Controlling the diffusive boundary layer thickness above the sediment–water interface in a thermostated rotating‐disk reactor
Bibliographic record
Abstract
Abstract The diffusive boundary layer (DBL) is a thin layer of fluid at the interface with a solid surface in which frictional forces cause molecular diffusion to become the dominant mode of solute transport. The thickness of the DBL is a function of the nature and roughness of sediment substrates, as well as the bottom‐current speed. In low‐energy natural aquatic environments, such as abyssal plains or lakes, the thickness of the DBL can reach several millimeters and significantly impede the diffusive rate of solutes through the sediment–water interface (SWI). Thus, precisely reproducing the DBL in the laboratory is required to simulate benthic diffusive fluxes similar to those encountered in situ. Yet, an experimental apparatus allowing precise control of the DBL thickness at the SWI in the laboratory has not been described in the literature. Here, we present a simple temperature‐controlled rotating‐disk system, which is suitable for the use with natural sediments and that is capable of generating thick DBLs. Water overlying the rotating sediment can be sampled discretely or continuously to monitor the chemical reaction progress. We tested the validity of the reactor by dissolving a foraminiferal sand bed in natural seawater. We find that (1) measured dissolution fluxes agree with those predicted by theory and (2) the dissolution of calcite in these seafloor‐like hydrodynamic conditions is controlled by mass transfer across the DBL above the bed. Guidelines for best practices under various experimental conditions, possible future developments, and the theoretical equations to compute the DBL thickness and diffusive fluxes in this reactor are described.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".