Abstract
For automotive exhaust valve applications, future vehicles will need durable materials operating at higher temperatures. Both commercial and model Ni-based alloys were tested in 1-h cycles at 800-950°C in wet air, and the oxide scales formed on wrought Ni-(14-25)wt%Cr binary alloys were characterized to fundamentally understand the behavior of chromia-forming alloys. The mass change curves were used to quantify the behavior of the tested alloys and fit growth and spallation rates using kp-p model. With the fitted kp and p values, the effect of alloy composition on oxidation behavior was analyzed by a machine learning approach using these rates as inputs. The machine learning analysis yielded a high accuracy for kp but not p. The future goal is to develop a predictive model for oxidation behavior to assist in alloy development for this application.
