Propagation of Nanocatalyst Particles Through Athabasca Sands
Bibliographic record
Abstract
Summary This paper presents results of an experimental study that systematically examined the propagation of nanodispersed catalyst suspension in sandpacks prepared with Athabasca reservoir sand and operated at the reservoir conditions. The concentration and size distribution of the particles at the injection and production end were measured. The pressure drops in different segments along length of the sandpack were monitored continuously. The retention behaviour of particles at the end of each experiment was examined by measuring the catalyst concentration in the bed as a function of the distance from the injection end of the sandpack and also by analysis of extracted samples using scanning electron microscopy. The results show that it is possible to propagate the nanodispersed catalyst suspension through sand beds without causing permeability damage, but a small fraction of the injected particles is retained in the sand. It was found that significantly higher retention occurs in the entrance region of the bed (compared with downstream regions) and that the total particle retention was higher in the Athabasca sand beds than in clean silica sand with the same flow and suspension properties. To the best of our knowledge, this is the first experimental study on transport of nanoparticles dispersed in viscous oil through reservoir sand beds. It provides valuable information on propagation and retention behaviour of nanoparticles. Considering the rapidly rising use of nanoparticles in industry, such transport will be encountered in numerous industrial applications and environmental problems.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".