Self-assembly of 5,6-dihydroxyindole-2-carboxylic acid: polymorphism of a eumelanin building block on Au(111)
Bibliographic record
Abstract
Investigating two-dimensional (2D) self-assembled structures of biological monomers governed by intermolecular interactions is a prerequisite to understand the self-assembly of more complex biomolecular systems. 5,6-Dihydroxyindole carboxylic acid (DHICA) is one of the building blocks of eumelanin - an irregular heteropolymer and the most common form of melanin which has potential applications in organic electronics and bioelectronics. By means of scanning tunneling microscopy, density functional theory and Monte Carlo calculations, we investigate DHICA molecular configurations and interactions underlying the multiple 2D patterns formed on Au(111). While DHICA self-assembled molecular networks (SAMNs) are dominated by the hydrogen bonding of carboxylic acid dimers, a variety of 2D architectures are formed due to the multiple weak interactions of the catechol group. The hydroxyl group also allows for redox reactions, caused by oxidation via O2 exposure, resulting in molecular rearrangement. The susceptibility of the molecules to oxidation is affected by their SAMNs architectures, giving insights on the reactivity of indoles as well as highlighting non-covalent assembly as an approach to guide selective oxidation reactions.
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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".