Deposition of PtxRu1−x Catalysts for Methanol Oxidation in Micro Direct Methanol Fuel Cells

Platinum-ruthenium electrodes (Pt_xRu_1-x) have been prepared by electrochemical and electroless deposition and investigated as catalysts for the oxidation of methanol in acidic solutions. Pt_xRu_1-x deposits were electrochemically deposited from acidic chloride electrolytes at potentials between −0.46 and 0.34 V (vs. NHE). The composition of the electrodeposit was estimated by energy dispersive X-ray spectroscopy and is a strong function of the electrode potential. An empirical model for the deposition process is presented and kinetic parameters are estimated and discussed. Also, the methanol oxidation activity of the Pt_xRu_1-x catalysts was characterized by cyclic voltammetry in 1.0 M CH₃OH, 1.0 M H₂SO₄ solutions. Electroless Pt_xRu_1-x samples were prepared in a modified Leaman bath with hydrazine dihydrochloride as the reducing agent. The kinetic results for the electrochemical deposition of Pt_xRu_1-x were directly applied and the deposition potential was estimated as approximately 0.40 V.     

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.     

Passivity Analysis of Dynamic Neural Networks with Different Time-scales

Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed networks are stable. In this paper, the passivity-based approach is used to derive stability conditions for dynamic neural networks with different time-scales. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input bounded output stability, are guaranteed in certain senses. A numerical example is also given to demonstrate the effectiveness of the theoretical results.     

Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.