Geochemical Effects of Hydrogen Storage in Unlined Rock Caverns: AModelling Study Using Limestone as the Host Rock
Bibliographic record
Abstract
Underground Hydrogen Storage (UHS) is a promising option for achieving large-scale renewable energy storage, and unlined rock cavern (URC) storage is an attractive alternative to conventional UHS options.Limestone could be a potential host rock for the construction of the URC.However, to confirm the viability of the limestone, a better understanding of the reactivity of hydrogen-brinelimestone systems is necessary.Therefore, we conducted a geochemical modelling study to explore the interaction between hydrogen and limestone.This investigation involved kinetic batch modelling under environmental conditions typical of shallow-depth unlined rock caverns (URCs).During the 100-year simulation, carbonate minerals like calcite, dolomite, magnesite, and siderite wholly dissolved due to redox reactions with hydrogen.As a result, over 80% of the hydrogen was lost, leading to methane (CH₄) gas production.However, these reactions were driven by methanogenesis, which is known to be kinetically limited under the low temperatures (40⁰) used in this study and needs to be catalysed through, e.g. by the microorganisms.Consequently, we adjusted the database to focus solely on abiotic reactions.Under these conditions, hydrogen exhibited behaviour akin to inert gas, showing negligible reactivity.In the absence of catalysed redox reactions, limestone emerges as a robust choice for URC construction.However, microorganisms in URCs could potentially catalyse these reactions, rendering limestone unsuitable for URC construction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".