Natural H<sub>2</sub> and Sulfate Production via Radiolysis in Low Porosity and Permeability Crystalline Rocks
Bibliographic record
Abstract
Abstract Natural hydrogen (H2) is a candidate low‐carbon energy source for society and sustains microbial ecosystems when coupled with oxidants (e.g., sulfate). In crystalline rock settings, water‐rock interactions, including radiolysis, generate both H2 and sulfate, but quantifying their production rates remains challenging when porosity and permeability are low. This study employs a Monte Carlo approach to estimate H2 and sulfate production via radiolysis in the Revell batholith (Ontario, Canada), a well characterized site which is representative of hydrogeologically tight conditions. Results are then compared to estimates from a similarly isolated, but more fractured site at Kidd Creek (Ontario, Canada) to examine the spectrum of elemental cycling and habitability that may exist in these globally widespread settings. At Revell, production rates for both H2 and sulfate are substantially lower than for Kidd Creek. Revell's most probable H2 production rate is estimated at 1.6 nmol m−3 rock yr−1, approximately half that of Kidd Creek, and Revell's sulfate production is 102–106‐fold lower. These differences are primarily driven by Revell's lower porosity and sulfide concentrations, respectively. While statistical analyses suggest a small theoretical probability of low levels of biological activity, Revell's potential for sulfate‐supported habitability is calculated to be among the lowest observed in subsurface settings globally. This study demonstrates a framework for quantifying potential H2 and sulfate production in settings where direct sampling of biomass, gas, and fluid is not feasible. It can be applied to investigations of the Earth's deep biosphere, geologic repositories, economic H2 exploration, and habitability for other planets and moons.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".