Catalytic NH3 oxidation affected by the nanometric roughness of the platinum overlayer.

Pulsed cathodic arc-plasma deposition was employed to create a few nanometre-thick Pt overlayer on a 50 µm-thick Fe-Cr-Al metal (SUS) foil, resulting in an effective NH3 oxidation catalyst fabrication. This catalyst exhibited a turnover frequency (TOF) exceeding 100 times that of Pt nanoparticles. In this study, Pt overlayer catalysts with varying degrees of surface roughness were fabricated using different metal foil substrates: mirror-polished (Pt/p-SUS), unpolished (Pt/SUS) and roughened by the formation of a surface oxide layer (Pt/Al2O3/SUS). The nanoscale roughness was comprehensively analysed using electron microscopy, laser scanning confocal microscopy and chemisorption techniques. NH3 oxidation activity, measured at 200 °C, followed an increasing trend in the order of Pt/Al2O3/SUS < Pt/SUS < Pt/p-SUS, despite a decrease in the apparent Pt surface area in the same order. Consequently, the calculated TOF was markedly higher for Pt/p-SUS (267 min-1) compared to Pt/SUS (107 min-1) and Pt/Al2O3/SUS (≤22 min-1). The smooth Pt overlayer surface also favoured N2 yield over N2O at this temperature. This discovery enhances our fundamental understanding of high-TOF NH3 oxidation over Pt overlayer catalysts, which holds significance for the advancement and industrial implementation of selective NH3 oxidation processes.

One-pot gram-scale rapid synthesis of MN4 complexes with 14-membered ring macrocyclic ligand as a precursor for carbon-based ORR and CO2RR catalysts.

Herein, CoN4, CuN4, and NiN4 complexes with a 14-membered ring hexaazamacrocycle ligand H2HAM were synthesised as precursors for ORR and CO2RR catalysts via a one-pot, gram-scale synthesis procedure, which involved microwave heating for only 10 min. Detailed structures of the obtained 14MR-MN4 complex were revealed by single-crystal X-ray diffraction measurements.

Atomic-Scale 3D Structure of a Supported Pd Nanoparticle Revealed by Electron Tomography with Convolution Neural Network-Based Image Inpainting.

Electron tomography based on scanning transmission electron microscopy (STEM) is used to analyze 3D structures of metal nanoparticles on the atomic scale. However, in the case of supported metal nanoparticle catalysts, the supporting material may interfere with the 3D reconstruction of metal nanoparticles. In this study, a deep learning-based image inpainting method is applied to high-angle annular dark field (HAADF)-STEM images of a supported metal nanoparticle to predict and remove the background image of the support. The inpainting method can separate an 11 nm Pd nanoparticle from the θ-Al2 O3 support in HAADF-STEM images of the θ-Al2 O3 -supported Pd catalyst. 3D reconstruction of the extracted images of the Pd nanoparticle reveals that the Pd nanoparticle adopts a deformed structure of the cuboctahedron model particle, resulting in high index surfaces, which account for the high catalytic activity for methane combustion. Using the xyz coordinate of each Pd atom, the local Pd-Pd bond distance and its variance in a real supported Pd nanoparticle are visualized, showing large strain and disorder at the Pd-Al2 O3 interface. The results demonstrate that 3D atomic-scale analysis enables atomic structure-based understanding and design of supported metal catalysts.

Catalysts informatics: paradigm shift towards data-driven catalyst design.

Designing catalysts is a challenging matter as catalysts are involved with various factors that impact synthesis, catalysts, reactor and reaction. In order to overcome these difficulties, catalysts informatics is proposed as an alternative way to design and understand catalysts. The underlying concept of catalysts informatics is to design the catalysts from trends and patterns found in catalysts data. Here, three key concepts are introduced: experimental catalysts database, knowledge extraction from catalyst data via data science, and a catalysts informatics platform. Methane oxidation is chosen as a prototype reaction for demonstrating various aspects of catalysts informatics. This work summarizes how catalysts informatics plays a role in catalyst design. The work covers big data generation via high throughput experiments, machine learning, catalysts network method, catalyst design from small data, catalysts informatics platform, and the future of catalysts informatics via ontology. Thus, the proposed catalysts informatics would help innovate how catalysts can be designed and understood.

Cr-Fe-Ni-Cu Quaternary Nanostructure as a Substitute for Precious Metals in Automotive Three-Way Catalysts.

The replacement of precious metals (Rh, Pd, and Pt) in three-way catalysts with inexpensive and earth-abundant metal alternatives is an ongoing challenge. In this research, we examined various quaternary metal catalysts by selecting from six 3d transition metals, i.e., Cr, Mn, Fe, Co, Ni, and Cu, equimolar amounts (0.1 mol each), which were prepared on the Al2O3 support (1 mol Al) using H2 reduction treatment at 900 °C. Among 15 combinations, the best catalytic performance was achieved by the CrFeNiCu system. Light-off of NO-CO-C3H6-O2-H2O mixtures proceeded at the lowest temperature of ≤200 °C for CO, ≤300 °C for C3H6, and ≤400 °C for NO when the molar fraction of Cr in Cr x Fe0.1Ni0.1Cu0.1 was around x = 0.1. The activity for CO/C3H6 oxidation was superior to that of reference Pt/Al2O3 catalysts but was less active for NO reduction. The structural analysis using scanning transmission electron microscopy and X-ray absorption spectroscopy showed that the as-prepared catalyst consisted of FeNiCu alloy nanoparticles dispersed on the Cr2O3-Al2O3 support. However, the structural change occurred under a catalytic reaction atmosphere, i.e., producing NiCu alloy nanoparticles dispersed on a NiFe2O4 moiety and Cr2O3-Al2O3 support. The oxidation of CO/C3H6 can be significantly enhanced in the presence of Cr oxide, resulting in a faster decrease in O2 concentration and thus regenerating the NiCu metallic surface, which is active for NO reduction to N2.

Infusion of Variable Chemical Structure to Tune Stacking among Metal-Organic Layers in 2D Nano MOFs.

Invited for the cover of this issue is the group of Biplab Manna at the University of Kumamoto. The image depicts various kinds of stacking between the metal-organic layers of MOFs. Read the full text of the article at 10.1002/chem.202201665.

Infusion of Variable Chemical Structure to Tune Stacking among Metal-Organic Layers in 2D Nano MOF.

Thickness of two-dimensional (2D) metal-organic frameworks (MOFs) govern their intriguing functionalities. Primarily this thickness is controlled by the stacking between the metal-organic layers (MOL). It is observed that until now such modulating factors for stacking efficiency of MOL are not well studied. Here, we report a fundamental hypothesis to comprehend regulation of stacking efficiency among MOLs as a function of chemical structure of organic ligands (dicarboxylic acids and pillar linkers). This basically involves a series of isostructural three-dimensional (3D) MOFs which contain linkers of variable chemical nature that could be depillared to generate 2D stacked MOFs of different thickness. Depending on the linkers, we encountered the formation of single MOL to stacked multiple MOLs as evidenced from atomic force microscopic and other experimental analysis. The present study gives a concrete correlation between the stacking within 2D MOFs (from monolayer to multilayers), and their 3D counter parts, which may provide a thickness tuning pathway for 2D MOFs.

Synthesis of Heterogeneous Catalysts in Catalyst Informatics to Bridge Experiment and High-Throughput Calculation.

The coupling of high-throughput calculations with catalyst informatics is proposed as an alternative way to design heterogeneous catalysts. High-throughput first-principles calculations for the oxidative coupling of methane (OCM) reaction are designed and performed where 1972 catalyst surface planes for the CH4 to CH3 reaction are calculated. Several catalysts for the OCM reaction are designed based on key elements that are unveiled via data visualization and network analysis. Among the designed catalysts, several active catalysts such as CoAg/TiO2, Mg/BaO, and Ti/BaO are found to result in high C2 yield. Results illustrate that designing catalysts using high-throughput calculations is achievable in principle if appropriate trends and patterns within the data generated via high-throughput calculations are identified. Thus, high-throughput calculations in combination with catalyst informatics offer a potential alternative method for catalyst design.

Synergistic Strengthening in Graphene Oxide and Oxidized Single-walled Carbon Nanotube Hybrid Material for use as Electrolytes in Proton Exchange Membrane Fuel Cells.

Herein, we report an efficient proton exchange membrane formed from a synergistic combination of graphene oxide (GO) and oxidized single-walled carbon nanotube (CNTOX) by the freeze-drying route that gives rise to enhanced fuel cell power density. At 25 °C and 100% relative humidity (RH), the 3DGO-CNTOX hybrid shows remarkably high out-of-plane and in-plane proton conductivities of 6.64×10-2 and 5.08 S cm-1 , respectively. Additionally, the measured performance using prepared films as proton conduction membranes in a proton exchange membrane fuel cell (PEMFC) exhibited a peak power density of 117.21 mW cm-2 . The high performance of these films can be ascribed to the freeze-dried-driven structural morphology of 3DGO-CNTOX that facilitates higher water retention capacity as well as the synergistic strengthening effect between GO and CNTOX with a highly interconnected proton conduction network. The current results imply that the new 3DGO-CNTOX hybrid material has potential for wide application as a proton exchange membrane.

High Proton Conductivity of 3D Graphene Oxide Intercalated with Aromatic Sulfonic Acids.

The development of efficient proton conductors that are capable of high power density, sufficient mechanical strength, and reduced gas permeability is challenging. Herein, we report the development of a series of aromatic sulfonic acid/graphene oxide hybrid membranes incorporating benzene sulfonic acid (BS), naphthalene sulfonic acid (NS), naphthalene disulfonic acid (DS) or pyrene sulfonic acid (PS) using a facile freeze dried method. For out-of-plane proton conductivity, the 3DGO-BS and 3DGO-NS yielded proton conductivities of 4.4×10-2  S cm-1 and 3.1×10-2  S cm-1 , respectively; this represents a two-times higher value than that which occurs for three dimensional graphene oxide (3DGO). Additionally, the respective prepared films as membranes in a proton exchange membrane fuel cell (PEMFC) show maximum power density of 98.76 mW cm-2 for 3DGO-NS while it is 92.75 mW cm-2 for 3DGO-BS which are close to double that obtained for 3DGO (50 mW cm-2 ).

High Durability of a 14-Membered Hexaaza Macrocyclic Fe Complex for an Acidic Oxygen Reduction Reaction Revealed by In Situ XAS Analysis.

Nonplatinum metal (NPM) catalysts for the oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs) have been developed; however, NPM catalysts still need to be improved in terms of both their catalytic activity and durability. To overcome these problems, an Fe active site contained within a more compact ligand than conventional, porphyrinic, 16-membered ring ligands, or more specifically, a hexaaza macrocyclic ligand with a 14-membered ring (14MR), was developed. In this study, the durability of the Fe-14MR complex was compared to that of Fe phthalocyanine (FePc), which has a 16-membered ring ligand, using in situ X-ray absorption spectroscopy; demetalation of the Fe complexes was directly observed during electrochemical experiments performed under acidic ORR conditions. It was found that Fe-14MR is significantly more resistant to demetalation than FePc during the ORR.

Data science assisted investigation of catalytically active copper hydrate in zeolites for direct oxidation of methane to methanol using H2O2.

Dozens of Cu zeolites with MOR, FAU, BEA, FER, CHA and MFI frameworks are tested for direct oxidation of CH4 to CH3OH using H2O2 as oxidant. To investigate the active structures of the Cu zeolites, 15 structural variables, which describe the features of the zeolite framework and reflect the composition, the surface area and the local structure of the Cu zeolite active site, are collected from the Database of Zeolite Structures of the International Zeolite Association (IZA). Also analytical studies based on inductively coupled plasma-optical emission spectrometry (ICP-OES), X-ray fluorescence (XRF), N2 adsorption specific surface area measurement and X-ray absorption fine structure (XAFS) spectral measurement are performed. The relationships between catalytic activity and the structural variables are subsequently revealed by data science techniques, specifically, classification using unsupervised and supervised machine learning and data visualization using pairwise correlation. Based on the unveiled relationships and a detailed analysis of the XAFS spectra, the local structures of the Cu zeolites with high activity are proposed.

Representing the Methane Oxidation Reaction via Linking First-Principles Calculations and Experiment with Graph Theory.

Representing the chemical reaction is a challenging matter faced in chemistry due to the complex molecular interactions and difficulties faced when determining intermediate reactions that may occur throughout the reaction. Graph theory and network analysis are used with first-principles calculations and experiments to investigate possible intermediate reactions that may occur during a reaction; in this case, catalyst-free methane oxidation is chosen as the prototype reaction. Network analysis is used to help illuminate several key intermediate compounds that potentially appear throughout the course of the prototype reaction and the detailed mechanisms of methane oxidation while showing good agreement with experimental data. Presenting the chemical reaction as a network, therefore, makes it possible to link experimental and computational data in a space that accounts for the impact of intermediate reactions upon the outcome of the overall reaction, thereby making network analysis an alternative method for representing chemical reactions.

Nanometric Iridium Overlayer Catalysts for High-Turnover NH3 Oxidation with Suppressed N2O Formation.

In the present study, we prepared a 12 nm thick Ir overlayer via pulsed cathodic arc plasma deposition on a 50 µm thick Fe-Cr-Al metal (SUS) foil. Using this thin-film catalyst made NH3-O2 reactions more environmentally benign due to a much lower selectivity for undesirable N2O (<5%) than that of a Pt overlayer (∼70%) at 225 °C. Despite its small surface area, Ir/SUS exhibited promising activity as an ammonia slip catalyst according to a turnover frequency (TOF) >70-fold greater than that observed with conventional Ir nanoparticle catalysts supported on γ-Al2O3. We found that the high-TOF NH3 oxidation was associated with the stability of the metallic Ir surface against oxidation by excess O2 present in simulated diesel exhaust. Additionally, we found that the Ir overlayer structure was thermally unstable at reaction temperatures ≥400 °C and at which point the Ir surface coverage dropped significantly; however, thermal deterioration was substantially mitigated by inserting a 250 nm thick Zr buffer layer between the Ir overlayer and the SUS foil substrate (Ir/Zr/SUS). Although N2O formation was suppressed by NH3 oxidation over Ir/Zr/SUS, other undesired byproducts (i.e., NO and NO2) were readily converted to N2 by coupling with a V2O5-WO3/TiO2 catalyst in a second reactor for selective catalytic reduction by NH3. These results demonstrated that this tandem reactor configuration converted NH3 to N2 with nearly complete selectivity at a range of 200-600 °C in the presence of excess O2 (8%) and H2O (10%).

Thermal Deactivation of Pd/CeO2-ZrO2 Three-Way Catalysts during Real Engine Aging: Analysis by a Surface plus Peripheral Site Model.

The thermal deactivation of Pd/CeO2-ZrO2 (Pd/CZ) three-way catalysts was studied via nanoscale structural characterization and catalytic kinetic analysis to obtain a fundamental modeling concept for predicting the real catalyst lifetime. The catalysts were engine-aged at 600-1100 °C and used for chassis dynamometer driving test cycles. Observations using an electron microscope and chemisorption experiments showed that the Pd particle size significantly changed in the range of 10-550 nm as a function of aging temperatures. The deactivated catalyst structure was modeled using different-sized hemispherical Pd particles that were in intimate contact with the support surface. Therefore, Pd/CZ contained two types of surface Pd sites residing on the surface of a hemisphere (Pds) and circular periphery of the Pd/CZ interface (Pdb), whereas a reference catalyst, Pd/Al2O3, contained only Pds. In all Pd particle sizes investigated herein, Pd/CZ exhibited higher reaction rates than Pd/Al2O3, which nonlinearly increased with increasing slope as the weight-based number of surface-exposed Pd atoms ([Pds] + [Pdb]) increased. This finding contrasted with that of Pd/Al2O3, where the reaction rate linearly increased with [Pds]. When the Pds sites in both catalysts were equivalent in terms of their specific activities, the activity difference between Pd/CZ and Pd/Al2O3 corresponded to the contribution from Pdb, where oxygen storage/release to/from CZ played a key role. This contribution linearly increased with [Pdb] and therefore decreased with Pd sintering. Although both Pds and Pdb sites showed nearly constant turnover frequencies despite the difference in the Pd particle size, the values for Pdb were more than 2 orders of magnitude greater than those for Pds when assuming a single-atom width one-dimensional Pdb row model. These results suggest that the thermal deterioration of the three-phase boundary site, where Pd, CZ, and the gas phase meet, determines the activity under surface-controlled conditions.

Selective Hydrogenation of Cinnamaldehyde over the Stepped and Plane Surface of Pd Nanoparticles with Controlled Morphologies by CO Chemisorption.

Carbon monoxide (CO) molecules are attracting attention as capping agents that control the structure of metal nanoparticles. In this study, we aimed to control the shape and surface structure of Pd particles by reducing the supported Pd precursor with CO. The reduction of Pd nanoparticles with CO promoted the exposure of step sites and generated spherical and concave-tetrahedral Pd particles on carbon and SiO2 supports. On the other hand, conventional H2-reduced Pd particles show a flattened shape. The preferential exposure of the step sites by the adsorbed CO molecules was supported by the density functional theory-calculated surface energy and the Wulff construction. Morphology- and surface-controlled Pd nanoparticles were used to study the surface structure and morphology effects of Pd nanoparticles on cinnamaldehyde (CAL) hydrogenation. With an increase in the fraction of step sites on Pd nanoparticles, the hydrogenation activity and selectivity of hydrocinnamaldehyde (HCAL) increased. On step sites, the adsorption of the C═C bond of CAL proceeded preferentially, and HCAL was efficiently and selectively generated.

Enhancement of Alkaline Hydrogen Oxidation Reaction of Ru-Ir Alloy Nanoparticles through Bifunctional Mechanism on Ru-Ir Pair Site.

Anion exchange membrane fuel cells (AEMFCs) are being developed for practical use. However, it is necessary to improve the hydrogen oxidation reaction (HOR) under alkaline conditions to enhance the performance of AEMFCs. In this study, carbon-supported Ru-Ir alloy nanoparticle catalysts (Ru-Ir/C) were developed because they offer higher HOR activity compared with the Pt-based catalysts. The mechanism of HOR enhancement on Ru-Ir/C was studied to reveal the effect of the surface composition of Ru/Ir on the HOR activity. The results showed that the HOR activity is related to the surface pair probability of Ru-Ir, Ru-Ru, and Ir-Ir but not to the hydrogen binding energy (HBE). In addition, the Ru-Ir pair site was found to be highly active, which can promote the HOR through a bifunctional mechanism that involves Ru-Ir pairs providing reactive OH- and H species, respectively.

Data-Driven Identification of the Reaction Network in Oxidative Coupling of the Methane Reaction via Experimental Data.

Identifying details of chemical reactions is a challenging matter for both experiments and computations. Here, the reaction pathway in oxidative coupling of methane (OCM) is investigated using a series of experimental data and data science techniques in which data are analyzed using a variety of visualization techniques. Data visualization, pairwise correlation, and machine learning unveil the relationships between experimental conditions and the selectivities of CO, CO2, C2H4, C2H6, and H2 in the OCM reaction. More importantly, the reaction network for the OCM reaction is constructed on the basis of the scores provided by machine learning and experimental data. In particular, the proposed reaction map not only contains the chemical compound but also contains experimental conditions. Thus, data-driven identification of chemical reactions can be achieved in principle via a series of experimental data, leading to more efficient experimental design and catalyst development.

Structure-Activity Relationship of Iron Oxides for NO Reduction in the Presence of C3 H6 , CO, and O2.

Spinel-type NiFe2 O4 exhibited the highest NO reduction activity among base-metal oxides under simulated exhaust of a gasoline-powered vehicle. The structure-activity relationship of iron oxides has been investigated through both experimental and computational studies. Spinel iron oxide (γ-Fe2 O3 ) exhibited a much higher NO reduction activity than that of iron oxide with other structures (α-Fe2 O3 and LaFeO3 ). Operando IR measurements clarified that the spinel structure facilitated the reaction between NOx and adsorbed oxidized hydrocarbon or cyanide species. The high reactivity of the spinel structure was ascribed to the high adsorption energy of NO, as elucidated by DFT calculations. Furthermore, molecular orbital calculations demonstrated that the local coordination structure of the spinel iron oxide induced the involvement of not only σ but also π orbitals during NO adsorption on Fe atoms. This work clarified the origin of the structure-dependent activity of metal oxides, with a focus on their local coordination structures.

Identification of active sites in CO oxidation over a Pd/Al2O3 catalyst.

The active sites of Pd/Al2O3 catalysts for CO oxidations were identified by investigating the dependence of CO oxidation activities on the surface structure and morphology of Pd nanoparticles. The maximum catalytic activity was obtained for Pd particles approximately 2 nm in particle size. We performed structural analyses on the Pd surface through infrared (IR) spectroscopy of the adsorbed CO molecules. A positive correlation was obtained between catalytic activity and the fraction of linear CO adsorbed on Pd corner sites and Pd(111) facets, indicating that these sites are highly active for CO oxidation. X-ray absorption fine structure (XAFS) and spherical aberration-corrected scanning transmission electron microscopy (Cs-STEM) measurements demonstrated that Pd nanoparticles less than 2 nm in particle size with amorphous-like structures and Pd particles with large, well-ordered structures favor the formation of a high fraction of corner sites and Pd(111) facets, respectively.