Tuning Oleophobicity of Silicon Oxide Surfaces with Mixed Monolayers of Aliphatic and Fluorinated Alcohols
Bibliographic record
Abstract
We demonstrate the formation of mixed monolayers derived from a microwave-assisted reaction of alcohols with silicon oxide surfaces in order to tune their surface oleophobicity. This simple, rapid method provides an opportunity to precisely tune the constituents of the monolayers. As a demonstration, we sought fluorinated alcohols and aliphatic alcohols as reagents to form monolayers from two distinct constituents for tuning the surface oleophobicity. The first aspect of this study sought to identify a fluorinated alcohol that formed monolayers with a relatively high surface coverage. It was determined that 1H,1H,2H,2H-perfluoro-1-octanol yielded high quality monolayers with a water contact angle (WCA) value of ∼110° and contact angle values of ∼80° with toluene and hexadecane exhibiting both an excellent hydrophobicity and oleophobicity. Tuning of the oleophobicity of the modified silicon oxide surfaces was achieved by controlling the molar ratio of 1H,1H,2H,2H-perfluoro-1-octanol within the reaction mixtures. Surface oleophobicity progressively decreased with a decrease in the fluorinated alcohol content while the monolayers maintained their hydrophobicity with WCA values of ∼110°. The simple and reliable approach to preparing monolayers of a tuned composition that is described in this article can be utilized to control the fluorocarbon content of the hydrophobic monolayers on silicon oxide surfaces.
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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".