Application of Novel Dopamine-Polypyrrole Nanofibers for Electrically Conductive Adhesives
Bibliographic record
Abstract
ABSTRACT Electrically conductive adhesives (ECAs) offer many advantages such as lower processing temperature, simpler processing steps and finer-pitch interconnection in comparison with the traditional soldering technology.However, due to the poor metallurgical connections of silver flakes in the ECA network, it requires a large amount of silver or other metallic fillers to achieve high conductivity, which is not cost-effective for industrial applications. In this work, we present the utilization of a novel type of dopamine-functionalized polypyrrole (DA-PPy) nanofibers to develop a hybrid nanocomposite adhesive with lower metallic contents. Compared to conventional ECAs, the hybrid ECAs displayed significantly higher electrical conductivity. In particular, the introduction of 3 wt% nanofibers into a conventional ECA with 57.9 wt% silver flakes resulted in a significant electrical conductivity enhancement from 110 S/cm to 2400 S/cm, which was comparable to that of ECA filled with 80 wt% silver flakes.
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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) | 0.001 | 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 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".