Tracing Water Flow and Colloidal Particles Transfer in an Unsaturated Soil
Bibliographic record
Abstract
In recent years, many studies have been carried out on colloidal particle transfer in the unsaturated zone because they can be a risk to the environment either directly or as a vector of pollutants. A study was conducted on the influence of porous media structure in unsaturated conditions on colloidal particle transport. Three granular materials were set up in columns to replicate a fluvio-glacial soil from the unsaturated zone in the Lyon area (France). It is a sand, a bimodal mixture in equal proportion by weight of sand and gravel, and a fraction of bimodal mixture. Nanoparticles of silica (SiO2-Au-FluoNPs), having a hydrodynamic diameter between 50 and 60 nm, labeled by organic fluorescent molecules were used to simulate the transport of colloidal particles. A nonreactive tracer, bromide ion (Br-) at a concentration of C0,s = 10-2 M was used to determine the hydrodispersive properties of porous media. The tests were carried out first, with a solution of nanoparticles (C0,p = 0.2 g/L) and secondly, with a solution of nanoparticles and bromine. The transfer model based on fractionation of water into two phases, mobile and immobile, MIM, correctly fits the elution curves. The retention of colloidal particles is greater in the two media of bimodal particle size than that in the sand, which clearly demonstrates the role of textural heterogeneity in the retention mechanism. The increase in ionic strength produced by alimenting the columns with colloidal particle suspension in the presence of bromide, increases retention up to 25% in the sand. The total concentration profile of nanoparticles collected at the end of the experiment shows that the colloidal particles are retained primarily at the entrance of the columns. Hydrodispersive calculated parameters indicate that flow is more heterogeneous in bimodal media compared to sand.
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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 | 0.000 |
| 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 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".