Translocation is a nonequilibrium process at all stages: Simulating the capture and translocation of a polymer by a nanopore
Bibliographic record
Abstract
Langevin dynamics simulations of the capture of polymers by a nanopore and the subsequent translocation through the nanopore are performed. These simulations are conducted for several polymer lengths at two different values for the Péclet number, which quantifies the drift-diffusion balance of the system. The capture-translocation process is divided into several stages, and the dynamics of translocation are characterized by measuring the average time for each stage and also the average conformation of the polymer at each stage. Comparison to the standard simulation approach of simulating only the translocation process reveals several important differences. While in the standard protocol, the polymer is essentially equilibrated at the start of translocation, simulations of the capture process reveal a polymer that is elongated when it approaches the pore and either remains elongated or becomes compressed at the start of translocation depending on the drift-diffusion balance. These results demonstrate that translocation is a non-equilibrium process at all stages and that simulations assuming equilibration could yield improper results, even at a qualitative level. The scaling of the translocation time with polymer length is found to be significantly different between the two simulation protocols thus demonstrating that the capture step is an essential part of modeling the translocation process.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".