New nickel catalysts supported on highly porous alumina intercalated laponite for methane reforming with CO2

Alumina intercalated laponite (Al-laponite) was prepared with a polyethylene oxide (PEO) surfactant and used as supports of nickel catalysts for the carbon dioxide reforming reaction with methane to synthesis gas. The effects of the supports of intercalated laponite and catalyst preparation on catalytic activity, stability and carbon deposition were investigated for the above reforming reaction. We found that the pore structure of the Al-laponite supports can be tailored with the surfactant and the catalyst with well-developed porosity exhibited higher catalytic activity and a longer time of catalyst stability. (C) 2001 Elsevier Science B.V. All rights reserved.

Investigation of the vapor-phase grafting of styrene onto PFA

Poly(tetrafluoroethylene-co-perfluoropropyI vinyl ether), PFA, was grafted with styrene from the vapor phase using a simultaneous radiation grafting method. The graft yields were measured as a function of the dose and dose rate and were found to be initially linearly dependent on the dose and independent of the dose rate up to dose rates of similar to3 kGy/h. However, at a dose rate of 6.2 kGy/h, the slope of the yield-grafting time plot decreased. Raman depth profiles of the grafts showed that the polystyrene concentrations were greatest near the surface of the grafted samples and decreased with depth. The maximum penetration depth of the graft depended on the radiation dose for a fixed dose rate. Fmoc-Rink loading tests showed that the grafts displayed superior loading compared to grafts prepared from bulk styrene or from styrene solutions other than methanol.

Availability of heavy metals in contaminated soil evidenced by chemical extractants

Heavy metals have been accumulating in Brazilian soils, due to natural processes, such as atmospheric deposition, or human industrial activities. For certain heavy metals, when in high concentrations in the soil, there is no specific extractant to determine the availability of these elements in the soil. The objective of the present study was to evaluate the availability of Cd, Cu, Fe, Mn, Pb and Zn for rice and soybeans, using different chemical extractants. In this study we used seven soil samples with different levels of contamination, in completely randomized experimental design with four replications. We determined the available concentrations of Cd, Cu, Fe, Mn, Pb and Zn extracted by Mehlich-1, HCl 0.1 mol L-1, DTPA, and organic acid extractants and the contents in rice and soybeans, which extracts were analyzed by ICP-OES. It was observed that Mehlich-1, HCl 0.1 mol L-1 and DTPA extractants were effective to assess the availability of Cd, Cu, Pb and Zn for rice and soybeans. However, the same was not observed for the organic acid extractant.

A new chemical route to synthesise TM-doped (TM = Co, Fe) TiO2 nanoparticles

Since the discovery of ferromagnetism well above room temperature in the Co-doped TiO2 system, diluted magnetic semiconductors based on TiO2 doped with transition metals have generated great interest because of their potential use in the development of spintronic devices. The purpose of this paper is to report on a new and swift chemical route to synthesise highly stable anatase single-phase Co- and Fe-doped TiO2 nanoparticles, with dopant concentrations of up to 10 at.-% and grain sizes that range between 20 and 30 nm. Complementary structural, microstructural and chemical analyses of the different nanopowders synthesised strongly support the hypothesis that a homogeneous distribution of the dopant element in the substitutional sites of the anatase structure has been achieved. Moreover, UV/Vis diffuse reflectance spectra of powder samples show redshifts to lower energies and decreasing bandgap energies with increasing Co or Fe concentration, which is consistent with n-type doping of the TiO2 anatase matrix. Films of Co-doped TiO2 were successfully deposited onto Si (100) substrates by the dip-coating method, with suspensions of Ti1-xCOxO2 nanoparticles in ethylene glycol. ((C)Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2008).

Catalytic combustion of toluene on Pt zeolite coated cordierite foams

The catalytic properties of Pt based cordierite foam catalysts have been evaluated in catalytic combustion of toluene (800 ppm in air). The catalysts contain identical Pt content (0.1%) which was introduced by three different ways: Pt ion exchange on MFI zeolite and then coating on the foam; Pt ion exchange after zeolite coating and finally Pt directly wet impregnated on the cordierite foam. The catalytic behaviour of Pt foam based catalysts was compared with that of PtMFI zeolite under powder form. Pt exchanged MFI supported on the cordierite foams present an improvement of activity for toluene combustion of about 50 degrees C on the light off temperature (T-50%). The enhanced performance of the structured catalysts is due not only to the open structure of foams and homogeneous thin layers catalyst deposited on their cell walls, but also to the fact that the size and location of Pt particles present in MFI zeolite are changed during the dipping step. Indeed, as prepared Pt samples and those used in the preparation of the slurry were observed by transmission electron microscopy revealing that the chemical interaction of PtMFI zeolite with the binder and detergent, both present in the slurry, leads to an increase of Pt particles size which were found to migrate from internal pores to the external surface of zeolite crystallites thereby increasing catalytic activity. (C) 2011 Elsevier B.V. All rights reserved.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

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.

Modifications of MCM-22 zeolite through sequential post-synthesis treatments. Implications on the acidic and catalytic behaviour

Desilication and a combination of alkaline followed by acid treatment were applied to MCM-22 zeolite using two different base concentrations. The samples were characterised by powder X-ray diffraction, Al-27 and Si-29 MAS-NMR spectroscopy, SEM, TEM and low temperature N-2 adsorption. The acidity of the samples was study through pyridine adsorption followed by FTIR spectroscopy and by the analyses of the hydroxyl region. The catalytic behaviour, anticipated by the effect of post-synthesis treatments on the acidity and space available inside the two internal pore systems was evaluated by using the model reaction of m-xylene transformation. The generation of mesoporosity was achieved upon alkaline treatment with 0.05 M NaOH solution and practically no additional gain was obtained when the more concentrate solution, 0.1 M, was used. Instead, Al extraction takes place along with Si, as shown by Si-29 and Al-27 MAS-NMR data, followed by Al deposition as extraframework species. Samples submitted to alkaline plus acid treatments present distinct behaviour. When the lowest NaOH solution was used no relevant effect was observed on the textural characteristics. Additionally, when the acid treatment was performed on an already fragilized MCM-22 structure, due to previous desilication with 0.1 M NaOH solution, the extraction of Al from both internal pore systems promotes their interconnection, evolving from a 2-D to a 3-D porous structure. This transformation has a marked effect in the catalytic behaviour, allowing an increase of m-xylene conversion as a consequence of an easier and faster molecular traffic in the 3-D structure. On the other hand, the continuous deposition of extraframework Al species inside the pores leads to a shape selective effect that privileges the formation of the more valuable isomer p-xylene.

Novel coordination polymers with (Pyrazolato)-based tectons: catalytic activity in the peroxidative oxidation of alcohols and cyclohexane

Coupling five rigid or flexible bis(pyrazolato)based tectons with late transition metal ions allowed us to isolate 18 coordination polymers (CPs). As assessed by thermal analysis, all of them possess a remarkable thermal stability, their decomposition temperatures lying in the range of 340-500 degrees C. As demonstrated by N-2 adsorption measurements at 77 K, their Langmuir specific surface areas span the rather vast range of 135-1758 m(2)/g, in agreement with the porous or dense polymeric architectures retrieved by powder X-ray diffraction structure solution methods. Two representative families of CPs, built up with either rigid or flexible spacers, were tested as catalysts in (0 the microwave-assisted solvent-free peroxidative oxidation of alcohols by t-BuOOH, and (ii) the peroxidative oxidation of cydohexane to cydohexanol and cydohexanone by H2O2 in acetonitrile. Those CPs bearing the rigid spacer, concurrently possessing higher specific surface areas, are more active than the corresponding ones with the flexible spacer. Moreover, the two copper(I)-containing CPs investigated exhibit the highest efficiency in both reactions, leading selectively to a maximum product yield of 92% (and TON up to 1.5 x 10(3)) in the oxidation of 1-phenylethanol and of 11% in the oxidation of cydohexane, the latter value being higher than that granted by the current industrial process.

Electrospun Polyaniline-Reduced Graphene Oxide Composite Nanofibers Based High Sensitive Ammonia Gas Sensor

Ammonia is an important gas in many power plants and industrial processes so its detection is of extreme importance in environmental monitoring and process control due to its high toxicity. Ammonia’s threshold limit is 25 ppm and the exposure time limit is 8 h, however exposure to 35 ppm is only secure for 10 min. In this work a brief introduction to ammonia aspects are presented, like its physical and chemical properties, the dangers in its manipulation, its ways of production and its sources. The application areas in which ammonia gas detection is important and needed are also referred: environmental gas analysis (e.g. intense farming), automotive-, chemical- and medical industries. In order to monitor ammonia gas in these different areas there are some requirements that must be attended. These requirements determine the choice of sensor and, therefore, several types of sensors with different characteristics were developed, like metal oxides, surface acoustic wave-, catalytic-, and optical sensors, indirect gas analyzers, and conducting polymers. All the sensors types are described, but more attention will be given to polyaniline (PANI), particularly to its characteristics, syntheses, chemical doping processes, deposition methods, transduction modes, and its adhesion to inorganic materials. Besides this, short descriptions of PANI nanostructures, the use of electrospinning in the formation of nanofibers/microfibers, and graphene and its characteristics are included. The created sensor is an instrument that tries to achieve a goal of the medical community in the control of the breath’s ammonia levels being an easy and non-invasive method for diagnostic of kidney malfunction and/or gastric ulcers. For that the device should be capable to detect different levels of ammonia gas concentrations. So, in the present work an ammonia gas sensor was developed using a conductive polymer composite which was immobilized on a carbon transducer surface. The experiments were targeted to ammonia measurements at ppb level. Ammonia gas measurements were carried out in the concentration range from 1 ppb to 500 ppb. A commercial substrate was used; screen-printed carbon electrodes. After adequate surface pre-treatment of the substrate, its electrodes were covered by a nanofibrous polymeric composite. The conducting polyaniline doped with sulfuric acid (H2SO4) was blended with reduced graphene oxide (RGO) obtained by wet chemical synthesis. This composite formed the basis for the formation of nanofibers by electrospinning. Nanofibers will increase the sensitivity of the sensing material. The electrospun PANI-RGO fibers were placed on the substrate and then dried at ambient temperature. Amperometric measurements were performed at different ammonia gas concentrations (1 to 500 ppb). The I-V characteristics were registered and some interfering gases were studied (NO2, ethanol, and acetone). The gas samples were prepared in a custom setup and were diluted with dry nitrogen gas. Electrospun nanofibers of PANI-RGO composite demonstrated an enhancement in NH3 gas detection when comparing with only electrospun PANI nanofibers. Was visible higher range of resistance at concentrations from 1 to 500 ppb. It was also observed that the sensor had stable, reproducible and recoverable properties. Moreover, it had better response and recovery times. The new sensing material of the developed sensor demonstrated to be a good candidate for ammonia gas determination.

Low-Spin Heme b3 in the Catalytic Center of Nitric Oxide Reductase from Pseudomonas nautica

Biochemistry, 2011, 50 (20), pp 4251–4262 DOI: 10.1021/bi101605p

The thermal effects on the methanol-to-olefins reaction: A modelling and experimental approach

With the projection of an increasing world population, hand-in-hand with a journey towards a bigger number of developed countries, further demand on basic chemical building blocks, as ethylene and propylene, has to be properly addressed in the next decades. The methanol-to-olefins (MTO) is an interesting reaction to produce those alkenes using coal, gas or alternative sources, like biomass, through syngas as a source for the production of methanol. This technology has been widely applied since 1985 and most of the processes are making use of zeolites as catalysts, particularly ZSM-5. Although its selectivity is not especially biased over light olefins, it resists to a quick deactivation by coke deposition, making it quite attractive when it comes to industrial environments; nevertheless, this is a highly exothermic reaction, which is hard to control and to anticipate problems, such as temperature runaways or hot-spots, inside the catalytic bed. The main focus of this project is to study those temperature effects, by addressing both experimental, where the catalytic performance and the temperature profiles are studied, and modelling fronts, which consists in a five step strategy to predict the weight fractions and activity. The mind-set of catalytic testing is present in all the developed assays. It was verified that the selectivity towards light olefins increases with temperature, although this also leads to a much faster catalyst deactivation. To oppose this effect, experiments were carried using a diluted bed, having been able to increase the catalyst lifetime between 32% and 47%. Additionally, experiments with three thermocouples placed inside the catalytic bed were performed, analysing the deactivation wave and the peaks of temperature throughout the bed. Regeneration was done between consecutive runs and it was concluded that this action can be a powerful means to increase the catalyst lifetime, maintaining a constant selectivity towards light olefins, by losing acid strength in a steam stabilised zeolitic structure. On the other hand, developments on the other approach lead to the construction of a raw basic model, able to predict weight fractions, that should be tuned to be a tool for deactivation and temperature profiles prediction.

Tailored deposition of coloured coatings: on the widening of the available colour range

Dissertação de mestrado integrado em Engenharia de Materiais

Surface phenomena and hydrodynamic effects on the deposition of Pseudomonas fluorescens

Biofilm adhesion to metals (copper, aluminium and brass) was studied at two different velocities and pH values of 7 and 9. Both bacteria and metals showed negative surface charges at those values of pH, which tends to slow down adhesion. Film densities increased with the fluid velocity and were also affected by the pH and by the growth rate of the bacteria. Long duration tests based on heat transfer measurements were run at five different fluid velocities and at pH = 7, showing in general an asymptotic behaviour and a control of deposition by adhesion and growth phenomena.

Secondary effects of catalytic diesel particulate filters: copper-induced formation of PCDD/Fs.

Potential risks of a secondary formation of polychlorinated dibenzodioxins/furans (PCDD/Fs) were assessed for two cordierite-based, wall-through diesel particulate filters (DPFs) for which soot combustion was either catalyzed with an iron- or a copper-based fuel additive. A heavy duty diesel engine was used as test platform, applying the eight-stage ISO 8178/4 C1 cycle. DPF applications neither affected the engine performance, nor did they increase NO, NO2, CO, and CO2 emissions. The latter is a metric for fuel consumption. THC emissions decreased by about 40% when deploying DPFs. PCDD/F emissions, with a focus on tetra- to octachlorinated congeners, were compared under standard and worst case conditions (enhanced chlorine uptake). The iron-catalyzed DPF neither increased PCDD/F emissions, nor did it change the congener pattern, even when traces of chlorine became available. In case of copper, PCDD/F emissions increased by up to 3 orders of magnitude from 22 to 200 to 12 700 pg I-TEQ/L with fuels of < 2, 14, and 110 microg/g chlorine, respectively. Mainly lower chlorinated DD/Fs were formed. Based on these substantial effects on PCDD/F emissions, the copper-catalyzed DPF system was not approved for workplace applications, whereas the iron system fulfilled all the specifications of the Swiss procedures for DPF approval (VERT).

Modelització i control d'un reactor de producció d'hidrogen per a l'alimentació de piles de combustible

Les piles de combustible permeten la transformació eficient de l’energia química de certs combustibles a energia elèctrica a través d’un procés electroquímic. De les diferents tecnologies de piles de combustible, les piles de combustible de tipus PEM són les més competitives i tenen una gran varietat d’aplicacions. No obstant, han de ser alimentades únicament per hidrogen. Per altra banda, l’etanol, un combustible interessant en el marc dels combustibles renovables, és una possible font d’hidrogen. Aquest treball estudia la reformació d’etanol per a l’obtenció d’hidrogen per a alimentar piles de combustible PEM. Només existeixen algunes publicacions que tractin l’obtenció d’hidrogen a partir d’etanol, i aquestes no inclouen l’estudi dinàmic del sistema. Els objectius del treball són el modelat i l’estudi dinàmic de reformadors d’etanol de baixa temperatura. Concretament, proposa un model dinàmic d’un reformador catalític d’etanol amb vapor basat en un catalitzador de cobalt. Aquesta reformació permet obtenir valors alts d’eficiència i valors òptims de monòxid de carboni que evitaran l’enverinament d’una la pila de combustible de tipus PEM. El model, no lineal, es basa en la cinètica obtinguda de diferents assaigs de laboratori. El reformador modelat opera en tres etapes: deshidrogenació d’etanol a acetaldehid i hidrogen, reformat amb vapor d’acetaldehid, i la reacció WGS (Water Gas Shift). El treball també estudia la sensibilitat i controlabilitat del sistema, caracteritzant així el sistema que caldrà controlar. L’anàlisi de controlabilitat es realitza sobre la resposta de dinàmica ràpida obtinguda del balanç de massa del reformador. El model no lineal és linealitzat amb la finalitat d’aplicar eines d’anàlisi com RGA, CN i MRI. El treball ofereix la informació necessària per a avaluar la possible implementació en un laboratori de piles de combustibles PEM alimentades per hidrogen provinent d’un reformador d’etanol.