Structural and Energetic Studies on the Interaction of Cationic Surfactants and Cellulose Nanocrystals
Bibliographic record
Abstract
We report a comprehensive study on the interactions between cationic surfactant homologues CnTAB (n = 12, 14, and 16) with negatively charged cellulose nanocrystals (CNCs). By combining different techniques, such as isothermal titration calorimetry (ITC), surface tension, light scattering, electrophoretic mobility, and fluorescence anisotropy measurements, we identified two different driving forces for the formation of surface induced micellar aggregates. For the C12TAB surfactant, a surfactant monolayer with the alkyl chains exposed to the water is formed via electrostatic interactions at low concentration. At a higher surfactant concentration, micellar aggregates are formed at the CNC surface. For the C14TAB and C16TAB systems, micellar aggregates are formed at the CNC surface at a much lower surfactant concentration via electrostatic interactions, followed by hydrophobic interactions between the alkyl chains. At higher surfactant concentration, charge neutralization and association of the surfactant decorated CNC aggregates led to flocculation.
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".