Interactions of Different Redox States of Phenyl-Capped Aniline Tetramers with Iron Oxide Surfaces and Consequences for Corrosion Inhibition
Bibliographic record
Abstract
The phenyl capped aniline tetramer (PCAT) is known for its redox properties and is being studied for its ability to inhibit corrosion of iron and steel in addition to being of interest for sensors and molecular electronics. Here we investigate the interactions, orientation and corrosion inhibition ability of all three oxidation states of the free base form of PCAT with iron oxide surfaces. Raman spectroscopy demonstrates interconversion of these molecules to one another due to charge transfer to the surface. Polarized mid-IR spectroscopy and atomic force microscopy were used to elucidate the molecular orientations on the surface. Electrochemical impedance spectroscopy shows the corrosion resistance of fully reduced PCAT coatings on low carbon steel to be higher than that for half-oxidized and fully oxidized PCAT coatings. A weight loss test, laser line measurements and Raman spectroscopy reveal that even though half-oxidized PCAT initially shows a lower corrosion resistance due to transformation into the fully oxidized form, with time it transforms back into the half-oxidized form and protects the surface. Fully oxidized PCAT molecules show opposite behavior, causing the degradation of the surface over time. We thus attained a deeper insight into the interplay of the different oxidation states for corrosion control.
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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".