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At least 73 records · Page 4

Understanding of Active Sites and Interconversion of Pd and PdO during CH 4 Oxidation

Pd-based catalysts are widely used in the oxidation of CH 4 and have a significant impact on global warming. However, understanding their active sites remains controversial, because interconversion between Pd and PdO occurs consecutively during the reaction. Understanding the intrinsic active sites under reaction conditions is critical for developing highly active and selective catalysts. In this study, we demonstrated that partially oxidized palladium (PdO x ) on the surface plays an important role for CH 4 oxidation. Regardless of whether the initial state of Pd corresponds to oxides or metallic clusters, the topmost surface is PdO x , which is formed during CH4 oxidation. A quantitative analysis using CO titration, diffuse reflectance infrared Fourier-transform spectroscopy, X-ray diffraction, and scanning transmission electron microscopy demonstrated that a surface PdO layer was formed on top of the metallic Pd clusters during the CH 4 oxidation reaction. Furthermore, the time-on-stream test of CH 4 oxidation revealed that the presence of the PdO layer on top of the metallic Pd clusters improves the catalytic activity. Our periodic density functional theory (DFT) calculations with a PdO x slab and nanoparticle models aided the elucidation of the structure of the experimental PdO particles, as well as the experimental C-O bands. The DFT results also revealed the formation of a PdO layer on the metallic Pd clusters. This study helps achieve a fundamental understanding of the active sites of Pd and PdO for CH 4 oxidation and provides insights into the development of active and durable Pd-based catalysts through molecular-level design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Metal–Nitrogen–Carbon Cluster–Decorated Titanium Carbide is a Durable and Inexpensive Oxygen Reduction Reaction Electrocatalyst

Clusters of nitrogen- and carbon-coordinated transition metals dispersed in a carbon matrix (e. g., Fe-N-C) have emerged as an inexpensive class of electrocatalysts for the oxygen reduction reaction (ORR). In this work, it was shown that optimizing the interaction between the nitrogen-coordinated transition metal clusters embedded in a more stable and corrosion-resistant carbide matrix yielded an ORR electrocatalyst with enhanced activity and stability compared to Fe-N-C catalysts. Utilizing first-principles calculations, an electrostatics-based descriptor of catalytic activity was identified, and nitrogen-coordinated iron (FeN 4 ) clusters embedded in a TiC matrix were predicted to be an efficient platinum-group metal (PGM)-free ORR electrocatalyst. Guided by theory, selected catalyst formulations were synthesized, and it was demonstrated that the experimentally observed trends in activity fell exactly in line with the descriptor-derived theoretical predictions. The Fe-N-TiC catalyst exhibited enhanced activity (20 %) and durability (3.5-fold improvement) compared to a traditional Fe-N-C catalyst. It was posited that the electrostatics-based descriptor provides a powerful platform for the design of active and stable PGM-free electrocatalysts and heterogenous single-atom catalysts for other electrochemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Higher loadings of Pt single atoms and clusters over reducible metal oxides: application to C–O bond activation

We develop higher loadings of isolated noble metal atoms and clusters on a mildly reducible metal oxide. Here we demonstrate the approach for Pt supported on TiO 2 and confirmed it by XRD, AC-HAADF-STEM, CO-FTIR, XAS, and XPS. Density functional theory calculations rationalize the experimental stability and the IR shifts using mixtures of CH 3 I and CO. The redispersed catalysts are thermally stable in inert gas or H 2 and afford enhanced selectivity and activity in hydrodeoxygenation reactions compared to metal nanoparticles by creating surface oxygen vacancies that promote C–O cleavage without side reactions. Higher metal loadings, e.g., 1%Pt/TiO 2 , on the oxide surface profoundly increase the activity of the bare oxide catalyst tenfold compared to ultra-low loadings typically used for single atom catalysis.

36 MATERIALS SCIENCE↗

Sulfur-Ligated [2Fe-2C] Clusters as Synthetic Model Systems for Nitrogenase

Metal clusters featuring carbon and sulfur donors have coordination environments comparable to the active site of nitrogenase enzymes. Here, we report a series of di-iron clusters supported by the dianionic yldiide ligands, in which the Fe sites are bridged by two μ 2 -C atoms and four pendant S donors. The [L 2 Fe 2 ] (L = {[Ph 2 P(S)] 2 C} 2– ) cluster is isolable in two oxidation levels, all-ferrous Fe 2 II and mixed-valence Fe II Fe III . The mixed-valence cluster displays two peaks in the Mössbauer spectra, indicating slow electron transfer between the two sites. The addition of the Lewis base 4-dimethylaminopyridine to the Fe2 II cluster results in coordination with only one of the two Fe sites, even in the presence of an excess base. Conversely, the cluster reacts with 8 equiv of isocyanide t BuNC to give a monometallic complex featuring a new C–C bond between the ligand backbone and the isocyanide. The electronic structure descriptions of these complexes are further supported by X-ray absorption and resonant X-ray emission spectroscopies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Confining platinum clusters in indium-modified ZSM-5 zeolite to promote propane dehydrogenation

Designing highly active and stable catalytic sites is often challenging due to the complex synthesis procedure and the agglomeration of active sites during high-temperature reactions. Here, we report a facile two-step method to synthesize Pt clusters confined by In-modified ZSM-5 zeolite. In-situ characterization confirms that In is located at the extra-framework position of ZSM-5 as In + , and the Pt clusters are stabilized by the In-ZSM-5 zeolite. The resulting Pt clusters confined in In-ZSM-5 show excellent propane conversion, propylene selectivity, and catalytic stability, outperforming monometallic Pt, In, and bimetallic PtIn alloys. The incorporation of In + in ZSM-5 neutralizes Brønsted acid sites to inhibit side reactions, as well as tunes the electronic properties of Pt clusters to facilitate propane activation and propylene desorption. The strategy of combining precious metal clusters with metal cation-exchanged zeolites opens the avenue to develop stable heterogeneous catalysts for other reaction systems.

58 GEOSCIENCES↗

Chemical abundances of the young inner-disc open cluster NGC 6705 observed by APOGEE: sodium-rich and not α-enhanced

Previous results in the literature have found the young inner-disc open cluster NGC 6705 to be mildly α-enhanced. We examined this possibility via an independent chemical abundance analysis for 11 red-giant members of NGC 6705. The analysis is based on near-infrared APOGEE spectra and relies on LTE calculations using spherical model atmospheres and radiative transfer. We find a mean cluster metallicity of $\rm [Fe/H] = +0.13 \pm 0.04$, indicating that NGC 6705 is metal-rich, as may be expected for a young inner-disc cluster. The mean α-element abundance relative to iron is $\rm \langle [\alpha /Fe]\rangle =-0.03 \pm 0.05$, which is not at odds with expectations from general Galactic abundance trends. NGC 6705 also provides important probes for studying stellar mixing, given its turn-off mass of M ∼ 3.3 M ⊙ . Its red giants have low 12 C abundances ([ 12 C/Fe] = −0.16) and enhanced 14 N abundances ([ 14 N/Fe] = +0.51), which are key signatures of the first dredge-up on the red giant branch. An additional signature of dredge-up was found in the Na abundances, which are enhanced by [Na/Fe] = +0.29, with a very small non-LTE correction. The 16 O and Al abundances are found to be near-solar. All of the derived mixing-sensitive abundances are in agreement with stellar models of approximately 3.3 M ⊙ evolving along the red giant branch and onto the red clump. As found in young open clusters with similar metallicities, NGC 6705 exhibits a mild excess in the s-process element cerium with $\rm [Ce/Fe] = +0.13\pm 0.07$.

79 ASTRONOMY AND ASTROPHYSICS↗

Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters

Introduction (120 words): Transport of metal ions across the aqueous-organic phase boundary is an essential step in a hydrometallurgical nuclear fuel reprocessing strategy. The study of transport agents for nuclear fuel elements is imperative to guide the design of ligands that boost the separation efficiency of the recovery process from fission products. However, limited studies have been made on the chemistry of these transport agents when complexing with transuranic elements in gas-phase where all surrounding factors are essentially excluded. This work investigates the reagent ligand complexations to transuranic and other metals and their dissociations in the gas phase. Comparisons are made between 4f and 5f elements and between ligands. Methods (120 words): (N,N-diisobutylcarbamoylmethyl)phenyloctylphosphine oxide (CMPO) and N,N,N',N'-tetraoctyldiglycolamide (TODGA) have been selected to complex with metal nitrates. The actinide americium and lanthanides neodymium, samarium, and europium were investigated as part of this work. The lanthanides were selected to act as size and electron configuration analogues of the minor actinides. Metal complexes with two ligands and two nitrates ([M(NO3)2(CMPO)2]+, for example) are studied in Bruker micrOTOF-Q II mass spectrometer equipped with collision-induced dissociation capability. The comparisons of the mass spectra are made in groups of homogenous ligands and mixed TODGA-CMPO ligands clusters. Comparisons are also made based on the complexed metals (Am and lanthanides). Preliminary data (300 words): Collision-induced dissociation mass spectrometry data are collected on two ligands complexed with metal nitrates where the two ligands are homogenous, with (CMPO)2 or (TODGA)2, or heterogeneous, with (TODGA)(CMPO). Several fragmentation patterns are observed among complexes with the CMPO ligand whereas the TODGA ligand commonly dissociates intact from the complex. Most of the metal complexes exhibit similar fragmentation patterns, but there are a few notable deviations in fragmentation patterns between the Am and Ln-bearing complexes. For the [M(CMPO)2(NO3)2]+ complexes, the initial loss of nitrate in the form of nitric acid is observed in all four complexes. However, [Am(CMPO)2(NO3)2]+ exhibits an additional fragmentation not found in the lanthanide complexes. Also, a significantly different ratio of the second nitric acid loss is found in the Am complex. These deviations may indicate the different interaction behaviors between actinides and lanthanides. The [M(TODGA)2(NO3)2]+ complexes exhibit the fragmentation as the loss of one TODGA ligand as an intact form and the loss of nitrate as nitric acid. The Am complex exhibits an additional fragmentation after losing the TOGDA ligand, which is not observed among the Ln complexes. The heterogeneous [M(TODGA)(CMPO)(NO3)2]+ complexes exhibit both similarities and differences between the Am and Ln complexes. For example, the heterogenous Am complex does not exhibit the loss of an intact TODGA ligand while all three Ln complexes do. This indicates that TODGA may bind more strongly to Am than Ln. Additionally, the intensity of the loss of CMPO ligand (as partially or whole) is found to be significantly larger than that of the loss of TODGA (as partially of whole) indicating that TODGA is bound to the metal significantly stronger than CMPO. Planned computational analysis will help understand the deviation in fragmentation behaviors between americium and lanthanide metal centers, or between TODGA and CMPO ligands. Novel aspect (20 words): Gas-phase actinide and lanthanide complex formation and fragmentation provide insight into the coordination environment differences of f-element metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatially Distributed Ramp Reversal Memory in VO 2

Ramp‐reversal memory has recently been discovered in several insulator‐to‐metal transition materials where a non‐volatile resistance change can be set by repeatedly driving the material partway through the transition. This study uses optical microscopy to track the location and internal structure of accumulated memory as a thin film of VO 2 is temperature cycled through multiple training subloops. These measurements reveal that the gain of insulator phase fraction between consecutive subloops occurs primarily through front propagation at the insulator‐metal boundaries. By analyzing transition temperature maps, it is found, surprisingly, that the memory is also stored deep inside both insulating and metallic clusters throughout the entire sample, making the metal‐insulator coexistence landscape more rugged. This non‐volatile memory is reset after heating the sample to higher temperatures, as expected. Diffusion of point defects is proposed to account for the observed memory writing and subsequent erasing over the entire sample surface. By spatially mapping the location and character of non‐volatile memory encoding in VO 2 , this study results enable the targeting of specific local regions in the film where the full insulator‐to‐metal resistivity change can be harnessed in order to maximize the working range of memory elements for conventional and neuromorphic computing applications.

36 MATERIALS SCIENCE↗