ANFIS-based Models for Coating Quality Prediction for Thin-Film Deposition Processes

Thin-film deposition processes have gained much popularity due to their unique capability to enhance the physical and chemical properties of various materials. Identification of the best parametric combination for a deposition process to achieve desired coating quality is often considered to be challenging due to the involvement of a large number of input process parameters and conflicting responses. This study discusses the development of adaptive neuro-fuzzy inference system-based models for the prediction of quality measures of two thin-film deposition processes, i.e., SiCN thin-film coating using thermal chemical vapor deposition (CVD) process and Ni–Cr alloy thin-film coating using direct current magnetron sputtering process. The predicted response values obtained from the developed models are validated and compared based on actual experimental results which exhibit a very close match between both the values. The corresponding surface plots obtained from the developed models illustrate the effect of each process parameter on the considered responses. These plots will help the operator in selecting the best parametric mix to achieve enhanced coating quality. Also, analysis of variance results identifies the importance of each process parameter in the determination of response values. The proposed approach can be applied to various deposition processes for modeling and prediction of observed response values. It will also assist as an operator in selecting the best parametric mix for achieving desired response values.

Application of quantitative electromagnetic technology to asses coating integrity of pipelines in México

There are several surface inspection methods to evaluate the integrity of the pipe coating, obtaining acceptable qualitative results in some soil types and low complexity pipeline systems. However, these methods do not determine the necessary parameters for a quantitative evaluation of coating quality. The Mexican Petroleum Institute has developed Surface Electromagnetic Pipeline Inspection (SEMPI) technology for the quantitative assessment of buried pipeline coating integrity. SEMPI is a theory-based technology that enables the development of instrumentation, field methodology, as well as data processing and interpretation techniques. The application of SEMPI consists of two stages: regional and local. The regional stage includes magnetic field, voltage and, soil resistivity (rs) measurements, where the main result is the determination of the electrical resistance of the coating (Tc) along the pipeline as an indicating parameter of the coating quality. A scale signalized from Tc data allows classifying the quality of pipe coating as good (green), fair (yellow) and poor (red). The local stage includes detailed electric field measurements of on anomalous pipeline sections (Tc < 50 Ohm.m2), locating damage in the coating with a detection accuracy of the ± 0.5 m. The equivalent unlined (holiday) area per meter of the inspected pipeline is calculated during the local stage. This work presents successful results from the implementation of regional and local stages of SEMPI technology in two pipelines located in the southeast region of Mexico.

Technological factors influence on the antifriction coatings quality

The conditions for the antifriction coatings formation during finishing antifriction non-abrasive treatment (FANT) are analyzed. The requirements for this kind of coatings and the main criteria for assessing their quality are noted. A relationship has been established between the quality of the coating obtained with FANT and the technological factors that determine the conditions for contacting the tool with the treated surface. It is proved that the shape and size of microroughnesses of the treated surface determine the efficiency of the microcutting process and filling the microcavities with the rubbed material. Technological factors influence on the coating quality was investigated during FANT by implementing a multifactor experiment, as a result of which a connection was established between the technological parameters of the process (total friction path, load on the tool), as well as the length of the supporting surface with indicators characterizing the coating quality. Statistical models were obtained for mass transfer of antifriction material, area (continuity) of the coating and surface roughness at natural values of the factors, which made it possible to establish the studied factors influence on the optimization parameters. The analysis of the experimental scattering graphs made it possible to clarify the nature of the factors changes and analyze their mutual influence on the optimization criteria. Taking into account the inversely proportional relationship of the optimization criteria, the achievement of their maximum values at the same time is impossible, therefore, the values are taken according to the final result of the FANT process. The range of the studied factors values is established, the regularities of their change are substantiated from the point of view of the selected optimization criteria. Determination the rational values of the FANT process technological parameters will improve the antifriction coatings quality obtained by a friction-mechanical method.

Infiltrated thin film structure with hydrogel-mediated precursor ink for durable SOFCs

The hydrogel of biomolecule-assisted metal/organic complex has the superior ability to form a uniform, continuous, and densely integrated structure, which is necessary for fine thin film fabrication. As a representative of nature-originated polymers with abundant reactive side chains, we select the gelatin molecule as an element for weaving the metal cations. Here, we demonstrate the interaction between the metal cation and gelatin molecules, and associate it with coating quality. We investigate the rheological property of gelatin solutions interacting with metal cation from the view of cross-linking and denaturing of gelatin molecules. Also, we quantitatively compare the corresponding interactions by monitoring the absorbance spectrum of the cation. The coated porous structure is systematically investigated from the infiltration of gelatin-mediated Gd0.2Ce0.8O2−δ (GDC) precursor into Sm0.5Sr0.5CoO3−δ (SSC) porous scaffold. By applying the actively interacting gelatin–GDC system, we achieve a thin film of GDC on SSC with excellent uniformity. Compare to the discrete coating from the typical infiltration process, the optimized thin film coated structure shows enhanced performance and stability.

Assessment of Coating Quality Obtained on Flame-Retardant Fabrics by a Magnetron Sputtering Method

Innovative textile materials can be obtained by depositing different coatings. To improve the thermal properties of textiles, aluminum and zirconium (IV) oxides were deposited on the Nomex® fabric, basalt fabric, and cotton fabric with flame-retardant finishing using the magnetron sputtering method. An assessment of coating quality was conducted. Evenly coated fabric ensures that there are no places on the sample surface where the values of thermal parameters such as resistance to contact heat and radiant heat deviate significantly from the specified ones. Energy-dispersive spectroscopy was used for the analysis of modified fabric surfaces. Non-contact digital color imaging system DigiEye was also used. The criterion allowing one to compare surfaces and find which surface is more evenly coated was proposed. The best fabrics from the point of view of coating quality were basalt and cotton fabrics coated with aluminum as well as basalt fabric coated with zirconia. The probability of occurrence of places on the indicated sample surfaces where the values of thermal parameters (i.e., resistance to contact heat and radiant heat) deviated significantly from the specified ones was smaller for Nomex® and cotton fabrics coated with zirconia and Nomex® fabric coated with aluminum.