958 resultados para 030503 Organic Chemical Synthesis
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Agência Financiadora: Fundação para a Ciência e a Tecnologia/MCTES (Portugal) - PEst-OE/EQB/UI0702/2012
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A rapid, specific, and sensitive method based on theQuick Easy Cheap Effective Rugged and Safe (QuEChERS) method and a cleanup using dispersive solid-phase extraction with MgSO4, PSA, and C18 sorbents has been developed for the routine analysis of 14 pesticides in strawberries. The analyses were performed by three different analytical methodologies: gas chromatography (GC) with electron capture detection (ECD), mass spectrometry (MS), and tandem mass spectrometry (MS/MS). The recoveries for all the pesticides studied were from 46 to 128%, with relative standard deviation of <15% in the concentration range of 0.005-0.250 mg/kg. The limit of detection (LOD) for all compoundsmetmaximumresidue limits (MRL) accepted in Portugal for organochlorine pesticides (OCP). A survey study of strawberries produced in Portugal in the years 2009-2010 obtained from organic farming (OF) and integrated pest management (IPM) was developed. Lindane and β-endosulfan were detected above the MRL in OF and IPM. Other OCP (aldrin, o,p0-DDT and their metabolites, and methoxychlor) were found below the MRL. The OCP residues detected decreased from 2009 to 2010. The QuEChERS method was successfully applied to the analysis of strawberry samples.
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This communication presents a novel kind of silicon nanomaterial: freestanding Si nanowire arrays (Si NWAs), which are synthesized facilely by one-step template-free electro-deoxidation of SiO2 in molten CaCl2. The self-assembling growth process of this material is also investigated preliminarily.
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Trabalho Final de Mestrado para obtenção do grau de mestre em Engenharia Química e Biológica
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Integrally asymmetric skinned Lenzing P84 and Matrimid 5218 polymide membranes and Ultem 1000 polyetherimide membranes were prepared. Crosslinking of membranes using aliphatic diamines resulted in marked improvement in chemical stability. This however resulted in a decline in flux with only Lenzing P84 demonstrating good flux in DMF. Further variation of membrane dope parameters and operating conditions allowed for good control of the MWCO of membranes made from Lenzing P84. SEM pictures of Lenzing P84 membranes revealed a significant difference in membranes morphology. The presence of macrovoids increased when using more DMF in the dope solution. These studies demonstrate the possibility of developing OSN membranes using different polyimides and opens up future possibilities for controlling the MWCO of these membranes. Preliminary modelling demonstrates that good control of the MWCO could extend the application of OSN membranes to allow the fraction of molecules in the NF range.
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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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A series of mono(eta(5)-cyclopentadienyl)metal-(II) complexes with nitro-substituted thienyl acetylide ligands of general formula [M(eta(5)-C5H5)(L)(C C{C4H2S}(n)NO2)] (M = Fe, L = kappa(2)-DPPE, n = 1,2; M = Ru, L = kappa(2)-DPPE, 2 PPh3, n = 1, 2; M = Ni, L = PPh3, n = 1, 2) has been synthesized and fully characterized by NMR, FT-IR, and UV-Vis spectroscopy. The electrochemical behavior of the complexes was explored by cyclic voltammetry. Quadratic hyperpolarizabilities (beta) of the complexes have been determined by hyper-Rayleigh scattering (HRS) measurements at 1500 nm. The effect of donor abilities of different organometallic fragments on the quadratic hyperpolarizabilities was studied and correlated with spectroscopic and electrochemical data. Density functional theory (DFT) and time-dependent DFT (TDDFT) calculations were employed to get a better understanding of the second-order nonlinear optical properties in these complexes. In this series, the complexity of the push pull systems is revealed; even so, several trends in the second-order hyperpolarizability can still be recognized. In particular, the overall data seem to indicate that the existence of other electronic transitions in addition to the main MLCT clearly controls the effectiveness of the organometallic donor ability on the second-order NLO properties of these push pull systems.
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New highly fluorescent calix[4]arene-containing phenylene-alt-ethynylene-3,6- and 2,7-carbazolylene polymers (CALIX-PPE-CBZs) have been synthesized for the first time and their photophysical properties evaluated. Both polymers were obtained in good isolated yields (70-84%), having M-w ranging from 7660-26,700 g mol(-1). It was found that the diethynyl substitution (3,6- or 2,7-) pattern on the carbazole monomers markedly influences the degree of polymerization. The amorphous yellow polymers are freely soluble in several nonprotic organic solvents and have excellent film forming abilities. TG/DSC analysis evidences similar thermal behaviors for both polymers despite their quite different molecular weight distributions and main-chain connectivities (T-g, in the range 83-95 degrees C and decomposition onsets around 270 degrees C). The different conjugation lengths attained by the two polymers dictates much of their photophysical properties. Thus, whereas the fully conjugated CALIX-PPE-2,7-CBZ has its emission maximum at 430 nm (E-g = 2.84 eV; Phi(F) = 0.62, CHCl3), the 3,6-linked counterpart (CALIX-PPE-3,6-CBZ) fluoresces at 403 nm with a significant lower quantum yield (E-g = 3.06 eV; Phi(F) = 0.31, CHCl3). The optical properties of both polymers are predominantly governed by the intrachain electronic properties of the conjugated backbones owing to the presence of calix[4]arenes along the polymer chain which disfavor significant interchain interactions, either in fluid- or solid-state.
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A number of novel, water-stable redox-active cobalt complexes of the C-functionalized tripodal ligands tris(pyrazolyl)methane XC(pz)(3) (X = HOCH2, CH2OCH2Py or CH2OSO2Me) are reported along with their effects on DNA. The compounds were isolated as air-stable solids and fully characterized by IR and FIR spectroscopies, ESI-MS(+/-), cyclic voltammetry, controlled potential electrolysis, elemental analysis and, in a number of cases, also by single-crystal X-ray diffraction. They showed moderate cytotoxicity in vitro towards HCT116 colorectal carcinoma and HepG2 hepatocellular carcinoma human cancer cell lines. This viability loss is correlated with an increase of tumour cell lines apoptosis. Reactivity studies with biomolecules, such as reducing agents, H2O2, plasmid DNA and UV-visible titrations were also performed to provide tentative insights into the mode of action of the complexes. Incubation of Co(II) complexes with pDNA induced double strand breaks, without requiring the presence of any activator. This pDNA cleavage appears to be mediated by O-centred radical species.
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This article reports on a new and swift hydrothermal chemical route to prepare titanate nanostructures (TNS) avoiding the use of crystalline TiO2 as starting material. The synthesis approach uses a commercial solution of TiCl3 as titanium source to prepare an amorphous precursor, circumventing the use of hazardous chemical compounds. The influence of the reaction temperature and dwell autoclave time on the structure and morphology of the synthesised materials was studied. Homogeneous titanate nanotubes with a high length/diameter aspect ratio were synthesised at 160 degrees C and 24 h. A band gap of 3.06 +/- 0.03 eV was determined for the TNS samples prepared in these experimental conditions. This value is red shifted by 0.14 eV compared to the band gap value usually reported for the TiO2 anatase. Moreover, such samples show better adsorption capacity and photocatalytic performance on the dye rhodamine 6G (R6G) photodegradation process than TiO2 nanoparticles. A 98% reduction of the R6G concentration was achieved after 45 min of irradiation of a 10 ppm dye aqueous solution and 1 g L-1 of TNS catalyst.
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Every year, particularly during the summer period, the Portuguese forests are devastated by forest fire that destroys their ecosystems. So in order to prevent these forest fires, public and private authorities frequently use methods for the reduction of combustible mass as the prescribed fire and the mechanical vegetation pruning. All of these methods of prevention of forest fires alter the vegetation layer and/or soil [1-2]. This work aimed the study of the variation of some chemical characteristics of soil that suffered prescribed fire. The studied an area was located in the Serra of Cabreira (Figure 1) with 54.6 ha. Twenty sampling points were randomly selected and samples were collected with a shovel before, just after the prescribed fire, and 125 and 196 days after that event. The parameters that were studied were: pH, soil moisture, organic matter and iron, magnesium and potassium total concentration. All the analysis followed International Standard Methodologies. This work allowed to conclude that: a) after the prescribed fire; i) the pH remained practically equal to the the initial value; ii) occurred a slight increase of the average of the organic matter contents and iron total contents; b) at the end of the sampling period compared to the initial values; i) the pH didn´t change significantly; ii) the average of the contents of organic matter decreased; and iii) the average of the total contents of Fe, Mg and K increased.
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Prescribed fire is a common forest management tool used in Portugal to reduce the fuel load availability and minimize the occurrence of wildfires. In addition, the use of this technique also causes an impact to ecosystems. In this presentation we propose to illustrate some results of our project in two forest sites, both located in Northwest Portugal, where the effect of prescribed fire on soil properties were recorded during a period of 6 months. Changes in soil moisture, organic matter, soil pH and iron, were examined by Principal Component Analysis multivariate statistics technique in order to determine impact of prescribed fire on these soil properties in these two different types of soils and determine the period of time that these forest soils need to recover to their pre-fire conditions, if they can indeed recover. Although the time allocated to this study does not allow for a widespread conclusion, the data analysis clearly indicates that the pH values are positively correlated with iron values at both sites. In addition, geomorphologic differences between both sampling sites, Gramelas and Anjos, are relevant as the soils’ properties considered have shown different performances in time. The use of prescribed fire produced a lower impact in soils originated from more amended bedrock and therefore with a ticker humus covering (Gramelas) than in more rocky soils with less litter covering (Anjos) after six months after the prescribed fire occurrence.
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Microwave assisted synthesis of the Cu(I) compound [Cu(µ4-4-ptz)]n [1, 4-ptz = 5-(4-pyridyl)tetrazolate] has been performed by employing a relatively easy method and within a shorter period of time compared to its sister compounds. The syntheses of the Cu(II) compounds [Cu3(µ3-4-ptz)4(µ2-N3)2(DMF)2]n∙(DMF)2n (2) and [Cu(µ2-4-ptz)2(H2O)2]n (3) using a similar method were reported previously by us. MOFs 1-3 revealed high catalytic activity toward oxidation of cyclic alkanes (cyclopentane, -hexane and -octane) with aqueous hydrogen peroxide, under very mild conditions (at room temperature), without any added solvent or additive. The most efficient system (2/H2O2) showed, for the oxidation of cyclohexane, a turnover number (TON) of 396 (TOF of 40 h−1), with an overall product yield (cyclohexanol and cyclohexanone) of 40% relative to the substrate. Moreover, the heterogeneous catalytic systems 1–3 allowed an easy catalyst recovery and reuse, at least for four consecutive cycles, maintaining ca. 90% of the initial high activity and concomitant high selectivity.