Dear Colleagues,

Coating is an essential component of most equipment in application. A protective coating on an automobile’s body protects the substrate from wear and corrosion, while a coating on an orthopedic implant enhances its biocompatibility and osteointegration. Depending on the application, coatings can be single or multi-layer and can vary in thickness from a few microns to a few millimeters.

The characterization of coatings is an important step prior to its application. Data generated from characterization can be numerical values like concentration of various elements in coating material, mechanical properties, data from corrosion experiments, data in the form of images obtained from optical or electron microscopy etc. Data like processing routes including plating, galvanizing, PVD, CVD, cold spray, additive manufacturing, etc., and post processing routes like heat-treatment cycles etc. are not numerical and can be used for classification purpose. Thus, the characterization of coatings generates a significant amount of data that can be utilized in developing new coatings as well as improving multiple targeted properties of existing coatings. Artificial intelligence algorithms can be helpful in determining various correlations among different parameters involved in development of a coating material.

The scope of this issue can be summarized as follows:

• All types of coating materials and coating methods.
• Experimental characterization including but not limited to nanoindentation, wear, corrosion, erosion, cavitation, etc.
• Composition–processing–structure–property relations.
• Computational simulations with special emphasis on development of models capable of simulating experiments as well as predicting properties.
• Artificial intelligence and machine learning algorithm application.
• New coating methods and characterization techniques.
• Calculation of PHAse Diagram (CALPHAD) approach.

Prospective authors are welcome to consult the editor regarding utilizing nanoindentation data and ways to apply artificial intelligence algorithms while developing predictive models.

Dr. Rajesh Jha
Guest Editor

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• protective coatings
• corrosion prevention
• materials characterization
• coating methods
• cladding
• additive manufacturing
• artificial intelligence
• CALPHAD