Shear‐induced aggregation of colloidal particles: A comparison between two different approaches to the modelling of colloidal interactions
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The process of shear‐induced aggregation of fully destabilized colloidal suspensions has been investigated by adopting a mixed deterministic‐stochastic modelling method. This method is based on a combination of a Monte Carlo algorithm, used to solve in a stochastic way the population balance equation for a purely aggregating suspension, and a Discrete Element Method, employed to simulate aggregation events in a fully predictive manner. The DEM was built in the framework of the well‐established Stokesian dynamics technique to get an accurate prediction of the hydrodynamic forces acting on the primary particles. Two different approaches were instead used to describe colloidal interactions: the first assumes primary particles to interact only by means of central forces; a second model assumes also tangential interactions to act on primary particles upon contact. To describe such interactions we adopted a spring‐like force model recently proposed by Becker and Briesen. Simulations were performed to ascertain the effect of these two different modelling approaches on the process of aggregation, showing that substantial differences appear in the predicted cluster morphology.
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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