On the template synthesis of nanostructured inorganic/organic hybrid films

Prussian Blue has been introduced as a mediator to achieve stable, sensitive, reproducible, and interference-free biosensors. However, Na(+), Li(+), H(+), and all group II cations are capable to block the activity of Prussian Blue and, because Na(+) can be found in most human fluids, Prussian Blue analogs have already been developed to overcome this problem. These analogs, such as copper hexacyanoferrate, have also been introduced in a conducting polypyrrole matrix to create hybrid materials (copper hexacyanoferrate/polypyrrole, CuHCNFe/Ppy) with improved mechanical and electrochemical characteristics. Nowadays, the challenges in amperometric enzymatic biosensors consist of improving the enzyme immobilization and in making the chemical signal transduction more efficient. The incorporation of nanostructured materials in biosensors can optimize both steps and a nanostructured hybrid CuHCNFe/Ppy mediator has been developed using a template of colloidal polystyrene particles. The nanostructured material has achieved sensitivities 7.6 times higher than the bulk film during H(2)O(2) detection and it has also presented better results in other analytical parameters such as time response and detection limit. Besides, the nanostructured mediator was successfully applied at glucose biosensing in electrolytes containing Prussian Blue blocking cations. (C) 2008 The Electrochemical Society.

Chemical characterization of agricultural supplies applied to organic tomato cultivation

The agricultural supplies used in the organic system to control pests and diseases as well as to fertilize soil are claimed to be beneficial to plants and innocuous to human health and to the environment. The chemical composition of six agricultural supplies commonly used in the organic tomato culture, was evaluated by instrumental neutron activation analysis (INAA). Results were compared to the maximum limits established by the Environment Control Agency of the Sao Paulo State (CETESB) and the Guidelines for Organic Quality Standard of Instituto Biodinamico (IBD). Concentrations above reference values were found for Co, Cr and Zn in compost, Cr and Zn in cattle manure and Zn in rice bran.

Chemical composition of tomato seeds affected by conventional and organic production systems

Tomato is amongst the most consumed vegetables in the world, not only for its culinary versatility but also for its high nutritional value. In the last years, consumers have shown an increased concern regarding food origin and safety. The organic tomato production has been a promising alternative for the consumer offering a safer food in relation to environmental, social and nutritional aspects. This study assessed the chemical composition of tomato seeds produced in both conventional and organic systems by INAA. The results showed significant differences (P <= 0.05) in the mass fractions of Br, Cs, Eu, Fe, K, Mo, Na, Rb and Sm between both systems, indicating influence of the crop management adopted in the different tomato production systems.

Comparison of adsorbent films obtained by plasma polymerization of oxygenated organic compounds

Thin films obtained by plasma polymerization of ethyl ether, methyl or ethyl acetate, acetaldehyde, acetone and 2-propanol were compared. Infrared spectroscopy (FFIR), resistance to chemicals, contact angle measurements, X-ray photoelectron spectroscopy (XPS), optical and scanning electron microscopy (SEM), and quartz crystal microbalance (QCM) were carried out. For all films FTIR showed high intensity for polar bonds yet the films are not resistant to polar solvents. Contact angle measurements revealed hydrophilic and organophilic surfaces and XPS pointed out a high proportion of oxygenated bonds. All films showed good step coverage and peeling was significant only with acetone and 2-propanol. All films are adsorbent for organic compounds in a large scale of polarity but acetaldehyde and 2-propanol act like a selective membrane. Also, deposition of these films on hydrophobic substrates leads to island formation. A possible model to explain the results must consider the hydrogen bridge formation on 2-propanol and acetaldehyde films. Ethyl ether, ethyl and methyl acetate showed good characteristics for development of sensor and sample pretreatment using miniaturized devices. (C) 2007 Elsevier B.V. All rights reserved.

Metallomics and chemical speciation: towards a better understanding of metal-induced stress in plants

Most metal ions are toxic to plants, even at low concentrations, despite the fact that some are essential for growth and play key roles in metabolism. The majority of metals induce the formation of reactive oxygen species, which require the synthesis of additional antoxidant compounds and enzymes for their removal. New techniques that have greatly improved the identification, localisation and quantification of metals within plant tissues have led to the science of metallomics. This advancement in knowledge should eventually allow the characterisation of plants used in the process of phytoremediation of soils contaminated with toxic metals.

Violation of Kohler's rule by the magnetoresistance of a quasi-two-dimensional organic metal

The interlayer magnetoresistance of the quasi-two-dimensional metal alpha-(BEDT-TTF)(2)KHg(SCN)(4) is considered. In the temperature range from 0.5 to 10 K and for fields up to 10 T the magnetoresistance has a stronger temperature dependence than the zero-field resistance. Consequently Kohler's rule is not obeyed for any range of temperatures or fields. This means that the magnetoresistance cannot be described in terms of semiclassical transport on a single Fermi surface with a single scattering time. Possible explanations for the violations of Kohler's rule are considered, both within the framework of semiclassical transport theory and involving incoherent interlayer transport. The issues considered are similar to those raised by the magnetotransport of the cuprate superconductors. [S0163-1829(98)13219-8].

Effects of promoters on catalytic activity and carbon deposition of Ni/gamma-Al2O3 catalysts in CO2 reforming of CH4

Catalytic reforming of methane with carbon dioxide was studied in a fixed-bed reactor using unpromoted and promoted Ni/gamma-Al2O3 catalysts. The effects of promoters, such as alkali metal oxide (Na2O), alkaline-earth metal oxides (MgO, CaO) and rare-earth metal oxides (La2O3, CeO2), on the catalytic activity and stability in terms of coking resistance and coke reactivity were systematically examined. CaO-, La2O3- and CeO2-promoted Ni/gamma-Al2O3 catalysts exhibited higher stability whereas MgO- and Na2O-promoted catalysts demonstrated lower activity and significant deactivation. Metal-oxide promoters (Na2O, MgO, La2O3, and CeO2) suppressed the carbon deposition, primarily due to the enhanced basicities of the supports and highly reactive carbon species formed during the reaction. In contrast, CaO increased the carbon deposition; however, it promoted the carbon reactivity. (C) 2000 Society of Chemical Industry.

Dissolved organic carbon in rainwater from areas heavily impacted by sugar cane burning

This work reports on rainwater dissolved organic carbon (DOC) from Ribeirao Preto (RP) and Araraquara over a period of 3 years. The economies of these two cities, located in Sao Paulo state (Brazil), are based on agriculture and related industries, and the region is strongly impacted by the burning of sugar cane foliage before harvesting. Highest DOC concentrations were obtained when air masses traversed sugar cane fields burned on the same day as the rain event. Significant increases in the DOC volume weighted means (VWM) during the harvest period, for both sites, and a good linear correlation (r=0.83) between DOC and K (a biomass burning marker) suggest that regional scale organic carbon emissions prevail over long-range transport. The DOC VWMs and standard deviations were 272 +/- 22 mu mol L-1 (n=193) and 338 +/- 40 mu mol L-1 (n=80) for RP and Araraquara, respectively, values which are at least two times higher than those reported for other regions influenced by biomass burning, such as the Amazon. These high DOC levels are discussed in terms of agricultural activities, particularly the large usage of biogenic fuels in Brazil, as well as the analytical method used in this work, which includes volatile organic carbon when reporting DOC values. Taking into account rainfall volume, estimated annual rainwater DOC fluxes for RP (4.8 g C m(-2) yr(-1)) and Araraquara (5.4 g C m(-2) yr(-1)) were close to that previously found for the Amazon region (4.8 g C m(-2) yr(-1)). This work also discusses whether previous calculations of the global rainwater carbon flux may have been underestimated, since they did not consider large inputs from biomass combustion sources, and suffered from a possible analytical bias. (c) 2008 Elsevier Ltd. All rights reserved.

Organic microcavity light-emitting diodes with metal mirrors: dependence of the emission wavelength on the viewing angle

Organic microcavity light-emitting diodes typically exhibit a blueshift of the emitting wavelength with increasing viewing angle. We have modeled the shift of the resonance wavelength for several metal mirrors. Eight metals (Al, Ag, Cr, Ti, Au, Ni, Pt, and Cu) have been considered as top or bottom mirrors, depending on their work functions. The model fully takes into account the dependence of the phase change that occurs on reflection on angle and wavelength for both s and p polarization, as well as on dispersion in the organic layers. Different contributions to the emission wavelength shift are discussed. The influence of the thickness of the bottom mirror and of the choice and thickness of the organic materials inside the cavity has been investigated. Based on the results obtained, guidelines for a choice of materials to reduce blueshift; are given. (C) 2002 Optical Society of America.

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.

Size-segregated chemical composition of aerosol emissions in an urban road tunnel in Portugal

An atmospheric aerosol study was performed in 2008 inside an urban road tunnel, in Lisbon, Portugal. Using a high volume impactor, the aerosol was collected into four size fractions (PM0.5, PM0.5-1, PM1-2.5 and PM2.5-10) and analysed for particle mass (PM), organic and elemental carbon (OC and EC), polycyclic aromatic hydrocarbons (PAH), soluble inorganic ions and elemental composition. Three main groups of compounds were discriminated in the tunnel aerosol: carbonaceous, soil component and vehicle mechanical wear. Measurements indicate that Cu can be a good tracer for wear emissions of road traffic. Cu levels correlate strongly with Fe, Mn, Sn and Cr, showing a highly linear constant ratio in all size ranges, suggesting a unique origin through sizes. Ratios of Cu with other elements can be used to source apportion the trace elements present in urban atmospheres, mainly on what concerns coarse aerosol particles. (C) 2013 Elsevier Ltd. All rights reserved.

Remediation efficiency of vapour extraction of sandy soils contaminated with cyclohexane: influence of air flow rate, water and natural organic matter content

Abstract This work reports the analysis of the efficiency and time of soil remediation using vapour extraction as well as provides comparison of results using both, prepared and real soils. The main objectives were: (i) to analyse the efficiency and time of remediation according to the water and natural organic matter content of the soil; and (ii) to assess if a previous study, performed using prepared soils, could help to preview the process viability in real conditions. For sandy soils with negligible clay content, artificially contaminated with cyclohexane before vapour extraction, it was concluded that (i) the increase of soil water content and mainly of natural organic matter content influenced negatively the remediation process, making it less efficient, more time consuming, and consequently more expensive; and (ii) a previous study using prepared soils of similar characteristics has proven helpful for previewing the process viability in real conditions.

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.

Organic-inorganic hybrid sol-gelcoatings for metal corrosion protection: a review of recent progress

This paper is a review of the most recent and relevant achievements (from 2001 to 2013) on the development of organic–inorganic hybrid (OIH) coatings produced by sol–gel-derivedmethods to improve resistance to oxidation/corrosion of different metallic substrates and their alloys. This review is focused on the research of OIH coatings based on siloxanes using the sol–gel process conducted at an academic level and aims to summarize the materials developed and identify perspectives for further research. The fundamentals of sol–gel are described, including OIH classification, the interaction with the substrate, their advantages, and limitations. The main precursors used in the synthesis ofOIHsol–gel coatings for corrosion protection are also discussed, according to the metallic substrate used. Finally, a multilayer system to improve the resistance to corrosion is proposed, based on OIH coatings produced by the sol–gel process, and the future research challenges are debated.

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.