CO<Subscript>2</Subscript> activation on single crystal based ceria and magnesia/ceria model catalysts

Novel multifunctional ceria based materials may show an improved performance in catalytic processes involving CO₂ activation and reforming of hydrocarbons. Towards a more detailed understanding of the underlying surface chemistry, we have investigated CO₂ activation on single crystal based ceria and magnesia/ceria model catalysts. All model systems are prepared starting from well-ordered and fully stoichiometric CeO₂(111) films on a Cu(111) substrate. Samples with different structure, oxidation state and compositions are generated, including CeO_2-x/Cu(111) (reduced), MgO/CeO_2-x/Cu(111) (reduced), mixed MgO-CeO₂/Cu(111) (stoichiometric), and mixed MgO-CeO_2-x/Cu(111) (reduced). The morphology of the model surfaces is characterized by means of scanning tunneling microscopy (STM), whereas the electronic structure and reactivity is probed by X-ray photoelectron spectroscopy (XPS). The experimental approach allows us to compare the reactivity of samples containing different types of Ce³⁺, Ce⁴⁺, and Mg²⁺ ions towards CO₂ at a sample temperature of 300 K. Briefly, we detect the formation of two CO₂-derived species, namely carbonate (CO₃ ^2-) and carboxylate (CO₂ ^-) groups, on the surfaces of all investigated samples after exposure to CO₂ at 300 K. In parallel to formation of the carbonate species, slow partial reoxidation of reduced CeO_2-x/Cu(111) occurs at large doses of CO₂. The reoxidation of the reduced ceria is largely suppressed on MgO-containing samples. The tendency for reoxidation of Ce³⁺ to Ce⁴⁺ by CO₂ decreases with increasing degree of intermixing between MgO and CeO_2-x. Additionally, we have studied the stability of the formed carbonate species as a function of annealing temperature.     

Particulate matter analysis at elementary schools in Curitiba,Brazil

The particulate matter indoors and outdoors of the classrooms at two schools in Curitiba, Brazil, was characterised in order to assess the indoor air quality. Information concerning the bulk composition was provided by energy-dispersive x-ray fluorescence (EDXRF). From the calculated indoor/outdoor ratios and the enrichment factors it was observed that S-, Cl- and Zn-rich particles are of concern in the indoor environment. In the present research, the chemical compositions of individual particles were quantitatively elucidated, including low-Z components like C, N and O, as well as higher-Z elements, using automated electron probe microanalysis low Z EPMA. Samples were further analysed for chemical and morphological aspects, determining the particle size distribution and classifying them according to elemental composition associations. Five classes were identified based on major elemental concentrations: aluminosilicate, soot, organic, calcium carbonate and iron-rich particles. The majority of the respirable particulate matter found inside of the classroom was composed of soot, biogenic and aluminosilicate particles. In view of the chemical composition and size distribution of the aerosol particles, local deposition efficiencies in the human respiratory system were calculated revealing the deposition of soot at alveolar level. The results showed that on average 42% of coarse particles are deposited at the extrathoracic level, whereas 24% are deposited at the pulmonary region. The fine fraction showed a deposition rate of approximately 18% for both deposition levels.     

Interaction of NO2 with Model NSR Catalysts: Metal–Oxide Interaction Controls Initial NOx Storage Mechanism

Using scanning tunneling microscopy (STM), molecular‐beam (MB) methods and time‐resolved infrared reflection absorption spectroscopy (TR‐IRAS), we investigate the mechanism of initial NO_x uptake on a model nitrogen storage and reduction (NSR) catalyst. The model system is prepared by co‐deposition of Pd metal particles and Ba‐containing oxide particles onto an ordered alumina film on NiAl(110). We show that the metal–oxide interaction between the active noble metal particles and the NO_x storage compound in NSR model catalysts plays an important role in the reaction mechanism. We suggest that strong interaction facilitates reverse spillover of activated oxygen species from the NO_x storage compound to the metal. This process leads to partial oxidation of the metal nanoparticles and simultaneous stabilization of the surface nitrite intermediate.     

Prediction of the structures of the plant-specific regions of vascular plant cellulose synthases and correlated functional analysis

Seed plants express cellulose synthase (CESA) protein isoforms with non-redundant functions, but how the isoforms function differently is unknown. Compared to bacterial cellulose synthases, CESAs have two insertions in the large cytosolic loop: the relatively well-conserved Plant Conserved Region (P-CR) and a Class Specific Region (CSR) that varies between CESAs. Absent any atomic structure of a plant CESA, we used ab initio protein structure prediction and molecular modeling to explore how these plant-specific regions may modulate CESA function. We modeled P-CR and CSR peptides from Arabidopsis thaliana CESAs representing the six clades of seed plant CESAs. As expected, the predicted wild type P-CR structures were similar. Modeling of the mutant P-CR of Atcesa8 ^R362K (fra6) suggested that changes in local structural stability and surface electrostatics may cause the mutant phenotype. Among CSRs within CESAs required for primary wall cellulose synthesis, the amino sequence and the modeled arrangement of helices was most similar in AtCESA1 and AtCESA3. Genetic complementation of known Arabidopsis mutants showed that the CSRs of AtCESA1 and AtCESA3 can function interchangeably in vivo. Analysis of protein surface electrostatics led to ideas about how the surface charges on CSRs may mediate protein–protein interactions. Refined modeling of the P-CR and CSR regions of GhCESA1 from cotton modified their tertiary structures, spatial relationships to the catalytic domain, and preliminary predictions about CESA oligomer formation. Cumulatively, the results provide structural clues about the function of plant-specific regions of CESA.     

Methane Activation by Platinum: Critical Role of Edge and Corner Sites of Metal Nanoparticles

Complete dehydrogenation of methane is studied on model Pt catalysts by means of state‐of‐the‐art DFT methods and by a combination of supersonic molecular beams with high‐resolution photoelectron spectroscopy. The DFT results predict that intermediate species like CH₃ and CH₂ are specially stabilized at sites located at particles edges and corners by an amount of 50–80 kJ mol^?1. This stabilization is caused by an enhanced activity of low‐coordinated sites accompanied by their special flexibility to accommodate adsorbates. The kinetics of the complete dehydrogenation of methane is substantially modified according to the reaction energy profiles when switching from Pt(111) extended surfaces to Pt nanoparticles. The CH₃ and CH₂ formation steps are endothermic on Pt(111) but markedly exothermic on Pt₇₉. An important decrease of the reaction barriers is observed in the latter case with values of approximately 60 kJ mol^?1 for first C? H bond scission and 40 kJ mol^?1 for methyl decomposition. DFT predictions are experimentally confirmed by methane decomposition on Pt nanoparticles supported on an ordered CeO₂ film on Cu(111). It is shown that CH₃ generated on the Pt nanoparticles undergoes spontaneous dehydrogenation at 100 K. This is in sharp contrast to previous results on Pt single‐crystal surfaces in which CH₃ was stable up to much higher temperatures. This result underlines the critical role of particle edge sites in methane activation and dehydrogenation.     

Rhodium(I)-NHC Complexes Bearing Bidentate Bis-Heteroatomic Acidato Ligands as gem-Selective Catalysts for Alkyne Dimerization

A series of Rh(κ²-BHetA)(η²-coe)(IPr) complexes bearing 1,3-bis-hetereoatomic acidato ligands (BHetA) including carboxylato (O,O), thioacetato (O,S), amidato (O,N), thioamidato (N,S), and amidinato (N,N), have been prepared by reaction of the dinuclear precursor [Rh(μ-Cl)(IPr)(η²-coe)]₂ with the corresponding anionic BHetA species. The Rh^I-NHC-BHetA compounds catalyze the dimerization of aryl alkynes, showing excellent selectivity for the head-to-tail enynes. Among them, the acetanilidato-based catalyst has shown an outstanding catalytic performance reaching unprecedented TOF levels of 2500 h⁻¹ with complete selectivity for the gem-isomer. Investigation of the reaction mechanism supports a non-oxidative pathway in which the BHetA ligand behaves as proton shuttle through intermediate κ¹-HBHetA species. However, in the presence of pyridine as additive, the identification of the common Rh^IIIH(C≡CPh)₂(IPr)(py)₂ intermediate gives support for an alternative oxidative route.     

A procedure for meaningful unsupervised clustering and its application for solvent classification

Artificial neural networks have proven to be a powerful tool for solving classification problems. Some difficulties still need to be overcome for their successful application to chemical data. The use of supervised neural networks implies the initial distribution of patterns between the pre-determined classes, while attribution of objects to the classes may be uncertain. Unsupervised neural networks are free from this problem, but do not always reveal the real structure of data. Classification algorithms which do not require a priori information about the distribution of patterns between the pre-determined classes and provide meaningful results are of special interest. This paper presents an approach based on the combination of Kohonen and probabilistic networks which enables the determination of the number of classes and the reliable classification of objects. This is illustrated for a set of 76 solvents based on nine characteristics. The resulting classification is chemically interpretable. The approach proved to be also applicable in a different field, namely in examining the solubility of C₆₀ fullerene. The solvents belonging to the same group demonstrate similar abilities to dissolve C₆₀. This makes it possible to estimate the solubility of fullerenes in solvents for which there are no experimental data      

Role of solvent and dendritic architecture on the redox core encapsulation

Dendrimers with redox cores can accept, donate, and/or store electrons and are used in nanoscale devices like artificial receptors, magnetic resonance imaging, sensors, light harvesting antennae, and electrical switches. However, the dendrimer molecular architectures can significantly alter the encapsulation of the redox core and charge transfer pathways, thereby changing the electron transfer rates. In this study, we used molecular dynamics simulations to investigate the role of solvent and peripheral groups on molecular structure and core encapsulation of iron-sulfur G2-benzyl ether dendrimers in polar and nonpolar solvent. We found that the dendrimer branches collapse in water and swell in chloroform. The presence of the long hydrophobic alkyl groups at the periphery deters the encapsulation of the core in water which may cause an increase in electron transfer rate. However, in chloroform, the dendrimer branches remain in the extended form, which leads to an increased radius of gyration. Our results suggest that peripheral alkyl chains in dendrimers cause steric hindrance, which prevents branches from back folding in chloroform solvent, but in water it reverses the trend. Overall, the presence of a hydrophobic interior and hydrophilic periphery in a dendrimer improves core encapsulation in water while hindering encapsulation in chloroform.