Corrosion testing is slow, labor-intensive, and sensitive to operator technique, limiting the generation of large, high-quality datasets for data-driven materials discovery. The Materials Acceleration Platform for Electrochemistry (MAP-E) is an autonomous, high-throughput system, capable of performing parallel electrochemical experiments. It integrates robotic liquid handling, sample transfer with a multi-channel potentiostatic control to extract corrosion metrics without human intervention. Validation against an ASTM G61-analog benchmark demonstrates good reproducibility, with a standard deviation of 75 mV in pitting potential across 32 automated measurements. The platform was then employed to autonomously construct pH-chloride stability diagrams for 304 stainless steel using an uncertainty-driven sampling strategy on a Gaussian process surrogate model. This approach reduces operator involvement and accelerates the exploration of environmental spaces. The MAP-E establishes a framework for autonomous electrochemical experimentation, enabling generation of corrosion datasets that inform materials discovery, alloy design, and durability assessment in service environments.
@article{arxiv.2603.09845,
title = {Materials Acceleration Platform for Electrochemistry: a Platform for Autonomous Electrochemistry},
author = {Daniel Persaud and Mike Werezak and Mark Xu and Melyne Zhou and Frank Benkel and Xin Pang and Vahid Attari and Brian DeCost and Ashley Dale and Nicholas Senior and Gabriel Birsan and Jason Hattrick-Simpers},
journal= {arXiv preprint arXiv:2603.09845},
year = {2026}
}