Return
Data Mining for Enhanced PEM Electrolysis
DOI:10.1149/1945-7111/ae335e.png)
Abstract
En 中文
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.
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.3
Papers:
3.3W
Citations:
9.4W

