971 resultados para NOBLE-METAL ELECTRODES
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In this work, a simple route to prepare carbon supported Pt/C, Pt:Ru/C, Pt:Mo/C and Pt:Ru:Mo/C catalysts is reported. The electrochemical properties of the several carbon materials used as substrates in the absence and in the presence of supported platinum and platinum alloys catalysts were investigated using cyclic voltammetry and employing the thin porous coating electrode technique. The activity of the dispersed catalysts composed of Pt/C with respect to the oxygen reduction and of alloy/C with respect to methanol oxidation was investigated using steady state polarization measurements. The performance with respect to the oxygen reduction reaction of the Pt/C catalyst prepared on heat-treated Vulcan carbon substrate is equivalent to that reported in the literature for the state-of-the-art electrocatysts. Pt:Ru:Mo/C samples prepared in this work presented the higher catalytic effect for methanol electro-oxidation.
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Dissertation submitted for obtainment of the Master’s Degree in Biotechnology, by the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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This work deals with the optical properties of supported noble metal nanoparticles, which are dominated by the so-called Mie resonance and are strongly dependent on the particles’ morphology. For this reason, characterization and control of the dimension of these systems are desired in order to optimize their applications. Gold and silver nanoparticles have been produced on dielectric supports like quartz glass, sapphire and rutile, by the technique of vapor deposition under ultra-high vacuum conditions. During the preparation, coalescence is observed as an important mechanism of cluster growth. The particles have been studied in situ by optical transmission spectroscopy and ex situ by atomic force microscopy. It is shown that the morphology of the aggregates can be regarded as oblate spheroids. A theoretical treatment of their optical properties, based on the quasistatic approximation, and its combination with results obtained by atomic force microscopy give a detailed characterization of the nanoparticles. This method has been compared with transmission electron microscopy and the results are in excellent agreement. Tailoring of the clusters’ dimensions by irradiation with nanosecond-pulsed laser light has been investigated. Selected particles are heated within the ensemble by excitation of the Mie resonance under irradiation with a tunable laser source. Laser-induced coalescence prevents strongly tailoring of the particle size. Nevertheless, control of the particle shape is possible. Laser-tailored ensembles have been tested as substrates for surface-enhanced Raman spectroscopy (SERS), leading to an improvement of the results. Moreover, they constitute reproducible, robust and tunable SERS-substrates with a high potential for specific applications, in the present case focused on environmental protection. Thereby, these SERS-substrates are ideally suited for routine measurements.
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Synthesis of well-defined nanoparticles has been intensively pursued not only for their fundamental scientific interest, but also for many technological applications. One important development of the nanomaterial is in the area of chemical catalysis. We have now developed a new aqueous-based method for the synthesis of silica encapsulated noble metal nanoparticles in controlled dimensions. Thus, colloid stable silica encapsulated similar to 5 nm platinum nanoparticle is synthesized by a multi-step method. The thickness of the silica coating could be controlled using a different amount of silica precursor. These particles supported on a high surface area alumina are also demonstrated to display a superior hydrogenation activity and stability against metal sintering after thermal activation.
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We have reported earlier that modification of commercial graphite Pt-supported catalysts with Teflon fluorinated polymeric coating of a very strong hydrophobic nature can significantly improve catalytic activity for aerial oxidation of water-insoluble alcohols such as anthracene methanol in supercritical carbon dioxide (scCO(2)). Thus, this paper presents some further characterization of these new catalyst materials and the working fluid phase during the catalysis. Using the same Teflon-modified metal catalysts, this paper addresses the oxidation of another water-insoluble alcohol molecule, m-hydrobenzoin in scCO(2). It is found that conversion and product distribution of this diol oxidation critically depend on the temperature and pressure of the scCO(2) used, which suggest the remarkable solvent properties of the scCO(2) under these unconventional oxidation conditions. (C) 2004 Elsevier Inc. All rights reserved.
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In this work, metal nanoparticles produced by nanosphere lithography were studied in terms of their optical properties (in connection to their plasmon resonances), their potential application in sensing platforms - for thin layer sensing and bio-recognition events -, and for a particular case (the nanocrescents), for enhanced spectroscopy studies. The general preparation procedures introduced early in 2005 by Shumaker-Parry et al. to produce metallic nanocrescents were extended to give rise to more complex (isolated) structures, and also, by combining colloidal monolayer fabrication and plasma etching techniques, to arrays of them. The fabrication methods presented in this work were extended not only to new shapes or arrangements of particles, but included also a targeted surface tailoring of the substrates and the structures, using different thiol and silane compounds as linkers for further attachment of, i.e. polyelectrolyte layers, which allow for a controlled tailoring of their nanoenvironment. The optical properties of the nanocrescents were studied with conventional transmission spectroscopy; a simple multipole model was adapted to explain their behaviour qualitatively. In terms of applications, the results on thin film sensing using these particles show that the crescents present an interesting mode-dependent sensitivity and spatial extension. Parallel to this, the penetrations depths were modeled with two simplified schemes, obtaining good agreement with theory. The multiple modes of the particles with their characteristic decay lengths and sensitivities represent a major improvement for particle-sensing platforms compared to previous single resonance systems. The nanocrescents were also used to alter the emission properties of fluorophores placed close to them. In this work, green emitting dyes were placed at controlled distances from the structures and excited using a pulsed laser emitting in the near infrared. The fluorescence signal obtained in this manner should be connected to a two-photon processes triggered by these structures; obtaining first insight into plasmon-mediated enhancement phenomena. An even simpler and faster approach to produce plasmonic structures than that for the crescents was tested. Metallic nanodiscs and nanoellipses were produced by means of nanosphere lithography, extending a procedure reported in the literature to new shapes and optical properties. The optical properties of these particles were characterized by extinction spectroscopy and compared to results from the literature. Their major advantage is that they present a polarization-dependent response, like the nanocrescents, but are much simpler to fabricate, and the resonances can be tailored in the visible with relative ease. The sensing capabilities of the metallic nanodiscs were explored in the same manner as for the nanocrescents, meaning their response to thin layers and to bio-recognition events on their surface. The sensitivity of these nanostructures to thin films proved to be lower than that of the crescents, though in the same order of magnitude. Experimental information about the near field extension for the Au nanodiscs of different sizes was also extracted from these measurements. Further resonance-tailoring approaches based on electrochemical deposition of metals on the nanodiscs were explored, as a means of modifying plasmon resonances by changing surface properties of the nanoparticles. First results on these experiments would indicate that the deposition of Ag on Au on a submonolayer coverage level can lead to important blue-shifts in the resonances, which would open a simple way to tailor resonances by changing material properties in a local manner.
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A comparison of 50 basalts recovered at Sites 706, 707, 713, and 715 along the Reunion hotspot trace during Ocean Drilling Program Leg 115 in the Indian Ocean shows that seafloor alteration had little effect on noble metal concentrations (Au, Pd, Pt, Rh, Ru, and Ir), determined by inductively coupled plasma-mass spectrometry (ICP-MS), which generally tend to decrease with magma evolution. Their compatible-element behavior may be related to the precipitation of Ir-Os-based alloys, chromite, sulfides, and/or olivine and clinopyroxene in some combination. The simplest explanation indicates silicate control of concentrations during differentiation. Basalts from the different sites show varying degrees of alkalinity. Noble metal abundances tend to increase with decreasing basalt alkalinity (i.e., with increasing percentages of mantle melting), indicating that the metals behave as compatible elements during mantle melting. The retention of low-melting-point Au, Pd, and Rh in mantle sulfides, which mostly dissolve before significant proportions of Ir-Os-based alloys melt, explains increasing Pd/Ir ratios with decreasing alkalinity (increasing melting percentages) in oceanic basalts. High noble metal concentrations in Indian Ocean basalts (weighted averages of Au, Pd, Rh, Pt, Ru, and Ir in Leg 115 basalts are 3.2, 8.1, 0.31, 7.3, 0.22, and 0.11 ppb, respectively), compared with basalts from some other ocean basins, may reflect fundamental primary variations in upper- mantle noble metal abundances
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Novel hierarchical SiO2 monolithic microreactors loaded with either Pd or Pt nanoparticles have been prepared in fused silica capillaries and tested in the Preferential Oxidation of CO (PrOx) reaction. Pd and Pt nanoparticles were prepared by the reduction by solvent method and the support used was a mesoporous SiO2 monolith prepared by a well-established sol–gel methodology. Comparison of the activity with an equivalent powder catalyst indicated that the microreactors show an enhanced catalytic behavior (both in terms of CO conversion and selectivity) due to the superior mass and heat transfer processes that take place inside the microchannel. TOF values at low CO conversions have been found to be ∼2.5 times higher in the microreactors than in the powder catalyst and the residence time seems to have a noticeable influence over the selectivity of the catalysts designed for this reaction. The Pd and Pt flexible microreactors developed in this work have proven to be effective for the CO oxidation reaction both in the presence and absence of H2, standing out as a very interesting and suitable option for the development of CO purification systems of small dimensions for portable and on-board applications.
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© 2015 Silveira et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.
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The combination of cyclic voltammetry and on line mass spectrometry, called differential electrochemical mass spectrometry (DEMS), is already a well established method for on line identification and quantitative detection of the products and intermediates of electrochemical reactions. This article aims to show the principles of the method and how this technique have been used to study electrochemical problems such the electrocatalytic oxidation of organic molecules, as methanol and ethanol, at noble metal electrodes.
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Biological rhythms are regulated by homeostatic mechanisms that assure that physiological clocks function reliably independent of temperature changes in the environment. Temperature compensation, the independence of the oscillatory period on temperature, is known to play a central role in many biological rhythms, but it is rather rare in chemical oscillators. We study the influence of temperature on the oscillatory dynamics during the catalytic oxidation of formic acid on a polycrystalline platinum electrode. The experiments are performed at five temperatures from 5 to 25 degrees C, and the oscillations are studied under galvanostatic control. Under oscillatory conditions, only non-Arrhenius behavior is observed. Overcompensation with temperature coefficient (q(10), defined as the ratio between the rate constants at temperature T + 10 degrees C and at T) < I is found in most cases, except that temperature compensation with q(10) approximate to I predominates at high applied currents. The behavior of the period and the amplitude result from a complex interplay between temperature and applied current or, equivalently, the distance from thermodynamic equilibrium. High, positive apparent activation energies were obtained under voltammetric, nonoscillatory conditions, which implies that the non-Arrhenius behavior observed under oscillatory conditions results from the interplay among reaction steps rather than, from a weak temperature dependence of the individual steps.
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The electrooxidation of small organic molecules on platinum surfaces usually involves different structure-dependent steps that include adsorption and desorption of various species and multiple reaction pathways. Because temperature plays a decisive role on each individual step, understanding its global influence on the reaction mechanism is often a difficult task, especially when the system is studied under far from equilibrium conditions in the presence of kinetic instabilities. Aiming at contributing to unravel this problem, herein, we report an experimental study of the role played by temperature on the electrooxidation of formic acid on a Pt(100) electrode. The system was investigated under both close and far from equilibrium conditions, and apparent activation energies were estimated using different strategies. Overall, comparable activation energies were estimated under oscillatory and quasi-stationary conditions, at high potentials. At low potentials, the poisoning process associated with the formic acid dehydration step presented a negligible dependence with temperature and, therefore, zero activation energy. On the basis of our experimental findings, we suggest that formic acid dehydration is the main, but maybe not the unique, step that differentiates the temperature dependence of the oscillatory electrooxidation of formic acid on Pt(100) with that on polycrystalline platinum.
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In this work, the surface-enhanced Raman scattering (SERS) spectra of pyridine (py) on thin films of Co and Ni electrodeposited on an Ag electrode activated by oxidation-reduction cycles (ORC) are presented. The SERS spectra from the thin films were compared to those of py on activated bare transition metal electrodes. It was verified that the SERS spectra of py on 3 monolayers (ML)-thick films of Ni and Co presented only bands assignable to the py adsorbed on transition metal surfaces. It was also observed that even for 50 ML-thick transition metal films, the py SERS intensity was ca. 40% of the intensity from the 3 ML-thick films. The relative intensities of the SERS bands depended on the thickness of the films, and for films thicker than 7 ML for Co and 9 ML for Ni they were very similar to those of the bare transition metal electrodes. The transition metal thin films over Ag activated electrodes presented SERS intensities 3 orders of magnitude higher than the ones from bare transition metal electrodes. These films are more suitable to study the adsorption of low Raman cross-section molecules than are ORC-activated transition metal electrodes.