<i>n</i>-decane diffusion in carbon nanotubes with vibration
Bibliographic record
Abstract
Carbon nanotubes (CNTs) have a wide range of applications in nanotechnology engineering. This research aims to quantify the effect of wall vibration on n-decane molecules' diffusion in double-walled CNTs (DWNTs) with different diameters and determine the diffusion mechanisms behind it. Molecular dynamics simulations are performed to generate mass density profiles of confined n-decane molecules. The root mean square fluctuation and mean squared displacement analyses show that the confinement suppresses n-decane molecules' fluctuations. A self-diffusion coefficient of n-decane molecules in a 13.6 Å-diameter DWNT is the largest. However, the vibration enhancement of the n-decane molecules' diffusion in a 27.1 Å-diameter DWNT is 207%, more extensive than that in 13.6 Å-diameter and 10.8 Å-diameter DWNTs. The n-decane-CNT attractive interactions, extreme confinement, and surface friction affect the n-decane molecules' diffusion in CNTs with vibration.
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 | 0.000 |
| 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".