Theoretical Justification of Coating Adhesion during Gas-Thermal Spraying

The article provides a brief overview of modern methods of thermal spraying. Particular attention is paid to high-speed flame spraying. The theoretical substantiation of the adhesion of coatings formed on machine parts using the methods of thermal spraying is presented.

Influence of part surface preparation on the coating adhesion strength of during plasma spraying

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Prediction of Coating Adhesion on Laser-Cleaned Metal Surfaces of Battery Cells Using Hyperspectral Imaging and Machine Learning

Electric vehicles are shaping the future of the automotive industry. The traction battery is one of the most important components of electric cars. To ensure that the battery operates safely, it is essential to physically and electrically separate the cells facing each other. Coating a cell with varnish helps achieve this goal. Current studies use a destructive method on a sampling basis, the cross-cut test, to investigate the coating quality. In this paper, we present a fast, nondestructive and inline alternative based on hyperspectral imaging and artificial intelligence. Therefore, battery cells are measured with hyperspectral cameras in the visible and near-infrared (VNIR and NIR) parts of the electromagnetic spectrum before and after cleaning then coated and finally subjected to cross-cut test to estimate coating adhesion. During the cross-cut test, the cell coating is destroyed. This work aims to replace cross-cut tests with hyperspectral imaging (HSI) and machine learning to achieve continuous quality control, protect the environment, and save costs. Therefore, machine learning models (logistic regression, random forest, and support vector machines) are used to predict cross-cut test results based on hyperspectral data. We show that it is possible to predict with an accuracy of ~75% whether problems with coating adhesion will occur. Hyperspectral measurements in the near-infrared part of the spectrum yielded the best results. The results show that the method is suitable for automated quality control and process control in battery cell coating, but still needs to be improved to achieve higher accuracies.

Conductive, Superhydrophobic, and Microwave-Absorbing Cotton Fabric by Dip-Coating of Aqueous Silk Nanofibers Stabilized MWCNTs and Octadecanoyl Chain Bonding

A facile dip-coating method to endow cotton fabric (CF) with satisfactory conductivity, superhydrophobicity and microwave absorption performance was proposed based on the combination of multi-walled carbon nanotubes (MWCNTs) incorporation and hydrophobic octadecanoyl chain bonding. The entanglement and bundling of MWCNTs induced by the particularly high aspect ratio and high interaction energy renders homogeneous dispersion of MWCNTs a challenging. The durable coating adhesion of MWCNTs on hydrophilic CF remains the other challenge due to the absence of strong interactions with intrinsic hydrophobic MWCNTs. In this work, silk nanofibers (SNFs) were synthesized by degrading silk at high temperature, which was adopted as dispersant to prepare individually dispersed MWCNTs via ultrasonication and homogenization processes. The coating adhesion of MWCNTs to CF (MWCNTs-CF) was enhanced via dipping coating and thermal treatment induced chemical immobilization cycles. Octadecanoyl chain-tethered MWCNTs-CF (C18-MWCNTs-CF) was manufactured by further treatment with stearoyl chloride to achieve superhydrophobicity. The scanning and transmission electron microscopy micrographs demonstrated that the aggregates of MWCNTs were successfully de-bundled into individually dispersed nanotubes by taking advantages of the high π-π interaction and electrostatic repulsive interactions between MWCNTs and SNFs. SNFs has the superiority of chemical bonding with CF at high temperature and providing active sites for subsequent hydrophobic treatment. The electrical conductivity, surface properties, thermal stability, mechanical properties, and microwave absorption performance of the CF samples were evaluated systematically. Compared with pristine CF (1.04🞩1010 Ω), the C18-MWCNTs-CF exhibited excellent conductive property with surface resistance reaching 55 Ω when the loaded MWCNTs on CF were 247.5 mg/g in the case of 3 dipping-drying cycles and possessed a relatively greater microwave absorption performance of -36.08 dB at 9.28 GHz with merely 2.7 mm thickness. Compared with pristine CF, C18-MWCNTs-CF exhibited superhydrophobicity with the WCA increasing from 26° to 150° even after 20 scratching cycles due to the combination of facile octadecanoyl group tethering and the increased surface roughness. The biodegradable and recyclable C18-MWCNTs-CF exhibited reasonable electrical conductivity, superhydrophobicity and microwave absorption that promises an ideal application prospect in the field of smart textile and wearable electronic devices.