Fast Drying Boosted Performance Improvement of Low-Temperature Paintable Carbon-Based Perovskite Solar Cell
Bibliographic record
Abstract
Low-temperature paintable carbon-based perovskite solar cells have been acknowledged as a promising photovoltaic device. However, the organometal trihalide perovskite film is always degraded by the solvents in the carbon paste, resulting in a fairly low efficiency. Unfortunately, in a conventional drying process, the movements of solvent molecules from a carbon paste to atmosphere are greatly obstructed by the biscale size of carbon black and graphite, which creates an extremely long evaporation path and drying time. To solve the problem, we have developed a simple, highly efficient and scalable method, a gas pump method (GPM), to dry the carbon paste very quickly which demonstrates a 7 times drying rate compared with conventional drying. As a result, the perovskite films covered by the carbon electrode (CE) dried by the GPM keep a uniform and continuous surface morphology, and the champion solar cell reveals a conversion efficiency of 12.30% with the area of 0.1 cm 2 and an open circuit voltage of 1.03 V, which are much higher than those (i.e., 4.73% and 0.81 V, respectively) observed for the PSC without GPM. Furthermore, the long-time stability test shows that the solar cells with the as-prepared CE retain more than 90% of its initial power conversion efficiency after 720 h.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".