Facile Preparation of Fluoroalkyl End-Capped Vinyltrimethoxysilane Oligomer/Sand Composites Possessing Superoleophilic/Superhydrophobic Characteristic: Application to Oil/Water Separation and Selective Removal of Fluorinated Aromatic Compounds from Aqueous Methanol Solution
Bibliographic record
Abstract
Fluoroalkyl end-capped vinyltrimethoxysilane oligomer [RF-(CH2-CHSi(OMe)3)n-RF: n = 2, 3, RF = CF(CF3)OC3F7: RF-(VM)n-RF], was applied to the facile preparation of the corresponding oligomer/sand (Ottawa sand: OS) composites [RF-(VM-SiO3/2)n-RF/OS] through the sol-gel reaction of the oligomer in the presence of micro-sized OS particles (590 - 840 μm) under alkaline conditions at room temperature. FE-SEM (Field Emission Scanning Electron Micrograph) images showed that the obtained composites consist of the RF-(VM-SiO3/2)n-RF oligomeric nanoparticles and the micro-sized OS particles. Interestingly, the RF-(VM-SiO3/2)n-RF/OS composites thus obtained can provide the superoleophilic/superhydrophobic characteristic on the composite surface, applying to the separation of not only the mixture of oil/water but also the W/O emulsion to isolate the transparent colorless oil. The fluorinated oligomeric OS composites were also found to be applicable to the selective removal of fluorinated aromatic compounds from an aqueous methanol solution. Especially, it was demonstrated that the fluorinated OS composites can supply a higher efficient and smooth separation ability for the separation of the mixture of oil and water than that of the corresponding fluorinated micro-sized controlled silica gel (μ-SiO2) composites (average particle size: 9.5 μm), which were prepared under similar conditions. In addition to the separation of oil/water, the fluorinated OS composites provided higher and more selective removal ability for the fluorinated aromatic compounds from aqueous solutions than that of the μ-SiO2 composites.
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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".