High Internal Phase Pickering Emulsions as Templates for a Cellulosic Functional Porous Material
Bibliographic record
Abstract
Emulsions stabilized by solid particles (Pickering emulsions) are remarkably more resistant to coalescence than emulsions generated with molecular surfactants. If enriched to at least 0.74 by volume fraction of the dispersed phase, then these so-called high internal phase Pickering emulsions (HIPPEs) find important use as templates for the fabrication of a wide spectrum of functional porous materials. Starting with ethyl cellulose (EC)—a nontoxic, food-grade, and biocompatible polymer derived from abundant cellulose—we show how spherical EC nanoparticles can be used to generate oil-in-water (O/W) or water-in-oil (W/O) Pickering emulsions without surfactants. We explore the conditions of ionic strength, oil volume fraction, and EC nanoparticle concentration under which HIPPEs with an internal phase volume fraction of 0.76 ± 0.04 are produced. Using EC nanoparticle-stabilized HIPPEs as a template, we then fabricate a hydrophobic/oleophilic polymeric porous material, which selectively absorbs oil, collects an oil spill from the surface of water, and breaks an O/W Pickering emulsion to its constituents.
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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) | 0.001 | 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 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".