16 resultados para glycerin complexation and charcoal adsorption
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Dissertação para Obtenção de Grau de Mestre em Engenharia Química e Bioquímica
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The main objective of this thesis was the development of a gold nanoparticle-based methodology for detection of DNA adducts as biomarkers, to try and overcome existing drawbacks in currently employed techniques. For this objective to be achieved, the experimental work was divided in three components: sample preparation, method of detection and development of a model for exposure to acrylamide. Different techniques were employed and combined for de-complexation and purification of DNA samples (including ultrasonic energy, nuclease digestion and chromatography), resulting in a complete protocol for sample treatment, prior to detection. The detection of alkylated nucleotides using gold nanoparticles was performed by two distinct methodologies: mass spectrometry and colorimetric detection. In mass spectrometry, gold nanoparticles were employed for laser desorption/ionisation instead of the organic matrix. Identification of nucleotides was possible by fingerprint, however no specific mass signals were denoted when using gold nanoparticles to analyse biological samples. An alternate method using the colorimetric properties of gold nanoparticles was employed for detection. This method inspired in the non-cross-linking assay allowed the identification of glycidamide-guanine adducts and DNA adducts generated in vitro. For the development of a model of exposure, two different aquatic organisms were studies: a goldfish and a mussel. Organisms were exposed to waterborne acrylamide, after which mortality was recorded and effect concentrations were estimated. In goldfish, both genotoxicity and metabolic alterations were assessed and revealed dose-effect relationships of acrylamide. Histopathological alterations were verified primarily in pancreatic cells, but also in hepatocytes. Mussels showed higher effect concentrations than goldfish. Biomarkers of oxidative stress, biotransformation and neurotoxicity were analysed after prolonged exposure, showing mild oxidative stress in mussel cells, and induction of enzymes involved in detoxification of oxygen radicals. A qualitative histopathological screening revealed gonadotoxicity in female mussels, which may present some risk to population equilibrium.
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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Dissertação para obtenção do Grau de Doutor em Engenharia Química
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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Dissertação para obtenção do grau de Mestre em Engenharia Química e Bioquímica
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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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This work describes the synthesis and characterization of a series of new α-diimine and P,O, β-keto and acetamide phosphines ligands, and their complexation to Ni(II), Co(II),Co(III) and Pd(II) to obtain a series of new compounds aiming to study their structural characteristics and to test their catalytic activity. All the compounds synthesized were characterized by the usual spectroscopic and spectrometric techniques: Elemental Analysis, MALDI-TOF-MS spectrometry, IR, UV-vis, 1H, 13C and 31P NMR spectroscopies. Some of the paramagnetic compounds were also characterized by EPR. For the majority of the compounds it was possible to solve their solid state structure by single crystal X-ray diffraction. Tests for olefin polymerization were performed in order to determine the catalytic activity of the Co(II) complexes. Chapter I presents a brief introduction to homogenous catalysis, highlighting the reactions catalyzed by the type of compounds described in this thesis, namely olefin polymerization and oligomerization and reactions catalyzed by the complexes bearing α-diimines and P,O type ligands. Chapter II is dedicated to the description of the synthesis of new α-diimines cobalt (II) complexes, of general formula [CoX2(α-diimine)], where X = Cl or I and the α-diimines are bis(aryl)acenaphthenequinonediimine) (Ar-BIAN) and 1,4-diaryl-2,3-dimethyl-1,4-diaza-1,3-butadiene (Ar-DAB). Structures solved by single crystal X-ray diffraction were obtained for all the described complexes. For some of the compounds, X-band EPR measurements were performed on polycrystalline samples, showing a high-spin Co(II) (S = 3/2) ion, in a distorted axial environment. EPR single crystal experiments on two of the compounds allowed us to determine the g tensor orientation in the molecular structure. In Chapter III we continue with the synthesis and characterization of more cobalt (II)complexes bearing α-diimines of general formula [CoX2(α-diimine)], with X = Cl or I and α-diimines are bis(aryl)acenaphthenequinonediimine) (Ar-BIAN) and 1,4-diaryl-2,3-dimethyl- 1,4-diaza-1,3-butadiene (Ar-DAB). The structures of three of the new compounds synthesized were determined by single crystal X-ray diffraction. A NMR paramagnetic characterization of all the compounds described is presented. Ethylene polymerization tests were done to determine the catalytic activity of several of the Co(II) complexes described in Chapter II and III and their results are shown. In Chapter IV a new rigid bidentate ligand, bis(1-naphthylimino)acenaphthene, and its complexes with Zn(II) and Pd(II), were synthesized. Both the ligand and its complexes show syn and anti isomers. Structures of the ligand and the anti isomer of the Pd(II) complex were solved by single crystal X-ray diffraction. All the compounds were characterized by elemental analysis, MALDI-TOF-MS spectrometry, and by IR, UV-vis, 1H, 13C, 1H-1H COSY, 1H-13C HSQC, 1H-13C HSQC-TOCSY and 1H-1H NOESY NMR when necessary. DFT studies showed that both conformers of [PdCl2(BIAN)] are isoenergetics and can be obtain experimentally. However, we can predict that the isomerization process is not available in square-planar complex, but is possible for the free ligand. The molecular geometry is very similar in both isomers, and only different orientations for naphthyl groups can be expected. Chapter V describes the synthesis of new P, O type ligands, β-keto phosphine, R2PCH2C(O)Ph, and acetamide phosphine R2PNHC(O)Me, as well as a series of new cobalt(III) complexes namely [(η5-C5H5)CoI2{Ph2PCH2C(O)Ph}], and [(η5- C5H5)CoI2{Ph2PNHC(O)Me}]. Treating these Co(III) compounds with an excess of Et3N, resulted in complexes η2-phosphinoenolate [(η5-C5H5)CoI{Ph2PCH…C(…O)Ph}] and η2- acetamide phosphine [(η5-C5H5)CoI{Ph2PN…C(…O)Me}]. Nickel (II) complexes were also obtained: cis-[Ni(Ph2PN…C(…O)Me)2] and cis-[Ni((i-Pr)2PN…C(…O)Me)2]. Their geometry and isomerism were discussed. Seven structures of the compounds described in this chapter were determined by single crystal X-ray diffraction. The general conclusions of this work can be found in Chapter VI.
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Dissertação apresentada para a obtenção do Grau de Doutor em Bioquímica, especialidade de Bioquímica-Física pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica
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The EM3E Master is an Education Programme supported by the European Commission, the European Membrane Society (EMS), the European Membrane House (EMH), and a large international network of industrial companies, research centres and universities
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In this work, a volumetric unit previously assembled by the research group was upgraded. This unit revamping was necessary due to the malfunction of the solenoid valves employed in the original experimental setup, which were not sealing the gas properly leading to erroneous adsorption equilibrium measurements. Therefore, the solenoid valves were substituted by manual ball valves. After the volumetric unit improvement its operation was validated. For this purpose, the adsorption equilibrium of carbon dioxide (CO2) at 323K and 0 - 20 bar was measured on two different activated carbon samples, in the of extrudates (ANG6) and of a honeycomb monolith (ACHM). The adsorption equilibrium results were compared with data previously measured by the research group, using a high-pressure microbalance from Rubotherm GmbH (Germany) – gravimetric. The results obtained using both apparatuses are coincident thus validating the good operation of the volumetric unit upgraded in this work. Furthermore, the adsorption equilibrium of CO2 at 303K and 0 - 10 bar on Metal-Organic Frameworks (MOFs) Cu-BTC and Fe-BTC was also studied. The CO2 adsorption equilibrium results for both MOFs were compared with the literature results showing good agreement, which confirms the good quality of the experimental results obtained in the new volumetric unit. Cu-BTC sample showed significantly higher CO2 adsorption capacity when compared with the Fe-BTC sample. The revamping of the volumetric unit included a new valve configuration in order to allow testing an alternative method for the measurement of adsorption equilibrium. This new method was employed to measure the adsorption equilibrium of CO2 on ANG6 and ACHM at 303, 323 and 353K within 0-10 bar. The good quality of the obtained experimental data was testified by comparison with data previously obtained by the research group in a gravimetric apparatus.
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This work is divided into two distinct parts. The first part consists of the study of the metal organic framework UiO-66Zr, where the aim was to determine the force field that best describes the adsorption equilibrium properties of two different gases, methane and carbon dioxide. The other part of the work focuses on the study of the single wall carbon nanotube topology for ethane adsorption; the aim was to simplify as much as possible the solid-fluid force field model to increase the computational efficiency of the Monte Carlo simulations. The choice of both adsorbents relies on their potential use in adsorption processes, such as the capture and storage of carbon dioxide, natural gas storage, separation of components of biogas, and olefin/paraffin separations. The adsorption studies on the two porous materials were performed by molecular simulation using the grand canonical Monte Carlo (μ,V,T) method, over the temperature range of 298-343 K and pressure range 0.06-70 bar. The calibration curves of pressure and density as a function of chemical potential and temperature for the three adsorbates under study, were obtained Monte Carlo simulation in the canonical ensemble (N,V,T); polynomial fit and interpolation of the obtained data allowed to determine the pressure and gas density at any chemical potential. The adsorption equilibria of methane and carbon dioxide in UiO-66Zr were simulated and compared with the experimental data obtained by Jasmina H. Cavka et al. The results show that the best force field for both gases is a chargeless united-atom force field based on the TraPPE model. Using this validated force field it was possible to estimate the isosteric heats of adsorption and the Henry constants. In the Grand-Canonical Monte Carlo simulations of carbon nanotubes, we conclude that the fastest type of run is obtained with a force field that approximates the nanotube as a smooth cylinder; this approximation gives execution times that are 1.6 times faster than the typical atomistic runs.
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Simulated moving bed (SMB) chromatography is attracting more and more attention since it is a powerful technique for complex separation tasks. Nowadays, more than 60% of preparative SMB units are installed in the pharmaceutical and in the food in- dustry [SDI, Preparative and Process Liquid Chromatography: The Future of Process Separations, International Strategic Directions, Los Angeles, USA, 2002. http://www. strategicdirections.com]. Chromatography is the method of choice in these ¯elds, be- cause often pharmaceuticals and ¯ne-chemicals have physico-chemical properties which di®er little from those of the by-products, and they may be thermally instable. In these cases, standard separation techniques as distillation and extraction are not applicable. The noteworthiness of preparative chromatography, particulary SMB process, as a sep- aration and puri¯cation process in the above mentioned industries has been increasing, due to its °exibility, energy e±ciency and higher product purity performance. Consequently, a new SMB paradigm is requested by the large number of potential small- scale applications of the SMB technology, which exploits the °exibility and versatility of the technology. In this new SMB paradigm, a number of possibilities for improving SMB performance through variation of parameters during a switching interval, are pushing the trend toward the use of units with smaller number of columns because less stationary phase is used and the setup is more economical. This is especially important for the phar- maceutical industry, where SMBs are seen as multipurpose units that can be applied to di®erent separations in all stages of the drug-development cycle. In order to reduce the experimental e®ort and accordingly the coast associated with the development of separation processes, simulation models are intensively used. One impor- tant aspect in this context refers to the determination of the adsorption isotherms in SMB chromatography, where separations are usually carried out under strongly nonlinear conditions in order to achieve higher productivities. The accurate determination of the competitive adsorption equilibrium of the enantiomeric species is thus of fundamental importance to allow computer-assisted optimization or process scale-up. Two major SMB operating problems are apparent at production scale: the assessment of product quality and the maintenance of long-term stable and controlled operation. Constraints regarding product purity, dictated by pharmaceutical and food regulatory organizations, have drastically increased the demand for product quality control. The strict imposed regulations are increasing the need for developing optically pure drugs.(...)