A disposable sensor based on immobilization of acetylcholinesterase to multiwall carbon nanotube modified screen-printed electrode for determination of carbaryl

A simple method has been devised for immobilization of acetylcholinesterase (AChE) covalent bonding to a multiwall carbon nanotube (MWNT)-cross-linked cellulose acetate composite on a screen-printed carbon electrode (SPCE) and a sensitive and disposable amperometric sensor for rapid determination of carbaryl pesticide is proposed. The immobilized enzyme was preserved on this film because of the excellent biocompatibility and non-toxicity of cellulose acetate. Based on the inherent conductive properties of the MWNT, the immobilized AChE had greater affinity for ATCl and excellent catalytic effect in the hydrolysis of ATCl. MWNT improved the interface enzymatic hydrolysis reaction and increased the amperometric response of the sensor. Under optimum conditions, the inhibition of carbaryl on AChE increased linearly with the increasing concentration of carbaryl in two ranges, from 0.01 to 0.5 μg mL⁻¹ and from 2 to 20 μg mL⁻¹, with the correlation coefficients of 0.9985 and 0.9977, respectively. The detection limit was 0.004 μg mL⁻¹ taken as the concentration equivalent to 10% decrease in signal. The sensor showed acceptable stability, accuracy and could be fabricated in batches, thus it is economic and portable. This type of disposable enzyme-based amperometric sensor has extensive application potential in environmental monitoring of pesticides.     

Influence of pencil lead hardness on voltammetric response of graphite reinforcement carbon electrodes

This work studied the voltammetric response of graphite reinforcement electrodes made of different pencil lead hardness. The studies showed that harder graphite leads, regardless of their manufacturer, are more appropriate as electrode material for voltammetric purposes due to their higher peak currents, increasing sensitivity and reproducibility, with ΔEp closer to the theoretical value for a reversible system.     

FEM model of the ohmic resistance of IP-SOFCs

In the present work, the ohmic resistance of an integrated planar-SOFC (IP-SOFC) has been evaluated by developing a model whose equations have been solved numerically through an FEM method. The model allows to estimate the distribution of voltage and current density in the cell. A comparison between simulated and experimental data of area specific resistance is reported, which shows satisfactory agreement. The mathematical model has also been used to carry out some parametric studies for optimisation purposes. Indeed, a reduction in cell pitch length and an increase in electrode thickness are predicted to lead to a reduction in ohmic losses in IP-SOFCs.     

Towards a new definition of EPOC parameters for anionic electrochemical catalysts: case of propene combustion

The electrochemical promotion of catalysis (EPOC) of propene combustion was investigated using Pt sputtered thin film on an O²⁻ conductor, 8 mol% Y₂O₃-stabilized-ZrO₂ (YSZ). In order to separate the influence of the thermal migration of the O²⁻ oxide ions from the electrolyte to the catalyst surface and the impact of an electrical polarization on the catalytic activity, several light-off experiments (cool down and heat up procedures) were successively performed under different polarizations, i.e. OCV, +2 and −2 V. These experiments have clearly shown that the presence of O²⁻ (thermally or electrochemically induced) inhibits the catalytic activity of the platinum for the propene deep oxidation. These results demonstrate the importance to define a normalized rate enhancement ratio, ρ _n , from a reference value of the catalytic rate corresponding to a Pt surface state free of O²⁻ ions.     

A strategy for the electro-organic synthesis of new hydrocaffeic acid derivatives

Electrochemical treatment processes can significantly contribute to the protection of the environment through the minimization of waste and toxic materials in effluents. From a pharmaceutical point of view and due to the existing resemblance between the electrochemical and biological reactions, it can be assumed that the oxidation mechanisms on the electrode and in the body share similar principles. In this paper, the application of electrochemical studies in the design of an environmentally friendly method was delineated for the new hydrocaffeic acid (HCA, 3,4-dihydroxy hydrocinnamic acid) derivatives synthesis at carbon electrodes in an undivided cell. In this cell, the EC mechanism reaction was involved, comprising two steps alternatively; (1) electrochemical oxidation and (2) chemical reaction. In particular, the electro-organic reactions of HCA, an important biological molecule, were studied in a water–acetonitrile (90:10 v/v) mixture in the presence of benzenesulfinic acid (3) and p-toluenesulfinic acid (4). The research included the use of a variety of experimental techniques, such as cyclic voltammetry, controlled-potential electrolysis and product spectroscopic identification.     

NiCoFe/C cathode electrocatalysts for direct ethanol fuel cells

A direct ethanol fuel cell (DEFC), which is less prone to ethanol crossover, is reported. The cell consists of PtRu/C catalyst as the anode, Nafion^® 117 membrane, and Ni–Co–Fe (NCF) composite catalyst as the cathode. The NCF catalyst was synthesized by mixing Ni, Co, and Fe complexes into a polymer matrix (melamine-formaldehyde resins), followed by heating the mixture at 800 °C under inert atmosphere. TEM and EDX experiments suggest that the NCF catalyst has alloy structures of Ni, Co and Fe. The catalytic activity of the NCF catalyst for the oxygen reduction reaction (ORR) was compared with that of commercially available Pt/C (CAP) catalyst at different ethanol concentrations. The decrease in open circuit voltage (V_oc) of the DEFC equipped with the NCF catalysts was less than that of CAP catalyst at higher ethanol concentrations. The NCF catalyst was less prone to ethanol oxidation at cathode even when ethanol crossover occurred through the Nafion^®117 film, which prevents voltage drop at the cathode. However, the CAP catalyst did oxidize ethanol at the cathode and caused a decrease in voltage at higher ethanol concentrations.     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.