The pendant drop experiment for aggregates of cohesive granular particles
Bibliographic record
Abstract
The pendant drop experiment can be used to study the interfacial tension of a liquid. Here we perform a similar experiment for a granular system. When a dense aggregate of cohesive particles extrudes from an orifice, a cluster of particles detaches, similar to the detachment of a liquid drop. We investigate the volume of the clusters formed from close-packed cohesive oil droplets in an aqueous solution. Our findings reveal that the volume of the clusters depends on the size of the orifice as well as the cohesion strength. Interestingly, we observe that the droplet size does not significantly impact the average cluster volume. We establish a simple scaling law that governs the size of a granular cluster which differs from that of a classic pendant drop. We propose that the key difference between continuum and granular systems is the constraints on rearrangements within the cohesive particles that prevent the clusters from adopting a minimal surface structure, as is the case for a classic pendant drop.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".