Nanoimmiscibility: Selective Absorption of Liquid Methanol–Water Mixtures in Carbon Nanotubes
Bibliographic record
Abstract
Despite the continuing research interests in CNT-liquid systems, the microscopic structure and transport behavior of liquid mixtures in carbon nanotubes (CNTs) remain poorly understood. Methanol and water liquids are completely miscible across the entire range of concentration; however, recent research reveals that they are immiscible at a molecular level. In this work, we carried out classical molecular dynamics to study the molecular distribution, structure ordering, clustering and transport behavior of liquid methanol-water mixtures within CNT confinement. We found that CNTs preferentially absorbed methanol over water molecule even though the latter has a smaller molecular size, indicating that chemical effect such as molecular hydrophilicity plays a crucial role in the molecular absorption of CNTs. Due to the selective absorption of CNTs, methanol aqueous solution changes from microscopically immiscible to macroscopically immiscible at nanoscale. This nanoscale immiscibility may be utilized in various applications of CNTs including direct methanol fuel cells, nanosensors, molecular sieves, nanofluidic chips, and capsules for drug delivery.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".