Highly-stable silver nanobelts joined via diffusion-free attachment
Bibliographic record
Abstract
Silver nanobelts are demonstrated here to undergo inter-particle joining at relatively low temperatures of less than 180 °C. For surface-coated networks of nanobelts this joining reduced the network sheet resistance by 95%. The joining mechanism appears to be non-diffusional oriented attachment, caused by the thermal reactivation of the halted oriented attachment mechanism that occurred originally at room temperature during the rapid nanobelt synthesis. This self-assembly mechanism was explored by in situ electrical and calorimetric experiments, and supported by electron microscopy. Unlike pentagonal silver nanowires, silver nanobelts do not rely on diffusional instability to achieve workably low joining temperatures. The oriented attachment displayed by nanobelts represents a new approach to achieving valuable reductions in network resistance, disentangled from the instability and diffusion-driven failure by nanoparticle degradation displayed by competing silver nanoparticles.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".