Composites of Shellac and Silver Nanowires as Flexible, Biobased, and Corrosion‐Resistant Transparent Conductive Electrodes
Bibliographic record
Abstract
Abstract Silver nanowires (AgNWs) are a promising material to replace indium tin oxide as transparent conductive electrodes (TCEs) in next‐generation flexible optoelectronics. AgNWs are more environmental friendly than indium tin oxide, and offer solution processability, high conductivity, and high optical transparency. Embedding AgNWs at the surface of a polymer matrix creates a planar, conductive surface that is ideal for use in thin‐film devices. However, a barrier to practical use is corrosionin the ambient environment, which damages the AgNW network and reduces the workable life span. This study presents the use of shellac, an eco‐friendly natural biopolymer, as a planarizing and protective matrix for AgNWs. Shellac has a long history as a coating due to its excellent film‐forming ability and barrier properties, yet it has been largely unexplored in electronics. Here, the first shellac‐based TCE comprising a AgNW network embedded at the surface of a shellac matrix is reported. Shellac‐AgNW TCEs provide high conductivity and optical transparency, as well as mechanical stability under tensile strain. They also effectively function as TCEs in light‐emitting devices. Furthermore, the barrier properties of shellac protect AgNWs from corrosion in humid air and corrosive acid vapors. These results position shellac as a sustainable alternative to persistent synthetic polymers, in flexible electronics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".