Energy generation systems use high-temperature structural Ni-based superalloys as internal rotating components, and these alloys require resistance to high-temperature oxidation. These state-of-the-art superalloys are utilized due to their excellent balance of materials properties, but their operating temperature is becoming limited by their melting temperature of about 1300 °C. Refractory alloys, on the other hand, exhibit melting temperatures hundreds of degrees greater than superalloys, but often lack high-temperature oxidation resistance. Traditional methods for experimental identification of oxidation resistant refractory alloys are time-consuming and resource-intensive. We therefore seek to predict the oxidation behavior of roughly 1 million different alloys under extreme environments by developing a simulation using Sim2Ls and the Sim2L python library. By allowing a developer to create and share end-to-end computational workflows, Sim2Ls helps to produce data that is Findable, Accessible, Interoperable, and Reusable (FAIR). High-throughput calculations are performed to predict oxide formation and thus oxidation resistance. The user begins by entering the input data which includes the composition of the alloy, temperature of the environment, phases to suspend, and the range of chemical potentials. Outputs of oxide layer property data and grand potential of oxygen for the possible phases are generated and configured into formats accepted by Sim2Ls. Relevant plots are printed out to the user and the inputs and outputs from a successful run are cached into a database. This workflow can be utilized to identify material systems in a high-throughput method thus accelerating the design of next-generation oxidation resistant refractory alloys.

National Science Foundation

Summer Undergraduate Research Fellowship

1. T.M. Butler, O.N. Senkov, T.I. Daboiku, M.A. Velez, H.E. Schroader, L.G. Ware, M.S. Titus, Oxidation behaviors of CrNb, CrNbTi, and CrNbTaTi concentrated refractory alloys, Intermetallics, Volume 140, 2022, 107374, ISSN 0966-9795
2. A. Jain, et al., Commentary: The Materials Project: a materials genome approach to accelerating materials innovation 1 (1) (2013) 11002.

Researchers should cite this work as follows:

• Noah Bradley Hallberg, Michael S Titus, Saswat Mishra (2022), "PyOxidation," https://nanohub.org/resources/pyoxidation. (DOI: 10.21981/AGYY-7Q60).

  BibTex | EndNote

1. alloys
2. High Temperature
3. oxidation
4. oxides
5. Sim2L
6. Simulation