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At least 217 records · Page 12

Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes

The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.

HAADF-STEM↗

On the contribution of Pair Distribution Function (PDF) to the characterization of nanocrystalline MOFs: The case of M-MOF-74

Nanoporous Metal-Organic Frameworks (MOFs) have a great potential in so many industrial applications including heterogeneous catalysis and gas storage/capture/separation. MOF-74 is one of the most interesting MOFs in an academic context, as it contains open metal sites, possesses high versatility in metal nature, and can be prepared with so small crystal size. As a consequence, the catalytic activity of these nanocrystalline materials is superior to that given by their conventional counterparts. However, their characterization by conventional X-ray diffraction (XRD) is insufficient. Here, we present a joint study of XRD and Pair Distribution Function (PDF) -both acquired under synchrotron radiation- of a series of nanocrystalline M-MOF-74 materials (M = Mg, Co, Ni, Cu or Zn) prepared at room temperature. Whereas the XRD continues being lacking for an adequate structural characterization, PDF provides key structural information at medium and short range and, therefore, is ideal for studying such nano-domains. It was confirmed that these materials are exclusively composed by MOF-74 phase and that their poor ability to diffract is due solely to their eminent nanocrystallinity, which resulted to be even more pronounced than it has been previously estimated. Beyond Scherrer-like approaches, PDF can give direct information about the range of crystal size in nanocrystalline materials. Moreover, the technique is also able to detect slight structural deviations in short-range environments, just like it is made clear in the case of Cu-MOF-74 compared with the rest of M-MOF-74 materials, which possesses a marked Jahn-Teller effect in the octahedral coordination of Cu.

36 MATERIALS SCIENCE↗

Comment on “STM study of the (111) and (100) surfaces of PdAg, Surf. Sci. 417 (1998) 292–300" and references therein

Investigation of isolated, single atoms on the surfaces of alloys is of great interest in the field of heterogeneous catalysis. Prior studies by Nieuwenhuys, etal. [Surf. Sci. 417 (1998) 292–300 and references therein] showed that annealing the (111) surface of a PdAg bulk alloy yielded a surface with ~5% Pd, predominantly in the form of single atoms, rendering it an ideal model for investigating the reactivity of single Pd atoms. Herein, new evidence is reported that establishes the bulk composition of the PdAg(111) alloy studied previously is 67 % Ag and 33 % Pd, whereas it was reported to be 33 % Ag and 67 % Pd in the prior studies. Furthermore, the bulk composition of a crystal derived from the same PdAg alloy boule used previously was determined using energy-dispersive X-ray spectroscopy (EDS)—a bulk sensitive technique. Surface-sensitive measurements, including X-ray photoelectron spectroscopy, were also performed and are in good agreement with the prior studies by Nieuwenhuys, etal.

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The surface chemistry of cuprous oxide

The chemical and electronic properties of copper combined with its large natural abundance lend this material to impact a wide range of technological applications, including heterogeneous catalysis. The reactivity of copper in its Cu 1+ oxidation state makes this specific configuration relevant in various chemical reactions, but the facile redox properties of copper make the isolation of individual states for fundamental studies difficult. Here, in this study, we review three Cu 2 O model systems used to study the interaction of Cu 1+ with small molecules making use of surface science techniques: Cu 2 O/Cu(111), thin polycrystalline Cu 2 O films on Cu foil, and bulk Cu 2 O crystals. Advantages and disadvantages of each system are discussed and exemplified through case studies of chemical adsorption and reactivity studies.

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Application of Single-Site Catalysts in the Hydrogen Economy

Catalysts development is an evolutionary process. The generation of new single-metal-site catalysts, with isolated metal atoms dispersed on the surface of substrates, offers maximum atom-utilization efficiency, high specific activity, and novel properties. The unique structure of single-site catalysts also enables their potential to bridge the gap between homogeneous and heterogeneous catalysis. This field is at an early stage, characterized by important discoveries and novel demonstrations of catalytic properties associated with the fine structure of single metal sites; however, specific applications, especially catalytic hydrogenation reactions, are still lacking. Here, we focus on applications of single-site catalysts in the hydrogen economy based on our studies of hydrogen generation/storage via single-metal-site catalysts. We hope this work will inspire the development of single-site catalysts for other applications.

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In situ spectroscopic insights into the redox and acid-base properties of ceria catalysts

Cerium oxide (ceria) plays an important and fascinating role in heterogeneous catalysis as illustrated by its versatile use as a catalyst, a catalyst support, or a promotor in various oxidation and reduction reactions. Central to these reactions is the rich defect chemistry, facile redox capability, and unusual acid-base properties of ceria. Understanding the unique redox and acid-base properties of ceria is essential to build the structure-catalysis relationship so that improved catalytic functions can be achieved for ceria-based materials. Among the characterization toolbox, spectroscopic approach indisputably stands out for its unparalleled power in offering chemical insights into the surface properties of ceria at atomic and molecular level. In this review, we summarize advances in revealing the redox and acid-base properties of ceria via a variety of spectroscopic methods including optical, X-ray, neutron, electronic and nuclear spectroscopy. Both direct spectroscopy characterization and its coupling with probe molecules are analyzed to illustrate how the nature, strength and density of different surface sites are influenced by the pretreatment, the morphology and size of ceria nanoparticles. Further directions in taking advantage of in situ/operando spectroscopy for better understanding the catalysis of ceria-based materials are detailed in the summary and outlook section.

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In-situ and In-operando Cobalt Oxidation Studied by Atom Probe Tomography

Heterogeneous catalysis is one of the pillars of the chemical industry and the “green chemistry” concept. However, the sparse understanding of surface mechanisms at molecular scale impedes development of high-performance catalysts and requires development of new tools and methodologies. Cobalt is notably able to dissociate CO 2 into CO(g) and O 2 (g), allowing further conversion to higher value compounds such as long-chain hydrocarbons. Such application leads inevitably to Co surface oxidation. Finally, from its pure form (Co(0)) to oxidized ones (CoO and Co 3 O 4 ) the formation mechanism remains unclear as well as the surface structure evolution and its influence on the chemical reaction.

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Nanoparticle Tracking to Probe Transport in Porous Media

From the granular and fractured subsurface environment to highly engineered polymer membranes used in pharmaceutical purification, porous materials are ubiquitous in nature and industrial applications. In particular, porous media are used extensively in processes including water treatment, pharmaceutical sterilization, food/beverage processing and heterogeneous catalysis, where hindered mass transport is either essential to the process or a necessary, but undesirable limitation. Unfortunately, there are currently no universal models capable of predicting mass transport based on a description of the porous material because real porous materials are complex, and because many coupled dynamic mechanisms (e.g. adsorption, steric effects, hydrodynamic effects, electrostatic interactions, etc.) give rise to the observed macroscopic transport phenomena. While classical techniques, like nuclear magnetic resonance and dynamic light scattering, provide useful information about mass transport in porous media at the ensemble level, they provide limited insight into the microscopic mechanisms that give rise to complex phenomena such as anomalous diffusion, hindered pore-space accessibility, and unexpected retention under flow, among many others. To address this issue, we have developed refractive index matching imaging systems, combined with single-particle tracking methods, allowing the direct visualization of single particle motion within a variety of porous materials. Here, we summarize our recent efforts to advance the understanding of nanoparticle transport in porous media using single-particle tracking methods in both fundamental and applied scenarios. First, we describe the basic principles for two-dimensional and three-dimensional single-particle tracking in porous materials. Then, we describe concrete examples of nanoparticle transport in porous materials from two perspectives: (1) understanding fundamental elementary particle transport processes in porous media, including pore accessibility and cavity escape, which limit transport in porous media; (2) facilitating applications in industrial processes, e.g. by understanding the mechanisms of particle fouling and remobilization in filtration membranes. Finally, we provide an outlook of opportunities associated with investigating other types of mass transport in confined environments using single-particle tracking methods, including electrophoretic and self-propelled motion.

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Fiber Composites of Metal–Organic Frameworks

The high chemical and structural diversity of metal–organic frameworks (MOFs), which are porous crystalline materials, has attracted significant academic and industrial interest. However, the poor processability of MOF powders limits their full potential in practical applications. Toward this end, MOF-based composite materials increase the framework robustness and subsequent utility. Among these hybrid materials, MOF composites prepared on commercially available textile fibers offer the high flexibility needed for important applications—such as heterogeneous catalysis, chemical sensing, pollutant removal, and drug release—while maintaining the functional properties of MOFs. The ability to further tailor these composites’ shapes for incorporation into industrial equipment increases their potential in applications such as adsorption devices and protective gears. In this Review, we summarize recently reported MOF/fiber fabrication methods and applications. In conclusion, our discussion on the advancements and remaining issues of these production methods segues into several highlighted applications of MOF/fiber composites, especially within adsorption devices and protective gears.

36 MATERIALS SCIENCE↗

Impact of Transition Metal Doping on the Structural and Optical Properties of Halide Perovskites

Metal ion doping into halide perovskite materials is a promising approach to enhance long-term film stability and improve solar cell performance. Moreover, the idea of doping metals into halide perovskites is also driven by applications in heterogeneous catalysis. Here, we investigate the incorporation of the transition metals Pt and Pd into mixed-halide perovskite materials. We find that Pt aggregates in large clusters in iodine- and bromine-rich perovskite film compositions, whereas Pd incorporation depends on the underlying bromine to iodine ratio. Furthermore, by using optical and structural characterization methods, we observe that phase segregation in the perovskite layer is suppressed upon doping of either of these metals into the material. This approach further shows the potential to obtain catalytically active halide perovskite films in which the perovskite can serve as a host matrix.

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Synthesis and Structural Study of Substituted Ternary Nitrides for Ammonia Production

Over the past few decades, inorganic nitride materials have grown in importance in part due to their potential as catalysts for the synthesis of NH 3 , a key ingredient in fertilizer and precursor to industrial chemicals. Of particular interest are the ternary (ABN) or higher-order nitrides with high metal-to-nitrogen ratios that show promise in enhancing NH 3 synthesis reaction rates and yields via heterogeneous catalysis or chemical looping. Although metal nitrides are predicted to be numerous, the stability of nitrogen triple bonds found in N 2 , especially in comparison to the metal–nitrogen bonds, has considerably hindered synthetic efforts to produce complex nitride compounds. In this study, we present an exhaustive down-selection process to identify ternary nitrides for a promising chemical looping NH 3 production mechanism. We also report on a facile and efficient two-step synthesis method that can produce well-characterized η-carbide Co 3 Mo 3 N/Fe 3 Mo 3 N or filled β-manganese Ni 2 Mo 3 N ternaries, as well as their associated quaternary, (Co,Fe) 3 Mo 3 N, (Fe,Ni) 2 Mo 3 N, and (Co,Ni) 2 Mo 3 N, solid solutions. To further explore the quaternary space, syntheses of (Co,Ni) 3 Mo 3 N (Ni ≤ 10 mol %) and Co 3 (Mo,W) 3 N (W ≤ 10 mol %) were also investigated. The structures of the nitrides were characterized via X-ray powder diffraction. The morphology and compositions were characterized with scanning electron microscopy. In conclusion, the multitude of chemically unique, but structurally related, nitrides suggests that properties such as nitrogen activity may be tunable, making the materials of great interest for NH 3 synthesis schemes.

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Observations of Nocturnal Sulfuric Acid Formation in Pittsburgh, PA

Measurements of sulfuric acid (H 2 SO 4 ) and sulfur trioxide (SO 3 ) were conducted in Pittsburgh, Pennsylvania, during field campaigns in Fall 2023 and Fall 2024. These measurements identified nocturnal concentrations of H 2 SO 4 comparable to those of daytime values. Nocturnal H 2 SO 4 concentrations were observed to increase by 5 × 10 5 to 5 × 10 7 molecules cm –3 above background on 16 of the 31 measurement nights. The median peak concentration during events was 6.5 × 10 6 molecules cm –3 , with a maximum of 1.0 × 10 8 molecules cm –3 , exceeding previously reported nighttime concentrations. Increases in H 2 SO 4 concentrations were positively correlated with the anomalously high SO 3 concentrations and condensation sink rates, indicating that the formation of H 2 SO 4 increased to overcome the loss rates to particles. Increases in particulate mass and the mass fraction of metals commonly emitted from coal combustion and steel production were also observed. The air masses were traced back to the southeast of Pittsburgh, a region home to a steel mill, coke plant, and a steel processing plant. The observations indicate a previously unrecognized nighttime formation pathway for H 2 SO 4 , potentially from heterogeneous catalysis with metal or black carbon, originating from steel and coke plant emissions. Further measurements are needed to identify key compounds and chemical processes driving these increases in nocturnal H 2 SO 4 concentrations.

aerosols↗

Stabilization of Dinuclear Rhodium and Iridium Clusters on Layered Titanate and Niobate Supports

Atomically dispersed organometallic clusters can provide well-defined nuclearity of active sites for both fundamental studies as well as new regimes of activity and selectivity in chemical transformations. More recently, dinuclear clusters adsorbed onto solid surfaces have shown novel catalytic properties resulting from the synergistic effect of two metal centers to anchor different reactant species. Difficulty in synthesizing, stabilizing, and characterizing isolated atoms and clusters without agglomeration challenges allocating catalytic performance to atomic structure. Here, we explore the stability of dinuclear rhodium and iridium clusters adsorbed onto layered titanate and niobate supports using molecular precursors. Both systems maintain their nuclearity when Statistical analysis of HAADF-STEM images revealed that rhodium and iridium dimers had mean cluster-to-cluster distances very similar to what is expected from a random distribution of atoms over a large area, indicating that they are dispersed without aggregation. The stability of dinuclear rhodium clusters supported on titanate nanosheets was also investigated by X-ray absorption fine structure (EXAFS), DRIFTS, and first-principles calculations. Both X-ray absorption spectroscopy and HAADF-STEM simulations, guided by density functional theory (DFT)-optimized structure models, suggested that rhodium dimers adsorb onto the nanosheets in an end-on binding mode that is stable up to 100 degrees C under reducing conditions. Finally, this study highlights that crystalline nanosheets derived from layered metal oxides can be used as model supports to selectively stabilize dinuclear clusters, which could have implications for heterogeneous catalysis.

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Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

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Automated Adsorption Workflow for Semiconductor Surfaces and the Application to Zinc Telluride

Surface adsorption is a crucial step in numerous processes, including heterogeneous catalysis, where the adsorption of key species is often used as a descriptor of efficiency. We present here an automated adsorption workflow for semiconductors which employs density functional theory calculations to generate adsorption data in a high-throughput manner. Starting from a bulk structure, the workflow performs an exhaustive surface search, followed by an adsorption structure construction step, which generates a minimal energy landscape to determine the optimal adsorbate-surface distance. An extensive set of energy-based, charge-based, geometric, and electronic descriptors tailored toward catalysis research are computed and saved to a personal user database. Finally, the application of the workflow to zinc telluride, a promising CO 2 reduction photocatalyst, is presented as a case study to illustrate the capabilities of this method and its potential as a material discovery tool.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson–Boltzmann continuum solvation methods with ab initio molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. Additionally, we show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. Therefore, this work provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmarking an Embedded Adaptive Sampling Configuration Interaction Method for Surface Reactions: H 2 Desorption from and CH 4 Dissociation on Cu(111)

Embedded (emb-) correlated wavefunction (CW) theory enables accurate assessments of both ground- and excited-state reaction mechanisms involved in heterogeneous catalysis. Embedded multireference second-order perturbation theory (emb-MRPT2) based on reference wavefunctions generated via embedded complete active space self-consistent field (emb-CASSCF) theory is currently state-of-the-art. However, the factorial scaling of CASSCF limits the size of active space and the complexity of systems that can be studied. In this work, we assess the efficacy of an alternative CW method, adaptive sampling configuration interaction (ASCI)–which enables large active spaces to be used–for studying surface reactions. We couple ASCI with density functional embedding theory (DFET) and benchmark its performance for two reactions: H 2 desorption from and CH 4 dissociation on the Cu(111) surface. Unlike embedded complete active space second-order perturbation theory (emb-CASPT2) that accurately reproduces a measured H 2 desorption barrier, embedded ASCI, using a very large active space (though one that still comprises a small portion of the full set of orbitals) fails to do so. Adding an extra correlation term from embedded Møller–Plesset second-order perturbation theory (emb-MP2) improves the desorption barrier and endothermicity predictions. Thus, the inaccuracy of embedded ASCI comes from the missing dynamic correlation from the many other electrons and orbitals not included in the active space. For CH 4 dissociation, again embedded ASCI overestimates the dissociation barrier compared to emb-CASPT2 predictions. Adding dynamic correlation from emb-MP2 helps correct the barrier. However, this composite approach suffers from double counting of correlation within embedded ASCI followed by emb-MP2 calculations. We therefore conclude that the state-of-the-art emb-MRPT2 based on reference wavefunctions generated via emb-CASSCF remains the method of choice for studying surface reactions. emb-ASCI is useful when large active spaces beyond the limit of emb-CASSCF are essential, such as to study complex surface reactions with significant multiconfigurational character (static correlation) but weak dynamic correlation.

08 HYDROGEN↗

Density Functional Tight-Binding Models for Band Structures of Transition-Metal Alloys and Surfaces across the d -Block

First-principles electronic structure simulations are an invaluable tool for understanding chemical bonding and reactions. While machine-learning models such as interatomic potentials significantly accelerate the exploration of potential energy surfaces, electronic structure information is generally lost. Particularly in the field of heterogeneous catalysis, simulated electron band structures provide fundamental insights into catalytic reactivity. This ab initio knowledge is preserved in semiempirical methods such as density functional tight binding (DFTB), which extend the accessible computational length and time scales beyond first-principles approaches. In this paper here we present Shell-Optimized Atomic Confinement (SOAC) DFTB electronic-part-only parametrizations for bulk and surface band structures of all d-block transition metals that enable efficient predictions of electronic descriptors for large structures or high-throughput studies on complex systems outside the computational reach of density functional theory.

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