In-situ Characterization of Metal/Oxide Catalysts for CO2 Conversion: From Fundamental Aspects to Real Catalysts Design
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36 MATERIALS SCIENCE↗
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Innovative Catalyst Design for the Direct Hydrogenation of CO2 to Methanol
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10 SYNTHETIC FUELS↗
Designing Perovskite Catalysts for Controlled Active Site Exsolution in the Microwave Dry Reforming of Methane
ACS Spring Meeting 2021, Virtual, April 5-16, 2021
Marin, Christopher↗
Metal–Organic Framework Nodes as a Supporting Platform for Tailoring the Activity of Metal Catalysts
Catalysis is a ubiquitous element of the modern economy, representing a cornerstone of many sectors including energy, materials, and pharmaceuticals. Within this realm, 80% of reactions are carried out by heterogeneous catalysts due to their advantageous physical and chemical characteristics. In some heterogeneous systems, the reaction rate can be optimized through rational catalyst design, in which support materials can be tailored structurally and stereoelectronically for targeted purposes to better facilitate the catalytic reaction. To this end, metal-organic frameworks (MOFs) have garnered recent attention due to their high porosity, crystallinity, and chemical tunability, which can be used to derive structure-activity relationships in the design of catalysts. In this Perspective, we survey examples of catalytically active guest metals on the inorganic nodes of MOFs. This is done with the intention of providing design guidelines for tailoring chemical reactivity and insights into the opportunities for future growth in this field. Strategies for rational design in MOF catalysis include electronic tuning of the metal node in the MOF support, installing promoter ions onto the node to effect the reactivity of grafted metals, modulation of the spatial environment around the transition metal using the metal node structure, and achieving site uniformity in supported catalysts. By highlighting these efforts, we seek to underscore the role of MOF nodes as nonspectator supports for catalytic metal complexes and provide future directions for rational catalyst design by tuning reactivity on these anchoring platforms.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Unifying principles for catalytic hydrotreating processes (Final Technical Report)
This project builds on the hypothesis that the hydrotreating processes for the removal of oxygen and sulfur are fundamentally similar at the atomic-scale and existing knowledge from the treatment of petroleum derived feedstock can be leveraged for the design of novel catalysts for the upgrade of bio-oil. We tested this hypothesis by comparing computed potential energy diagrams for hydrodesulfurization (HDS) of thiophene over MoS 2 with hydrodeoxygenation (HDO) of furan over MoO 3 and concluded that certain aspects, such as catalyst promotion with transition metals, are valid strategies for both reactions. On the other hand, we also noticed significant differences in the mechanism for hydrogen (H 2 ) activation, which requires sites with metallic character. While MoS 2 is known to have metallic edge states that can catalyze H 2 dissociation, this elementary step is prohibitively slow on defect-free oxides. Only in the presence of vacancies or by creating metal/oxide interfaces can efficient H 2 activation sites during HDO be formed. The need for bifunctional catalyst when it comes to efficient and selective HDO or dehydrogenation reactions was further corroborated in joint experimental and theoretical studies of the Guerbet reaction for the coupling of biomass derived oxygenates over PdCu alloys, nitrate reduction over In-promoted Pd nanoparticles, and ethylene dehydroaromatization over Ga-exchanged ZSM-5 zeolites. All of these catalytic systems have in common that catalytic sites with distinct functional requirements are needed to create a working catalyst. Detailed computational studies were carried out for HDO of m -cresol and phenol on Ru-modified TiO 2 surfaces, which allowed us to attribute catalytic activity to the metal/oxide interface. A surprising finding was that heterolytic cleavage of the H-H bond across the Ru/TiO 2 interface was critically important, despite lower barriers for homolytic H 2 activation on Ru metal. The explanation lies in the high barriers for hydrogen spillover from Ru to TiO 2 , which becomes unnecessary in the heterolytic activation pathway. Moreover, we also reported that proton transfer steps between metal and oxide sites are mediated by weakly adsorbed surface water. During attempts to develop and validate a kinetic Monte Carlo (kMC) model for HDO reactions at the Ru/TiO 2 interface, it became clear that lateral interactions are paramount to describe realistic surface chemistry and without these interactions, the reduction and hydroxylation behavior from our simulations was inconsistent with reported experiments. To assess the importance of lateral interactions in popular computational catalyst design strategies relying on the identification of reactivity descriptors, which can be used along with Brønsted–Evans–Polanyi (BEP) and scaling relations as input to a microkinetic model (MKM) to make predictions for activity or selectivity trends, we compared predicted trends with those obtained from descriptor-based kMC models. We critically evaluated the benefits of kMC over MKM in terms of trend predictions and computational cost when using only a small set of input parameters. After confirming that in the absence of lateral interactions the kMC and MKM approaches yield identical trends and mechanistic information, we observed substantial differences between the two kinetic models when lateral interactions were introduced. The mean-field implementation applies coverage corrections directly to the descriptors, causing an artificial overprediction of the activity of strongly binding metals. In contrast, the cluster expansion in kMC implementation can differentiate among the highly active metals but it is very sensitive to the set of included interaction parameters. Considering that computational screening relies on a minimal set of descriptors, for which MKM makes reasonable trend predictions at a ca. three orders of magnitude lower computational cost than kMC, we concluded that the MKM approach does provide an overall better entry point for computational catalyst design. Overall, this project has led to 11 peer-reviewed publications, and their scientific is impact is well illustrated by their combined 702 citations.
08 HYDROGEN↗
Rational design of high-performance low-loading oxygen reduction catalysts for alkaline fuel cells
The lack of mechanistic understanding and catalyst design principles for alkaline electrolytes, especially for the sluggish oxygen reduction reaction, has impeded the advancement of alkaline fuel cells. Here, in this study, we propose a modified volcano plot and apply this rationale to strategically design Pt nanosheets with PdH x nanosheets substrates. This catalyst exhibited high stability with a specific activity of 1.71 mA cm −2 at 0.95 V versus the reversible hydrogen electrode, surpassing the benchmark of Pt/C by 49-fold. Spectroscopic, electrochemical and electron microscopic characterizations revealed that such performance enhancement originated from tensile-strained Pt{111} facets, improving oxidative stability and suppressing carbon corrosion. In fuel cell testing, the catalyst enabled a peak power density of 1.67 W cm −2 with a loading of 10 µg PGM Cathode cm −2 . Further optimization delivered a peak power density of 21.7 W mg −1 PGM Cathode+Anode with a total specific catalyst cost US$\$$1.27 kW −1 , surpassing the US Department of Energy’s Pt group metal loading and cost targets. This study provides valuable insights into catalyst design for the alkaline oxygen reduction reaction.
36 MATERIALS SCIENCE↗
Resonance-Promoted Formic Acid Oxidation via Dynamic Electrocatalytic Modulation
It is a truth universally acknowledged that faster catalysts enable more efficient transformation of molecules to useful products and enhance the utilization of natural resources. However, the limit of static catalyst performance defined by the Sabatier principle has motivated a dynamic approach to catalyst design, whereby catalysts oscillate between varying energetic states. In this work, the concept of dynamic catalytic resonance was experimentally demonstrated via the electrocatalytic oxidation of formic acid over Pt. Oscillation of the electrodynamic potential between 0 and 0.8 V NHE via a square waveform at varying frequency (10 –3 < f < 10 3 Hz) increased the turnover frequency to ~20 s –1 at 100 Hz, over one order of magnitude (20×) faster than optimal potentiostatic conditions. We attribute the accelerated dynamic catalysis to nonfaradaic formic acid dehydration to surface-bound carbon monoxide at low potentials, followed by surface oxidation and desorption to carbon dioxide at high potentials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces
Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.
Adsorption↗
Reacting CO 2 with Light Alkanes to Value-Added Products
Catalytic conversion of anthropogenic carbon dioxide (CO 2 ) into value-added products is a promising strategy to mitigate global carbon emissions. Concurrently, the shale gas revolution has provided an abundant supply of light alkanes (methane, ethane, propane, and butane), presenting a unique opportunity to employ these underutilized hydrocarbons as an effective, low-cost hydrogen source for CO 2 reduction. In this Perspective, we summarize past efforts, current state, and future opportunities for reacting CO 2 with light alkanes to generate a diverse range of value-added products. Compared with direct alkane conversion, the introduction of CO 2 fundamentally alters reaction thermodynamics and kinetics, enabling selective C–H and C–C bond activation while suppressing catalyst deactivation from coke formation. Building on decades of research in dry reforming and CO 2 -assisted dehydrogenation, recent advances in catalyst design have enabled CO 2 -assisted dehydrogenation processes that approach chemical equilibrium for the selective production of olefins and syngas. Importantly, advances in catalyst design and reactor engineering have further expanded the product scope beyond gas-phase (syngas and olefins) to include liquid-phase (oxygenates and aromatics), and solid-phase products (carbon nanomaterials). We highlight key catalyst design principles for controlling reaction pathways and discuss major challenges and opportunities in developing selective and versatile platforms for the simultaneous upgrading of CO 2 and light alkanes.
CO2↗
Data Science Meets Physical Organic Chemistry
At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Mechanistic Insights and Rational Design of Ca-Doped CeO 2 Catalyst for Acetic Acid Ketonization
Carboxylic acid ketonization has recently gained significant attention to produce biomass-derived hydrocarbon fuels as it not only removes the highly reactive carboxylic functional group but also increases the size of the carbon chain. In this work, Ca-doped CeO 2 -based catalysts were investigated for acetic acid ketonization using a combined experimental and computational approach. Acetic acid conversion was performed across a range of temperatures including higher temperatures relevant to catalytic hot gas filtration (450 °C). Ca addition slightly decreases overall acetic acid ketonization reactivity yet stabilizes the catalyst at the higher temperatures necessary for catalytic hot gas filtration. From density functional theory calculations of the ketonization reaction mechanism, the C–C coupling and water formation steps are identified as two of the most energy-consuming steps on a CeO 2 surface with a proximal oxygen vacancy and the presence of a Ca dopant stabilizes the key intermediates. Calculations predict an optimal structure comprising three Ca ensembles to minimize the reaction free energies for C–C coupling and water formation steps. These findings provide a priori information to guide future experiments for ketonization catalyst design and development.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The Development of Catalysts for Upgrading of Pyrolysis Vapor for Refinery Feedstocks and Intermediates: Cooperative Research and Development, CRADA Number CRD-12-00497 (Final Report)
Fast pyrolysis of biomass with vapor phase upgrading (VPU) can produce refinery feedstocks or intermediates that can meet the Department of Energy’s goal of cost-competitive hydrocarbon fuels by 2017. A key technical barrier for this technology is the lack of selective, cost effective catalysts that can produce high yields of fuel-appropriate hydrocarbons from the pyrolysis vapors. In overcoming this barrier, it will be important to engage leading catalyst development companies to devote their resources and expertise to the development of these materials. Thus, we propose a Cooperative Research and Development Agreement (CRADA) between the National Renewable Energy Laboratory (NREL), a world leader in biomass pyrolysis research and Johnson Matthey (JM), a world leader in the production of advanced catalyst materials to develop and test novel catalysts for efficient VPU. Through its Intercat Inc. subsidiary in Savannah, Ga., Johnson Matthey is internationally recognized as a leader in zeolite-based vapor phase upgrading in refinery duties and an emerging developer of biomass conversion technologies. The research and development efforts described in the proposed work will build upon existing collaborations between NREL and JM and play to the strengths of both institutions. NREL will analyze the composition of pyrolysis vapors as an input to catalyst design, screen and test catalysts, characterize the resulting oil and conduct techno-economic analysis. Catalyst samples will be produced and funded by JM. JM will design and synthesize catalysts, characterize fresh and used catalysts and develop catalyst supports needed to achieve commercially meaningful lifetimes. The project will span catalyst development and testing from the fundamental stage using quantum mechanical modeling and chemical reaction analysis to catalyst screening to integrated pilot studies.
09 BIOMASS FUELS↗
Generalized Brønsted‐Evans‐Polanyi Relationships for Reactions on Metal Surfaces from Machine Learning
Abstract Brønsted‐Evans‐Polanyi (BEP) relationships, i. e., a linear scaling between reaction and activation energies, lie at the core of computational design of heterogeneous catalysts. However, BEPs are not general and often require reparameterization for each class of reactions. Here we construct generalized BEPs (gBEPs), which can predict activation energies for a diverse dataset of reactions of C, O, N and H containing molecules on metal surfaces. In a first step we develop a set of descriptors based on scaling relationships that can capture the change in chemical identity of reactants during the reaction. Subsequently, we use the reaction energy, these descriptors and a single descriptor for the surface structure to parameterize machine learning based regression approaches for the prediction of activation energies. The best approach we developed shows a Mean Absolute Error (MAE) of 0.11 eV for the training set (80 % of the data set) and 0.23 eV for the test set (20 % of the data set). The methodology presented here allows to calculate activation energies within fractions of seconds on a typical personal computer and due to its generality, accuracy and simplicity in application it might prove to be useful in transition metal catalyst design.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Understanding and tuning organocatalysts for versatile condensation polymer deconstruction
Plastics are widely used for their durability and versatility, but recycling remains a major challenge, especially for mixed or contaminated waste. Mechanical recycling works well for clean, single-polymer streams like PET but has limited efficiency for complex waste streams. Chemical recycling, particularly glycolysis, is often employed to selectively deconstruct condensation polymers under mild conditions. This study explores catalyst design for glycolysis using linear free energy (Hammett) analysis to evaluate how catalyst structure influences polymer deconstruction. Polycaprolactone (PCL) is used as a model polyester due to its solubility and low deconstruction temperature. Triazabicyclodecene (TBD) paired with benzoic acid derivatives depicts a clear linear trend in depolymerization rates with Hammett values. TBD with p-aminobenzoic acid (PABA) stands out for its catalytic efficiency, thermal stability, and scalability, along with PABA's commercial availability as vitamin B-10. The TBD : PABA catalyst not only effectively breaks down PCL but also enables sequential deconstruction of polycarbonate, PET, and Nylon in mixed waste streams. These results highlight the value of Hammett-guided catalyst design and establish TBD : PABA as a promising, scalable organocatalyst for mixed plastic recycling, enabling recovery of individual polymer building blocks from blended waste and offering a practical route toward circular plastics.
Zheng, Jackie [Univ. of Tennessee, Knoxville, TN (↗
Electrocatalysts Development for Hydrogen Oxidation Reaction in Alkaline Media: from Mechanism Understanding to Materials Design
Anion exchange member (AEM) fuel cells have gained great attention recently mainly owing to the advantages of non-precious metal catalysts application. Despite of the similar oxygen reduction reaction (ORR) kinetics in acid and base, the reaction kinetics of hydrogen oxidation reaction (HOR) is two orders of magnitude slower in alkaline systems than in acid. To understand the slower kinetics of HOR in base, two major interpretations have been proposed, including 1) hydrogen binding energy as a major descriptor for HOR in both acid and base; and 2) bifunctional theory based on the contributions from both hydrogen and hydroxide adsorption for HOR in alkaline electrolyte. Here, we discuss the possible HOR mechanisms in alkaline electrolytes with the corresponding Tafel behavior change. Besides the discussion of traditional Tafel-Volmer and Heyrovsky-Volmer HOR mechanisms, the recently proposed hydroxide adsorption step is discussed to illustrate the HOR mechanism difference in acid and base. We further correlate the hydroxide adsorption step involved mechanism with HOR catalyst design, and summarize its role in HOR and HER activities improvement in alkaline electrolyte over the same catalyst. The representative works of alkaline HOR catalyst development were briefly introduced, and the strategy of strengthening interaction between H2 desorption and H2O recombination was finally proposed for future HOR catalyst design in alkaline environment.
Hydrogen oxidation reaction, Hydrogen evolution re↗
Oxidative Dehydrogenation of Propane to Propylene with Soft Oxidants via Heterogeneous Catalysis
Oxidative dehydrogenation of propane to propylene can be achieved using conventional, oxygen-assisted dehydrogenation of propane (O 2 –ODHP) or via the use of soft oxidants, such as CO 2 , N 2 O, S-containing compounds, and halogens/halides. The major roles of soft oxidants include inhibiting overoxidation and improving propylene selectivity, which are considered to be current challenges in O 2 -assisted dehydrogenation. For both CO 2 – and N 2 O–ODHP reactions, significant efforts have been devoted to developing redox-active (e.g., chromium, vanadate, iron, etc.), nonredox-type main group metal oxide (e.g., group IIIA, gallium), and other transition metal/metal oxide catalysts (e.g., molybdenum, palladium platinum, rhodium, ruthenium, etc.), as well as zeolite-based catalysts with adjustable acid–base properties, unique pore structures, and topologies. Metal sulfides have shown promising performance in DHP, whereas the development of suitable catalysts has lagged for SO 2 - or S-assisted ODHP. Recently, significant efforts have been focused on homogeneous and heterogeneous ODHP using halogens (e.g., Br 2 , I 2 , Cl 2 , etc.) and hydrogen halides (e.g., HCl and HBr) for the development of facile processes for C 3 H 6 synthesis. This work aims to provide a critical, comprehensive review of recent advances in oxidative dehydrogenation of propane with these soft oxidants, especially highlighting the current state of understanding of the following factors: (i) relationships between composition, structure, and catalytic performance, (ii) effects of the support, acidity, and promoters, (iii) reaction pathway and mechanistic insights, and (iv) the various roles of soft oxidants. Theoretical and computational insights toward understanding reaction mechanisms and catalyst design principles are also covered. Future research opportunities are discussed in terms of catalyst design and synthesis, deactivation and regeneration, reaction mechanisms, and alternative approaches.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Recent Advancements in Catalytic Fast Pyrolysis for the Production of Fuels and Chemicals from Biomass
Catalytic fast pyrolysis (CFP) is a promising biorefinery technology platform for generating both fuel blendstocks and chemical co-products. The versatility of this platform is afforded by (1) the coupling of a thermochemical deconstruction step to a catalytic step that enables tuning of the product slate and (2) the diversity of accessible products across gaseous, liquid, and solid streams. However, there are a number of challenges impeding commercial viability for this CFP platform, including high process costs caused by low carbon efficiency to bio-oil due to coking and light gas formation, the quality and properties of the bio-oil dictate processability for downstream operations, and the heterogeneity of the bio-oil limits quality of resulting fuel blendstocks. This presentation will discuss our efforts to address these challenges through a combined experimental-computational approach to catalyst design and process development, with a specific focus on (1) modifying product composition through catalyst design and (2) generating olefinic and oxygenated chemical co-products.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Supported Oxygen Evolution Catalysts by Design: Toward Lower Precious Metal Loading and Improved Conductivity in Proton Exchange Membrane Water Electrolyzers
Reducing the precious metal content of water oxidation catalysts for proton-exchange-membrane water electrolyzers remains a critical barrier to their large-scale deployment. Herein, we present an engineered architecture for supported iridium catalysts, which enables decreased precious metal content and improved activity and conductivity. The improvement in performance at lower precious metal loading is realized by the deposition of a conformal layer of platinum nanoparticles on titanium dioxide (TiO 2 ) using a facile photoreduction method to prepare conductive layer coated supports (CCSs). Platinum nanoparticles are homogeneously dispersed on TiO 2 , and the conductivity of the subsequent catalysts with 39 wt % precious group metal loadings is significantly higher than the commercial 75 wt % loaded IrO 2 -TiO 2 catalysts. The conformal conductive layer also maintains an enhanced conductivity and electrochemical activity upon thermal annealing when compared to catalysts without the conductive layer and nonconformal heterogeneous conductive layer. The iridium mass activity from half-cell studies shows a 141% improvement for CCS supported catalysts at 42% lower loadings compared to the commercial catalysts. The conductive layer also improves the single cell electrolyzer performance at a similar catalyst loading in comparison to a commercial state-of-the-art catalyst. Here, we correlate the physical properties of the engineered catalysts with their electrochemical performance in electrolyzers to understand structure-activity relationships, and we anticipate further performance improvements upon synthesis and materials optimizations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗