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Record W4417485730 · doi:10.1016/j.seta.2025.104786

A Comprehensive review of underground hydrogen storage technology via hydrogen Hydrates: Analysis of nucleation Kinetics, phase characteristics and storage mechanisms

2025· article· en· W4417485730 on OpenAlexaff
Xuan Wang, Mingzhe Guo, Ziting Sun, Yi Pan, Shuangchun Yang

Bibliographic record

VenueSustainable Energy Technologies and Assessments · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
FundersNational Science Fund for Distinguished Young ScholarsFundamental Research Funds for the Central UniversitiesChina National Funds for Distinguished Young ScientistsNational University's Basic Research Foundation of China
KeywordsHydrogen storageNucleationHydrogenPhase (matter)Coupling (piping)Hydrogen sulphideSolid hydrogen

Abstract

fetched live from OpenAlex

To address the issues of high-pressure gaseous hydrogen storage occupying large space and potential safety hazards such as leakage, underground hydrogen storage technology using hydrates has been widely regarded for its ability to provide large-scale, safe, efficient and long-term hydrogen storage solutions. This paper innovatively overcomes the limitations of traditional single-dimensional studies by constructing a cross-scale integration quantitative coupling relationship of “nucleation kinetics − phase characteristics − reservoir optimization.” Firstly, it clarifies the phase characteristics and temperature–pressure conditions of hydrogen hydrates, providing theoretical data for hydrogen storage applications; secondly, it focuses on kinetic mechanisms in bulk and confined spaces, revealing the synergistic effects of “pore size − surface hydrophilicity/hydrophobicity − fluid mobility” on nucleation in confined spaces; finally, it summarizes the mechanisms of hydrate-based hydrogen storage under reservoir conditions (marine reservoirs and permafrost layers). This innovation significantly differs from previous studies: earlier studies often investigated nucleation, phase characteristics, or reservoirs in isolation, and paid insufficient attention to the coupling effects of multiple factors in confined spaces and differentiated reservoir optimization. The main contribution of this research is the establishment of universal theoretical framework and differentiated strategies, providing key technical references and research paradigms for subsequent reservoir optimization and industrial applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.264
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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