Text-mining and bibliometric analyses for proton exchange membrane electrolyzers

Date

2026-02-20

Author

Firtin, Ayca
Yilmaz, Ayca
Eroğlu, İnci
Yildirim, Ramazan
Eroglu, Damla

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The dependence on technology has increased, along with the development and change in living standards, which has led to increased energy demand and emissions. Therefore, researchers have focused on green hydrogen production to meet the energy demand and reduce emissions. The proton exchange membrane (PEM) electrolysis is one of the most promising methods for producing green hydrogen, attracting increasing attention from researchers in academia and industry. This study focuses on the bibliometric and text-mining analyses of PEM electrolyzers to identify general trends and the current state of the literature, thereby guiding researchers in future work. In this regard, a dataset was first generated using keywords and abstracts extracted from the Scopus webpage. Then, bibliometric and text-mining analyses were conducted on the dataset using R Studio and Python modeling. Our results demonstrate that research on PEM electrolyzers has increased significantly over the past few years, along with an expansion in the diversity of research topics within the field. Most studies in the literature have focused on material design and the integration of PEM electrolyzers with alternative energy systems. Furthermore, techno-economic analysis, life cycle assessment, multi-objective optimization, and machine learning are identified as emerging research areas. Overall, this work provides a comprehensive overview of the current state of PEM electrolyzer research and identifies future directions emphasizing advanced materials development, renewable energy integration, and sustainable energy management strategies.

Subject Keywords

Bibliometric analysis, Hydrogen production, PEM electrolyzer, Proton exchange membrane electrolysis, Text-mining

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105028593320&origin=inward
https://hdl.handle.net/11511/118634

Collections

Graduate School of Natural and Applied Sciences, Article