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Meeting MS&T26: Materials Science & Technology
Symposium Advanced Coatings for Wear and Corrosion Protection
Presentation Title Developing Predictive Control for Reactive Plasma Spray Deposition of Nitride Coatings
Author(s) Aranya Aumit Paul, Samantha Murrillo, Abigail Peck, Christopher J. Marvel
On-Site Speaker (Planned) Aranya Aumit Paul
Abstract Scope Reactive plasma spraying (RPS) is an underutilized technology for in-situ formation of thick ceramic coatings relevant to energy-related industrial applications, including hydrogen permeation barriers. While conventional thin film deposition techniques produce dense nitride films, they are limited in scalability. RPS enables deposition of thicker coatings, but optimal processing conditions for controlling phase composition and microstructural density are not clearly defined. This study established a data-driven predictive framework based on Principal Component Analysis to correlate input RPS processing conditions to output TiN microstructural characteristics and properties. Parameters investigated include variations in powder feedstock, primary and secondary gas composition, feedstock flow rate, and spray distance. Deposition rate and porosity are quantified using light optical microscopy, phase fractions of TiN, TiO2, and Ti using X-ray diffraction, and hardness via microhardness indentation. Results demonstrate that deposition behavior is predominantly governed by spray distance, while powder feed rate strongly influences TiN phase stability.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Developing Predictive Control for Reactive Plasma Spray Deposition of Nitride Coatings
Galvanic Compatibility of Wear-Resistant Laser-Clad Fe–Mn–Al–Cr–C Coatings with A356 Aluminum
Microstructural Evolution in a New Inorganic Trivalent Chromium Electrodeposition Solution
Optimization of Composition of Functionally Active Mixtures for Titanium Chromium Coating to Improve Wear Resistance of Carbon Steels
Sensing, Predicting and Validating Coating Lifetime Performance via Electrochemical Testing and Machine Learning
Tribological and Anti-Scaling Performance of Graphene-Enriched Thin Polyether Ether Ketone (PEEK) Coatings

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