Design of an adsorbent employing activated carbon fiber to remove lead

Zorflex® activated carbon fibers (ACF), reference FM100 198B, are used before and after an oxidizing procedure with H3PO4 to study the adsorption of Pb2+. The point of zero charge was determined for the modified and unmodified fiber giving values of 2.3 and 4.3, respectively. After oxidizing the ACF, the fiber showed to have a greater Pb2+ adsorption capacity in comparison with the unmodified fiber, which is related with the acid sites increase, where lead was mainly adsorbed. Determination of the BET area was carried out by nitrogen physisorption at 77K. ACFs presented superficial areas between 1000 and 1500 m²/g showing mostly, a microporous structure. The preliminary design of an adsorbent using the modified fiber is presented where the fiber superior physicochemical properties over the unmodified one are observed.

Glass pipette-carbon fiber microelectrodes for evoked potential recordings

Current methods for recording field potentials with tungsten electrodes make it virtually impossible to use the same recording electrode also as a lesioning electrode, for example for histological confirmation of the recorded site, because the lesioning procedure usually wears off the tungsten tip. Therefore, the electrode would have to be replaced after each lesioning procedure, which is a very high cost solution to the problem. We present here a low cost, easy to make, high quality glass pipette-carbon fiber microelectrode that shows resistive, signal/noise and electrochemical coupling advantages over tungsten electrodes. Also, currently used carbon fiber microelectrodes often show problems with electrical continuity, especially regarding electrochemical applications using a carbon-powder/resin mixture, with consequent low performance, besides the inconvenience of handling such a mixture. We propose here a new method for manufacturing glass pipette-carbon fiber microelectrodes with several advantages when recording intracerebral field potentials

Estudo eletroanalítico do herbicida paraquat em soluções aquosas por voltametria de onda quadrada utilizando ultramicroeletrodos

The electrochemical behavior of paraquat on Pt, Au and carbon fiber ultramicroelectrodes were studied in laboratory samples by square wave voltammetry at high frequencies. The results showed two reversible peaks for paraquat reduction, in agreement to the literature data. The first peak was associated to the reduction of paraquat molecule in solution, with the further adsorption of the intermediate on the electrode surface. This adsorbed species undergoes to electroreduction in a reaction associated to the second voltammetric peak. The variation in pH and square wave parameters showed the best conditions to reduce paraquat as pH 5.0, frequency as high as 1000 s-1, scan increment of 2 mV and square wave amplitude of 50 mV. At such conditions, a variation of paraquat concentrations from 4.3 x 10-6 to 1.66 x 10-4 mol L-1 presented values for the detection limit equal to 3.9, 6.2 and 20.3 ppb on Pt, Au and carbon, respectively, at 1000 s-1. These values are quite below17 the allowed limit of paraquat in drinking water.

Modelling of mechanical properties of CRFC composites under flexure loading

Carbon Fibre Reinforced Carbon (CFRC) Composites are increasing their applications due to their high strength and Young’s Modulus at high temperatures in inert atmosphere. Although much work has been done on processing and structure and properties relationship, few studies have addressed the modelling of mechanical properties. This work is divided in two parts. In the first part, a modelling of mechanical properties was carried out for two bi-directional composites using a model based on the Bernoulli-Euler theory for symmetric laminated beams. In the second part, acoustic emission (AE) was used as an auxiliary technique for monitoring the failure process of the composites. Differences in fracture behaviour are reflected in patterns of AE.

Effect of particle morphology on the mechanical and thermo-mechanical behavior of polymer composites

Fiber reinforced polymer composites have been used in many applications, such as in automobile, aerospace and naval industries, due basically to their high strength-to-weight and modulus-to-weight, among other properties. Even though particles are usually not able to lead to the level of reinforcement of fibers, particle reinforced polymer composites have been proposed for many new applications due to their low cost, easy fabrication and isotropic properties. In this work, polymer composites were prepared by incorporating glass particles of different morphologies on poly(aryl sulfones) matrices. Particles with aspect ratios equal to 1, 2.5 and 10 were used. The prepared composites were characterized using electron microscopy and thermal analysis. Mechanical properties of the composites were evaluated using a four-point bending test. The thermo-mechanical behavior of the obtained composites was also investigated. The results showed that the morphology of the particles alter significantly the mechanical properties of composites. Particles with larger values of aspect ratio led to large elastic modulus but low levels of strain at failure. This result was explained by modeling the thermo-mechanical behavior of the composites using a viscoelastic model. Parameters of the model, obtained from a Cole-Cole type of plot, demonstrated that interactions at the polymer-reinforcing agent interface were higher for composites with large aspect ratio particles. Higher levels of interactions at interfaces can lead to higher degrees of stress transfer and, consequently, to composites with large elastic modulus, as experimentally observed.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

Carbon isotope fractionation for cotton genotype selection

The objective of this work was to evaluate the carbon isotope fractionation as a phenomic facility for cotton selection in contrasting environments and to assess its relationship with yield components. The experiments were carried out in a randomized block design, with four replicates, in the municipalities of Santa Helena de Goiás (SHGO) and Montividiu (MONT), in the state of Goiás, Brazil. The analysis of carbon isotope discrimination (Δ) was performed in 15 breeding lines and three cultivars. Subsequently, the root growth kinetic and root system architecture from the selected genotypes were determined. In both locations, Δ analyses were suitable to discriminate cotton genotypes. There was a positive correlation between Δ and seed-cotton yield in SHGO, where water deficit was more severe. In this site, the negative correlations found between Δ and fiber percentage indicate an integrative effect of gas exchange on Δ and its association with yield components. As for root robustness and growth kinetic, the GO 05 809 genotype performance contributes to sustain the highest values of Δ found in MONT, where edaphoclimatic conditions were more suitable for cotton. The use of Δ analysis as a phenomic facility can help to select cotton genotypes, in order to obtain plants with higher efficiency for gas exchange and water use.

Characterization and treatment of sisal fiber residues for cement-based composite application

Sisal fiber is an important agricultural product used in the manufacture of ropes, rugs and also as a reinforcement of polymeric or cement-based composites. However, during the fiber production process a large amount of residues is generated which currently have a low potential for commercial use. The aim of this study is to characterize the agricultural residues by the production and improvement of sisal fiber, called field bush and refugo and verify the potentiality of their use in the reinforcement of cement-based composites. The residues were treated with wet-dry cycles and evaluated using tensile testing of fibers, scanning electron microscopy (SEM) and Fourier transform infrared (FTIR) spectroscopy. Compatibility with the cement-based matrix was evaluated through the fiber pull-out test and flexural test in composites reinforced with 2 % of sisal residues. The results indicate that the use of treated residue allows the production of composites with good mechanical properties that are superior to the traditional composites reinforced with natural sisal fibers.