Optical Printing of Conductive Silver on Ultrasmooth Nanocellulose Paper for Flexible Electronics
Bibliographic record
Abstract
The nanofibrillated cellulose paper (nanocellulose paper or nanopaper), which is flexible, transparent, ultrasmooth, and biodegradable, has emerged as a new substrate material for the next generation of paper‐based flexible electronics. Herein a visible light‐induced printing technique for depositing highly conductive silver (Ag) patterns on nanopaper is reported. The optical Ag printing process is simple to implement at room temperature and only requires nontoxic, low‐cost aqueous chemical solutions and an inexpensive light projection setup. The abundant carboxyl groups on the nanopaper enable efficient absorption of Ag+ ions on the nanopaper surface for light‐induced reduction of Ag+ into a thin film of densely packed silver nanoparticles (AgNPs). Chemical annealing of the deposited AgNPs further enhances the conductivity of the printed Ag patterns. The mechanical and electrical properties of the printed Ag patterns on nanopaper are characterized, and the application of the optical Ag printing technique fabricating the nanopaper‐based flexible circuits and electrochemical biosensors is also demonstrated. The optical printing technique will enable new designs and applications of nanopaper‐based 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 | 0.000 | 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 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".