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Films of titania-supported monometallic Pd, Pt, and bimetallic Pt-Pd catalysts made of metallic nanoparticles were prepared by magnetron sputtering and studied in the oxidative dehydrogenation (ODH) of cyclohexene. Pd/TiOx and Pt-Pd/TiOx were found active at as low temperature as 150 °C and showed high catalytic activity with high conversion (up to 81%) and benzene selectivity exceeding 97% above 200 °C. In turn, the Pt/TiOx catalyst performed poorly with the onset of benzene production at 200 °C only and conversions not exceeding 5%. The activity of bimetallic Pt-Pd catalysts far exceeded all of the other investigated catalysts at temperatures below 250 °C. However, the production of benzene significantly dropped with a further temperature increase due to the enhanced combustion of CO2 at the expense of benzene formation. As in situ NAP-XPS measurement of the Pt-Pd/TiOx catalyst in the reaction conditions of the ODH of cyclohexene revealed Pd surface enrichment during the first temperature ramp, we assume that Pd surface enrichment is responsible for enhanced activity at low temperatures in the bimetallic catalyst. At the same time, the Pt constituent contributes to stronger cyclohexene adsorption and oxygen activation at elevated temperatures, leading to changes in conversion and selectivity with a drop in benzene formation and increased combustion to CO2. Both the monometallic Pd and the Pt-Pd-based catalysts produced a small amount of the second valuable product, cyclohexadiene, and below 250 °C produced only a negligible amount of CO2 (<0.2%). To summarize, Pd- and Pt-Pd-based catalysts were found to be promising candidates for highly selective low-temperature dehydrogenation of cyclic hydrocarbons that showcased reproducibility and stability after the temperature activation. Importantly, these catalysts were fabricated by utilizing proven methods suitable for large-scale production on extended surfaces.
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In this work, we investigated cyclohexane oxidative dehydrogenation (ODH) catalyzed by cobalt ferrite nanoparticles supported on reduced graphene oxide (RGO). We aim to identify the active sites that are specifically responsible for full and partial dehydrogenation using advanced spectroscopic techniques such as X-ray photoelectron emission microscopy (XPEEM) and X-ray photoelectron spectroscopy (XPS) along with kinetic analysis. Spectroscopically, we propose that Fe3+/Td sites could exclusively produce benzene through full cyclohexane dehydrogenation, while kinetic analysis shows that oxygen-derived species (O*) are responsible for partial dehydrogenation to form cyclohexene in a single catalytic sojourn. We unravel the dynamic cooperativity between octahedral and tetrahedral sites and the unique role of the support in masking undesired active (Fe3+/Td) sites. This phenomenon was strategically used to control the abundance of these species on the catalyst surface by varying the particle size and the wt % content of the nanoparticles on the RGO support in order to control the reaction selectivity without compromising reaction rates which are otherwise extremely challenging due to the much favorable thermodynamics for complete dehydrogenation and complete combustion under oxidative conditions.
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Understanding chemical reactivity and magnetism of 3d transition metal nanoparticles is of fundamental interest for applications in fields ranging from spintronics to catalysis. Here, we present an atomistic picture of the early stage of the oxidation mechanism and its impact on the magnetism of Co nanoparticles. Our experiments reveal a two-step process characterized by (i) the initial formation of small CoO crystallites across the nanoparticle surface, until their coalescence leads to structural completion of the oxide shell passivating the metallic core; (ii) progressive conversion of the CoO shell to Co3O4 and void formation due to the nanoscale Kirkendall effect. The Co nanoparticles remain highly reactive toward oxygen during phase (i), demonstrating the absence of a pressure gap whereby a low reactivity at low pressures is postulated. Our results provide an important benchmark for the development of theoretical models for the chemical reactivity in catalysis and magnetism during metal oxidation at the nanoscale.
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The pronounced effects of the composition of four-atom monometallic Cu and Pd and bimetallic CuPd clusters and the support on the catalytic activity and selectivity in the oxidative dehydrogenation of cyclohexene are reported. The ultra-nanocrystalline diamond supported clusters are highly active and dominantly produce benzene; some of the mixed clusters also produce cyclohexadiene, which are all clusters with a much suppressed combustion channel. The also highly active TiO2-supported tetramers solely produce benzene, without any combustion to CO2. The selectivity of the zirconia-supported mixed CuPd clusters and the monometallic Cu cluster is entirely different; though they are less active in comparison to clusters with other supports, these clusters produce significant fractions of cyclohexadiene, with their selectivity towards cyclohexadiene gradually increasing with the increasing number of copper atoms in the cluster, reaching about 50% for Cu3Pd1. The zirconia-supported copper tetramer stands out from among all the other tetramers in this reaction, with a selectivity towards cyclohexadiene of 70%, which far exceeds those of all the other cluster-support combinations. The findings from this study indicate a positive effect of copper on the stability of the mixed tetramers and potential new ways of fine-tuning catalyst performance by controlling the composition of the active site and via cluster-support interactions in complex oxidative reactions under the suppression of the undesired combustion of the feed.
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For very small nanocluster-based catalysts, the exploration of the influence of the particle size, composition, and support offers precisely variable parameters in a wide material search space to control catalysts' performance. We present the mechanism of the CO2 methanation reaction on the oxidized bimetallic Cu3Pd tetramer (Cu3PdO2) supported on a zirconia model support represented by Zr12O24 based on the energy profile obtained from density functional theory calculations on the reaction of CO2 and H2. In order to determine the role of the Pd atom, the performance of Cu3PdO2 with monometallic Cu4O2 at the same support has been compared. Parallel to methane formation, the alternative path of methanol formation at this catalyst has also been investigated. The results show that the exchange of a single atom in Cu4 with a single Pd atom improves catalyst/s performance via lowering the barriers associated with hydrogen dissociation steps that occur on the Pd atom. The above-mentioned results suggest that the doping strategy at the level of single atoms can offer a precise control knob for designing new catalysts with desired performance.
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Ultrasmall clusters of subnanometer size can possess unique and even unexpected physical and chemical propensities which make them interesting in various fields of basic science and for potential applications, such as catalysis, photocatalysis, electrocatalysis, and optical and chemical sensors, just to name a few examples. These small particles often offer the tunability of their performance in an atom-by-atom fashion and an economic atom-efficient use of the metal loading. In this paper we review recent progress in the characterization and theory of well-defined subnanometer clusters in catalytic processes, and discuss their optical properties and stability, along with the potential of the size-selected clusters for the understanding of catalytic processes and for the development of new classes of catalysts.
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The effect of particle size and support on the catalytic performance of supported subnanometer copper clusters was investigated in the oxidative dehydrogenation of cyclohexene. From among the investigated seven size-selected subnanometer copper particles between a single atom and clusters containing 2-7 atoms, the highest activity was observed for the titania-supported copper tetramer with 100% selectivity toward benzene production and being about an order of magnitude more active than not only all the other investigated cluster sizes on the same support but also the same tetramer on the other supports, Al2O3, SiO2, and SnO2. In addition to the profound effect of cluster size on activity and with Cu4 outstanding from the studied series, Cu4 clusters supported on SiO2 provide an example of tuning selectivity through support effects when this particular catalyst also produces cyclohexadiene with about 30% selectivity. Titania-supported Cu5 and Cu7 clusters supported on TiO2 produce a high fraction of cyclohexadiene in contrast to their neighbors, while Cu4 and Cu6 solely produce benzene without any combustion, thus representing odd-even oscillation of selectivity with the number of atoms in the cluster.
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Size-selected clusters are important model catalysts because of their narrow size and compositional distributions, as well as enhanced activity and selectivity in many reactions. Still, their structure-activity relationships are, in general, elusive. The main reason is the difficulty in identifying and quantitatively characterizing the catalytic active site in the clusters when it is confined within subnanometric dimensions and under the continuous structural changes the clusters can undergo in reaction conditions. Using machine learning approaches for analysis of the operando X-ray absorption near-edge structure spectra, we obtained accurate speciation of the CuxPdy cluster types during the propane oxidation reaction and the structural information about each type. As a result, we elucidated the information about active species and relative roles of Cu and Pd in the clusters.
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The metal-organic framework (MOF), NU-1000, and its metalated counterparts have found proof-of-concept application in heterogeneous catalysis and hydrogen storage among others. A vapor-phase technique, akin to atomic layer deposition (ALD), is used to selectively deposit divalent Cu ions on oxo, hydroxo-bridged hexa-zirconium(IV) nodes capped with terminal -OH and -OH2 ligands. The subsequent reaction with steam yields node-anchored, CuII-oxo, hydroxo clusters. We find that cluster installation via AIM (ALD in MOFs) is accompanied by an expansion of the MOF mesopore (channel) diameter. We investigated the behavior of the cluster-modified material, termed Cu-AIM-NU-1000, to heat treatment up to 325 °C at atmospheric pressure with a low flow of H2 into the reaction cell. The response under these conditions revealed two important results: (1) Above 200 °C, the initially installed few-metal-ion clusters reduce to neutral Cu atoms. The neutral atoms migrate from the nodes and aggregate into Cu nanoparticles. While the size of particles formed in the MOF interior is constrained by the width of mesopores (â¼3 nm), the size of those formed on the exterior surface of the MOF can grow as large as â¼8 nm. (2) Reduction and release of Cu atoms from the MOFs nodes is accompanied by the dynamic structural transformation of NU-1000 as it reverts back to its original dimension following the release. These results show that while the MOF framework itself remains intact at 325 °C in an H2 atmosphere, the small, AIM-installed CuII-oxo, hydroxo clusters are stable with respect to reduction and conversion to metallic nanoparticles only up to â¼200 °C.
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Understanding the origins of enhanced reactivity of supported, subnanometer in size, metal oxide clusters is challenging due to the scarcity of methods capable to extract atomic-level information from the experimental data. Due to both the sensitivity of X-ray absorption near edge structure (XANES) spectroscopy to the local geometry around metal ions and reliability of theoretical spectroscopy codes for modeling XANES spectra, supervised machine learning approach has become a powerful tool for extracting structural information from the experimental spectra. Here, we present the application of this method to grazing incidence XANES spectra of size-selective Cu oxide clusters on flat support, measured in operando conditions of the methanation reaction. We demonstrate that the convolution neural network can be trained on theoretical spectra and utilized to "invert" experimental XANES data to obtain structural descriptors-the Cu-Cu coordination numbers. As a result, we were able to distinguish between different structural motifs (Cu2O-like and CuO-like) of Cu oxide clusters, transforming in reaction conditions, and reliably evaluate average cluster sizes, with important implications for the understanding of structure, composition, and function relationships in catalysis.
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Lithium-oxygen (Li-O2) batteries are a promising class of rechargeable Li batteries with a potentially very high achievable energy density. One of the major challenges for Li-O2 batteries is the high charge overpotential, which results in a low energy efficiency. In this work size-selected subnanometer Ir clusters are used to investigate cathode materials that can help control lithium superoxide formation during discharge, which has good electronic conductivity needed for low charge potentials. It is found that Ir particles can lead to lithium superoxide formation as the discharge product with Ir particle sizes of â¼1.5 nm giving the lowest charge potentials. During discharge these 1.5 nm Ir nanoparticles surprisingly evolve to larger ones while incorporating Li to form core-shell structures with Ir3Li shells, which probably act as templates for growth of lithium superoxide during discharge. Various characterization techniques including DEMS, Raman, titration, and HRTEM are used to characterize the LiO2 discharge product and the evolution of the Ir nanoparticles. Density functional calculations are used to provide insight into the mechanism for formation of the core-shell Ir3Li particles. The in situ formed Ir3Li core-shell nanoparticles discovered here provide a new direction for active cathode materials that can reduce charge overpotentials in Li-O2 batteries.
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The discovery of more efficient, economical, and selective catalysts for oxidative dehydrogenation is of immense economic importance. However, the temperatures required for this reaction are typically high, often exceeding 400 °C. Herein, we report the discovery of subnanometer sized cobalt oxide clusters for oxidative dehydrogenation of cyclohexane that are active at lower temperatures than reported catalysts, while they can also eliminate the combustion channel. These results found for the two cluster sizes suggest other subnanometer size (CoO)x clusters will also be active at low temperatures. The high activity of the cobalt clusters can be understood on the basis of density functional studies that reveal highly active under-coordinated cobalt atoms in the clusters and show that the oxidized nature of the clusters substantially decreases the binding energy of the cyclohexene species which desorb from the cluster at low temperature.
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Cu nanoassemblies formed transiently during reaction from size-selected subnanometer Cu4 clusters supported on amorphous OH-terminated alumina convert CO2 into methanol and hydrocarbons under near-atmospheric pressure at rates considerably higher than those of individually standing Cu4 clusters. An in situ characterization reveals that the clusters self-assemble into 2D nanoassemblies at higher temperatures which then disintegrate upon cooling down to room temperature. DFT calculations postulate a formation mechanism of these nanoassemblies by hydrogen-bond bridges between the clusters and H2O molecules, which keep the building blocks together while preventing their coalescence.
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We have used ab initio density functional theory together with ab initio atomistic thermodynamics, and in situ x-ray absorption near edge spectroscopy (XANES) experiments, to study the oxidation of sub-nanometer clusters of Cu n O x supported on a hydroxylated amorphous alumina substrate in an O2-rich environment. We obtain (pâ, T) phase diagrams: these differ notably for the nanoclusters compared to the bulk. Both the theory and experiment suggest that in the presence of oxygen, the cluster will oxidize from its elemental state to the oxidized state as the temperature decreases. We obtain a clear trend for the transition of Cu n â Cu n O n/2: we see that the smaller the cluster, the greater is the tendency toward oxidation. However, we do not see a monotonic size-dependent trend for the transition of Cu n O n/2 â Cu n O n . We suggest that theoretically computed Bader charges constitute a simple yet quantitative way to align experimental measures of XANES edges with theoretical calculations, so as to yield oxidation states for nanoclusters. Our results have important implications for the use of small clusters in fields such as nanocatalysis and nanomedicine.
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Size-selected clusters containing a handful of atoms may possess noble catalytic properties different from nano-sized or bulk catalysts. Size- and composition-selected clusters can also serve as models of the catalytic active site, where an addition or removal of a single atom can have a dramatic effect on their activity and selectivity. In this perspective, we provide an overview of studies performed under both ultra-high vacuum and realistic reaction conditions aimed at the interrogation, characterization, and understanding of the performance of supported size-selected clusters in heterogeneous and electrochemical reactions, which address the effects of cluster size, cluster composition, cluster-support interactions, and reaction conditions, the key parameters for the understanding and control of catalyst functionality. Computational modeling based on density functional theory sampling of local minima and energy barriers or ab initio molecular dynamics simulations is an integral part of this research by providing fundamental understanding of the catalytic processes at the atomic level, as well as by predicting new materials compositions which can be validated in experiments. Finally, we discuss approaches which aim at the scale up of the production of well-defined clusters for use in real world applications.
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The controlled preparation of Au nanoparticles (NPs) in the size range of 6 to 22 nm is explored in this study. The Au NPs were prepared by the reduction of tetrachloroauric acid using maltose in the presence of nonionic surfactant Tween 80 at various concentrations to control the size of the resulting Au NPs. With increasing concentration of Tween 80 a decrease in the size of produced Au NPs was observed, along with a significant decrease in their size distribution. The size-dependent catalytic activity of the synthesized Au NPs was tested in the reduction of 4-nitrophenol with sodium borohydride, resulting in increasing catalytic activity with decreasing size of the prepared nanoparticles. Eley-Rideal catalytic mechanism emerges as the more probable, in contrary to the Langmuir-Hinshelwood mechanism reported for other noble metal nanocatalysts.
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A combined experimental and theoretical investigation of Ag-Pt sub-nanometer clusters as heterogeneous catalysts in the COâCO2 reaction (COox) is presented. Ag9 Pt2 and Ag9 Pt3 clusters are size-selected in the gas phase, deposited on an ultrathin amorphous alumina support, and tested as catalysts experimentally under realistic conditions and by first-principles simulations at realistic coverage. Inâ situ GISAXS/TPRx demonstrates that the clusters do not sinter or deactivate even after prolonged exposure to reactants at high temperature, and present comparable, extremely high COox catalytic efficiency. Such high activity and stability are ascribed to a synergic role of Ag and Pt in ultranano-aggregates, in which Pt anchors the clusters to the support and binds and activates two CO molecules, while Ag binds and activates O2 , and Ag/Pt surface proximity disfavors poisoning by CO or oxidized species.