Model of inhibited surface adsorption: Application to foam stabilization and destabilization
Bibliographic record
Abstract
A classic statistical mechanical model of surface adsorption of an object that interacts with another component present in a medium was developed in this work. The effective Hamiltonian for the process is proposed and developed here, which takes into consideration the interactions between one of the objects with a surface and the interaction with another object in the medium. This model allowed for the prediction of the binding isotherm for the object. Monte Carlo computer simulations were employed to model the behavior of the system, which was in good agreement with the theory. This model was complemented with an equilibrium kinetic model of the same system and simulations. Qualitative agreement between the two approaches was achieved by introducing a degeneracy in the cooperative interaction between the object and the component, namely simultaneous positive and negative binding cooperativity of the same process. The model developed and the results obtained will help explain the variability in the foamability of barista milk, where free fatty acids are known to inhibit the adsorption of proteins to the air bubble surface. Here, we suggest that the variability observed could be due to the ratio of free fatty acids to protein, which was never considered before.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".