Self-Assembled Monolayers of a Fluorinated Phosphonic Acid as a Protective Coating on Aluminum
Bibliographic record
Abstract
Aluminum (Al) placed in hot water (HW) at 90 °C is roughened due to its reaction with water, forming Al hydroxide and Al oxide, as well as releasing hydrogen gas. The roughened surface is thus hydrophilic and possesses a hugely increased surface area, which can be useful in applications requiring hydrophilicity and increased surface area, such as atmospheric moisture harvesting. On the other hand, when using HW to roughen specified areas of an Al substrate, ways to protect the other areas from HW attacks are necessary. We demonstrated that self-assembled monolayers (SAMs) of a fluorinated phosphonic acid (FPA, CF3(CF2)13(CH2)2P(=O)(OH)2) derivatized on the native oxide of an Al film protected the underneath metal substrate from HW attack. The intact wettability and surface morphology of FPA-derivatized Al subjected to HW treatment were examined using contact angle measurement, and scanning electron microscopy and atomic force microscopy, respectively. Moreover, the surface and interface chemistry of FPA-derivatized Al before and after HW treatment were investigated by time-of-flight secondary ion mass spectrometry (ToF-SIMS), verifying that the FPA SAMs were intact upon HW treatment. The ToF-SIMS results therefore explained, on the molecular level, why HW treatment did not affect the underneath Al at all. FPA derivatization is thus expected to be developed as a patterning method for the formation of hydrophilic and hydrophobic areas on Al when combined with HW treatment.
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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".