Facile Preparation of Nanostructured, Superhydrophobic Filter Paper for Efficient Water/Oil Separation
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a facile and cost-effective method to obtain superhydrophobic filter paper and demonstrate its application for efficient water/oil separation. By coupling structurally distinct organosilane precursors (e.g., octadecyltrichlorosilane and methyltrichlorosilane) to paper fibers under controlled reaction conditions, we have formulated a simple, inexpensive, and efficient protocol to achieve a desirable superhydrophobic and superoleophilic surface on conventional filter paper. The silanized superhydrophobic filter paper showed nanostructured morphology and demonstrated great separation efficiency (up to 99.4%) for water/oil mixtures. The modified filter paper is stable in both aqueous solutions and organic solvents, and can be reused multiple times. The present study shows that our newly developed binary silanization is a promising method of modifying cellulose-based materials for practical applications, in particular the treatment of industrial waste water and ecosystem recovery.
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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) | 0.002 | 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 it