ReviewRSC applied interfaces2025
Porous carbons: a class of nanomaterials for efficient adsorption-based hydrogen storage.
Review in RSC applied interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- High-capacity reversible hydrogen storage in Na-decorated Al-N-O nanocluster: a DFT-D3 study.Scientific reports · 2026Article
- Exploring the Impact of Electric Field and OLiACS omega · 2026Article
- Reversible Hydrogen Storage Properties of Superalkali NLiACS omega · 2026Article
- Enhancing hydrogen uptake in TiFe at moderate pressuresRSC advances · 2025Article
- Recent advances in porous graphitic frameworks: a critical mini-review.RSC advances · 2025Review
- Polar Triptycene-Based Nonmetal Organic Frameworks Show Enhanced Hydrogen Adsorption.Journal of the American Chemical Society · 2025Article
- Dimensions, structure, and morphology variations of carbon-based materials for hydrogen storage: a review.Discover nano · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hydrogen has become a promising clean energy source as governments worldwide aim to reduce their reliance on fossil fuels and achieve net-zero emissions. However, a major barrier for hydrogen economy is the challenges associated with the efficient storage of hydrogen, due to its low density, ultra-low boiling point, and extreme volatility. Current practice of using high-pressure tanks has safety concerns and is costly. As a potential solution, adsorption-based hydrogen storage using porous materials has shown great promise due to fast kinetics and their ability to store a comparable amount of hydrogen at much lower pressure. This approach takes advantage of physisorption of hydrogen in porous materials with high surface areas. A number of different classes of materials have been studied for adsorption-based hydrogen storage. Among these materials, porous carbon has shown great promise due to its high surface area, tunable pore size, versatile surface chemistry, scalability, and high chemical and thermal stability. This review provides a comprehensive overview of porous carbon materials, such as graphene, carbon nanotubes, and activated carbons, for hydrogen storage. We delve into the fundamental principles and mechanisms behind adsorptive hydrogen storage, focusing on the critical roles of surface area, pore size, and surface chemistry in determining hydrogen uptake. Strategies to enhance hydrogen storage capacity through structural and chemical modifications are discussed. Additionally, we examine the life cycle assessment of porous carbons and explore recent advancements in machine learning applications to optimize their performance. Finally, we offer insights into the future outlook of porous carbons as a sustainable hydrogen storage solution.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.