Optimization of Solution Precursor Plasma Spray Process by Statistical Design of Experiment

Abstract

The solution precursor plasma spray (SPPS) process, in which a solution precursor of the desired resultant material is fed into a plasma jet by atomizing gas or high pressure, was developed in the 1990s and has been studied extensively since then. Recently, it has been shown that the SPPS process is suitable for deposition of porous electrodes for solid oxide fuel cells (SOFC). High efficiency SOFC requires electrodes with 30-40% porosity. Due to the complexity of the SPPS process and the large number of processing parameters, it is difficult to investigate the effect of each parameter on the two important properties, i.e., coating porosity and deposition efficiency, separately. Design of experiments can use a small number of experimental runs to analyze the effect of each processing parameter on the properties of the fabricated product, after which the processing parameter combinations for fabricating a target product can be found. In this project, a small central composite design (CCD), a second-order statistical model, was used to analyze and optimize the SPPS process for Ni-YSZ anode deposition. The processing parameters investigated include: (1) Hydrogen flow rate, which determines arc voltage, (2) Current, (3) Solute flow rate, (4) Solution concentration, (5) Distance between nozzle and gun, and (6) Stand off distance. The effects of the selected processing parameters were analyzed, and the resultant model was used to select a combination of processing parameters, which produced a coating with the desired characteristics.