Hydrogen economy research using Latent Dirichlet Allocation topic modeling: Review, trends and future directions

Research output: Contribution to journalReview articlepeer-review

Abstract

The hydrogen economy has recently gained significant importance as a critical component of energy systems, offering a way to reduce carbon emissions and pave the way to a sustainable, clean energy future. This review leverages Latent Dirichlet Allocation (LDA) topic modeling to comprehensively analyze the rapidly expanding body of literature on hydrogen economy. In this review paper, we identify research areas, track their evolution, and explore different topics in this field. We examine literature from various perspectives on various subject areas and compare it before and after 2020 to highlight progress and shifting focuses. Our findings demonstrate a significant rise in research output on the hydrogen economy post-2020. Moreover, key trends include green hydrogen production, renewable energy integration, and the use of waste and biomass in hydrogen generation. We further discuss future research directions and map our findings to the current industry status and internationally announced hydrogen plans. Finally, we highlight the limitations and implications of our research for academia, industry, and policymakers. This review provides a comprehensive view of the hydrogen economy, using LDA to reveal in-depth insights into this emerging field.

Original languageBritish English
Article number100953
JournalCleaner Engineering and Technology
Volume26
DOIs
StatePublished - May 2025

Keywords

  • Bibliometric
  • Hydrogen economy
  • LDA
  • Machine learning
  • Review

Fingerprint

Dive into the research topics of 'Hydrogen economy research using Latent Dirichlet Allocation topic modeling: Review, trends and future directions'. Together they form a unique fingerprint.

Cite this