Controlled Synthesis of 3D Silver Fractal Flowers for High-Performance Conductive Adhesives
Bibliographic record
Abstract
Silver-based electrically conductive adhesives (ECAs) are widely used in the connection, conduction, and packaging of electronic components. However, commercial ECAs typically contain more than 90 wt % Ag fillers, creating an urgent demand for low-Ag-content alternatives that maintain excellent performance. To address this issue, Ag with 3D structures has significant low-content and structural advantages in efficiently constructing 3D conductive networks in the ECAs system. Herein, three types of Ag-based fractal flowers with 3D branched structures (Ag FW-I, Ag FW-II, and Ag FW-III) were successfully synthesized using a novel, facile, and efficient chemical reduction method. The Ag FW-II particles served as the primary conductive framework, while Ag FW-I and Ag FW-III acted as auxiliary fillers, bridging gaps and connecting isolated regions. When the Ag FW-I, Ag FW-II, and Ag FW-III contents were optimized to 17.5, 50, and 12.5 wt %, respectively, the resulting ternary ECAs can deliver the lowest bulk resistivity of 1.15 × 10 –4 Ω·cm and a high adhesion strength of 12.88 MPa. These Ag FWs-based ECAs demonstrate the best balance of conductivity and adhesion strength, offering a promising solution for the electronic packaging industry.
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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) | 0.001 | 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 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".