Polymer Chain Conformation Triggers Electro-osmotic Flow in Uncharged Nanochannels
Bibliographic record
Abstract
Electroosmotic flow (EOF) in nanoscale systems is traditionally associated with charged channel walls. Here, we report a new EOF mechanism in polyelectrolyte (PE) solutions confined within uncharged nanochannels, revealed by dissipative particle dynamics simulations. The flow is found to arise from a PE chain conformation-induced spanwise charge separation in the electric double layer (EDL). The flow exhibits vanishing velocity gradients on the channel wall, indicating a wall-dissipation-free transport of liquids. Comprehensive parametric studies are also performed to reveal the characteristics of the new EOF. Chain topology and stiffness critically regulate this conformation-induced EOF: increasing chain rigidity suppresses charge separation and reduces flow velocity, most prominently in linear chains and least in star-like chains. Long rigid chains adopt U-shaped or claw-like conformations under electric fields and channel confinement, reshaping charge separations and reducing the EOF velocity. Channel confinement further modulates flow characteristics, with PE distributions exhibiting different patterns for various chain topologies, evolving from single to double and even triple layers. The EOF velocity also exhibits a nonmonotonic variation with the decaying nanoconfinement due to oscillations of the charge separation in the EDL. For all topologies, the charge separation and the EOF are gradually suppressed due to screening effects of added salt. This work promotes the investigation of electroosmotic transport of complex fluids and offers insights for designing nanofluidic pumping systems based on molecular conformation.
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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) | 0.000 | 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 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".