Characterization of d.c. plasma torch voltage fluctuations

The arc root fluctuations at the anode-nozzle of a d.c. plasma spray torch with a special configuration of the electrodes allowing to work with the same gas flowrate with nozzle diameters ranging from 6 to 10 mm were systematically studied. The plasma gas was Ar/H2 (25 vol % H2), the current was varied between 200 and 600 A and the plasma gas flowrate between 24 and 80 slm. After 30–60 mn working the nozzle wall started to be sufficiently eroded to have a stagnant arc spot which lived until arcing created another one. It was shown that the life time of the upstream arc spots were 30–40 % longer than the downstream ones which could play an important role in the electrode erosion. Dimensional analysis allowed to find a relationship between the nozzle diameter D, the arc current I and gas flow rate G and the mean spot lifetime which is closely connected with the difference between D and the electrical diameter of the arc column. The comparison of voltage signal and light emission at a point of the plasma jet close to the nozzle exit on its axis allowed to determine the mean electrical field within the plasma column and the mean position of the arc root. The comparison with the electrode erosion area for well defined conditions showed a good correlation with the calculated arc root position.     

Electrochemical Characterisations of Al<Subscript>2</Subscript>O<Subscript>3</Subscript>–13%TiO<Subscript>2</Subscript> Coated by Atmospheric Plasma Spray

Atmospheric plasma sprayed alumina–titania (Al₂O₃–13%TiO₂), coated on stainless steel (XC18), were characterized. The coating structure and morphology were studied by scanning electron microscopy. Their presented micro cracks, laminar splats. The coatings were studied by X-ray diffraction. The main phase transformation is that of α-Al₂O₃ into metastable γ-Al₂O₃. The α-Al₂O₃ phase is due to the occurrence of partially melted particles Electrochemical behaviours of coatings were mainly investigated by potentiodynamic polarization and electrochemical impedance spectroscopy in 0.01 M [K₃Fe(CN)₆/K₄Fe(CN)₆] as a function of process parameters. Also, schematic equivalent circuit was proposed. The results were expected to facilitate the understanding and improvement of the coating behaviours.     

Artificial Intelligence Computation to Establish Relationships Between APS Process Parameters and Alumina–Titania Coating Properties

Modeling the behavior of air plasma spray (APS) process, one of the challenges nowadays is to identify the parameter interdependencies, correlations and individual effects on coating properties, characteristics and influences on the in-service properties. APS modeling requires a global approach which considers the relationships between coating characteristics/ in-service properties and process parameters. Such an approach permits to reduce the development costs. This is why a robust methodology is needed to study these interrelated effects. Artificial intelligence based on fuzzy logic and artificial neural network concepts offers the possibility to develop a global approach to predict the coating characteristics so as to reach the required operating parameters. The model considered coating properties (porosity) and established the relationships with power process parameters (arc current intensity, total plasma gas flow rate, hydrogen content) on the basis of artificial intelligence rules. Consequently, the role and the effects of each power process parameter were discriminated. The specific case of the deposition of alumina–titania (Al₂O₃–TiO₂, 13% by weight) by APS was considered.     

Towards gas chromatography-mass spectrometry coupling protocols for both identifying and quantification essential oils of Thymus capitatus Hoff et Link

Essential oil of Thymus capitatus Hoff et Link is analysed by using four techniques: GC/pyrolyse/MS, GC/FID, electronic impact GC/MS (quadripole), and GC/MS (ion trap). Both major and trace components are analysed. The GC/pyrolyse/MS coupling provides reference to the exact mass compositions without any need of the previously purified references, neither for major or trace components. The comparison between this reference analysis and GC/FID shows that the FID response coefficients may vary by a mean 7% from one component to another. As it was expected, quadripole or ion trap response coefficients vary to a much greater extent (a mean 25%), although the two MS techniques response coefficients are first order consistent. We conclude that GC/MS coupling could be used not only as it is usual for reliable identifications, but also for a complete quantitative routine analysis of essential oils. Expected precision could be very similar to GC/FID precision provided correcting species by species the MS analysis by a mean value of the response coefficient measured for the MS 70 eV electronic impact ionisation technologies. The GC/pyrolyse/MS coupling is proposed as a relevant tool for analysing reference samples containing trace natural species that could not be purified.     

Plasma Spray Process Operating Parameters Optimization Based on Artificial Intelligence

During plasma spray process, many intrinsic operating parameters allow tailoring in-flight particle characteristics (temperature and velocity) by controlling the plasma jet properties, thus affecting the final coating characteristics. Among them, plasma flow mass enthalpy, flow thermal conductivity, momentum density, etc. result from the selection of extrinsic operating parameters such as the plasma torch nozzle geometry, the composition and flow rate of plasma forming gases, the arc current intensity, beside the coupled relationships between those operating parameters make difficult in a full prediction of their effects on coating properties. Moreover, temporal fluctuations (anode wear for example) require “real time” corrections to maintain particle characteristic to targeted values. An expert system is built to optimize and control some of the main extrinsic operating parameters. This expert system includes two parts: (1) an artificial neural network (ANN) which predicts an extrinsic operating window and (2) a fuzzy logic controller (FLC) to control it. The paper details the general architecture of the system, discusses its limits and the typical characteristic times. The result shows that ANN can predict the characteristics of particles in-flight from coating porosity within maximal error 3 and 2 % in temperature and velocity respectively. And ANN also can predict the operating parameters from in-flight particle characteristics with maximal error 2.34, 4.80 and 8.66 % in current intensity, argon flow rate, and hydrogen flow rate respectively.     

Different spray processes for different Al2O3 coating properties

Among the different coating technologies, a thermal spray has a leading position because of its versatility: an extremely wide variety of materials can be deposited to protect back materials from wear, corrosion, thermal flux, etc. For example, atmospheric plasma spray is a rather well-established process but some other ones, such as flame technology, can also be used with lower economical impact. After a respective optimization of the processing parameters, both plasma and wire flame thermal processes were tested to form Al₂O₃ coatings. For each process, in-flight particle conditions, coating cross-section micro-structures and coating properties were successively determined. The experimental parameters were correlated to in-flight particle characteristics and to coating micro-structure and compared to resulting coating features. The evolution of particle velocity and temperature showed well-marked trends and the mean values were dependent on the spray process. The results emphasized the difference of spray system in terms of kinetic and thermal transfers to the particles. Then, the differences observed on in-flight particle characteristics can be used to explain the differences observed in coating properties, such as porosity content and hardness.     

Chemical modification of polynorbornene. I. Sulfonation in dilute solution

The sulfonation of dilute solutions of polynorbornene (PN) in CCl₄ has been carried out using SO₃–triethylphosphate complexes of various stoichiometries dissolved in dichloroethane (DCE) or trifluoro-trichloro-ethane (TTE). This leads to an electrophilic substitution, with very few side reactions, yielding high sulfonation ratios (ca. 85%). The initial reaction is first order in both reactants (PN and SO₃) and has an activation energy of 17.5 kJ mol^?1. The reaction becomes diffusion-controlled after ca. 30 min at room temperature due to the precipitation of the partially sulfonated polymer. The initial rate is almost independent of the isomeric structure (cis or trans) and the molecular weight of the polymer, as well as on the stoichiometry of the SO₃–TEP complex; it is higher when TTE is used as solvent. The final sulfonation ratio is strongly dependent on the concentration of SO₃ and seems to be controlled by the conditions of diffusion inside the precipitated solid.     

Chemical modification of polynorbornene. II. Extended sulfonation processes

In the sulfonation of polynorbornene in dilute solution, the nature of the sulfonation agent mainly influences the reaction rate, according to its strength and also affects some side reactions (chain scission and crosslinking). The sulfonation can be carried out in suspension after swelling the highly porous powder in dichloroethane up to a 55% sulfonation ratio with preservation of the initial particular nature of the polymer; the latter may be then either partly or totally water soluble, depending on the initial size of the particles. Partial sulfonation, leading to ionomers, may be carried out in bulk at moderate temperature, in a mixing chamber, after gelification of the polymers, plasticized with CCl₄.