Probing particle heteroaggregation using analytical centrifugation
Bibliographic record
Abstract
The controlled aggregation of colloidal particles is not only a widespread natural phenomenon but also serves as a tool to design complex building blocks with tailored shape and functionalities. However, the quantitative characterization of such heteroaggregation processes remains challenging. Here, we demonstrate the use of analytical centrifugation to characterize the heteroaggregation of silica particles and soft microgels bearing similar surface charges. We investigate the attachment as well as the stability of the formed heteroaggregates as a function of particle to microgel surface ratio, microgel size and the influence of temperature. The attachment of microgels onto the colloidal particles induces a change in the sedimentation coefficient, which is used to quantitatively identify the number of attached microgels. We corroborate the shift in sedimentation coefficient by computer simulations of the frictional properties of heteroaggregates via a modified Brownian dynamic algorithm. The comparison between theoretical investigations and experiments suggest that the microgels deform and flatten upon attachment.
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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 | 0.001 | 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 | 0.001 |
| 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 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".