Free-standing nanopaper electrode for all-printed super-flexible perovskite solar cells
Bibliographic record
Abstract
Abstract The development of all-printed, flexible solar cells of high efficiency and ultra-low weight will offer advancements for new market entrants. Herein, we report the design and fabrication of all-printed in ambient air, super-flexible perovskite solar cells with approaching 20% power conversion efficiency and extremely low weight of 5.1 g m-2 leading to an unprecedented power-to-weight ratio of 38,470 W Kg-1. This performance advance was achieved through the design of a highly transparent and conducting nanopaper used as a free-standing bottom electrode (FSBE). The FSBE consisted of cellulose nanocrystals grafted with semi-metallic super-reduced polyoxometalate clusters that enabled high conductivities up to 18 S cm-1 combined with transparency >96%. It also acted as a conformal barrier preventing performance loss upon heating at 95 oC under continuous illumination in inert environment; and strong resistance to decomposition when immersed in a mild citric acid water solution for 100 days, which we further exploit to demonstrate full device recyclability. The inherent flexibility of cellulose nanocrystals enabled remarkable flexibility of these cells under 2,000 repeated bending and folding cycles and mechanical strength upon extensive strain up to 20%. Notably, the nanopaper remained unaffected for strains up to 60%. These findings open the door for efficient and lightweight solar cells with a low environmental impact.
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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 | 0.001 | 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".