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At least 145 records · Page 8

A measure of active interfaces in supported catalysts for high-temperature reactions

Formulating knowledge of structure-function relationships in heterogeneous catalysis is central to the design of efficient catalysts; yet, the elucidation of dominant reaction sites has remained as a challenge. Here, in this paper, we present a methodology that can be used to visualize metal-gas and metal-oxide-gas interfaces in three dimensions and to quantify their catalytic activity levels. As a case study, CH 4 oxidation occurring in a Pt/CeO 2 system is chosen. By employing thermally robust Pt@CeO 2 model catalysts with size-tunable and monodisperse cores, and gas-permeable shells, we reconstruct a series of structures in 3D via electron tomography and match the information to activity data and theoretical calculations. This strategy reveals that two different interfaces catalyze the CH 4 oxidation and that their contribution to the overall rate changes with the Pt size, temperature, and gas atmosphere. Our results provide an analytic platform on which to explore reaction pathways and mechanisms applicable to multiple reactions and materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of machine learning to discover new intermetallic catalysts for the hydrogen evolution and the oxygen reduction reactions

The adsorption energies for hydrogen, oxygen, and hydroxyl were calculated by means of density functional theory on the lowest energy surface of 24 pure metals and 332 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B taking into account the effect of biaxial elastic strains. This information was used to train two random forest regression models, one for the hydrogen adsorption and another for the oxygen and hydroxyl adsorption, based on 9 descriptors that characterized the geometrical and chemical features of the adsorption site as well as the applied strain. All the descriptors for each compound in the models could be obtained from physico-chemical databases. The random forest models were used to predict the adsorption energy for hydrogen, oxygen, and hydroxyl of ≈2700 binary intermetallic compounds with stoichiometries AB, A 2 B, and A 3 B made of metallic elements, excluding those that were environmentally hazardous, radioactive, or toxic. This information was used to search for potential good catalysts for the HER and ORR from the criteria that their adsorption energy for H and O/OH, respectively, should be close to that of Pt. Further, this investigation shows that the suitably trained machine learning models can predict adsorption energies with an accuracy not far away from density functional theory calculations with minimum computational cost from descriptors that are readily available in physico-chemical databases for any compound. Moreover, the strategy presented in this paper can be easily extended to other compounds and catalytic reactions, and is expected to foster the use of ML methods in catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A deep learning approach for semantic segmentation of unbalanced data in electron tomography of catalytic materials

In computed TEM tomography, image segmentation represents one of the most basic tasks with implications not only for 3D volume visualization, but more importantly for quantitative 3D analysis. In case of large and complex 3D data sets, segmentation can be an extremely difficult and laborious task, and thus has been one of the biggest hurdles for comprehensive 3D analysis. Heterogeneous catalysts have complex surface and bulk structures, and often sparse distribution of catalytic particles with relatively poor intrinsic contrast, which possess a unique challenge for image segmentation, including the current state-of-the-art deep learning methods. To tackle this problem, we apply a deep learning-based approach for the multi-class semantic segmentation of a γ-Alumina/Pt catalytic material in a class imbalance situation. Specifically, we used the weighted focal loss as a loss function and attached it to the U-Net’s fully convolutional network architecture. We assessed the accuracy of our results using Dice similarity coefficient (DSC), recall, precision, and Hausdorff distance (HD) metrics on the overlap between the ground-truth and predicted segmentations. Our adopted U-Net model with the weighted focal loss function achieved an average DSC score of 0.96 ± 0.003 in the γ-Alumina support material and 0.84 ± 0.03 in the Pt NPs segmentation tasks. We report an average boundary-overlap error of less than 2 nm at the 90th percentile of HD for γ-Alumina and Pt NPs segmentations. The complex surface morphology of γ-Alumina and its relation to the Pt NPs were visualized in 3D by the deep learning-assisted automatic segmentation of a large data set of high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) tomography reconstructions.

36 MATERIALS SCIENCE↗

Synthesis of Pt 3 Zn 1 and Pt 1 Zn 1 intermetallic nanocatalysts for dehydrogenation of ethane

Pt 3 Zn 1 and Pt 1 Zn 1 intermetallic nanoparticles supported on SiO 2 were synthesized by combining atomic layer deposition (ALD) of ZnO, incipient wetness impregnation (IWI) of Pt, and appropriate hydrogen reduction. Here, the formation of Pt 1 Zn 1 and Pt 3 Zn 1 intermetallic nanoparticles was observed by both X-ray diffraction (XRD) and synchrotron X-ray absorption spectroscopy (XAS). STEM images showed that the 2–3 nm Pt-based intermetallic nanoparticles were uniformly dispersed on a SiO 2 support. The relationships between Pt–Zn intermetallic phases and synthesis conditions were established. In situ XAS measurements at Pt L 3 and Zn K edges during hydrogen reduction provided a detailed image of surface species evolution. Owing to a combined electronic and geometric effect, Pt 1 Zn 1 exhibited much higher reactivity and stability than Pt 3 Zn 1 and Pt in both the direct dehydrogenation and oxidative dehydrogenation of ethane to ethylene reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Activity of Silica-Alumina for the Conversion of Polyethylene into Tunable Aromatics Below Pyrolytic Temperatures

Plastic waste is a mounting problem that lacks global strategy, largely due to inadequate recycling capabilities. One alternative gaining traction in the heterogeneous catalysis community is the upcycling of polyolefins into value-added products, such as hydrogen-free conversion to alkylaromatic compounds over Pt/Al 2 O 3 . Here, we examined the activity of nominally metal-free, mesoporous silica-alumina mixed oxide materials (SiO 2 –Al 2 O 3 ) for the conversion of polyethylene into aromatic compounds at temperatures of and below 280 °C. Yields with the silica-alumina catalysts are comparable to those obtained over Pt(1 wt %)/Al 2 O 3 under identical conditions, and product selectivity can be tuned by altering reaction conditions or the acid site density of the SiO 2 –Al 2 O 3 . Notably, the fraction of polyaromatic products increases with the Brønsted acid site density of the catalyst, as does the degree of polymer deconstruction. These catalysts can be reused without regeneration, and their activity improves with each recycling event, producing soluble product yields up to 83%. Preliminary work on the mechanism of the reaction suggests that acid sites are responsible for initiating depolymerization and aromatization reactions, in analogy to previous work in the literature. Finally, this work showcases the activity of SiO 2 –Al 2 O 3 for polyolefin deconstruction/aromatization at subpyrolytic temperatures and lays the foundation for future studies involving solid acid and bifunctional catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electron donation of non-oxide supports boosts O 2 activation on nano-platinum catalysts

Activation of O 2 is a critical step in heterogeneous catalytic oxidation. Here, the concept of increased electron donors induced by nitrogen vacancy is adopted to propose an efficient strategy to develop highly active and stable catalysts for molecular O 2 activation. Carbon nitride with nitrogen vacancies is prepared to serve as a support as well as electron sink to construct a synergistic catalyst with Pt nanoparticles. Extensive characterizations combined with the first-principles calculations reveal that nitrogen vacancies with excess electrons could effectively stabilize metallic Pt nanoparticles by strong p-d coupling. The Pt atoms and the dangling carbon atoms surround the vacancy can synergistically donate electrons to the antibonding orbital of the adsorbed O 2 . This synergistic catalyst shows great enhancement of catalytic performance and durability in toluene oxidation. The introduction of electron-rich non-oxide substrate is an innovative strategy to develop active Pt-based oxidation catalysts, which could be conceivably extended to a variety of metal-based catalysts for catalytic oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of the Hydrogen Pretreatment of Gallium and Platinum Promoted ZSM-5 for the Ethane Dehydroaromatization Reaction

Here, the performances of gallium and platinum promoted ZSM-5 catalysts, fresh and reduced, were studied for the dehydroaromatization of ethane to aromatics. Fresh and reduced 2% Ga/ZSM-5, 1.5% Ga–0.5% Pt/ZSM-5, and 0.5% Pt/ZSM-5 were tested in a fixed-bed reactor system at 615 °C for 2 h time on stream. It was observed that the hydrogen reduction of the fresh Pt-containing catalysts led to an increase in catalytic conversion. The addition of platinum to the gallium catalyst resulted in an increase in the reducibility of the Ga species on the surface of the zeolite. The GaPt catalysts exhibited an increase in ethane conversion and the stability of aromatic production selectivity over the Ga and Pt catalysts. The as-prepared fresh catalysts were characterized by ICP and BET methods. The fresh and reduced catalysts were further analyzed by XRD, H 2 -TPR, XPS, pyridine DRIFTS, TGA, and TEM.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Distinct Kinetic Signatures of Photodesorption from Metal Nanoparticles

Visible photon fluxes can influence the rate and selectivity of heterogeneously catalyzed reactions on metal nanoparticle surfaces. Models describing the influence of photon fluxes have typically introduced photon flux dependent apparent thermal kinetic parameters (reaction orders, activation energies, binding energies, etc.). This has relied on empirical fitting of reaction rate data, making mechanistic interpretations of how photon fluxes influence elementary step rates challenging and inconsistent with fundamental descriptions of photochemistry on metal surfaces developed from surface science studies. Using the CO adsorption–desorption quasi-equilibrium reaction on Pt/Al 2 O 3 catalysts as a model system, we measured steady state adsorbed CO (CO*) coverages under isothermal and isobaric (1 mbar CO) conditions as a function of temperature (473–573 K) and of 440 nm photon flux ((0.1–5.2) × 10 3 # hv Pt site –1 s –1 ) using in situ IR spectroscopy. Steady state CO* coverage on Pt was photon flux dependent with increasing photon flux causing decreasing coverage, consistent with photons driving CO* desorption rates faster than thermal CO* desorption rates. However, photon flux dependent CO* coverages were essentially temperature independent, inconsistent with models that describe photon effects using perturbations to apparent thermal kinetic parameters. Instead, 120 steady state CO* coverages as a function of temperature and photon flux are quantitatively described by a kinetic model in which the overall desorption rate is a summation of independent thermal and photon induced CO* desorption rates. Site-resolved analysis reveals distinct kinetic parameters for photon driven desorption of CO* from well-coordinated, under-coordinated, and highly under-coordinated Pt sites, with temperature-dependent apparent quantum efficiencies (AQE) consistent with temperature dependence of vibrational quanta distribution of adsorbed CO. The rigorous kinetic rate laws for independent photon and thermal driven pathways allow for predictive modeling of the influence of photon fluxes on the rates of CO* desorption under catalytic conditions. Further, the analysis provides evidence that steady state continuous wave photon fluxes can drive desorption/adsorption reactions on metal surfaces out of thermal equilibrium, reconciling surface science observations of molecular photodesorption with applied catalysis. The work establishes a general kinetic framework to be considered for photon driven processes on metals, and defines catalyst, reaction, and photon flux characteristic design principles for breaking Sabatier limitations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CH 4 steam reforming on Pt + Pd/Al 2 O 3 monolith: impact of Mn 0.5 Fe 2.5 O 4 spinel addition

The performance of Pt + Pd/Al 2 O 3 monolith catalysts was analyzed under a feed (H 2 + CO + CH 4 + NO + O 2 + H 2 O + CO 2 ) simulating the exhaust gas of stoichiometric natural gas vehicles (NGVs). The flow reactor results show enhanced low temperature (<400 °C) CH 4 oxidation activity under cyclic lean/rich feed modulation and with Mn 0.5 Fe 2.5 O 4 (MFO) spinel addition to the platinum group metal (PGM) catalyst. In the absence of the MFO spinel, the PGM catalyst can achieve full CH 4 conversion, but the presence of spinel in the catalyst limits the high temperature (>500 °C) CH 4 conversion. The depletion of gas phase O 2 , as indicated by the detection of products CO and H 2 in the reactor effluent at higher temperature and CH 4 conversion, portends the emergence of steam reforming of CH 4 (SRM). To investigate the cause of the detrimental impact of spinel under the high temperature, net rich regime, we show through a combination of SRM experiments and post-reaction catalyst characterization that SRM is negatively impacted by the accumulation of Mn and Fe spinel species on the PGM catalyst. This is due to the migration of the base metal species and potential encapsulation and blockage of PGM active sites. The latter is supported by density functional theory (DFT) calculations that indicate favorable metal oxide decoration of active Pt step sites. Lastly, a zoned catalyst design is developed that mitigates the detrimental metals migration while exploiting the methane conversion enhancement afforded by spinel oxides under oxygen rich conditions.

03 NATURAL GAS↗

Azo(xy) vs Aniline Selectivity in Catalytic Nitroarene Reduction by Intermetallics: Experiments and Simulations

Intermetallic nanoparticles are promising catalysts in hydrogenation and fuel cell technologies. Much is known about the ability of intermetallic nanoparticles to selectively reduce nitro vs alkene, alcohol, or halide functional groups; less is known about their selectivity toward aniline vs azo or azoxy condensation products that result from the reduction of a nitro group alone. Because azo(xy)arenes bear promise as dyes, chemical stabilizers, and building blocks to functional materials but can be difficult to isolate, developing high surface area nanoparticle catalysts that display azo(xy) selectivity is desirable. To address this question, we studied a family of nanocrystalline group 10 metal (Pd, Pt)- and group 14 metal (Ge, Sn, Pb)-containing intermetallics-Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , Pd 3 Pb, and PtSn-in the catalytic reduction of nitroarenes. In contrast to monometallic Au, Pt, and Pd nanoparticles and "random" PdxSn1 – x nanoalloys, which are selective for aniline, nanoparticles of atomically precise intermetallic Pd 2 Ge, Pd 2 Sn, Pd 3 Sn 2 , and PtSn prefer an indirect condensation pathway and have a high selectivity for the azo(xy) products. The only exception is Pd 3 Pb, the most active among the intermetallic nanoparticles studied here, which is instead selective for aniline. Employing a novel application of molecular dynamics-based on machine learned potentials within a DeePMD framework-to heterogeneous catalysis, we are able to identify key reaction species on the different types of catalysts employed, furthering our understanding of the unique selectivity of these materials. By demonstrating how intermetallic nanoparticles can be as active yet more selective than other more traditional catalysts, this work provides new physical insights and opens new opportunities in the use of these materials in other important chemical transformations and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗

Pd-Ru pair on Pt surface for promoting hydrogen oxidation and evolution in alkaline media

Hydrogen oxidation reaction in alkaline media is critical for alkaline fuel cells and electrochemical ammonia compressors. The slow hydrogen oxidation reaction in alkaline electrolytes requires large amounts of scarce and expensive platinum catalysts. While transition metal decoration can enhance Pt catalysts’ activity, it often reduces the electrochemical active surface area, limiting the improvement in Pt mass activity. Here, we enhance Pt catalysts’ activity without losing surface-active sites by using a Pd-Ru pair. Utilizing a mildly catalytic thermal pyrolysis approach, Pd-Ru pairs are decorated on Pt, confirmed by extended X-ray absorption fine structure and high-angle annular dark-field scanning transmission electron microscopy. Density functional theory and ab-initio molecular dynamics simulations indicate preferred Pd and Ru dopant adsorption. The Pd-Ru decorated Pt catalyst exhibits a mass-based exchange current density of 1557 ± 85 A g –1 metal for hydrogen oxidation reaction, demonstrating superior performance in an ammonia compressor.

25 ENERGY STORAGE↗

In situ Formation of Platinum-Carbon Catalysts in Propane Dehydrogenation

The catalytic production of propylene via propane dehydrogenation (PDH) is a key reaction in the chemical industry. By combining operando transmission electron microscopy with density functional theory analysis, we show that the intercalation and ordering of carbon on Pt interstitials to form Pt-C solid solutions is relevant for increasing propylene production. More specifically, we found that at the point of enhanced propylene formation, the structure of platinum nanoparticles is transformed into a transient caesium chloride-type Pt-C polymorph. At more elevated temperatures, the zincblende and rock salt polymorphs seemingly coexist. When propylene production was highest, multiple crystal structures consisting of Pt and carbon were occasionally found to coexist in one individual nanoparticle, distorting the Pt lattice. Catalyst coking was detected at all stages of the reaction, but did initially not affect all particles. These findings could lead to the development of novel synthesis strategies towards tailoring highly efficient PDH catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthesis of monodisperse high entropy alloy nanocatalysts from core@shell nanoparticles

We report that high-entropy alloy (HEA) nanoparticles (NPs) hold great promise in electrocatalysis because of their nearly unlimited compositions, tailorable active sites, and high durability. However, the synthesis of these compositionally complex structures as monodisperse NPs remains a challenge by colloidal routes because the different rates of metal precursor reduction lead to phase separation. Here, we report the conversion of core@shell NPs into HEA NPs through annealing, with conservation of sample monodispersity. This potentially general route for high-quality HEA NPs was demonstrated by preparing PdCu@PtNiCo NPs via seed-mediated co-reduction, wherein Pt, Ni, and Co were co-deposited on PdCu seeds in solution. These multimetallic NPs were then converted to single-crystalline and single-phase PdCuPtNiCo NPs through annealing. On account of their small particle size, highly dispersed Pt/Pd content, and low elemental diffusivity, these HEA NPs were found to be a highly efficient and durable catalyst for the oxygen reduction reaction. They were also highly selective for the four-electron transfer pathway. We expect that this new synthetic strategy will facilitate the synthesis of new HEA NPs for catalysis and other applications.

36 MATERIALS SCIENCE↗

Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts

Uncertainty analysis, reported experimental literature data, and density functional theory were synthesized to model the effect of surface tin coverage on platinum-based catalysts for nonoxidative propane dehydrogenation to propylene. Here, this study tests four different platinum–tin skin surface models as potential catalytic sites, Pt 3 Sn/Pt(100), PtSn/Pt(100), Pt 3 Sn/Pt(111), and Pt 2 Sn/Pt(211), and compares them to the corresponding pure Pt surface sites using an uncertainty analysis methodology that uses BEEF-vdW with its ensembles (BMwE) to generate the uncertainty for the energies of the intermediates and transition states. One experimental data set with two experimental observations, selectivity to propylene and turnover frequency of propylene, was used as a calibration data set to evaluate the impact of the experimental data on informing the models. This study finds that the prior model for Pt 3 Sn/Pt(100) is the most active and Pt 2 Sn/Pt(211) is the most selective toward propylene. Active sites on the (100) facet have the highest probability of being responsible for C 1 and C 2 product formations (C–C bond cleavage). Increasing the Sn coverage on the (100) surface facet to a PtSn/Pt(100) active site leads to a significantly reduced rate and might explain the experimentally observed higher selectivity of Sn-doped catalysts relative to pure Pt catalysts. Next, this study finds that for all surfaces, except PtSn/Pt(100), the rate-controlling steps are the initial dehydrogenation steps alongside some partially rate-controlling second dehydrogenation steps. For PtSn/Pt(100), only the initial terminal dehydrogenation step to CH 3 CH 2 CH 2 * and second dehydrogenation steps are rate-controlling. Next, the calibrated models for all surfaces were found to be selective toward propylene production and model the reported turnover frequency successfully. Nevertheless, Pt 2 Sn/Pt(211) emerges as the active site with some (minor) evidence as the main active site based on Jeffreys’ scale interpretation of Bayes factors. This observation agrees with prior studies that also found step sites to be most likely the most relevant active sites for pure Pt catalysts. Overall, the results indicate that tin, in addition to affecting the binding strength of the adsorbed species, prevents deeper dehydrogenation (reducing coking) and cracking reactions through increasing activation barriers for unwanted side reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unveiling Spatial and Temporal Dynamics of Plasmon-Enhanced Localized Fields in Metallic Nanoframes through Ultrafast Electron Microscopy

Plasmonic nanomaterials, particularly noble metal nanoframes (NFs), are important for applications such as catalysis, biosensing, and energy harvesting due to their ability to enhance localized electric fields and atomic efficiency via localized surface plasmon resonance (LSPR). Yet the fundamental structure-function relationships and plasmonic dynamics of the NFS are difficult to study experimentally and thus far rely predominately on computational methodologies, limiting their utilization. This study leverages the capabilities of ultrafast electron microscopy (UEM), specifically photon-induced near-field electron microscopy (PINEM), to probe the light-matter interactions within plasmonic NF structures. Here, the effects of shape, size, and plasmonic coupling of Pt@Au core-shell NFs on spatial and temporal characteristics of plasmon-enhanced localized electric fields are explored. Importantly, time-resolved PINEM analysis reveals that the plasmonic fields around hexagonal NF prisms exhibit a spatially dependent excitation and decay rate, indicating a nuanced interplay between the spatial geometry of the NF and the temporal evolution of the localized electric field. These results and observations uncover nanophotonic energy transfer dynamics in NFs and highlight their potential for applications in biosensing and photocatalysis.

Plasmonics↗

Elucidating CO Oxidation Pathways on Rh Atoms and Clusters on the “29” Cu 2 O/Cu(111) Surface

We report single-atom catalysts have attracted a great deal of attention due to their distinct reactivity and potential for cost savings. However, despite the wealth of literature in recent years, identifying the exact nature of the active sites and associated reaction mechanisms remains challenging in many cases. Herein, we take a surface science approach to understand how Rh single atoms and small clusters behave on the thin film “29” Cu 2 O grown on Cu(111). We find that in contrast to Pt, which is present solely as single atoms on the “29” Cu 2 O surface, Rh atoms and clusters coexist and each enable low-temperature CO oxidation, but via different pathways. Specifically, the single Rh atoms produce CO 2 at 444 K via a Mars van Krevelen mechanism whereas the Rh clusters can also dissociate CO, as demonstrated via isotope labeling, and liberate CO 2 at 313 K. Density functional theory (DFT) calculations quantify the energetics of these different pathways and demonstrate that only extended Rh is capable of CO dissociation. Low-temperature scanning tunneling microscopy (STM) reveals that unlike Pt atoms on the same surface, which stay atomically dispersed, the distribution of Rh structures is dependent on pretreatment conditions. DFT calculations reveal the greater tendency of Rh atoms to cluster than Pt, and STM image simulations confirm the active sites. Ambient pressure X-ray photoelectron spectroscopy studies on the same single crystal model systems demonstrate that 1% of a monolayer of Rh on the “29” Cu 2 O thin film significantly accelerates its reduction by CO at 400 K, thus confirming the ultrahigh vacuum surface science findings. Together, these results illustrate how well-defined single crystal experiments are useful in building structure–function relationships that elucidate the reactivity of different ensemble sizes with a level of detail beyond what is possible with high surface area catalysis.

36 MATERIALS SCIENCE↗