Effects on the Self-Assembly of <i>n</i>-Alkane/Gold Nanoparticle Mixtures Spread at the Air–Water Interface
Bibliographic record
Abstract
Nanoparticle films formed at the air-water interface readily form rigid films, where the nanoparticles irreversibly associate into floating "islands", often riddled with voids and defects, upon solvent evaporation. Improving the nanoparticle mobility in these films is key to achieving control over the nanoparticle packing parameters, which is attractive for a variety of applications. In this study, a variety of n-alkanes were mixed with tetradecanethiol-capped 2 nm gold nanoparticles and studied as Langmuir films at 18 and 32 °C. Pressure-area isotherms at 18 °C reveal a mixed liquid-expanded phase of nanoparticles and alkane at the air-water interface, but only for n-alkanes that are equal to or exceed the nanoparticle capping ligand in carbon chain length. Transmission electron microscopy images of the corresponding films suggest that the nanoparticles are mixed with a continuous hydrocarbon phase at 0 mN/m and that the hydrocarbon is squeezed out of the nanoparticle film during compression.
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) | 0.001 | 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".