Multi‐Functional Silole Hole Transport Layer for Efficient and Stable Lead–Tin Perovskite and Tandem Solar Cells
Bibliographic record
Abstract
Despite high theoretical efficiencies and rapid improvements in performance, high-efficiency ≈1.2 eV mixed Sn-Pb perovskite solar cells (PSCs) generally rely on poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT: PSS) as the hole transport layer (HTL); a material that is considered to be a bottleneck for long-term stability due to its acidity and hygroscopic nature. Seeking to replace PEDOT: PSS with an alternative HTL with improved atmospheric and thermal stability, herein, a silole derivative (Silole-COOH) tuned with optimal electronic properties and efficient carrier transport by incorporating a carboxyl functional group is designed, which results in an optimal band alignment for hole extraction from Sn-Pb perovskites and robust air and thermal stability. Thin films composed of the Silole-COOH exhibit superior conductivity and carrier mobility compared to PEDOT: PSS, in addition to reduced nonradiative quasi-Fermi-level splitting losses at the HTL/perovskite interface and improved quality of Sn-Pb perovskite. Replacement of PEDOT: PSS with Silole-COOH leads to 23.2%-efficient single-junction Sn-Pb PSCs, 25.8%-efficient all-perovskite tandems, and long operating stability in ambient air.
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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".