Two-Dimensional Aggregation of Rod-Like Particles: A Model Investigation
Bibliographic record
Abstract
In this work, a 2D computer model was created for the aggregation of rodlike particles, on the basis of a molecular-dynamic approach. With the help of the model, it is possible to visualize the motion of the aggregating particles, clearly and faithfully, offering the possibility of structural, kinetic, and dynamic analysis of the aggregation. The aggregation, in the model, is governed by long-range and short-range attractive particle−particle forces, two-dimensional streams, breaking forces, and the degree of particle-anisometry. The long-range forces initiate the motions of the particles and clusters and also cause restructuring in the growing aggregates, which process can be hindered by sufficiently strong short-range, attractive forces. The off-lattice computer simulation of the aggregation revealed that (i) the greater extent of restructuring resulted in the formation of denser and more compact clusters with higher fractal dimensions. Interestingly, the attractive short-range forces, through the restructuring, could also influence the driving force of aggregation. It was found that the more intensive the restructuring, the weaker the driving force is in the second stage of aggregation. (ii) An increase in the effective range of long-range forces (without restructuring) resulted in higher fractal dimensions and kinetic constants. The increase of D f with the effective range of forces was interpreted in terms of a percolation-like aggregation. (iii) Moreover, increasing anisometry of the particles (without restructuring) also resulted in an increase of fractal dimensions, confirming that the investigated aggregations take place in a transition range between the diffusion-limited-like aggregation and percolation (gelation). Our model was implemented successfully in a real phenomenon, the aggregation of cylindrical-shaped carbon particles at water (aqueous surfactant solution)/air interfaces. The effectiveness of the computer model was proved by comparing the structural, kinetics, and mechanism-related parameters obtained for the simulations with those of the real experiments.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".