Electrical response and biodegradation of Sepia melanin-shellac films printed on paper
Bibliographic record
Abstract
Sepia melanin, a biopigment extracted from the ink sac of cuttlefish, is relevant to sustainable organic electronics. In this work, we flexographically print films from an ink of Sepia melanin including shellac as a bio-sourced binder on silver electrode-patterned paper. We examine the electrical response in high humidity and ambient conditions (here the electronic conductivity is as high as 10−4 S/cm). Additionally, we study the biodegradation of the printed films and their individual constituents based on their mineralization into CO2 under composting conditions. The printed films exhibit biodegradation levels of about 97 ± 25% in 85 d. We observe microorganism colonization on the printed film’s surface. The analysis of the microbial community on the compost reveals that bacterial species within the Acidimicrobiia class, specifically Actinomarinales order, are potentially responsible for the biodegradation of the printed film. Meanwhile, ecotoxicity tests conducted by germinating Lolium multiflorum and Tagetes erecta suggest that printed films have negligible phytotoxicity. Sepia melanin, a biopigment extracted from cuttlefish ink, shows promise for sustainable organic electronics. Here, printed films including Sepia melanin and shellac are studied for their compostability and electrical behavior, showing electrical conductivities of about 10−4 S/cm and biodegradability.
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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".