Transient physics in the compression and mixing dynamics of two nanochannel-confined polymer chains
Bibliographic record
Abstract
We use molecular dynamics (MD) simulation and nanofluidic experiments to probe the non-equilibrium transient physics of two nanochannel-confined polymers driven against a permeable barrier in a flow field. For chains with a persistence length P smaller than the channel diameter D, both simulation and experiment with dsDNA reveal nonuniform mixing of the two chains, with one chain dominating locally in what we term "aggregates." Aggregates undergo stochastic dynamics, persisting for a limited time, then disappearing and reforming. Whereas aggregate-prone mixing occurs immediately at sufficiently high flow speeds, chains stay segregated at intermediate flow for some time, often attempting to mix multiple times, before suddenly successfully mixing. Observation of successful mixing nucleation events in nanofluidic experiments reveal that they arise through a peculiar "back-propagation" mechanism whereby the upstream chain, closest to the barrier, penetrates and passes through the downstream chain (farthest from the barrier) moving against the flow direction. Simulations suggest that the observed back-propagation nucleation mechanism is favored at intermediate flow speeds and arises from a special configuration where the upstream chain exhibits one or more folds facing the downstream chain, while the downstream chain has an unfolded chain end facing upstream.
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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".