Determination of the Diffusion Coefficient of Oxygen for a Cover System Including a Pulp and Paper By-Product
Bibliographic record
Abstract
Abstract Among the several solutions that have been proposed to curb the problem posed by the generation of acid rock drainage (ARD), the placement of covers with capillary barrier effect (CCBE) has received particular attention. With the creation of a capillary barrier, oxygen has to migrate through a nearly saturated layer, a much slower process than in air. As a consequence, its availability is drastically reduced, reducing ARD generation. An experimental procedure was developed to obtain the diffusion coefficient of oxygen through compacted deinking residues, an organic matter-rich by-product of paper recycling. With the oxygen concentrations obtained as a function of time, it was possible to deduce the diffusion coefficients based on the best reproductions of laboratory results, using the computer code POLLUTE v.6. As expected, it was found that the diffusion coefficient—and the associated flux—is highly influenced by the degree of saturation of the sample. Beyond a threshold in the vicinity of 85%, a one order of magnitude drop in the diffusion coefficient was observed. A comparison of the results obtained with previously published data shows that deinking residues constitute a very effective oxygen barrier material due both to its ability to maintain a high degree of saturation and to rapidly consume oxygen. Given the latter, special care was needed in defining the most appropriate equipment design, sample preparation method, and testing procedure.
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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 | 0.000 |
| 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".