Interface Molecular Engineering for Laminated Monolithic Perovskite/Silicon Tandem Solar Cells with 80.4% Fill Factor
Bibliographic record
Abstract
Abstract A multipurpose interconnection layer based on poly(3,4‐ethylenedioxythiophene) doped with poly(styrene sulfonate) (PEDOT:PSS), and d‐sorbitol for monolithic perovskite/silicon tandem solar cells is introduced. The interconnection of independently processed silicon and perovskite subcells is a simple add‐on lamination step, alleviating common fabrication complexities of tandem devices. It is demonstrated experimentally and theoretically that PEDOT:PSS is an ideal building block for manipulating the mechanical and electrical functionality of the charge recombination layer by controlling the microstructure on the nano‐ and mesoscale. It is elucidated that the optimal functionality of the recombination layer relies on a gradient in the d‐sorbitol dopant distribution that modulates the orientation of PEDOT across the PEDOT:PSS film. Using this modified PEDOT:PSS composite, a monolithic two‐terminal perovskite/silicon tandem solar cell with a steady‐state efficiency of 21.0%, a fill factor of 80.4%, and negligible open circuit voltage losses compared to single‐junction devices is shown. The versatility of this approach is further validated by presenting a laminated two‐terminal monolithic perovskite/organic tandem solar cell with 11.7% power conversion efficiency. It is envisioned that this lamination concept can be applied for the pairing of multiple photovoltaic and other thin film technologies, creating a universal platform that facilitates mass production of tandem devices with high efficiency.
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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".