Probing Contaminant Transport to and from Clay Surfaces in Organic Solvents and Water Using Solution Calorimetry
Bibliographic record
Abstract
Clays, in tailings, are a significant ongoing environmental concern in the mining and oilsands production industries, and clay rehabilitation following contamination poses challenges episodically. Understanding the fundamentals of clay behavior can lead to better environmental impact mitigation strategies. Systematic calorimetric measurements are shown to provide a framework for parsing the synergistic and antagonistic impacts of trace (i.e., parts per million level) components on the surface compositions of clays. The enthalpy of solution of as-received and "contaminated" clays, in as-received and "contaminated" organic solvents and water, at 60 °C and atmospheric pressure, provides important illustrative examples. Clay contamination included pre-saturation of clays with water and organic liquids. Solvent contamination included the addition of trace water to organic solvents and trace organic liquids to water. Enthalpy of solution outcomes are interpreted using a quantitative mass and energy balance modeling framework that isolates terms for solvent and trace contaminant sorption/desorption and surface energy effects. Underlying surface energies are shown to dominate the energetics of the solvent-clay interaction, and organic liquids as solvents or as trace contaminants are shown to displace water from as-received clay surfaces. This approach can be readily extended to include pH, salts, or other effects and is expected to provide mechanistic and quantitative insights underlying the stability of clays in tailings ponds and the behaviors of clays in diverse industrial and natural environments.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".