Data Mining for Enhanced PEM Electrolysis
Abstract
Despite numerous publications on PEM electrolyser production, a lack of standardized methodologies and reporting guidelines complicates direct comparisons. We conducted a systematic exploratory data analysis, creating a database comprising more than 1,000 samples from 127 publications, which considered over 85 parameters encompassing material selection, MEA fabrication, cell assembly, and characterization. Through statistical analysis, we identified trends and hidden influencing factors. Furthermore, we utilized an Extreme Gradient Boosting model quantifying feature importance, revealing critical factors often underreported relative to their impact. This work provides a foundation for standardizing research data, showing that systematic data management is key in overcoming the comparability challenges and accelerating development.
Fields of Study & Subjects
Fuel Cells and Related Materials
Hybrid Renewable Energy Systems
Additive Manufacturing and 3D Printing Technologies
Publication details
- Journal / source
- Journal of The Electrochemical Society
- Publisher
- The Electrochemical Society
- Volume
- 173
- Issue
- 2
- Pages
- 024503–024503
- Publication date
- 5 January 2026
- Language
- EN