Marker pen writing of perovskite solar modules
Bibliographic record
Abstract
Solution-processed perovskite photovoltaics promise low-cost, lightweight, and wearable power sources. Processing techniques play a crucial role in this field. Here, we introduce a large-area, patternable, and cyclable film writing technique that utilizes marker pen as a fabrication tool. By adjusting ink concentration, pressure, writing speed, tip width, solvent engineering, and using fiber-capillary structure of marker pens, we demonstrate control over perovskite ink colloids, film thickness (from 200 to > 1000 nm) and area (from 1 to 100+ cm2) patterning on rigid and flexible substrates, as well as ambient writing of crystalline perovskite film. Marker pen written rigid and flexible carbon-electrode perovskite solar modules in mask- and laser-free manners achieve 16.3% and 14.5% power conversion efficiencies, respectively. This method offers an opportunity for rapid on-site fabrication of lightweight and deformable power sources on various substrates, including inflated elastic balloons and folded cellophane paper, and produces customizable irregular solar modules. Solution-processed perovskite photovoltaics hold promises for low-cost and lightweight power sources. Here, the authors utilize a marker pen as a fabrication tool to produce large-area, patternable, and cyclable film, and demonstrate flexible solar modules and power sources on flexible substrates.
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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) | 0.002 | 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".