Straining and Attachment of Colloids in Physically Heterogeneous Porous Media
Why this work is in the frame
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Bibliographic record
Abstract
Colloid transport studies were conducted in water‐saturated physically heterogeneous systems to gain insight into the processes controlling transport in natural aquifer and vadose zone (variably saturated) systems. Stable monodispersed colloids (carboxyl latex microspheres) and porous media (Ottawa quartz sands) that are negatively charged were employed in these studies. The physically heterogeneous systems consisted of various combinations of a cylindrical sand lens embedded in the center of a larger cylinder of matrix sand. Colloid migration was found to strongly depend on colloid size and physical heterogeneity. A decrease in the peak effluent concentration and an increase in the colloid mass removal in the sand near the column inlet occurred when the median grain size of the matrix sand decreased or the size of the colloid increased. These observations and numerical modeling of the transport data indicated that straining was sometimes an important mechanism of colloid retention. Experimental and simulation results suggest that attachment was more important when the colloid size was small relative to the sand pore size. Transport differences between conservative tracers and colloids were attributed to flow bypassing of finer‐textured sands, colloid retention at interfaces of soil textural contrasts, and exclusion of colloids from smaller pore spaces. Colloid retention in the heterogeneous systems was also influenced by spatial variations in the pore water velocity. Parameters in straining and attachment models were successfully optimized to the colloid transport data. The straining model typically provided a better description of the effluent and retention data than the attachment model, especially for larger colloids and finer‐textured sands. Consistent with previously reported findings, straining occurred when the ratio of the colloid and median grain diameters was >0.5%.
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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) | 0.000 | 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 it