Personne : Laroche, Gaétan
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Laroche
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Gaétan
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Université Laval. Département de génie des mines, de la métallurgie et des matériaux
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ncf10316941
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Publication Accès libre Optical emission spectroscopy as a process-monitoring tool in plasma enhanced chemical vapor deposition of amorphous carbon coatings - multivariate statistical modelling(Elsevier Science, 2018-03-01) Turgeon, Stéphane; Anooshehpour, Farid; Laroche, Gaétan; Mantovani, D. (Diego); Cloutier, MaximeProduction of Diamond-Like Carbon (DLC) nanocoatings using plasma enhanced chemical vapor deposition is studied by Optical Emission Spectroscopy (OES) as a plasma diagnostic technique. The objective of the current research is to establish a predictive model of DLC properties using a multivariate analysis method. This model is based on OES data instead of process parameters, which are reactor dependent and accordingly, their effect on the plasma deposition process may vary from one reactor to another. The predictive potential of OES is evaluated using partial least square regression (PLSR) analysis. The results show that OES derived data are capable of replacing some process parameters to predict the DLC properties. The perspective of PLSR modelling and OES application for the development and monitoring of a structurally graded DLC coating is also discussed.Publication Accès libre Partial least squares regression as a tool to predict fluoropolymer surface modification by dielectric barrier discharge in a corona process configuration in a nitrogen-organic gaseous precursor environment(American Chemical Society, 2018-05-16) Turgeon, Stéphane; Laroche, Gaétan; Vallade, JulienA dielectric barrier discharge in a corona process configuration is used to treat the surface of fluoropolymers in a nitrogen–organic precursor environment. The surface chemistry, thickness, and water contact angle of the deposited coatings are measured and used to build up an output matrix to be correlated with an input matrix built using electrical parameters of the discharge, the gas mixture chemical composition, and spectroscopic parameters measured in both the infrared and ultraviolet–visible emission spectral regions. A partial least-squares regression (PLSR) model enables determining the most important plasma parameters to drive the coating physicochemical characteristics. From the PLSR model, it is determined that the plasma electrical parameters drive the surface modification process, at the expense of other plasma characteristics such as gas flow, gaseous precursor concentration, nitrogen vibrational temperature, and the level of gaseous precursor conversion within the plasma.Publication Accès libre Correlation between the plasma characteristics and the surface chemistry of plasma-treated polymers through partial least squares analysis(ACS Publications, 2013-12-06) Turgeon, Stéphane; Duchesne, Carl; Ghasemzadeh-Barvarz, Massoud; Laroche, Gaétan; Mavadat, MaryamWe investigated the effect of various plasma parameters (relative density of atomic N and H, plasma temperature, and vibrational temperature) and process conditions (pressure and H2/(N2 + H2) ratio) on the chemical composition of modified poly(tetrafluoroethylene) (PTFE). The plasma parameters were measured by means of near-infrared (NIR) and UV-visible emission spectroscopy with and without actinometry. The process conditions of the N2-H2 microwave discharges were set at various pressures ranging from 100 to 2000 mTorr and H2/(N2+H2) gas mixture ratios between 0 and 0.4. The surface chemical composition of the modified polymers was determined by X-ray photoelectron spectroscopy (XPS). A mathematical model was constructed using the partial least-squares regression algorithm to correlate the plasma information (process condition and plasma parameters as determined by emission spectroscopy) with the modified surface characteristics. To construct the model, a set of data input variables containing process conditions and plasma parameters were generated, as well as a response matrix containing the surface composition of the polymer. This model was used to predict the composition of PTFE surfaces subjected to N2-H2 plasma treatment. Contrary to what is generally accepted in the literature, the present data demonstrate that hydrogen is not directly involved in the defluorination of the surface but rather produces atomic nitrogen and/or NH radicals that are shown to be at the origin of fluorine atom removal from the polymer surface. The results show that process conditions alone do not suffice in predicting the surface chemical composition and that the plasma characteristics, which cannot be easily correlated with these conditions, should be considered. Process optimization and control would benefit from plasma diagnostics, particularly infrared emission spectroscopy.