Conductive Cellulose Composites with Low Percolation Threshold for 3D Printed Electronics
Bibliographic record
Abstract
Abstract We are reporting a 3D printable composite paste having strong thixotropic rheology. The composite has been designed and investigated with highly conductive silver nanowires. The optimized electrical percolation threshold from both simulation and experiment is shown from 0.7 vol. % of silver nanowires which is significantly lower than other composites using conductive nano-materials. Reliable conductivity of 1.19 × 102 S/cm has been achieved from the demonstrated 3D printable composite with 1.9 vol. % loading of silver nanowires. Utilizing the high conductivity of the printable composites, 3D printing of designed battery electrode pastes is demonstrated. Rheology study shows superior printability of the electrode pastes aided by the cellulose’s strong thixotropic rheology. The designed anode, electrolyte, and cathode pastes are sequentially printed to form a three-layered lithium battery for the demonstration of a charging profile. This study opens opportunities of 3D printable conductive materials to create printed electronics with the next generation additive manufacturing process.
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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) | 0.000 | 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) | 0.001 | 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".