General mechanism and mitigation for strong adhesion of frozen oil sands on solid substrates
Bibliographic record
Abstract
Oil sands adhered on truck bed reduce transport capacity of the truck, require manual cleaning, and create hurdles for automated surface mining. Study on the adhesion properties of oil sands to solid substrates is important to minimize the fouling of substrates during mining operation. In this work, we study the influence of hydrophobicity and mechanical properties of the substrates on the adhesion strength of frozen oil sands. By using an adhesion force apparatus with temperature control, we measure the adhesion strength of both ice and frozen oil sands on six types of substrates with water contact angle from ∼20◦ to ∼130◦ and Young’s modulus from a few MPa to 300 GPa. A clear linear correlation between the adhesion strength of pure ice and that of frozen oil sands is observed. Furthermore, the adhesion strength increases with the load on the oil sands sample and reaches a plateau at ∼450 kPa. The maximum adhesion strength may be due to the limit of particle packing of oil sands. We also demonstrate that spray coating of anti-freezing liquids is effective for the mitigation of the adhesion of frozen oil sands. Substrates coated with various anti-freezing liquids showed undetectable oil sands adhesion strength at -20 ◦C with 0.06 MPa of load. The study on oil sands adhesion and potential fouling mitigation method may provide a potential solution to industries looking to reduce fouling of surfaces by frozen granular matter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".