Rapid Covalent Modification of Silicon Oxide Surfaces through Microwave-Assisted Reactions with Alcohols
Bibliographic record
Abstract
We demonstrate the method of a rapid covalent modification of silicon oxide surfaces with alcohol-containing compounds with assistance by microwave reactions. Alcohol-containing compounds are prevalent reagents in the laboratory, which are also relatively easy to handle because of their stability against exposure to atmospheric moisture. The condensation of these alcohols with the surfaces of silicon oxides is often hindered by slow reaction kinetics. Microwave radiation effectively accelerates this condensation reaction by heating the substrates and/or solvents. A variety of substrates were modified in this demonstration, such as silicon oxide films of various thicknesses, glass substrates such as microscope slides (soda lime), and quartz. The monolayers prepared through this strategy demonstrated the successful formation of covalent surface modifications of silicon oxides with water contact angles of up to 110° and typical hysteresis values of 2° or less. An evaluation of the hydrolytic stability of these monolayers demonstrated their excellent stability under acidic conditions. The techniques introduced in this article were successfully applied to tune the surface chemistry of silicon oxides to achieve hydrophobic, oleophobic, and/or charged surfaces.
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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".