JOURNAL ARTICLE
Advancements and challenges in sodium borohydride hydrogen storage: A comprehensive review of hydrolysis, regeneration, and recycling technologies.
Published In: Journal of Renewable & Sustainable Energy, 2025, v. 17, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Chin, Siew Xian; Vincent, Jei; Razak, Nor Farhah; Daud, Nurulhaidah; Chowdhury, Shahriah; Wongchoosuk, Chatchawal; Chia, Chin Hua 3 of 3
Abstract
This article provides a comprehensive review of sodium borohydride (NaBH₄) as a hydrogen storage material, focusing on its hydrolysis for hydrogen production and regeneration methods from 2004 to 2024. NaBH₄ offers advantages such as high gravimetric hydrogen capacity (~10.6 wt.%), stability, controlled hydrogen release, and the potential for recycling from its hydrolysis by-product sodium metaborate (NaBO₂). The review details various catalysts—including cobalt, nickel, ruthenium, iron, noble metals, and metal-free carbon-based materials—that enhance hydrolysis efficiency, discussing their activity, cost, recyclability, and challenges. It also examines key reaction parameters (temperature, pH, NaBH₄ concentration) and additives that influence hydrogen generation kinetics. Finally, the article evaluates three main NaBH₄ regeneration approaches—thermochemical, mechanochemical, and electrochemical—highlighting their respective benefits and limitations for sustainable, large-scale hydrogen storage applications.
Additional Information
- Source:Journal of Renewable & Sustainable Energy. 2025/01, Vol. 17, Issue 1, p1
- Document Type:Literature Review
- Subject Area:Environmental Sciences
- Publication Date:2025
- ISSN:1941-7012
- DOI:10.1063/5.0242699
- Accession Number:183417675
- Copyright Statement:Copyright of Journal of Renewable & Sustainable Energy is the property of American Institute of Physics and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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