React‐on‐Demand (RoD) Fabrication of Highly Conductive Metal–Polymer Hybrid Structure for Flexible Electronics via One‐Step Direct Writing or Printing
Bibliographic record
Abstract
Abstract As a fast prototyping technique, direct writing of flexible electronics is gaining popularity for its low‐cost, simplicity, ultrahigh portability, and ease of use. However, the latest handwritten circuits reported either have relative low conductivity or require additional post‐treatment, keeping this emerging technology away from end‐users. Here, a one‐step react‐on‐demand (RoD) method for fabricating flexible circuits with ultralow sheet resistance, enhanced safety, and durability is proposed. With the special functionalized substrate, a real‐time 3D synthesis of silver plates in microscale is triggered on‐demand right beneath the tip in the water‐swelled polyvinyl alcohol (PVA) coating, forming a 3D metal–polymer hybrid structure of ≈7 µm with one single stroke. The as‐fabricated silver traces show an enhanced durability and ultralow sheet resistance down to 4 mΩ sq−1 which is by far the lowest sheet resistance reported in literatures achieved by direct writing. Meanwhile, PVA seal small particles inside the film, adding additional safety to this technology. Since neither nanomaterials nor a harsh fabrication environment are required, the proposed method remains low cost, user friendly, and accessible to end users. With little effort, the RoD approach can be extended to various printing systems, offering a particle‐free, sintering‐free solution for high‐resolution, high‐speed production of flexible electronics.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".