Melanin granules extracted from Sepia ink: a nanoscale study of charge carrier transport
Bibliographic record
Abstract
Abstract Eumelanin, the brown-black member of the melanin family of biopigments, has emerged as a promising material for sustainable organic electronics. Sepia eumelanin develops hierarchically from (5, 6)-dihydroxyindole (DHI) and (5, 6)-dihydroxyindole-2-carboxylic acid (DHICA) monomers, and its structure is made up of granules with typical size in the 100–300 nm range. Literature reports that Sepia eumelanin (from now on indicated as Sepia melanin), derived from the ink sac of cuttlefish, exhibits predominant electronic transport in dry state and mixed ionic–electronic transport in its hydrated state when studied at millimetric or micrometric distance ranges. To explore the upper limit of the conductivity of Sepia melanin and unlock its full technological potential, we investigated its electrical response at the nanoscale where the influence of granule boundaries is expected to be minimal. Using electrodes patterned at the nanoscale by e-beam lithography, we run current–voltage, current–time and electrochemical impedance spectroscopy measurements; we observed predominant electronic transport mechanisms in Sepia melanin, with conductivities that increase as the interelectrode distance decreases. Temperature-resolved experiments permitted us to deduce the transport activation energy. Our work highlights the importance of exploring the electrical response of natural materials across varying distance scales to exploit their full potential for sustainable organic electronics.
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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".