Enhancing Droplet Spreading on a Hydrophobic Plant Surface by Surfactant/Cellulose Nanocrystal Complexes
Bibliographic record
Abstract
A surfactant is an efficient and common additive used to enhance the spreading of droplets on hydrophobic surfaces. However, a high surfactant concentration is required to achieve the desired performance, resulting in environmental pollution and increased costs. Additionally, the pesticide loading capacity of surfactants at low concentrations (below their critical micelle concentrations) is a concern. Thus, in this study, we developed a strategy to enhance pesticide loading and droplet deposition by mixing small amounts of sodium dodecyl sulfate (SDS) (0.1 wt %) and cationically modified cellulose nanocrystals (PCNC). The reduced surface tension, increased viscosity and adhesion, and electrostatic and hydrogen interactions resulted in a low retraction velocity, excellent spreading, and resistance to air turbulence. The improved loading content was facilitated by the hydrophobic domains of PCNC and SDS micelles.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".