Micellization, Interaction and Microenvironment in the Mixed Solution of Pluronics and Surfynol 104 with Nuclear Magnetic Resonance
Bibliographic record
Abstract
The micellization, intermolecular interaction and microenvironment of molecular segments in the mixed aqueous solution of PEO-PPO-PEO triblock copolymer (Pluronic(superscript ®) F88, P84 and P123) and Surfynol(superscript ®) 104 (S1O4) were studied by nuclear magnetic resonance method. The results showed that the addition of S1O4 decreased the critical micellization temperature of copolymer. When its concentration was 0.5g/L, the most reduction was up to more than 10℃ for F88, which was most hydrophilic in the selected copolymers. This reduction was caused by the hydrophobic interaction between S1O4 molecules and PPO segments. The addition of S104 enhanced the hydration of PEO segments most obviously for P123. And S104 slightly increased the hydration of PPO segments before the micellization, but obviously decreased their hydration after micellization, which was attributed to the hydrophobic interaction mentioned above and temperature rising. This effect was most observable for F88.
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".