Supplemental Data for the Journal Article Entitled Accelerating FEM-based Corrosion Predictions using Machine Learning submitted for publication to the Journal of the Electrochemical Society.

This repository contains the Supplemental Data for the Journal Article Entitled Accelerating FEM-based Corrosion Predictions using Machine Learning submitted for publication to the Journal of the Electrochemical Society.

Authors:

David Montes de Oca Zapiain 1, Demitri Maestas 1, Matthew Roop 1,2, Philip Noel 1, Michael Melia 1, Ryan Katona 1

1 Sandia National Laboratories, Albuquerque, NM 87185, USA 2 University of New Mexico, Albuquerque, NM 87131, USA

Each folder contains a ReadMe.txt describing the files and their organization within each folder. 

Acknowledgements:Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc.,for the U.S. Department of Energy National Nuclear Security Administration under contract DE-NA0003525. The views expressed in the articledo not necessarily represent the views of the U.S. Department of Energy or the United States Government. SAND No: SAND2023-14419O