Development of combined acidification and separation of slurry: effect on slurry fractions composition and gaseous emission

Doutoramento em Engenharia do Ambiente - Instituto Superior de Agronomia - UL

Design of composites for thermal management: Aluminum reinforced with diamond-containing bimodal particle mixtures

A new design route is proposed in order to fabricate aluminum matrix diamond-containing composite materials with optimized values of thermal conductivity (TC) for thermal management applications. The proper size ratio and proportions of particulate diamond–diamond and diamond–SiC bimodal mixtures are selected based on calculations with predictive schemes, which combine two main issues: (i) the volume fraction of the packed particulate mixtures, and (ii) the influence of different types of particulates (with intrinsically different metal/reinforcement interfacial thermal conductances) on the overall thermal conductivity of the composite material. The calculated results are validated by comparison with measurements on composites fabricated by gas pressure infiltration of aluminum into preforms of selected compositions of particle mixtures. Despite the relatively low quality (low price) of the diamond particles used in this work, outstanding values of TC are encountered: a maximum of 770 W/m K for Al/diamond–diamond and values up to 690 W/m K for Al/diamond–SiC.

TGA/FTIR study of the pyrolysis of diammonium hydrogen phosphate–tobacco mixtures

Diammonium hydrogen phosphate (DAP) is commonly used as a flavor ingredient of commercial cigarettes. In addition, among its other uses, it is employed to expand the tobacco volume, to manufacture reconstituted tobacco sheet, and to denicotinize tobacco. However, the use of DAP as a cigarette ingredient is a controversial issue. Some authors have stated that ammonium compounds added to tobacco increase smoke ammonia and “smoke pH”, resulting in more free nicotine available in the smoke. On the other hand, other researchers have reported that the larger ammonium content of a cigarette blend due to the presence of DAP was not reflected in increased smoke ammonia. In this work, the thermal behavior of DAP, tobacco and DAP-tobacco mixtures has been studied by TGA/FTIR. The chemical processes involved in the different pyrolysis steps of DAP have been suggested. Marked changes in the pyrolytic behavior of both, tobacco and DAP have been detected when analyzing the behavior of the mixtures. A displacement of the decomposition steps mainly related to the glycerol and lignin from tobacco toward lower temperatures has been observed, whereas that associated with cellulose is displaced toward higher temperature. Additionally, no peak corresponding to the phosphorous oxides decomposition has been detected in the curves relating to the DAP-tobacco mixtures. All these features are indicative of the strong interactions between DAP and tobacco. The FTIR spectra show no significant qualitative differences between the qualitative overall composition of the gases evolved from the pyrolysis of tobacco in the absence and in the presence of DAP. Nevertheless, depending on the temperature considered, the addition of DAP contributes to a decrease in the generation of hydrocarbons and an increase in the formation of CO, CO2 and oxygenated compounds in terms of amount generated per mass of pyrolysed tobacco.

Simple approximate MAP inference for Dirichlet processes mixtures

The Dirichlet process mixture model (DPMM) is a ubiquitous, flexible Bayesian nonparametric statistical model. However, full probabilistic inference in this model is analytically intractable, so that computationally intensive techniques such as Gibbs sampling are required. As a result, DPMM-based methods, which have considerable potential, are restricted to applications in which computational resources and time for inference is plentiful. For example, they would not be practical for digital signal processing on embedded hardware, where computational resources are at a serious premium. Here, we develop a simplified yet statistically rigorous approximate maximum a-posteriori (MAP) inference algorithm for DPMMs. This algorithm is as simple as DP-means clustering, solves the MAP problem as well as Gibbs sampling, while requiring only a fraction of the computational effort. (For freely available code that implements the MAP-DP algorithm for Gaussian mixtures see http://www.maxlittle.net/.) Unlike related small variance asymptotics (SVA), our method is non-degenerate and so inherits the “rich get richer” property of the Dirichlet process. It also retains a non-degenerate closed-form likelihood which enables out-of-sample calculations and the use of standard tools such as cross-validation. We illustrate the benefits of our algorithm on a range of examples and contrast it to variational, SVA and sampling approaches from both a computational complexity perspective as well as in terms of clustering performance. We demonstrate the wide applicabiity of our approach by presenting an approximate MAP inference method for the infinite hidden Markov model whose performance contrasts favorably with a recently proposed hybrid SVA approach. Similarly, we show how our algorithm can applied to a semiparametric mixed-effects regression model where the random effects distribution is modelled using an infinite mixture model, as used in longitudinal progression modelling in population health science. Finally, we propose directions for future research on approximate MAP inference in Bayesian nonparametrics.

Discrete Velocity Models for Mixtures Without Nonphysical Collision Invariants

An important aspect of constructing discrete velocity models (DVMs) for the Boltzmann equation is to obtain the right number of collision invariants. It is a well-known fact that DVMs can also have extra collision invariants, so called spurious collision invariants, in plus to the physical ones. A DVM with only physical collision invariants, and so without spurious ones, is called normal. For binary mixtures also the concept of supernormal DVMs was introduced, meaning that in addition to the DVM being normal, the restriction of the DVM to any single species also is normal. Here we introduce generalizations of this concept to DVMs for multicomponent mixtures. We also present some general algorithms for constructing such models and give some concrete examples of such constructions. One of our main results is that for any given number of species, and any given rational mass ratios we can construct a supernormal DVM. The DVMs are constructed in such a way that for half-space problems, as the Milne and Kramers problems, but also nonlinear ones, we obtain similar structures as for the classical discrete Boltzmann equation for one species, and therefore we can apply obtained results for the classical Boltzmann equation.

Activated Carbons Produced from Mixtures of Synthetic Polymers by Physical and Chemical Activation: Application on MCPA Removal

The production of AC was achieved using the most common industrial and consumer solid waste, namely PET, alone or blended with other synthetic polymer such PAN. The PET-PAN mixture (1:1 W/W %) was subjected to carbonization, with a pyrolysis yield off 31.9%, between that obtained with PET (16.9%) or PAN (42.6%) separately. By mixing PET, as a raw material, with PAN (different ratio), an improvement in the final yield of the AC production, for the same activation time, with CO2, was found.

Activated Carbons Produced from Mixtures of Synthetic Polymers by Physical and Chemical Activation: Application on MCPA Removal

The production of AC was achieved using the most common industrial and consumer solid waste, namely PET, alone or blended with other synthetic polymer such PAN. The PET-PAN mixture (1:1 W/W %) was subjected to carbonization, with a pyrolysis yield off 31.9%, between that obtained with PET (16.9%) or PAN (42.6%) separately. By mixing PET, as a raw material, with PAN (different ratio), an improvement in the final yield of the AC production, for the same activation time, with CO2, was found.

Liquid Mixtures Involving Hydrogenated and Fluorinated Alcohols: Thermodynamics, Spectroscopy, and Simulation

This article reports a combined thermodynamic, spectroscopic, and computational study on the interactions and structure of binary mixtures of hydrogenated and fluorinated substances that simultaneously interact through strong hydrogen bonding. Four binary mixtures of hydrogenated and fluorinated alcohols have been studied, namely, (ethanol + 2,2,2-trifluoroethanol (TFE)), (ethanol + 2,2,3,3,4,4,4-heptafluoro-1-butanol), (1-butanol (BuOH) + TFE), and (BuOH + 2,2,3,3,4,4,4-heptafluoro-1-butanol). Excess molar volumes and vibrational spectra of all four binary mixtures have been measured as a function of composition at 298 K, and molecular dynamics simulations have been performed. The systems display a complex behavior when compared with mixtures of hydrogenated alcohols and mixtures of alkanes and perfluoroalkanes. The combined analysis of the results from different approaches indicates that this results from a balance between preferential hydrogen bonding between the hydrogenated and fluorinated alcohols and the unfavorable dispersion forces between the hydrogenated and fluorinated chains. As the chain length increases, the contribution of dispersion increases and overcomes the contribution of H-bonds. In terms of the liquid structure, the simulations suggest the possibility of segregation between the hydrogenated and fluorinated segments, a hypothesis corroborated by the spectroscopic results. Furthermore, a quantitative analysis of the infrared spectra reveals that the presence of fluorinated groups induces conformational changes in the hydrogenated chains from the usually preferred all-trans to more globular arrangements involving gauche conformations. Conformational rearrangements at the CCOH dihedral angle upon mixing are also disclosed by the spectra.

Seemingly unrelated linear regression for contaminated data based on Gaussian mixtures

In this thesis, new classes of models for multivariate linear regression defined by finite mixtures of seemingly unrelated contaminated normal regression models and seemingly unrelated contaminated normal cluster-weighted models are illustrated. The main difference between such families is that the covariates are treated as fixed in the former class of models and as random in the latter. Thus, in cluster-weighted models the assignment of the data points to the unknown groups of observations depends also by the covariates. These classes provide an extension to mixture-based regression analysis for modelling multivariate and correlated responses in the presence of mild outliers that allows to specify a different vector of regressors for the prediction of each response. Expectation-conditional maximisation algorithms for the calculation of the maximum likelihood estimate of the model parameters have been derived. As the number of free parameters incresases quadratically with the number of responses and the covariates, analyses based on the proposed models can become unfeasible in practical applications. These problems have been overcome by introducing constraints on the elements of the covariance matrices according to an approach based on the eigen-decomposition of the covariance matrices. The performances of the new models have been studied by simulations and using real datasets in comparison with other models. In order to gain additional flexibility, mixtures of seemingly unrelated contaminated normal regressions models have also been specified so as to allow mixing proportions to be expressed as functions of concomitant covariates. An illustration of the new models with concomitant variables and a study on housing tension in the municipalities of the Emilia-Romagna region based on different types of multivariate linear regression models have been performed.

Competition between boson condensation and molecule formation in 2D Bose-Fermi mixtures with a pairing interaction

The study of ultra-cold atomic gases is one of the most active field in contemporary physics. The main motivation for the interest in this field consists in the possibility to use ultracold gases to simulate in a controlled way quantum many-body systems of relevance to other fields of physics, or to create novel quantum systems with unusual physical properties. An example of the latter are Bose-Fermi mixtures with a tunable pairing interaction between bosons and fermions. In this work, we study with many-body diagrammatic methods the properties of this kind of mixture in two spatial dimensions, extending previous work for three dimensional Bose-Fermi mixtures. At zero temperature, we focus specifically on the competition between boson condensation and the pairing of bosons and fermions into molecules. By a numerical solution of the main equations resulting by our many-body diagrammatic formalism, we calculate and present results for several thermodynamic quantities of interest. Differences and similarities between the two-dimensional and three-dimensional cases are pointed out. Finally, our new results are applied to discuss a recent proposal for creating a p-wave superfluid in Bose-Fermi mixtures with the fermionic molecules which form for sufficiently strong Bose-Fermi attraction.

Ultracold Bose-Fermi mixtures with pairing: quantum phase transition, mechanical stability, and trap confinement

Ultracold dilute gases occupy an important role in modern physics and they are employed to verify fundamental quantum theories in most branches of theoretical physics. The scope of this thesis work is the study of Bose-Fermi (BF) mixtures at zero temperature with a tunable pairing between bosons and fermions. The mixtures are treated with diagrammatic quantum many-body methods based on the so-called T-matrix formalism. Starting from the Fermi-polaron limit, I will explore various values of relative concentrations up to mixtures with a majority of bosons, a case barely considered in previous works. An unexpected quantum phase transition is found to occur in a certain range of BF coupling for mixture with a slight majority of bosons. The mechanical stability of mixtures has been analysed, when the boson-fermion interaction is changed from weak to strong values, in the light of experimental results recently obtained for a double-degenerate Bose-Fermi mixture of 23 Na - 40 K. A possible improvement in the description of the boson-boson repulsion based on Popov's theory is proposed. Finally, the effects of a harmonic trapping potential are described, with a comparison with the experimental data for the condensate fraction recently obtained for a trapped 23 Na - 40 K mixture.

Analytic models of self-gravitating rotating gaseous tori with central black hole

In this thesis project, I present stationary models of rotating fluids with toroidal distributions that can be used to represent the active galactic nuclei (AGN) central obscurers, i.e. molecular tori (Combes et al., 2019), as well as geometrically thick accretion discs, like ADAF discs (Narayan and Yi, 1995) or Polish doughnuts (Abramowicz, 2005). In particular, I study stationary rotating systems with a more general baroclinic distribution (with a vertical gradient of the angular velocity), which are often more realistic and less studied, due to their complexity, than the barotropic ones (with cylindrical rotation), which are easier to construct. In the thesis, I compute analytically the main intrinsic and projected properties of the power-law tori based on the potential-density pairs of Ciotti and Bertin (2005). I study the density distribution and the resulting gravitational potential for different values of α, in the range 2 < α < 5. For the same models, I compute the surface density of the systems when seen face-on and edge-on. I then apply the stationary Euler equations to obtain rotational velocity and temperature distributions of the self-gravitating models in the absence of an external gravitational potential. In the thesis I also consider the power-law tori with the presence of a central black hole in addition to the gas self-gravity, and solving analytically the stationary Euler equations, I compute how the properties of the system are modified by the black hole and how they vary as a function of the black hole mass. Finally, applying the Solberg-Høiland criterion, I show that these baroclinic stationary models are linearly stable in the absence of the black hole. In the presence of the black hole I derive the analytical condition for stability, which depends on α and on the black hole mass. I also study the stability of the tori in the hypothesis that they are weakly magnetized, finding that they are always unstable to this instability.

Spectral properties of resonant Bose-Fermi mixtures

The object of study of the present work are Bose-Fermi mixtures in three dimensions at zero temperature. The system is characterized by a great tunability of physical parameters that is achieved by means of a Fano-Feshbach resonance. As a result, there are mainly two regimes: we move from a situation in which bosons and fermions are weakly interacting to a context in which bosons are coupled to fermions so as to form molecules that are composite fermions, as the coupling between the two types of particles is increased. In the former case, we can describe the mixture as a weakly attractive Bose-Fermi one, while in the latter the same is described in terms of molecules and excess atoms or particles which are unpaired. The main aim of the thesis is to analyze the spectral weight functions which represent the single-particle excitation spectra of the system and are relevant to recent radio-frequency spectroscopy experiments of the system. In order to pursue this objective, diagrammatic methods are used. The formalism is developed within the T-matrix approach: it consists of an approximate calculation whichselects exclusively the class of Feynman’s diagrams that collects all possible repeated boson-fermion interaction.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Direct Visualization Of The Action Of Triton X-100 On Giant Vesicles Of Erythrocyte Membrane Lipids.

The raft hypothesis proposes that microdomains enriched in sphingolipids, cholesterol, and specific proteins are transiently formed to accomplish important cellular tasks. Equivocally, detergent-resistant membranes were initially assumed to be identical to membrane rafts, because of similarities between their compositions. In fact, the impact of detergents in membrane organization is still controversial. Here, we use phase contrast and fluorescence microscopy to observe giant unilamellar vesicles (GUVs) made of erythrocyte membrane lipids (erythro-GUVs) when exposed to the detergent Triton X-100 (TX-100). We clearly show that TX-100 has a restructuring action on biomembranes. Contact with TX-100 readily induces domain formation on the previously homogeneous membrane of erythro-GUVs at physiological and room temperatures. The shape and dynamics of the formed domains point to liquid-ordered/liquid-disordered (Lo/Ld) phase separation, typically found in raft-like ternary lipid mixtures. The Ld domains are then separated from the original vesicle and completely solubilized by TX-100. The insoluble vesicle left, in the Lo phase, represents around 2/3 of the original vesicle surface at room temperature and decreases to almost 1/2 at physiological temperature. This chain of events could be entirely reproduced with biomimetic GUVs of a simple ternary lipid mixture, 2:1:2 POPC/SM/chol (phosphatidylcholine/sphyngomyelin/cholesterol), showing that this behavior will arise because of fundamental physicochemical properties of simple lipid mixtures. This work provides direct visualization of TX-100-induced domain formation followed by selective (Ld phase) solubilization in a model system with a complex biological lipid composition.