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Polyoxometalates (POMs) featuring 7, 12, 18, or more, redox-accessible transition-metal ions are ubiquitous as selective catalysts, electrocatalysts, and sensitized photocatalysts, especially for oxidation reactions. The corresponding synthetic and catalytic chemistry of stable, discrete, and capping-ligand-free polythiometalates (PTMs), which could be especially attractive for reduction reactions, is much less well developed. Among the challenges is the propensity of PTMs to agglomerate and form larger clusters of indeterminate size, as well as the tendency for agglomeration to block access of candidate reactants to potential catalyst active-sites. Nevertheless, the pervasive presence of transition-metal sulfur clusters metalloenzymes or cofactors that catalyze reduction reactions, and the justifiable proliferation of studies of 2D metalchalcogenides, and especially their edge sites, as reduction catalysts, point to the promise of well-defined and controllable PTMs as catalysts for reduction reactions, including complex, bond-forming, many-electron reactions. Here we report the fabrication of agglomeration-immune, reactant-accessible, capping-ligand-free CoIIMoIV6S24n- clusters as periodic arrays in a water-stable, hierarchically porous Zr-metal-organic-framework (MOF; NU1K) by first preparing and installing a disk-like Anderson polyoxometalate, CoIIMoVI6O24m(-), in size-matched (

Well-defined RhMo6O24n− clusters were encapsulated within a hierarchically porous MOF NU-1K and tested for an illustrative gas-phase CO oxidation reaction.

Manganese substitution induces crystallite shrinkage and loss of saturation magnetization for the manganese ferrite nanoparticles synthesized by thermal decomposition.

Dehydrogenation is the first reaction of the aqueous phase reforming (APR) mechanism of polyols, and its rate is likely affected by the environment at the active site. This study focuses on reactions of methanol on benchmark Pt/γ-Al2O3 catalysts probed by infrared spectroscopy under high vacuum. CO in linear and bridging coordination are the dominant surface species on metal sites. Pt particle sizes and reaction temperatures are varied to identify the kinetically preferred active site for methanol dehydrogenation as either lowly coordinated (edges, corners, interface) or highly coordinated (terraces) metal atoms. Interpretation of temperature-dependent IR spectra up to 450 °C show that larger Pt particles produce more CO at lower temperatures from complete methanol dehydrogenation. Similarly, time-resolved isothermal experiments at 150 °C showed equilibrium conversion occurred much faster on larger Pt particles than smaller ones. Features of evolving ν(C≡O) bands (shape, vibrational frequencies, integrals) suggest that, even on small Pt particles, CO first forms on the scarcely available terraces, or possibly in the form of islands. We have thus experimentally identified highly coordinated Pt metal as the more active site in overall methanol dehydrogenation. The electronic and chemical effects of co-adsorbed water and hydrogen on dehydrogenation activity and the CO spectra are discussed. The co-adsorption of water, an abundant APR component needed for the water-gas shift reaction, does not appear to affect methanol dehydrogenation on large Pt particles but hinders the reaction on small Pt particles as evident by limited growth in the respective ν(C≡O) bands.

Conversion of oxygenates derived from biomass is a promising strategy for production of fuels and chemicals. The needed H2 can be supplied simultaneously (and sustainably) via aqueous phase reformi...

Adsorption is an important step in heterogeneous catalysis, as it predetermines how many reactant molecules can participate in a surface reaction per unit time. While the rate of adsorption process...

The mechanism of ethene hydrogenation to ethane on six dicationic 3d transition metal catalysts is investigated. Specifically, a combination of density functional theory (DFT), microkinetic modeling, and high throughput reactor experiments is used to interrogate the active sites and mechanisms for Mn@NU-1000, Fe@NU-1000, Co@NU-1000, Ni@NU-1000, Cu@NU-1000, and Zn@NU-1000 catalysts, where NU-1000 is a metal–organic framework (MOF) capable of supporting metal cation catalysts. The combination of experiments and simulations suggests that the reaction mechanism is influenced by the electron configuration and spin state of the metal cations as well as the amount of hydrogen that is adsorbed. Specifically, Ni@NU-1000, Cu@NU-1000, and Zn@NU-1000, which have more electrons in their d shells and operate in lower spin states, utilize a metal hydride active site and follow a mechanism where the metal cation binds with one or more species at all steps, whereas Mn@NU-1000, Fe@NU-1000, and Co@NU-1000, which have fewer electrons in their d shells and operate in higher spin states, utilize a bare metal cation active site and follow a mechanism where the number of species that bind to the metal cation is minimized. Instead of binding with the metal cation, catalytic species bind with oxo ligands from the NU-1000 support, as this enables more facile H2 adsorption. The results reveal opportunities for tuning activity and selectivity for hydrogenation on metal cation catalysts by tuning the properties that influence hydrogen content and spin, including the metal cations themselves, the ligands, the binding environments and supports, and/or the gas phase partial pressures.

Nickel-functionalized UiO-66 metal organic frameworks (MOFs) oligomerize ethylene in the absence of cocatalysts or initiators after undergoing ethylene-pressure-dependent transients and maintain stable oligomerization rates for >15 days on stream. Higher ethylene pressures shorten induction periods and engender more active sites for ethylene oligomerization; these sites exhibit invariant selectivity-conversion characteristics to justify that only one type of catalytic center is relevant for oligomerization. The number of active sites is estimated using in situ NO titration to disambiguate the effect of increased reaction rates upon exposure to increasing ethylene pressures. After accounting for augmented site densities with increasing ethylene pressures, ethylene oligomerization is first order in ethylene pressure from 100 to 1800 kPa with an activation energy of 81 kJ mol-1 at temperatures from 443-503 K on Ni/UiO-66. A representative Ni/UiO-66 cluster model that mimics high ethylene pressure process conditions is validated with ab initio thermodynamic analysis, and the Cossee-Arlman mechanism is posited based on comparisons between experimental and computed activation enthalpies from density functional theory calculations on these cluster models of Ni/UiO-66. The insights gained from experiment and theory help rationalize evolution in structure and stability for ethylene oligomerization Ni/UiO-66 MOF catalysts.

The energetics, coordination, and Raman vibrations of Li solvates in ionic liquid (IL) electrolytes are studied with density functional theory (DFT). Li+ coordination with asymmetric anions of cyano(trifluoromethanesulfonyl)imide ([CTFSI]) and (fluorosulfonyl)(trifluoro-methanesulfonyl)imide ([FTFSI]) is examined in contrast to their symmetric analogs of bis(trifluoromethanesulfonyl)imide ([TFSI]), bis(fluorosulfonyl)imide ([FSI]), and dicyanamide ([DCA]). The dissociation energies that can be used to describe the solvation strength of Li+ are calculated on the basis of the energetics of the individual components and the Li solvate. The calculated dissociation energies are found to be similar for Li+-[FTFSI], Li+-[TFSI], and Li+-[FSI] where only Li+-O coordination exists. Increase in asymmetry and anion size by fluorination on one side of the [TFSI] anion does not result in significant differences in the dissociation energies. On the other hand, with [CTFSI], both Li+-O and Li+-N coordination are present, and the Li solvate has smaller dissociation energy than the solvation by [DCA] alone, [TFSI] alone, or a 1:1 mixture of [DCA]/[TFSI] anions. This finding suggests that the Li+ solvation can be weakened by asymmetric anions that promote competing coordination environments through enthalpic effects. Among the possible Li solvates of (Li[CTFSI]n)−(n−1), where n = 1, 2, 3, or 4, (Li[CTFSI]2)−1 is found to be the most stable with both monodentate and bidentate bonding possibilities. Based on this study, we hypothesize that the partial solvation and weakened solvation energetics by asymmetric anions may increase structural heterogeneity and fluctuations in Li solvates in IL electrolytes. These effects may further promote the Li+ hopping transport mechanism in concentrated and multicomponent IL electrolytes that is relevant to Li-ion batteries.

Metal-oxo moieties are important catalytic intermediates in the selective partial oxidation of hydrocarbons and in water splitting. Stable metal-oxo species have reactive properties that vary depending on the spin state of the metal, complicating the development of structure-property relationships. To overcome these challenges, we train machine-learning (ML) models capable of predicting metal-oxo formation energies across a range of first-row metals, oxidation states, and spin states. Using connectivity-only features tailored for inorganic chemistry as inputs to kernel ridge regression or artificial neural network (ANN) ML models, we achieve good mean absolute errors (4-5 kcal/mol) on set-aside test data across a range of ligand orientations. Analysis of feature importance for oxo formation energy prediction reveals the dominance of nonlocal, electronic ligand properties in contrast to other transition metal complex properties (e.g., spin-state or ionization potential). We enumerate the theoretical catalyst space with an ANN, revealing expected trends in oxo formation energetics, such as destabilization of the metal-oxo species with increasing d-filling, as well as exceptions, such as weak correlations with indicators of oxidative stability of the metal in the resting state or unexpected spin-state dependence in reactivity. We carry out uncertainty-aware evolutionary optimization using the ANN to explore a > 37 000 candidate catalyst space. New metal and oxidation state combinations are uncovered and validated with density functional theory (DFT), including counterintuitive oxo formation energies for oxidatively stable complexes. This approach doubles the density of confirmed DFT leads in originally sparsely populated regions of property space, highlighting the potential of ML-model-driven discovery to uncover catalyst design rules and exceptions. Keywords: metal-oxo species; machine learning; density functional theory; spin-state-dependent reactivity; transition metal catalysis

Interfacial systems are ubiquitous and important to myriad processes of interest such as protein-protein interactions and catalysis of reactions. Investigating interfacial systems at the molecular level presents unique challenges to both experiments and molecular simulations. The challenges in molecular simulations of interfacial systems range from scalability of quantum simulations to transferability of empirical force fields in classical simulations. In this article, we focus on the advances in force field development to study interfacial systems using protein-surface interactions and heterogeneous catalysis as case studies. We also discuss the emerging role of machine learning in force field development. We conclude by providing our perspective on accelerating the progress in force field development through concerted efforts for data collection and standardization of parameter fitting protocols for extending the force fields to new interfacial systems.

Water influences catalytic reactions in multiple ways, including energetic and mechanistic effects. While simulations have provided significant insight into the roles that H2O molecules play in aqueous-phase heterogeneous catalysis, questions still remain as to the extent to which H2O structures influence catalytic mechanisms. Specifically, influences of the configurational variability in the water structures at the catalyst interface are yet to be understood. Configurational variability is challenging to capture, as it requires multiscale approaches. Herein, we apply a multiscale sampling approach to calculate reaction thermodynamics and kinetics for COH* dehydrogenation to CO* and CH3OH* dehydrogenation to CH2OH* on Pt(111) catalysts under liquid H2O. We explore various pathways for these dehydrogenation reactions that could influence the overall mechanism of methanol decomposition by including participation of H2O structures both energetically and mechanistically. We find that the liquid H2O environment significantly influences the mechanism of COH* dehydrogenation to CO* but leaves the mechanism of CH3OH* dehydrogenation to CH2OH* largely unaltered.

Six first-row transition metal cations (Mn2+, Fe2+, Co2+, Ni2+, Cu2+, Zn2+) were evaluated as catalysts for ethene dimerization to 1-butene. This is an important reaction in the chemistry of C C bond formation and in the conversion of natural gas to higher hydrocarbons. Two related classes of transition metal cation catalysts were investigated: 1) single transition metal cations supported on zirconium oxide nodes of the metal–organic framework NU-1000 and 2) small metal hydroxide clusters with two metal atoms (M2) that could be grown by atomic layer deposition on a support exhibiting isolated hydroxyl groups. Using scaling relations, the free energies of co-adsorbed hydrogen and ethene (i.e., (H/C2H4)*) and adsorbed ethyl (i.e., C2H5*) were identified as descriptors for ethene dimerization catalysis. Using degree of rate control analysis, it was determined that the rate controlling steps are either ethene insertion (C C bond forming) or β-hydride elimination (C H bond breaking), depending on the metal. Using degree of catalyst control analysis, it was determined that activity on all the catalysts studied could be improved by tuning the free energy of C2H5*.

Density functional theory (DFT) calculations and microkinetic modeling are used to model reactions in the oxidation of n-butane to 1-butanol, 1-butanal, and 1-butene over pure metal and metal alloy (111) surfaces. Specifically, catalytic thermodynamic and kinetic energies are calculated with DFT, and linear scaling relationships are developed that link these values to simpler “descriptors” of catalytic activity. The scaling relationships are used in microkinetic modeling to identify the optimal descriptor values, which maximize the rate and selectivity to 1-butanol. Degree of rate control (DRC) analysis is performed to reveal the catalytic intermediates and transition states that have the greatest influence on the rate. The Cu3Pd(111) and Ag3Pd(111) surfaces are found to be the most active for n-butane oxidation to 1-butanol, with Cu3Pd additionally exhibiting high selectivity for 1-butanol. Achieving high activity and selectivity toward 1-butanol is found to require a precise balance of the catalyst affi...

Single atoms and few-atom clusters of platinum are uniformly installed on the zirconia nodes of a metal-organic framework (MOF) NU-1000 via targeted vapor-phase synthesis. The catalytic Pt clusters, site-isolated by organic linkers, are shown to exhibit high catalytic activity for ethylene hydrogenation while exhibiting resistance to sintering up to 200 °C. In situ IR spectroscopy reveals the presence of both single atoms and few-atom clusters that depend upon synthesis conditions. Operando X-ray absorption spectroscopy and X-ray pair distribution analyses reveal unique changes in chemical bonding environment and cluster size stability while on stream. Density functional theory calculations elucidate a favorable reaction pathway for ethylene hydrogenation with the novel catalyst. These results provide evidence that atomic layer deposition (ALD) in MOFs is a versatile approach to the rational synthesis of size-selected clusters, including noble metals, on a high surface area support.

Three new strontium manganese vanadates, Sr 2 Mn 2 (V 3 O 10 )(VO 4 ) ( I ), Sr 3 Mn(V 2 O 7 ) 2 ( II ), and Sr 2 Mn(VO 4 ) 2 (OH) ( III ), were prepared using a high temperature (580 °C) hydrothermal method with various chloride salts as the mineralizer. Minor differences in the chloride stoichiometry led to significant differences in product. Compound I crystallizes in the monoclinic space group P 2 1 / c ( a = 6.8773(12) A, b = 15.061(3) A, c = 11.609(2) A, β = 96.745(8)°), and consists of edge-shared octahedral manganese(II) dimers coordinated by trimeric [V 3 O 10 ] and monomeric [VO 4 ] groups. Compound II crystallizes in the tetragonal crystal system, P 4 3 2 1 2 ( a = 6.9951(2) A, c = 25.4390(7) A), and is built from monomeric manganese(II) octahedra chelated by two pyrovanadate [V 2 O 7 ] groups and linked to each other by additional pyrovanadates to form layers. Compound III is a noncentrosymmetric variation on the brackebuschite structure type, crystallizing in the monoclinic space group P 2 1 ( a = 7.6316(3) A, b = 6.1204(3) A, c = 8.6893(3) A, β = 111.3940(10)°). The structure is composed of octahedral manganese(III) edge-sharing chains coordinated to corner-sharing monomeric [VO 4 ] groups, thereby forming a manganese vanadate chain. All compounds were characterized by single-crystal X-Ray diffraction, powder X-Ray diffraction, infrared spectroscopy and single-crystal Raman spectroscopy. Density functional theory calculations were employed to investigate the relative stability of compound III .

Interest into the roles of water on aqueous phase heterogeneous catalysis is burgeoning. This short review summarizes the influences of hydrogen bonding on adsorption and how water molecules act as co-catalysts in aqueous phase heterogeneous catalysis. These phenomena, which involve interactions and/or reactions with “dangling” hydroxyl or hydroxide groups from nearby water molecules, are related to interfacial phenomena that have been observed at water/oil interfaces in organic synthesis. The hypothesized water structures at water/oil interfaces in organic synthesis is presented, and predictions about how analogous structural effects could influence catalytic chemistry at water/transition metal interfaces are discussed. The focus of this review is on computational methods and observations, but some experimental methods and findings are discussed as well.

Activation of the C-H bonds in ethane to form ethanol is a highly desirable, yet challenging, reaction. Metal-organic frameworks (MOFs) with open Fe sites are promising candidates for catalyzing this reaction. One advantage of MOFs is their modular construction from inorganic nodes and organic linkers, allowing for flexible design and detailed control of properties. In this work, we studied a series of single-metal atom Fe model systems with ligands that are commonly used as MOF linkers and tried to understand how one can design an optimal Fe catalyst. We found linear relationships between the binding enthalpy of oxygen to the Fe sites and common descriptors for catalytic reactions, such as the Fe 3d energy levels in different reaction intermediates. We further analyzed the three highest-barrier steps in the ethane oxidation cycle (including desorption of the product) with the Fe 3d energy levels. Volcano relationships are revealed with peaks toward higher Fe 3d energy and stronger electron-donating group functionalization of linkers. Furthermore, we found that the Fe 3d energy levels positively correlate with the electron-donating strength of functional groups on the linkers. Finally, we validated our hypotheses on larger models of MOF-74 iron sites. Compared with MOF-74, functionalizing the MOF-74 linkers with NH

Solvent plays an important role in liquid phase heterogeneous catalysis; however, methods for calculating the free energies of catalytic phenomena at the solid-liquid interface are not well-established. For example, solvent molecules alter the energies of catalytic species and participate in catalytic reactions and can thus significantly influence catalytic performance. In this work, we begin to establish methods for calculating the free energies of such phenomena, specifically, by employing an explicit solvation method using a multiscale sampling (MSS) approach. This MSS approach combines classical molecular dynamics with density functional theory. We use it to calculate the free energies of solvation of catalytic species, specifically adsorbed NH*, NH2*, CO*, COH*, CH2OH*, and C3H7O3* on Pt(111) surfaces under aqueous phase and under a mixed H2O/CH3OH solvent. We compare our calculated values with analogous values from implicit solvation for validation and to identify situations where implicit solvation is sufficient versus where explicit solvent is needed to compute adsorbate free energies. Our results indicate that explicit quantum-based methods are needed when adsorbates form chemical bonds and/or strong hydrogen bonds with H2O solvent. Using MSS, we further separate the calculated free energies into energetic and entropic contributions in order to understand how each influences the free energy. We find that adsorbates that exhibit strong energies also exhibit strong and negative entropies, and we attribute this relationship to hydrogen bonding between the adsorbates and the solvent molecules, which provides a large energetic contribution but reduces the overall mobility of the solvent.

We demonstrate the use of gas phase metal hydroxide clusters to identify descriptors and generate scaling relationships for predicting catalytic performances of porphyrin-supported metal hydroxide catalysts. Using the gas phase clusters for these purposes takes just 5 % of the time that would have been required if the porphyrin-supported models had been used.

Advances in scientific software and computing infrastructure have enabled researchers across disciplines to simulate and model highly complex systems. At the same time, these increases in simulation duration and scale have led to significant growths in the sizes of output data, which can be as much as hundreds of gigabytes or more. While there exist solutions to assist with most standard post-simulation analytics, researchers must develop their own code to support customized analytical tasks. Given the nature of these output data, most naive in-house sequential codes end up being inefficient, and in most cases, time-consuming. In this paper, we propose a solution to this issue by transparently combining the strengths of a high-performance computing cluster and a big data infrastructure to support an end-to-end scientific workflow. More specifically, we present a case study around the design of a research computing environment at Clemson University where these two computing systems are integrated and accessible from one another. This environment allows simulation data to be automatically transferred across systems and complex analytical tasks on these data to be developed using the Hadoop/Spark frameworks. Results show that a hybrid workflow for molecular dynamics simulation can provide significant performance improvements over a traditional workflow. Furthermore, code complexity of Hadoop/Spark solutions is shown to be less than that of a traditional solution.

The mechanism of methanol coupling to methyl formate over single-crystal gold catalysts has been firmly established but barely reconciled with experiments performed under practical conditions. Now, a method to close this gap has been reported, which enables the prediction of the reaction´s selectivity for a broad range of experimental conditions.

Catalytic fuel production and energy generation from biomass-derived compounds generally involve the aqueous phase, and water molecules at the catalyst interface have energetic and entropic consequences on the reaction free energies. These effects are difficult to elucidate, hindering rational catalyst design for these processes and inhibiting their widespread adoption. In this work, we combine density functional theory (DFT) and classical molecular dynamics (MD) simulations to garner molecular-level insights into H2O–adsorbate interactions. We obtain ensembles of liquid configurations with classical MD and compute the electronic energies of these systems with DFT. We examine CO, CH2OH, and C3H7O3 intermediates, which are critical in biomass reforming and direct methanol electrooxidation, on the Pt(111) surface under various explicit and explicit/implicit water configurations. We find that liquid H2O molecules arrange around surface intermediates in ways that favor hydrogen bonding, with larger and more h...

Here we review our simulations of adsorption on metal–organic frameworks (MOFs) and platinum (Pt) catalysts, focusing on the modelling methods required to understand these two very different system...

Grand canonical Monte Carlo simulations were used to calculate hydrogen adsorption in IRMOF-16, NU-100, and UiO-68 functionalized with Mg or Fe catecholates on the linkers. We examined how altering the number of metal catecholate groups affects H2 uptake and deliverable capacity near ambient temperature. We find that large free volume and an isosteric heat of adsorption (Qst) of 20 kJ mol−1 at low loading will maximize gravimetric deliverable capacity while a small pore diameter will maximize volumetric deliverable capacity. This suggests a trade-off between the properties that lead to maximal gravimetric and volumetric capacities. For example, our calculations suggest that NU-100 functionalized with six Fe catecholate groups per linker takes up 5.5 wt.% deliverable H2 at 243 K and 100 bar, but only 24.2 g L−1 deliverable H2.

Metal nanoparticles encapsulated within metal organic frameworks (MOFs) offer steric restrictions near the catalytic metal that can improve selectivity, much like in enzymes. A microkinetic model is developed for the regio-selective oxidation of n-butane to 1-butanol with O2 over a model for MOF-encapsulated bimetallic nanoparticles. The model consists of a Ag3Pd(111) surface decorated with a 2-atom-thick ring of (immobile) helium atoms which creates an artificial pore of similar size to that in common MOFs, which sterically constrains the adsorbed reaction intermediates. The kinetic parameters are based on energies calculated using density functional theory (DFT). The microkinetic model was analysed at 423 K to determine the dominant pathways and which species (adsorbed intermediates and transition states in the reaction mechanism) have energies that most sensitively affect the reaction rates to the different products, using degree-of-rate-control (DRC) analysis. This analysis revealed that activation of the C–H bond is assisted by adsorbed oxygen atoms, O*. Unfortunately, O* also abstracts H from adsorbed 1-butanol and butoxy as well, leading to butanal as the only significant product. This suggested to (1) add water to produce more OH*, thus inhibiting these undesired steps which produce OH*, and (2) eliminate most of the O2 pressure to reduce the O* coverage, thus also inhibiting these steps. Combined with increasing butane pressure, this dramatically improved the 1-butanol selectivity (from 0 to 95%) and the rate (to 2 molecules per site per s). Moreover, 40% less O2 was consumed per oxygen atom in the products. Under these conditions, a terminal H in butane is directly eliminated to the Pd site, and the resulting adsorbed butyl combines with OH* to give the desired 1-butanol. These results demonstrate that DRC analysis provides a powerful approach for optimizing catalytic process conditions, and that highly selectivity oxidation can sometimes be achieved by using a mixture of O2 and H2O as the oxidant. This was further demonstrated by DRC analysis of a second microkinetic model based on a related but hypothetical catalyst, where the activation energies for two of the steps were modified.

Metal−organic frameworks (MOFs) are permanently porous solids, which are promising hydrogen storage materials. However, the maximum H2 adsorption energies in MOFs are only around 10 kJ·mol−1, leading to small adsorption capacities at ambient temperature. In this work we use ab initio calculations and grand canonical Monte Carlo (GCMC) simulations to explore metal alkoxide functionalization for improving H2 storage in IRMOF-1, IRMOF-10, IRMOF-16, UiO-68, and UMCM-150. We examine functionalization with lithium, magnesium, manganese, nickel, and copper alkoxides. We show that lithium and magnesium alkoxides physically bind H2 and manganese, nickel, and copper alkoxides chemically bind H2. H2 binding energies calculated with quantum mechanics are −10, −22, −20, −78, and −84 kJ·mol−1, respectively, for the first hydrogen molecule. Of these, lithium and manganese alkoxides bind H2 too weakly to enhance adsorption at ambient temperature, even at 100 bar. Owing to the strong binding energies, Ni and Cu exhibit hi...

A coverage-dependent, mean-field microkinetic model of catalytic NO oxidation, NO+0.5O 2 ⇌NO 2 , at a Pt(111) surface has been developed, based on large supercell density functional theory (DFT) calculations. DFT is used to determine the overall energetics and activation energies of candidate reaction steps as a function of surface coverage. Surface coverage is found to have a significant but non-uniform effect on the energetics, pathways, and activation energies of reaction steps involving formation or cleavage of ON—O and O=O bonds, and inclusion of this coverage dependence is essential for obtaining a qualitatively correct representation of the catalysis. Correlations are used to express all reaction parameters in terms of a single coverage variable θ and steady-state solutions to the resultant mean-field models are obtained in the method of DeDonder relations. At conditions representative of NO oxidation catalysis, the surface coverage is predicted to be 0.25 ≤ θ ≤ 0.4 ML and to be controlled by equilibrium between gas-phase NO and NO 2 and chemisorbed O. O 2 dissociative adsorption (O 2(g) →2O*) is rate limiting in the model. The DFT-based mean-field model captures many features of the experimentally observed catalysis, and its short-comings point the way toward more robust models of coverage-dependent kinetics.

Batch reactor results and analysis are reported for the reaction of NO with O2 to form NO2 over a Pt(1 1 1) single crystal at atmospheric pressure. The apparent activation energy and NO, O2, and NO2 reaction orders are found to be 80 kJ mol−1, 1.3, 1, and −2 and are comparable to previous studies on supported Pt catalysts which take inhibition by the product NO2 into account. The absolute rates on a per Pt atom basis are the highest yet reported 0.34 ± 0.02 s−1, at 300 °C, 73 ppm NO, 27 ppm NO2 and 5% O2. Auger electron spectroscopy and X-ray photoelectron spectroscopy are used to show that the surface chemisorbed oxygen coverage under reaction conditions is 0.76 ± 0.06 ML, consistent with a coverage controlled by NO2 dissociation. DFT calculations are used to compare the stability of possible surface intermediates on a clean Pt(1 1 1) surface with those on a p(√3 × √3)-2O (2/3 ML) ordering surface. In contrast to the clean surface, O2 adsorption and dissociation are endothermic at 2/3 ML oxygen, but a peroxynitrite intermediate OONO* is slightly stable and may provide an alternative, associative pathway to NO2 formation that is consistent with the observed first order reaction kinetics in O2.

The reactivity of heterogeneous metal catalysts can be a strong function of the coverage of adsorbates. For example, Pt-catalyzed NO oxidation to NO2 requires high concentrations of chemisorbed (surface-bound) O, but the development of surface oxides is detrimental to reaction kinetics. Quantifying the structures, properties, and especially the conditions that produce various adsorbate coverages is essential to developing qualitatively and quantitatively correct models of surface reactivity. In this work, we examine these ideas in the context of oxidation reactions on Pt(111), the lowest energy face of bulk Pt. We use extensive supercell density functional theory (DFT) calculations to catalog and characterize the stable binding sites and arrangements of chemisorbed O on Pt(111), as a function of O coverage, θ. O atoms are found to uniformly prefer FCC binding sites and to arrange to minimize various destabilizing interactions with neighbor O. These destabilizing interactions are shown to have electronic a...

Metal nanoparticles (NP) encapsulated by metal-organic frameworks (MOFs) are novel composite materials that have shown promise as regioselective catalysts. The regioselectivity in these materials arises from steric constraints imposed by the porous MOF structure, which limit the way molecules approach and interact with the metal surface. Here we introduce a conceptually simple DFT approach to model reactions under such steric constraints. This approach is computationally efficient and accounts for the steric constraints imposed by a MOF pore in a general way. The adsorption of reactants, intermediates, and products associated with oxidation of n-butane to 1-butanol (and 2-butanol) on clean and oxygen-covered palladium surfaces is investigated with (and without) the constraints of a pore. Reaction energies are calculated, and we find that the thermodynamic favorability of the intermediate reactions is affected by the presence of steric constraints, oxygen coverage, and the exposed crystal surface of the metal. Based on these results, the Pd(111) surface with 0.25 ML oxygen coverage and steric constraints (which could be provided by a suitable MOF) seems promising to favor the desired sequence of reactions that would lead to the conversion of n-butane to 1-butanol.

Pt is the most common catalyst for NO oxidation to NO2, a key reaction in NOx remediation chemistry. In this work, density functional theory calculations and plane-wave supercell models are used to...

Stepwise adsorption in a metal-organic framework with both micro- and meso-pores is caused by adsorbates first filling the micropores, then adsorbing along the mesopore walls, and finally filling the mesopores.

The effects of adsorbate coverage on catalytic surface reactions are not well understood. Here, we contrast the rates of ${\mathrm{O}}_{2}$ and ${\mathrm{NO}}_{2}$ dissociations, two competing reactions in NO oxidation catalysis, versus oxygen coverage at a Pt(111) surface. In situ x-ray photoelectron spectroscopy experiments show that the ${\mathrm{NO}}_{2}$ dissociation rate is less sensitive to O coverage than is ${\mathrm{O}}_{2}$. Density-functional theory simulations reveal an ${\mathrm{NO}}_{2}$ reaction pathway that is more adaptable to an increasingly crowded surface than is ${\mathrm{O}}_{2}$ dissociation. While the rates are comparable at low coverage, ${\mathrm{NO}}_{2}$ dissociation is many orders of magnitude faster at O coverages typical of NO oxidation catalysis.