Nanoalloy composition-temperature phase diagram for catalyst design: Case study of Ag-Au

By coupling a cluster expansion with density functional theory (DFT) calculations, we determine the configurational thermodynamics (site preferences and occupations) for alloyed nanoparticles (NPs) as functions of composition (c) and temperature (T), exemplified using a 55-atom Ag-Au truncated cuboctahedron NP. The c−T phase diagram for site occupations gives detailed design information for alloyed NP, especially the thermodynamically stable active sites for catalysis and how they change with stoichiometry and processing temperature. Generally, Ag prefers core and Au prefers shell, agreeing with our universal core-shell preference assessed from DFT impurity segregation energies but with interesting multishell configurations having specific active sites

Direct Separation of Short Range Order in Intermixed Nanocrystalline and Amorphous Phases

Diffraction anomalous fine-structure (DAFS) and extended x-ray absorption fine-structure (EXAFS) measurements were combined to determine short range order (SRO) about a single atomic type in a sample of mixed amorphous and nanocrystalline phases of germanium. EXAFS yields information about the SRO of all Ge atoms in the sample, while DAFS determines the SRO of only the ordered fraction. We determine that the first-shell distance distribution is bimodal; the nanocrystalline distance is the same as the bulk crystal, to within 0.01(2)   Å, but the mean amorphous Ge-Ge bond length is expanded by 0.076(19)   Å. This approach can be applied to many systems of mixed amorphous and nanocrystalline phases

Metal Core Bonding Motifs of Monodisperse Icosahedral Au13 and Larger Au Monolayer-Protected Clusters As Revealed by X-ray Absorption Spectroscopy and Transmission Electron Microscopy

The atomic metal core structures of the subnanometer clusters Au13[PPh3]4[S(CH2)11CH3]2Cl2 (1) and Au13[PPh3]4[S(CH2)11CH3]4 (2) were characterized using advanced methods of electron microscopy and X-ray absorption spectroscopy. The number of gold atoms in the cores of these two clusters was determined quantitatively using high-angle annular dark field scanning transmission electron microscopy. Multiple-scattering-path analyses of extended X-ray absorption fine structure (EXAFS) spectra suggest that the Au metal cores of each of these complexes adopt an icosahedral structure with a relaxation of the icosahedral strain. Data from microscopy and spectroscopy studies extended to larger thiolate-protected gold clusters showing a broader distribution in nanoparticle core sizes (183 ± 116 Au atoms) reveal a bulklike fcc structure. These results further support a model for the monolayer-protected clusters (MPCs) in which the thiolate ligands bond preferentially at 3-fold atomic sites on the nanoparticle surface, establishing an average composition for the MPC of Au180[S(CH2)11CH3]40. Results from EXAFS measurements of a gold(I) dodecanethiolate polymer are presented that offer an alternative explanation for observations in previous reports that were interpreted as indicating Au MPC structures consisting of a Au core, Au2S shell, and thiolate monolayer

Critical behavior of ferromagnetic pure and random diluted nanoparticles with competing interactions: variational and Monte Carlo approaches

The magnetic properties and critical behavior of both ferromagnetic pure and metallic nanoparticles having concurrently atomic disorder, dilution and competing interactions, are studied in the framework of an Ising model. We have used both the free energy variational principle based on the Bogoliubov inequality and Monte Carlo simulation. As a case of study for random diluted nanoparticles we have considered the Fe$_{0.5}$Mn$_{0.1}$Al$_{0.4}$ alloy characterized for exhibiting, under bulk conditions, low temperature reentrant spin glass (RSG) behavior and for which experimental and simulation results are available. Our results allow concluding that the variational model is successful in reproducing features of the particle size dependence of the Curie temperature for both pure and random diluted particles. In this last case, low temperature magnetization reduction was consistent with the same type of RSG behavior observed in bulk in accordance with the Almeida-Thouless line at low fields and a linear dependence of the freezing temperature with the reciprocal of the particle diameter was also obtained. Computation of the correlation length critical exponent yielded the values $\nu=0.926\pm 0.004$ via Bogoliubov and$\nu =0.71\pm 0.04$ via Monte Carlo. This fact indicates that even though thermodynamical models can be indeed used in the study of nanostructures and they can reproduce experimental features, special attention must be paid regarding critical behavior. From both approaches, differences in the $\nu$ exponent with respect to the pure Ising model agree with Harris and Fisher arguments.Comment: 11 pages, 11 figures. Submitted to Phys. Rev.

In situ elucidation of the active state of Co-CeOx catalysts in the dry reforming of methane: the important role of the reducible oxide support and interactions with cobalt

The dry reforming of methane was systematically studied over a series (2-30 wt%) of Co (~5nm in size) loaded CeO2 catalysts, with an effort to elucidate the behavior of Co and ceria in the catalytic process using in-situ methods. For the systems under study, the reaction activity scaled with increasing Co loading, and a 10 wt% Co-CeO2 catalyst exhibiting the best catalytic activity and good stability at 500 °C with little evidence for carbon accumulation. The phase transitions and the nature of active components in the catalyst were investigated during pretreatment and under reaction conditions by ex-situ/in-situ techniques including X-ray diffraction (XRD) and ambient-pressure X-ray photoelectron spectroscopy (AP-XPS). These studies showed a dynamical evolution in the chemical composition of the catalysts under reaction conditions. A clear transition of Co3O4 → CoO → Co, and Ce4+ to Ce3+, was observed during the temperature programmed reduction under H2 and CH4. However, introduction of CO2, led to partial re-oxidation of all components at low temperatures, followed by reduction at high temperatures. Under optimum CO and H2 producing conditions both XRD and AP-XPS indicated that the active phase involved a majority of metallic Co with a small amount of CoO both supported on a partially reduced ceria (Ce3+/Ce4+). We identified the importance of dispersing Co, anchoring it onto ceria surface sites, and then utilizing the redox properties of ceria for activating and then oxidatively converting methane while inhibiting coke formation. Furthermore, a synergistic effect between cobalt and ceria and the interfacial site are essential to successfully close the catalytic cycle.Peer ReviewedPostprint (author's final draft

Towards Structural Reconstruction from X-Ray Spectra

We report a statistical analysis of Ge K-edge X-ray emission spectra simulated for amorphous GeO$_2$ at elevated pressures. We find that employing machine learning approaches we can reliably predict the statistical moments of the K$\beta''$ and K$\beta_2$ peaks in the spectrum from the Coulomb matrix descriptor with a training set of $\sim 10^4$ samples. Spectral-significance-guided dimensionality reduction techniques allow us to construct an approximate inverse mapping from spectral moments to pseudo-Coulomb matrices. When applying this to the moments of the ensemble-mean spectrum, we obtain distances from the active site that match closely to those of the ensemble mean and which moreover reproduce the pressure-induced coordination change in amorphous GeO$_2$. With this approach utilizing emulator-based component analysis, we are able to filter out the artificially complete structural information available from simulated snapshots, and quantitatively analyse structural changes that can be inferred from the changes in the K$\beta$ emission spectrum alone

MECHANISTIC STUDIES OF THE COMPLETE ELECTROCHEMICAL OXIDATION OF ETHANOL INTO CO2 OVER PLATINUM-BASED CORE-SHELL NANOCATALYSTS

Direct ethanol fuel cells (DEFCs) are a promising technology for the generation of electricity via the direct conversion of ethanol into CO2, showing higher thermodynamic efficiency and volumetric energy density than hydrogen fuel cells. However, implementation of DEFCs is hampered by low selectivity of CO2 generation at the anode where the ethanol oxidation reaction (EOR) happens. Therefore, anode catalysts with high reactivity for the EOR and high selectivity for CO2 generation via breaking C-C bond are highly needed. To evaluate the catalysts’ capability of splitting C-C bond of the ethanol molecule, highly sensitive CO2 detection technique was developed in this research using a CO2 microelectrode. Such an in situ CO2 measurement tool enabled the real time detection of the partial pressure of CO2 during the EOR using linear sweeping voltammetry measurements, through which electro-kinetic details of CO2 generation could be obtained. Electro-kinetics of CO2 generation were studied on the PtRh/SnO2 core-shell catalysts made by a ‘surfactant-free’ method. The results showed that Pt and Rh components located in the core were partially oxidized and therefore improved the CO2 generation at low electrical potential. In addition, in situ CO2 measurements provided the mechanistic understanding of potentiodynamics of the EOR, particularly the influence of *OH adsorbates on CO2 generation rate and CO2 selectivity. Our results showed that at low potential, inadequate *OH adsorbates impaired the removal of reaction intermediates, and thus Pt/Rh/SnO2 exhibited the best performance toward CO2 generation due to its strong ability to dissociate water molecules forming *OH oxidants, while at high potential, Rh sites were overwhelmingly occupied (poisoned) by *OH adsorbates, and thus Pt/SnO2 exhibited the best performance toward CO2 generation

이원계 금속 나노입자의 설계 및 연료 산화에서의 전기촉매 작용

학위논문 (박사)-- 서울대학교 대학원 : 화학생물공학부(에너지환경 화학융합기술전공), 2014. 2. 성영은.This study purposes the synthesis of nano-sized bimetallic electrocatalysts toward fuel oxidation reaction with the lower price and the enhanced activity compared to the existing catalysts. Moreover, a facile and rapid synthesis is introduced via a microwave-assisted synthesis instead of the conventional methods, and the complete oxidation reaction of fuel can be further achieved to improve the efficiency. The electrochemical and morphological properties of carbon supported platinum and tin oxide nanoparticles were evaluated in the first part, and the heterogeneous rhodium-tin alloyed nanoparticles deposited on the carbon as an electrocatalyst for the fuel oxidation were prepared to further reach to the complete oxidation reaction into the carbon dioxide as well as the better electrocatalytic activity and durability for fuel oxidation. The electrocatalyst of carbon supported platinum and tin oxide nanoparticle was prepared through the microwave-assisted synthesis. It is clearly observed that the platinum nanoparticles and tin dioxide nanoparticles were uniformly dispersed onto the supporting material. The catalyst containing 16 wt% of tin oxide nanoparticles exhibited the highest activity and durability for the ethanol oxidation. The onset potentials of prepared electrocatalysts were negatively shifted compared to that of the commercial catalyst, result from the adsorbed CO species on platinum are more easily oxidized at lower potentials by hydroxyl groups adsorbed onto the surface of nearby tin oxide. In addition to the bifunctional effect, it is confirmed that the electronic effect was also acted in the platinum-tin oxide nanocomposites. As the amounts of tin oxide increased, the white line of Pt L3-edge decreased. According to the cyclic voltammetry results and theoretical calculations, the excess amounts of tin oxide nanoparticles dispersed on the carbon surface play a role as an isolating barrier that hinders the electron transfer between platinum and carbon support, while too low amounts of tin oxide nanoparticles limit the transfer of adsorbed hydroxyl groups for the oxidation of carbon monoxide species. Without platinum as one of the most valuable metal, the rhodium-tin alloy nanoparticle was formed for the efficient electrocatalyst toward fuel oxidation. The alloyed bimetallic nanoparticles were uniformly distributed onto the whole surface of carbon supporting material through the microwave-assisted method. Electrocatalytic activity and the ratios of peak current density at forward scan and backward scan were significantly enhanced in the tin-abundant sample. Moreover, the rhodium-tin electrocatalysts produced much carbon dioxide compared to the platinum-based conventional catalyst, result from the accomplishment of additional total oxidation of ethanol including the C-C bond splitting. Not only the increased production of carbon dioxide but also the negative shift in onset potentials was observed. As the tin ratios were increased, the white lines of Rh K-edge were up-shifted that the interactions between rhodium and adsorbed species become stronger than the pure metallic rhodium. It indicates the electronic modifications can be powerful strategy to fulfill both the increased performance and the lower expense. Even in concentrated fuel solutions and at lower operating potentials, the superior activity and durability were maintained. These results correlated with the lower overpotentials and the increased reaction rates under various fuel concentrations, confirmed from the Tafel plots and Butler-Volmer equations. Consequently, the bimetallic nanoparticles with improved electrocatalytic activity and durability toward fuel oxidation were successfully synthesized through the facile and swift method.Abstract i List of Tables vi List of Figures vii Chapter 1. Introduction 1 1.1. Renewable energy and fuel cells 1 1.2. Fuel cell fundamentals 6 1.3. Electrochemical reactions and nano-electrocatalysts 13 1.4. Subject of research in the thesis 20 1.5. References 23 Chapter 2. Experimental 28 2.1. Synthesis of nanoparticle as electrocatalysts 28 2.1.1.Selective deposition of platinum and tin oxide nanoparticle 28 2.1.2. Heterogeneous rhodium-tin alloy nanoparticles 30 2.2. Physicochemical characterization 32 2.3. Electrochemical characterization 34 2.4. in-situ fourier transform infrared spectroscopy 36 2.5. X-ray absorption spectroscopy 37 2.6. References 40 Chapter 3. Results and Discussion 41 3.1. Selective deposition of platinum and tin oxide nanoparticles 41 3.1.1. Physicochemical characterization 41 3.1.2. Electrochemical characterization 56 3.1.3. Electrochemical stability test 69 3.2. Heterogeneous rhodium-tin oxide nanoparticles 73 3.2.1. Physicochemical characterization 73 3.2.2. Electrochemical characterization 91 3.2.3. Electrochemical durability test 107 3.3. References 118 Chapter 4. Conclusions 125 국 문 초 록 128Docto

Improved modeling of nanocrystals from atomic pair distribution function data

Accurate determination of the structure of nanomaterials is a key step towards understanding and controlling their properties. This is especially challenging for small nanoparticles, where traditional electron microscopy provides partial information about the morphology and internal atomic structure for a limited number of particles, and x-ray powder diffraction data is often broad and diffuse and not amenable to quantitative crystallographic analysis. In these cases a better approach is to use atomic pair distribution function (PDF) analysis of synchrotron x-ray total scattering data, in tandem with high-resolution imaging techniques. Even with these tools available, extracting detailed models of nanoparticle cores is notoriously difficult and time consuming. For many years, poor fits were considered to be a de facto limitation of nanoparticle studies using PDF methods, and semi-quantitative analyses were commonly employed. In this work, we aim to challenge this assumption. We started with a survey of 12 canonical metallic nanomaterials, both elemental and alloyed, prepared using different synthesis methods, with significantly different shapes and sizes as disparate as 2 nm wires and 40 nm particles, using PDF data collected at multiple synchrotron sources and beamlines. Widely applied shape-tuned attenuated crystal (AC) fcc models proved inadequate, yielding structured, coherent, and correlated fit residuals. However, equally simple discrete cluster models could account for the largest amplitude features in these difference signals. A hypothesis testing based approach to nanoparticle structure modeling systematically ruled out effects from crystallite size, composition, shape, and surface faceting as primary factors contributing to the AC misfit, and it was found that these previously ignored signals could be explained as originating from well defined domain structures in the nanoparticle cores. This analysis gave insight into how sensitive PDF analyses could be towards identifying the presence of interfaces inside ultrasmall nanoparticle cores using atomistic modeling, but still hinged on manual trial-and-error testing of clusters from different structural motifs. To address this challenge, we developed a structure screening methodology, called cluster-mining, wherein libraries of clusters from multiple structural motifs were built algorithmically and individually refined against experimental PDFs. This differs from traditional approaches for crystallographic analysis of nanoparticles where a single model containing many refinable parameters is used to fit peak profiles from a measured diffraction pattern. Instead, cluster-mining uses many structure models and highly constrained refinements to screen libraries of discrete clusters against experimental PDF data, with the aim of finding the most representative cluster structures for the ensemble average nanoparticle from any given synthesis. Finally, we wanted to identify other nanomaterial systems where this approach might prove useful, and demonstrated that the PDF was also capable of detecting seemingly subtle morphological variations in highly faceted titania photocatalyts. This opens a new avenue towards characterizing shape-controlled metal oxide nanomaterials with well-defined surface facets. To extend this work in the future, our goal is to develop new tools for building discrete nanoparticles algorithmically, integrate statistical approaches to make model selection more efficient, and ultimately, move towards an atomic scale understanding of nanoparticle structure that is comparable to bulk materials