Rolling Silver Nanowire Electrodes: Simultaneously Addressing Adhesion, Roughness, and Conductivity
Bibliographic record
Abstract
Silver nanowire mesh electrodes represent a possible mass-manufacturable route toward transparent and flexible electrodes for plastic-based electronics such as organic photovoltaics (OPVs), organic light emitting diodes (OLEDs), and others. Here we describe a route that is based upon spray-coated silver nanowire meshes on polyethylene terephthalate (PET) sheets that are treated with a straightforward combination of heat and pressure to generate electrodes that have low sheet resistance, good optical transmission, that are topologically flat, and adhere well to the PET substrate. The silver nanowire meshes were prepared by spray-coating a solution of silver nanowires onto PET, in air at slightly elevated temperatures. The as-prepared silver nanowire electrodes are highly resistive due to the poor contact between the individual silver nanowires. Light pressure applied with a stainless steel rod, rolled over the as-sprayed silver nanowire meshes on PET with a speed of 10 cm s(-1) and a pressure of 50 psi, results in silver nanowire mesh arrays with sheet resistances of less than 20 Ω/□. Bending of these rolled nanowire meshes on PET with different radii of curvature, from 50 to 0.625 mm, showed no degradation of the conductivity of the electrodes, as shown by the constant sheet resistance before and after bending. Repeated bending (100 times) around a rod with a radius of curvature of 1 mm also showed no increase in the sheet resistance, demonstrating good adherence and no signs of delamination of the nanowire mesh array. The diffuse and direct transmittance of the silver nanowires (both rolled and as-sprayed) was measured for wavelengths from 350 to 1200 nm, and the diffuse transmission was similar to that of the PET substrate; the direct transmission decreases by about 7-8%. The silver nanowires were then incorporated into OPV devices with the following architecture: transparent electrode/PEDOT:PSS/P3HT:PC61BM/LiF/Al. While slightly lower in efficiency than the standard indium tin oxide substrate (ITO), the rolled silver nanowire electrodes had a very good device yield, showing that short circuits resulting from the silver nanowire electrodes can be successfully avoided by this rolling approach.
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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".