and 300 °C. Pelletized corn residues were mechanically mixed with Cu/Al₂O₃ catalyst pellets. The mixture was then thermally treated in a fixed bed reactor for 40 min of residence time at low temperatures of wet flue gas simulated by O₂ (4% v/v), CO₂ (12% v/v), and steam (14% v/v), balanced with N₂. The higher heating value (HHV) of torrefied pellets was also examined within the operating conditions. It was found that torrefaction temperature affected the product distribution, yields, and HHV significantly, while the presence of Cu/Al₂O₃ catalyst pellets promoted the conversion of CO to CO₂ and the production of H₂ from raw biomass pellets via CO oxidation and water-gas shift reactions. This finding provides a favorable outlook for the energy utilization of pelletized agro-residues via torrefaction with wet flue gas as a pretreatment method, in which inexpensive catalysts could be applied to eliminate toxic gases and/or generate valuable hydrogen during the torrefaction process.

The relevance of multidimensional and porous crystalline materials to nuclear waste reme-diation and storage applications has motivated exploratory research focused on materials discovery of compounds, such as actinide mixed-oxoanion phases, which exhibit rich structural chemistry. The novel phase K1.8 Na1.2 [(UO2)BSi4 O12 ] has been synthesized using hydrothermal methods, rep-resenting the first example of a uranyl borosilicate. The three-dimensional structure crystallizes in the orthorhombic space group Cmce with lattice parameters a = 15.5471(19) \AA, b = 14.3403(17) \AA, c = 11.7315(15) \AA, and V = 2615.5(6) \AA3, and is composed of UO6 octahedra linked by [BSi4 O12 ]5− chains to form a [(UO2)BSi4 O12 ]3− framework. The synthesis method, structure, results of Raman, IR, and X-ray absorption spectroscopy, and thermal stability are discussed.