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Iron is considered as attractive energy carrier in a carbon-free circular energy economy. The reduction of iron oxide is crucial for its applica-tion as a metal fuel as it determines the efficiency of the cycle. Temperature programmed reduction of α-Fe2O3 was monitored by complementary X-ray absorption spectroscopy (XAS) and diffraction (XRD) to obtain the phase composition with high time resolution. Synchrotron Mössbauer spectroscopy (SMS) was additionally employed due to its high sensitivity to the different iron species. Theoretical calculations of surface and bulk adsorption processes were performed to establish the potential reaction pathways and the corresponding energy barriers. A kinetic particle model was then developed to bridge the experimental data and theoretical calculations, which reproduced the reduction onset and behavior. The reduction process was found to be strongly dependent on the heating rate in terms of the reduction window and the observed intermediate species. We propose that a core-shell mechanism determines the reaction by forming an iron layer which subsequently hinders diffusion of water out of the porous particles leading to some unreduced FeO at high temperature. This study demonstrates the need for complementary methods for describing complex heterogeneous systems and overcoming the chemical sensitivity limitations of any single method.
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CeO2-supported noble metal clusters are attractive catalytic materials for several applications. However, their atomic dispersion under oxidizing reaction conditions often leads to catalyst deactivation. In this study, the noble metal cluster formation threshold is rationally adjusted by using a mixed CeO2-Al2O3 support. The preferential location of Pd on CeO2 islands leads to a high local surface noble metal concentration and promotes the in situ formation of small Pd clusters at a rather low noble metal loading (0.5â wt %), which are shown to be the active species for CO conversion at low temperatures. As elucidated by complementary in situ/operando techniques, the spatial separation of CeO2 islands on Al2O3 confines the mobility of Pd, preventing the full redispersion or the formation of larger noble metal particles and maintaining a high CO oxidation activity at low temperatures. In a broader perspective, this approach to more efficiently use the noble metal can be transferred to further systems and reactions in heterogeneous catalysis.
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The surface structure and chemical properties of Y-stabilized zirconia (YSZ) have been subjects of intense debate over the past three decades. However, a thorough understanding of chemical processes occurring at YSZ powders faces significant challenges due to the absence of reliable reference data acquired for well-controlled model systems. Here, we present results from polarization-resolved infrared reflection absorption spectroscopy (IRRAS) obtained for differently oriented, Y-doped ZrO2 single-crystal surfaces after exposure to CO and D2O. The IRRAS data reveal that the polar YSZ(100) surface undergoes reconstruction, characterized by an unusual, red-shifted CO band at 2132â cm-1. Density functional theory calculations allowed to relate this unexpected observation to under-coordinated Zr4+ cations in the vicinity of doping-induced O vacancies. This reconstruction leads to a strongly increased chemical reactivity and water spontaneously dissociates on YSZ(100). The latter, which is an important requirement for catalysing the water-gas-shift (WGS) reaction, is absent for YSZ(111), where only associative adsorption was observed. Together with a novel analysis Scheme these reference data allowed for an operando characterisation of YSZ powders using DRIFTS (diffuse reflectance infrared Fourier transform spectroscopy). These findings facilitate rational design and tuning of YSZ-based powder materials for catalytic applications, in particular CO oxidation and the WGS reaction.
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Ammonia is a storage molecule for hydrogen, which can be released by catalytic decomposition. Inexpensive iron catalysts suffer from a low activity due to a too strong iron-nitrogen binding energy compared to more active metals such as ruthenium. Here, we show that this limitation can be overcome by combining iron with cobalt resulting in a Fe-Co bimetallic catalyst. Theoretical calculations confirm a lower metal-nitrogen binding energy for the bimetallic catalyst resulting in higher activity. Operando spectroscopy reveals that the role of cobalt in the bimetallic catalyst is to suppress the bulk-nitridation of iron and to stabilize this active state. Such catalysts are obtained from Mg(Fe,Co)2O4 spinel pre-catalysts with variable Fe:Co ratios by facile co-precipitation, calcination and reduction. The resulting Fe-Co/MgO catalysts, characterized by an extraordinary high metal loading reaching 74 wt.%, combine the advantages of a ruthenium-like electronic structure with a bulk catalyst-like microstructure typical for base metal catalysts.
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Herein we report the one-pot cobalt catalysed synthesis of the dimethylacetal of acetaldehyde from synthesis gas and methanol. The product can be used as a fuel additive either as it is or after transacetalisation with long-chain alcohols. The product is obtained at moderate temperatures in good selectivities and high CO-conversions. A variation of the promotor metal (Au, Pt, Pd, and Ru) and of the support (γ-Al2O3 and CeO2) in the catalyst was conducted, which showed a great impact of both the support and promotor on the activity and structure of the catalyst. Furthermore, a specific variation of temperatures and pressure for the most active catalyst and a model catalyst was conducted giving an interesting insight into ongoing processes.
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The study presents an ab-initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF-vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first-principles-based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange-correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT-constrained microkinetic model optimization for other heterogeneously catalyzed systems.
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Due to its outstanding properties, graphene has emerged as one of the most promising 2D materials in a large variety of research fields. Among the available fabrication protocols, chemical vapor deposition (CVD) enables the production of high quality single-layered large area graphene. To better understand the kinetics of CVD graphene growth, multiscale modeling approaches are sought after. Although a variety of models have been developed to study the growth mechanism, prior studies are either limited to very small systems, are forced to simplify the model to eliminate the fast process, or they simplify reactions. While it is possible to rationalize these approximations, it is important to note that they have non-trivial consequences on the overall growth of graphene. Therefore, a comprehensive understanding of the kinetics of graphene growth in CVD remains a challenge. Here, we introduce a kinetic Monte Carlo protocol that permits, for the first time, the representation of relevant reactions on the atomic scale, without additional approximations, while still reaching very long time and length scales of the simulation of graphene growth. The quantum-mechanics-based multiscale model, which links kinetic Monte Carlo growth processes with the rates of occurring chemical reactions, calculated from first principles makes it possible to investigate the contributions of the most important species in graphene growth. It permits the proper investigation of the role of carbon and its dimer in the growth process, thus indicating the carbon dimer to be the dominant species. The consideration of hydrogenation and dehydrogenation reactions enables us to correlate the quality of the material grown within the CVD control parameters and to demonstrate an important role of these reactions in the quality of the grown graphene in terms of its surface roughness, hydrogenation sites, and vacancy defects. The model developed is capable of providing additional insights to control the graphene growth mechanism on Cu(111), which may guide further experimental and theoretical developments.
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Enfermedades Cardiovasculares , Grafito , Humanos , Carbono , Simulación por Computador , GasesRESUMEN
For the calculation of anharmonic contributions to free energy barriers, constrained thermodynamic λ-path integration (λ-TI) from a harmonic reference force field to density functional theory is presented as an alternative to the established Blue Moon ensemble method (ξ-TI), in which free energy gradients along the reaction coordinate ξ are integrated. With good agreement in all cases, the λ-TI method is benchmarked against the ξ-TI method for several reactions, including the internal CH3 group rotation in ethane, a nucleophilic substitution of CH3Cl, a retro-Diels-Alder reaction, and a proton transfer in zeolite H-SSZ-13. An advantage of λ-TI is that one can use virtually any reference state to compute anharmonic contributions to reaction free energies or free energy barriers. This is particularly relevant for catalysis, where it is now possible to compute anharmonic corrections to the free energy of a transition state relative to any reference, for example, the most stable state of the active site and the reactants in the gas phase. This is in contrast to ξ-TI, where free energy barriers can only be computed relative to an initial state with all reactants coadsorbed. Finally, the Bennett acceptance ratio method combined with λ-TI is demonstrated to reduce the number of required integration grid points with tolerable accuracy, favoring thus λ-TI over ξ-TI in terms of computational efficiency.
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Oxide supports play an important role in enhancing the catalytic properties of transition metal nanoparticles in heterogeneous catalysis. How extensively interactions between the oxide support and the nanoparticles impact the electronic structure as well as the surface properties of the nanoparticles is hence of high interest. In this study, the influence of a magnesium oxide support on the properties of copper nanoparticles with different size, shape, and adsorption sites is investigated using density functional theory (DFT) calculations. By proposing simple models to reduce the cost of the calculations while maintaining the accuracy of the results, we show using the nonreducible oxide support MgO as an example that there is no significant influence of the MgO support on the electronic structure of the copper nanoparticles, with the exception of adsorption directly at the Cu-MgO interface. We also propose a simplified methodology that allows us to reduce the cost of the calculations, while the accuracy of the results is maintained. We demonstrate in addition that the Cu nanowire model corresponds well to the nanoparticle model, which reduces the computational cost even further.
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The hydrogenation of CO2 to methanol over Cu/ZnO-based catalysts is highly sensitive to the surface composition and catalyst structure. Thus, its optimization requires a deep understanding of the influence of the pre-catalyst structure on its evolution under realistic reaction conditions, including the formation and stabilization of the most active sites. Here, the role of the pre-catalyst shape (cubic vs spherical) in the activity and selectivity of ZnO-supported Cu nanoparticles was investigated during methanol synthesis. A combination of ex situ, in situ, and operando microscopy, spectroscopy, and diffraction methods revealed drastic changes in the morphology and composition of the shaped pre-catalysts under reaction conditions. In particular, the rounding of the cubes and partial loss of the (100) facets were observed, although such motifs remained in smaller domains. Nonetheless, the initial pre-catalyst structure was found to strongly affect its subsequent transformation in the course of the CO2 hydrogenation reaction and activity/selectivity trends. In particular, the cubic Cu particles displayed an increased activity for methanol production, although at the cost of a slightly reduced selectivity when compared to similarly sized spherical particles. These findings were rationalized with the help of density functional theory calculations.
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A frontier challenge in single-atom (SA) catalysis is the design of fully inorganic sites capable of emulating the high reaction selectivity traditionally exclusive of organometallic counterparts in homogeneous catalysis. Modulating the direct coordination environment in SA sites, via the exploitation of the oxide support's surface chemistry, stands as a powerful albeit underexplored strategy. We report that isolated Rh atoms stabilized on oxygen-defective SnO2 uniquely unite excellent TOF with essentially full selectivity in the gas-phase hydroformylation of ethylene, inhibiting the thermodynamically favored olefin hydrogenation. Density Functional Theory calculations and surface characterization suggest that substantial depletion of the catalyst surface in lattice oxygen, energetically facile on SnO2 , is key to unlock a high coordination pliability at the mononuclear Rh centers, leading to an exceptional performance which is on par with that of molecular catalysts in liquid media.
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The correct description of catalytic reactions happening on bimetallic particles is not feasible without proper accounting of the segregation process. In this study, we tried to shed light on the structure of large CoCu particles, for which quite controversial results were published before. However, density functional theory (DFT) is challenging to be directly used for the systematic study of nanometer-sized particles. Therefore, we constructed a neural network-based potential and further applied it to the Monte Carlo simulations for the description of the segregation phenomenon. The resulting approach shows high efficiency and can be used in systems with thousands of atoms. The accuracy and transferability of the model to other sizes and compositions make this methodology useful for solving segregation problems.
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Nanopartículas , Redes Neurales de la Computación , Método de MontecarloRESUMEN
Although the CVD synthesis of graphene on Cu(111) is an industrial process of outstanding importance, its theoretical description and modeling are hampered by its multiscale nature and the large number of elementary reactions involved. In this work, we propose an analytical model of graphene nucleation and growth on Cu(111) surfaces based on the combination of kinetic nucleation theory and the DFT simulations of elementary steps. In the framework of the proposed model, the mechanism of graphene nucleation is analyzed with particular emphasis on the roles played by the two main feeding species, C and C2. Our analysis reveals unexpected patterns of graphene growth, not typical for classical nucleation theories. In addition, we show that the proposed theory allows for the reproduction of the experimentally observed characteristics of polycrystalline graphene samples in the most computationally efficient way.
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Converting CO2 into value-added chemicals and fuels, such as methanol, is a promising approach to limit the environmental impact of human activities. Conventional methanol synthesis catalysts have shown limited efficiency and poor stability in a CO2/H2 mixture. To design improved catalysts, crucial for the effective utilization of CO2, an in-depth understanding of the active sites and reaction mechanism is desired. The catalytic performance of a series of carbon-supported Cu catalysts, with Cu particle sizes in the range of 5 to 20 nm, was evaluated under industrially relevant temperature and pressure, i.e. 260 °C and 40 bar(g). The CO2 hydrogenation reaction exhibited clear particle size effects up to 13 nm particles, with small nanoparticles having the lower activity, but higher methanol selectivity. MeOH and CO formation showed a different size-dependence. The TOFCO increased from 1.9 × 10-3 s-1 to 9.4 × 10-3 s-1 with Cu size increasing from 5 nm to 20 nm, while the TOFMeOH was size-independent (8.4 × 10-4 s-1 on average). The apparent activation energies for MeOH and CO formation were size-independent with values of 63 ± 7 kJ mol-1 and 118 ± 6 kJ mol-1, respectively. Hence the size dependence was ascribed to a decrease in the fraction of active sites suitable for CO formation with decreasing particle size. Theoretical models and DFT calculations showed that the origin of the particle size effect is most likely related to the differences in formate coverage for different Cu facets whose abundancy depends on particle size. Hence, the CO2 hydrogenation reaction is intrinsically sensitive to the Cu particle size.
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Water influences critically the kinetics of the autocatalytic conversion of methanol to hydrocarbons in acid zeolites. At very low conversions but otherwise typical reaction conditions, the initiation of the reaction is delayed in presence of H2O. In absence of hydrocarbons, the main reactions are the methanol and dimethyl ether (DME) interconversion and the formation of a C1 reactive mixture-which in turn initiates the formation of first hydrocarbons in the zeolite pores. We conclude that the dominant reactions for the formation of a reactive C1 pool at this stage involve hydrogen transfer from both MeOH and DME to surface methoxy groups, leading to methane and formaldehyde in a 1:1 stoichiometry. While formaldehyde reacts further to other C1 intermediates and initiates the formation of first C-C bonds, CH4 is not reacting. The hydride transfer to methoxy groups is the rate-determining step in the initiation of the conversion of methanol and DME to hydrocarbons. Thus, CH4 formation rates at very low conversions, i.e., in the initiation stage before autocatalysis starts, are used to gauge the formation rates of first hydrocarbons. Kinetics, in good agreement with theoretical calculations, show surprisingly that hydrogen transfer from DME to methoxy species is 10 times faster than hydrogen transfer from methanol. This difference in reactivity causes the observed faster formation of hydrocarbons in dry feeds, when the concentration of methanol is lower than in presence of water. Importantly, the kinetic analysis of CH4 formation rates provides a unique quantitative parameter to characterize the activity of catalysts in the methanol-to-hydrocarbon process.
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This corrects the article DOI: 10.1103/PhysRevLett.125.256101.
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Herein, we propose a novel computational protocol that enables calculating free energies with improved accuracy by combining the best available techniques for enthalpy and entropy calculation. While the entropy is described by enhanced sampling molecular dynamics techniques, the energy is calculated using ab initio methods. We apply the method to assess the stability of isobutene adsorption intermediates in the zeolite H-SSZ-13, a prototypical problem that is computationally extremely challenging in terms of calculating enthalpy and entropy. We find that at typical operating conditions for zeolite catalysis (400 °C), the physisorbed π-complex, and not the tertiary carbenium ion as often reported, is the most stable intermediate. This method paves the way for sampling-based techniques to calculate the accurate free energies in a broad range of chemistry-related disciplines, thus presenting a big step forward toward predictive modeling.
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Cobalt-copper (CoCu) catalysts have industrial potential in CO/CO2 hydrogenation reactions, and CoCu alloy has been elucidated as a major active phase during reactions. However, due to elemental surface segregation and dealloying phenomena, the actual surface morphology of CoCu alloy is still unclear. Combining theory and experiment, the dual effect of surface segregation and varied CO coverage over the CoCu(111) surface on the reactivity in CO2 hydrogenation reactions is explored. The relationship between C-O bond scission and further hydrogenation of intermediate *CH2 O was discovered to be a key step to promote ethanol production. The theoretical investigation suggests that moderate Co segregation provides a suitable surface Co ensemble with lateral interactions of co-adsorbed *CO, leading to promoted selectivity to ethanol, in agreement with theory-inspired experiments.
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Extending the toolbox from mono- to bimetallic catalysts is key in realizing efficient chemical processes1. Traditionally, the performance of bimetallic catalysts featuring one active and one selective metal is optimized by varying the metal composition1-3, often resulting in a compromise between the catalytic properties of the two metals4-6. Here we show that by designing the atomic distribution of bimetallic Au-Pd nanocatalysts, we obtain a synergistic catalytic performance in the industrially relevant selective hydrogenation of butadiene. Our single-crystalline Au-core Pd-shell nanorods were up to 50 times more active than their alloyed and monometallic counterparts, while retaining high selectivity. We find a shell-thickness-dependent catalytic activity, indicating that not only the nature of the surface but also several subsurface layers play a crucial role in the catalytic performance, and rationalize this finding using density functional theory calculations. Our results open up an alternative avenue for the structural design of bimetallic catalysts.
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Adsorption processes are often governed by weak interactions for which the estimation of entropy contributions by means of the harmonic approximation is prone to be inaccurate. Thermodynamic integration (TI) from the harmonic to the fully interacting system (λ-path integration) can be used to compute anharmonic corrections. Here, we combine TI with (curvilinear) internal coordinates in periodic systems to make the formalism available in computational studies. Our implementation of ab initio molecular dynamics in VASP is independent of the reaction path and can be thus applied to study adsorption processes relative to the gas phase and does hence provide a useful tool for computational catalysis. We discuss the application of the approach on three model systems for which exact semianalytical solutions exist and illustrate and quantify the importance of anharmonic vibrations, hindered rotations, and hindered translations (dissociation). Eventually, we apply the method to study the adsorption of small adsorbates in a zeolite (H-SSZ-13).