A Predictive Model for Droplet Transport in Solution Precursor Thermal Spray Process

In the solution precursor thermal spray process (SPTS), a solution is used as the liquid feedstock suitable for depositing sub-micron-sized particles. This approach simplifies feedstock preparation, reduces costs, and offers greater flexibility in using dopants or mixing multiple components, making it more appealing compared to conventional coating technologies such as powder technology. However, predicating the coating particle conditions (i.e. size, velocity, temperature) upon impact remains challenging due to the complexity of the physio-chemical processes occurring within the sub-micron particles produced by SPTS. In this project, a five-stage droplet evolution model including solvent vaporization, solute precipitation, boiling, thermal decomposition, and melting is developed and implemented into an in-house code. Lithium cobalt nitrate dissolved in water is used as the precursor solution for producing lithium cobalt oxide, a potential material for manufacturing the cathode of solid-state batteries via thermal spray. The effects of critical factors such as droplet size, solute concentration, and plasma flow characteristics, including velocity and temperature on particle morphology upon impact, final particle size, and shell thickness are investigated to develop a predictive model of the SPTS particle state. This comprehensive model can help improve control over SPTS coating design, potentially impacting advanced coatings technologies across various industries.