Graphitization on Natural Biopolymer Shellac: Toward Substrate Independent Coatings and a Recyclable Flexible Heater
Bibliographic record
Abstract
Abstract Extraction of graphene and graphene derivatives from non‐toxic, biocompatible, eco‐friendly, and biodegradable resources with a one‐step production process is a challenge. This work is the first attempt at the one‐step graphenization of Shellac, a biopolymer derived from natural resources, achieved using direct laser patterning. Interestingly, the process highlights substrate independence by producing reduced graphene oxide (rGO) from multiple substrates, such as glass slides, Copper (Cu) adhesive tape, and overhead projector (OHP) plastic films. The produced rGO is fully characterized, and it is found that the sheet resistance is as low as 5.4., 24.65, and 8.4 Ω Sq−1. on the glass slide, OHP plastic sheet, and Cu adhesive, respectively. Moreover, developing various logos on resin‐coated ceramic tiles demonstrated the possibility of patterning desired conductive rGO patterns. Furthermore, a recyclable flexible rGO/Shellac heater is fabricated to validate its electrothermal performance (117.3 °C at 9.5 V) with foldable stability. The proposed one‐step substrate independent two‐material fabrication will revolutionize the process, potentially replacing conventional toxic routes of graphene production.
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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".