Multiplicity and transverse momentum dependence of two- and four-particle correlations in pPb and PbPb collisions

Measurements of two- and four-particle angular correlations for charged particles emitted in pPb collisions are presented over a wide range in pseudorapidity and full azimuth. The data, corresponding to an integrated luminosity of approximately 31nb-1, were collected during the 2013 LHC pPb run at a nucleon-nucleon center-of-mass energy of 5.02 TeV by the CMS experiment. The results are compared to 2.76 TeV semi-peripheral PbPb collision data, collected during the 2011 PbPb run, covering a similar range of particle multiplicities. The observed correlations are characterized by the near-side (|δφ|≈0) associated pair yields and the azimuthal anisotropy Fourier harmonics (vn). The second-order (v2) and third-order (v3) anisotropy harmonics are extracted using the two-particle azimuthal correlation technique. A four-particle correlation method is also applied to obtain the value of v2 and further explore the multi-particle nature of the correlations. Both associated pair yields and anisotropy harmonics are studied as a function of particle multiplicity and transverse momentum. The associated pair yields, the four-particle v2, and the v3 become apparent at about the same multiplicity. A remarkable similarity in the v3 signal as a function of multiplicity is observed between the pPb and PbPb systems. Predictions based on the color glass condensate and hydrodynamic models are compared to the experimental results. © 2013 CERN.

Ethanol electro-oxidation in an alkaline medium using Pd/C, Au/C and PdAu/C electrocatalysts prepared by electron beam irradiation

Carbon-supported Pd, Au and bimetallic PdAu (Pd:Au 90:10, 50:50 and 30:70 atomic ratios) electrocatalysts were prepared using electron beam irradiation. The obtained materials were characterized by energy dispersive X-ray analysis (EDX), X-ray diffraction (XRD) and transmission electron microscopy (TEM), and their catalytic activities toward ethanol electro-oxidation were evaluated in an alkaline medium using electrochemical techniques, in situ attenuated total reflectance Fourier transformed infrared spectroscopy (ATR-FTIR) analysis and a single alkaline direct ethanol fuel cell (ADEFC). EDX analyses showed that the actual Pd: Au atomic ratios were very similar to the nominal ones. X-ray diffractograms of PdAu/C electrocatalysts evidenced the presence of Pd-rich (fcc) and Au-rich (fcc) phases. TEM analysis showed a homogeneous dispersion of nanoparticles on the carbon support, with an average size in the range of 3-5 nm and broad size distributions. Cyclic voltammetry (CV) and chronoamperometry (CA) experiments revealed the superior ambient activity toward ethanol electro-oxidation of PdAu/C electrocatalysts with Pd: Au ratios of 90:10 and 50:50. In situ ATR-FTIR spectroscopy measurements have shown that the mechanism for ethanol electro-oxidation is dependent on catalyst composition, leading to different reaction products, such as acetaldehyde and acetate, depending on the number of electrons transferred. Experiments on a single ADEFC were conducted between 50 and 900 C, and the best performance of 44 mW cm-2 in 2.0molL-1 ethanol was obtained at 850C for the Pd:Au 90:10 catalysts. This superior performance is most likely associated with enhancement of ethanol adsorption on Pd, oxidation of the intermediates, the presence of gold oxide-hydroxyl species, low mean particle diameters and better distribution of particles on the support. © 2013 Elsevier Ltd. All rights reserved.

Influence of solvent on the morphology and photocatalytic properties of ZnS decorated CeO2 nanoparticles

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Transverse sphericity of primary charged particles in minimum bias proton-proton collisions at root s=0.9, 2.76 and 7 TeV

Measurements of the sphericity of primary charged particles in minimum bias proton-proton collisions at root s = 0.9, 2.76 and 7 TeV with the ALICE detector at the LHC are presented. The observable is measured in the plane perpendicular to the beam direction using primary charged tracks with p(T) > 0.5 GeV/c in vertical bar eta vertical bar < 0.8. The mean sphericity as a function of the charged particle multiplicity at mid-rapidity (N-ch) is reported for events with different p(T) scales ("soft" and "hard") defined by the transverse momentum of the leading particle. In addition, the mean charged particle transverse momentum versus multiplicity is presented for the different event classes, and the sphericity distributions in bins of multiplicity are presented. The data are compared with calculations of standard Monte Carlo event generators. The transverse sphericity is found to grow with multiplicity at all collision energies, with a steeper rise at low N-ch, whereas the event generators show an opposite tendency. The combined study of the sphericity and the mean p(T) with multiplicity indicates that most of the tested event generators produce events with higher multiplicity by generating more back-to-back jets resulting in decreased sphericity (and isotropy). The PYTHIA6 generator with tune PERUGIA-2011 exhibits a noticeable improvement in describing the data, compared to the other tested generators.

Structural and textural studies of NiO impregnation in mesoporous ZrO2-CeO2 for catalysis applications.

The synthesis of zirconia-based ordered mesoporous structures for catalytic applications is a research area under development. These systems are also potential candidates as anodes in intermediate temperature solid oxide fuel cells (it-SOFC) due to an enhancement on their surface area [1-4]. The structural features of mesoporous zirconia-ceria materials in combination with oxygen storage/release capacity (OSC) are crucial for various catalytic reactions. The direct use of hydrocarbons as fuel for the SOFC (instead of pure H2), without the necessity of reforming and purification reactors can improve global efficiency of these systems [4]. The X-ray diffraction data showed that ZrO2-x%CeO2 samples with x>50 are formed by a larger fraction of the cubic phase (spatial group Fm3m), while for x<50 the major crystalline structure is the tetragonal phase (spatial group P42/nmc). The crystallite size of the cubic phase increases with increase in ceria content. The tetragonal crystallite size decreases when ceria content increases. After impregnation, the Rietveld analysis showed a NiO content around 60wt.% for all samples. The lattice parameters for the ZrO2 tetragonal phase are lower for higher ZrO2 contents, while for all samples the cubic NiO and CeO2 parameters do not present changes. The calculated densities are higher for higher ceria content, as expected. The crystallite size of NiO are similar (~20nm) for all samples and 55nm for the NiO standard. Nitrogen adsorption experiments revealed a broader particle size distribution for higher CeO2 content. The superficial area values were around 35m2/g for all samples, the average pore diameter and pore volumes were higher when increasing ceria content. After NiO impregnation the particle size distribution was the same for all samples, with two pore sizes, the first around 3nm and a broader peak around 10nm. The superficial area increased to approximately 45m2/g for all samples, and the pore volume was also higher after impregnation and increased when ceria content increased. These results point up that the impregnation of NiO improves the textural characteristics of the pristine material. The complementary TEM/EDS images present a homogeneous coating of NiO particles over the ZrO2-x%CeO2 support, showing that these samples are excellent for catalysis applications. [1] D. Y. Zhao, J. Feng, Q. Huo, N. Melosh, G. H. Fredrickson, B. F. Chmelka, G. D. Stucky, Science 279, 548-552 (1998). [2] C. Yu, Y. Yu, D. Zhao, Chem. Comm. 575-576 (2000). [3] A. Trovarelli, M. Boaro, E. Rocchini, C. de Leitenburg, G. Dolcetti, J. Alloys Compd. 323-324 (2001) 584-591. [4] S. Larrondo, M. A. Vidal, B. Irigoyen, A. F. Craievich, D. G. Lamas, I. O. Fábregas, et al. Catal. Today 107–108 (2005) 53-59.

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

Chemical and physical properties of Amazonian aerosol particles

- ZUSAMMENFASSUNG:Die vorliegende Dissertation befasst sich mit der Bestimmung der chemischen und physikalischen Eigenschaften von Aerosolpartikeln im Amazonasbecken, die während Zeiten mit Biomasseverbrennung und bei Hintergrundbedingungen bestimmt wurden. Die Messungen wurden während zwei Kampagnen im Rahmen des europäischen Beitrags zum LBA-EUSTACH Experiment in Amazonien. Die Daten umfassen Messungen der Anzahlkonzentrationen, Größenverteilungen, optischen Eigenschaften sowie Elementzusammensetzungen und Kohlenstoffgehalte der gesammelten Aerosole. Die Zusammensetzung des Aerosols wies auf folgende drei Quellen hin: natürlichen biogenen, Mineralstaub, und pyrogenes Aerosol. Aller drei Komponenten trugen signifikant zur Extinktion des Sonnenlichts bei. Insgesamt ergab sich eine Steigerung der Meßwerte um ca. das Zehnfache während der Trockenzeit im Vergleich zur Regenzeit, was auf eine massive Einbringung von Rauchpartikeln im Submikrometerbereich in die Atmosphäre während der Trockenzeit zurückzuführen ist. Dementsprechend sank die Einzelstreualbedo von ca. 0,97 auf 0,91. Der Brechungsindex der Aerosolpartikel wurde mit einer neuen iterative Methoden, basierend auf der Mie-Theorie berechnet. Es ergaben sich durchschnittliche Werte von 1,42 – 0,006i für die Regenzeit und 1,41 – 0,013i für die Trockenperiode. Weitere klimatisch relevante Parameterergaben für Hintergrundaerosole und für Aerosole aus Biomasseverbrennung folgende Werte: Asymmetrieparameter von 0,63 ± 0,02 bzw. 0,70 ± 0,03 und Rückstreuungsverhältnisse von 0,12 ± 0,01 bzw. 0,08 ± 0,01. Diese Veränderungen haben das Potential, das regionale und globale Klima über die Variierung der Extinktion der Sonneneinstrahlung als auch der Wolkeneigenschaften zu beeinflussen.

Imaging and modeling of pore scale processes in porous media using X-ray computed tomography and lattice Boltzmann solver

In der Erdöl– und Gasindustrie sind bildgebende Verfahren und Simulationen auf der Porenskala im Begriff Routineanwendungen zu werden. Ihr weiteres Potential lässt sich im Umweltbereich anwenden, wie z.B. für den Transport und Verbleib von Schadstoffen im Untergrund, die Speicherung von Kohlendioxid und dem natürlichen Abbau von Schadstoffen in Böden. Mit der Röntgen-Computertomografie (XCT) steht ein zerstörungsfreies 3D bildgebendes Verfahren zur Verfügung, das auch häufig für die Untersuchung der internen Struktur geologischer Proben herangezogen wird. Das erste Ziel dieser Dissertation war die Implementierung einer Bildverarbeitungstechnik, die die Strahlenaufhärtung der Röntgen-Computertomografie beseitigt und den Segmentierungsprozess dessen Daten vereinfacht. Das zweite Ziel dieser Arbeit untersuchte die kombinierten Effekte von Porenraumcharakteristika, Porentortuosität, sowie die Strömungssimulation und Transportmodellierung in Porenräumen mit der Gitter-Boltzmann-Methode. In einer zylindrischen geologischen Probe war die Position jeder Phase auf Grundlage der Beobachtung durch das Vorhandensein der Strahlenaufhärtung in den rekonstruierten Bildern, das eine radiale Funktion vom Probenrand zum Zentrum darstellt, extrahierbar und die unterschiedlichen Phasen ließen sich automatisch segmentieren. Weiterhin wurden Strahlungsaufhärtungeffekte von beliebig geformten Objekten durch einen Oberflächenanpassungsalgorithmus korrigiert. Die Methode der „least square support vector machine” (LSSVM) ist durch einen modularen Aufbau charakterisiert und ist sehr gut für die Erkennung und Klassifizierung von Mustern geeignet. Aus diesem Grund wurde die Methode der LSSVM als pixelbasierte Klassifikationsmethode implementiert. Dieser Algorithmus ist in der Lage komplexe geologische Proben korrekt zu klassifizieren, benötigt für den Fall aber längere Rechenzeiten, so dass mehrdimensionale Trainingsdatensätze verwendet werden müssen. Die Dynamik von den unmischbaren Phasen Luft und Wasser wird durch eine Kombination von Porenmorphologie und Gitter Boltzmann Methode für Drainage und Imbibition Prozessen in 3D Datensätzen von Böden, die durch synchrotron-basierte XCT gewonnen wurden, untersucht. Obwohl die Porenmorphologie eine einfache Methode ist Kugeln in den verfügbaren Porenraum einzupassen, kann sie dennoch die komplexe kapillare Hysterese als eine Funktion der Wassersättigung erklären. Eine Hysterese ist für den Kapillardruck und die hydraulische Leitfähigkeit beobachtet worden, welche durch die hauptsächlich verbundenen Porennetzwerke und der verfügbaren Porenraumgrößenverteilung verursacht sind. Die hydraulische Konduktivität ist eine Funktion des Wassersättigungslevels und wird mit einer makroskopischen Berechnung empirischer Modelle verglichen. Die Daten stimmen vor allem für hohe Wassersättigungen gut überein. Um die Gegenwart von Krankheitserregern im Grundwasser und Abwässern vorhersagen zu können, wurde in einem Bodenaggregat der Einfluss von Korngröße, Porengeometrie und Fluidflussgeschwindigkeit z.B. mit dem Mikroorganismus Escherichia coli studiert. Die asymmetrischen und langschweifigen Durchbruchskurven, besonders bei höheren Wassersättigungen, wurden durch dispersiven Transport aufgrund des verbundenen Porennetzwerks und durch die Heterogenität des Strömungsfeldes verursacht. Es wurde beobachtet, dass die biokolloidale Verweilzeit eine Funktion des Druckgradienten als auch der Kolloidgröße ist. Unsere Modellierungsergebnisse stimmen sehr gut mit den bereits veröffentlichten Daten überein.

A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-δ as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results.

A Model to Predict Percolation Threshold and Effective Conductivity of Infiltrated Electrodes for Solid Oxide Fuel Cells

We present a mechanistic modeling methodology to predict both the percolation threshold and effective conductivity of infiltrated Solid Oxide Fuel Cell (SOFC) electrodes. The model has been developed to mirror each step of the experimental fabrication process. The primary model output is the infiltrated electrode effective conductivity which provides results over a range of infiltrate loadings that are independent of the chosen electronically conducting material. The percolation threshold is utilized as a valuable output data point directly related to the effective conductivity to compare a wide range of input value choices. The predictive capability of the model is demonstrated by favorable comparison to two separate published experimental studies, one using strontium molybdate and one using La0.8Sr0.2FeO3-delta as infiltrate materials. Effective conductivities and percolation thresholds are shown for varied infiltrate particle size, pore size, and porosity with the infiltrate particle size having the largest impact on the results. (C) 2013 The Electrochemical Society. All rights reserved.

Development And Use Of A Model To Predict Properties Of Infiltrated Solid Oxide Fuel Cell Anodes

Solid oxide fuel cells (SOFCs) provide a potentially clean way of using energy sources. One important aspect of a functioning fuel cell is the anode and its characteristics (e.g. conductivity). Using infiltration of conductor particles has been shown to be a method for production at lower cost with comparable functionality. While these methods have been demonstrated experimentally, there is a vast range of variables to consider. Because of the long time for manufacture, a model is desired to aid in the development of the desired anode formulation. This thesis aims to (1) use an idealized system to determine the appropriate size and aspect ratio to determine the percolation threshold and effective conductivity as well as to (2) simulate the infiltrated fabrication method to determine the effective conductivity and percolation threshold as a function of ceramic and pore former particle size, particle fraction and the cell¿s final porosity. The idealized system found that the aspect ratio of the cell does not affect the cells functionality and that an aspect ratio of 1 is the most efficient computationally to use. Additionally, at cell sizes greater than 50x50, the conductivity asymptotes to a constant value. Through the infiltrated model simulations, it was found that by increasing the size of the ceramic (YSZ) and pore former particles, the percolation threshold can be decreased and the effective conductivity at low loadings can be increased. Furthermore, by decreasing the porosity of the cell, the percolation threshold and effective conductivity at low loadings can also be increased

The Effect of Various Electrode Microstructure Parameters on the Effective Conductivity and Three-Phase Boundary Density of Infiltrated SOFC Electrodes

Solid oxide fuel cell (SOFC) technology has the potential to be a significant player in our future energy technology repertoire based on its ability to convert chemical energy into electrical energy. Infiltrated SOFCs, in particular, have demonstrated improved performance and at lower cost than traditional SOFCs. An infiltrated electrode comprises porous ceramic scaffolding (typically constructed from the oxygen ion conducting material) that is infiltrated with electron conducting and catalytic particles. Two important SOFC electrode properties are effective conductivity and three phase boundary density (TPB). Researchers study these electrode properties separately, and fail to recognize them as competing properties. This thesis aims to (1) develop a method to model the TPB density and use it to determine the effect of porosity, scaffolding particle size, and pore former size on TPB density as well as to (2) compare the effect of porosity, scaffolding particle size, and pore former size on TPB density and effective conductivity to determine a desired set of parameters for infiltrated SOFC electrode performance. A computational model was used to study the effect of microstructure parameters on the effective conductivity and TPB density of the infiltrated SOFC electrode. From this study, effective conductivity and TPB density are determined to be competing properties of SOFC electrodes. Increased porosity, scaffolding particle size, and pore former particle size increase the effective conductivity for a given infiltrate loading above percolation threshold. Increased scaffolding particle size and pore former size ratio, however, decreases the TPB density. The maximum TPB density is achievable between porosities of 45% and 60%. The effect of microstructure parameters are more prominent at low loading with scaffolding particle size being the most significant factor and pore former size ratio being the least significant factor.

Visualization and quantitative analysis of nanoparticles in the respiratory tract by transmission electron microscopy

ABSTRACT: Nanotechnology in its widest sense seeks to exploit the special biophysical and chemical properties of materials at the nanoscale. While the potential technological, diagnostic or therapeutic applications are promising there is a growing body of evidence that the special technological features of nanoparticulate material are associated with biological effects formerly not attributed to the same materials at a larger particle scale. Therefore, studies that address the potential hazards of nanoparticles on biological systems including human health are required. Due to its large surface area the lung is one of the major sites of interaction with inhaled nanoparticles. One of the great challenges of studying particle-lung interactions is the microscopic visualization of nanoparticles within tissues or single cells both in vivo and in vitro. Once a certain type of nanoparticle can be identified unambiguously using microscopic methods it is desirable to quantify the particle distribution within a cell, an organ or the whole organism. Transmission electron microscopy provides an ideal tool to perform qualitative and quantitative analyses of particle-related structural changes of the respiratory tract, to reveal the localization of nanoparticles within tissues and cells and to investigate the 3D nature of nanoparticle-lung interactions.This article provides information on the applicability, advantages and disadvantages of electron microscopic preparation techniques and several advanced transmission electron microscopic methods including conventional, immuno and energy-filtered electron microscopy as well as electron tomography for the visualization of both model nanoparticles (e.g. polystyrene) and technologically relevant nanoparticles (e.g. titanium dioxide). Furthermore, we highlight possibilities to combine light and electron microscopic techniques in a correlative approach. Finally, we demonstrate a formal quantitative, i.e. stereological approach to analyze the distributions of nanoparticles in tissues and cells.This comprehensive article aims to provide a basis for scientists in nanoparticle research to integrate electron microscopic analyses into their study design and to select the appropriate microscopic strategy.

The effect of long-term water table manipulations on vegetation, pore water, substrate quality, and carbon cycling in a Northern poor fen peatland

Northern peatlands are large reservoirs of soil organic carbon (C). Historically peatlands have served as a sink for C since decomposition is slowed primarily because of a raised water table (WT) that creates anoxic conditions. Climate models are predicting dramatic changes in temperature and precipitation patterns for the northern hemisphere that contain more than 90% of the world’s peatlands. It is uncertain whether climate change will shift northern peatlands from C sequestering systems to a major global C source within the next century because of alterations to peatland hydrology. This research investigated the effects of 80 years of hydrological manipulations on peatland C cycling in a poor fen peatland in northern Michigan. The construction of an earthen levee within the Seney National Wildlife Refuge in the 1930’s resulted in areas of raised and lowered WT position relative to an intermediate WT site that was unaltered by the levee. We established sites across the gradient of long-term WT manipulations to examine how decadal changes in WT position alter peatland C cycling. We quantified vegetation dynamics, peat substrate quality, and pore water chemistry in relation to trace gas C cycling in these manipulated areas as well as the intermediate site. Vegetation in both the raised and lowered WT treatments has different community structure, biomass, and productivity dynamics compared to the intermediate site. Peat substrate quality exhibited differences in chemical composition and lability across the WT treatments. Pore water dissolved organic carbon (DOC) concentrations increased with impoundment and WT drawdown. The raised WT treatment DOC has a low aromaticity and is a highly labile C source, whereas WT drawdown has increased DOC aromaticity. This study has demonstrated a subtle change of the long-term WT position in a northern peatland will induce a significant influence on ecosystem C cycling with implications for the fate of peatland C stocks.