Electrical Conductive Adhesives Enhanced with High‐<scp>A</scp>spect‐<scp>R</scp>atio Silver Nanobelts
Bibliographic record
Abstract
The utilization of high‐aspect‐ratio silver nanobelts (NBs) is reported with the typical silver micro flakes to develop advanced electrical conductive adhesive (ECA) composite materials. Ag NBs (10–40 nm thick, 100–400 nm wide and 1–10 µm long) were synthesized by chemical reduction of silver nitride. The incorporation of a small amount of the Ag NBs (NBs to flakes weight‐ratio K = 0.03) into a conventional ECA with 60 wt% Ag micro flakes results in an electrical conductivity enhancement by 1300%. It is also found that adding a 2 wt% (K = 0.03) of the NBs into a conventional ECA with 80 wt% Ag flakes reduced the bulk resistivity to 3 × 10−5 Ω · cm for the hybrid ECAs, which is comparable to that of a typical eutectic solder, showing great potential as an alternative electrical interconnect materials.
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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) | 0.001 | 0.001 |
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".