Synthesis and Characterization of Furan-Based Non-Ionic Surfactants (<i>fbnios</i>)
Bibliographic record
Abstract
Two series of furan-based non-ionic surfactants ( fbnios ) were prepared by a combination of Williamson ether synthesis and anionic polymerization of ethylene oxide (EO). The reaction of 1-bromooctane and 1-bromododecane with 2,5- bis (hydroxymethyl)furan after deprotonation with potassium tert -butoxide yielded the corresponding alkane furfuryl alcohols (C x -F-OH with x = 8 or 12). Deprotonation of C x -F-OH with potassium tert -pentoxide enabled the anionic polymerization of EO, which yielded four C 8 -F-EO y samples with y = 3, 6, 9, and 14 and four C 12 -F-EO y samples with y = 9, 12, 18, and 23. The chemical composition of the fbnios was determined by NMR and matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-ToF MS) analysis, while their dispersity ( Đ ) was characterized by gel permeation chromatography (GPC) and MALDI-ToF MS. The purity of the C x -F-EO y samples exceeded 92%, and they were produced with narrow molecular weight distributions ( Đ ≤ 1.02, as determined by GPC analysis). The critical micelle concentration (CMC) of the C x -F-EO y samples was determined by surface tension and pyrene fluorescence measurements. These showed that the CMC of the fbnios could be tuned by adjusting the molecular parameters x and y, with the CMC increasing for decreasing x and increasing y . In particular, the CMC of the C 8 -F-EO y and C 12 -F-EO y samples was significantly higher and lower, respectively, than for typical non-ionic surfactants ( nios ) like the Triton X and Brij surfactant families. The efficiency, effectiveness, and cross section of the EO y headgroup of the fbnios were also determined. Together, the CMC, efficiency, and effectiveness of the fbnios demonstrate that this new surfactant family displays tensioactive properties that match and even exceed those of traditional nios, suggesting that they could extend further the already broad range of applications for nios .
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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 | 0.000 | 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) | 0.000 | 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".