Nanoconfinement Effect on <i>n</i>-Alkane Flow
Bibliographic record
Abstract
Nanoconfinement induces change of microscopic structures of n -alkanes, which, in turn, alters their dynamics. We study a fundamental question of nanoscale n -alkane flow through in-depth theoretical analysis of relating microscopic structures to macroscopic dynamic properties. We show that the velocity profile and corresponding flux are governed by the interfacial resistance from first-layer n -alkanes near a nanopore wall and the viscous resistance from other n -alkanes in nanopores. We find that n -alkane flow through nanopores is a function of nanopore wall energy, nanopore diameter, and n -alkane properties, which allows a wide range of enhancement factors, spanning over 4 orders of magnitude reported in the literature, to be quantitatively rationalized. Most importantly, we demonstrate that there is huge potential in manipulating n -alkane flow by tuning nanopore wall composition and nanopore size. We propose a theoretical framework of modeling the flow of macromolecule fluids beyond n -alkanes at the nanoscale.
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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) | 0.001 | 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".