Synergizing MAPbI<sub>3–<i>x</i></sub>Cl<sub><i>x</i></sub>-Based Solar Cells with Columnar Mesogenic Interfacial Layers for Superior Efficiency
Bibliographic record
Abstract
Perovskite solar cells (PSCs) face several challenges, particularly the recombination of charge carriers at the interface between the perovskite material and the hole transport layer. This recombination is primarily attributed to poor charge transport and injection, which reduce the open-circuit voltage, efficiency, and stability of PSCs. In this study, we investigate the effect of incorporating a triphenylene-based columnar mesogen, 2,3,6,7,10,11-hexabutyloxytriphenylene (HAT4), as an interfacial layer between MAPbI 3– x Cl x and PEDOT:PSS to improve the performance of PSCs. The quasi-one-dimensional (1D) charge propagation of the columnar interfacial layer significantly improves the short-circuit current and open-circuit voltage of PSCs with an ITO/PEDOT:PSS/HAT4/MAPbI 3– x Cl x /PCBM/BCP/Ag configuration. This enhancement is attributed to the reduced recombination of the charge carriers at the interface. The best device achieved a maximum efficiency of 12.23% compared to 10.57% for the reference device without the columnar mesogen layer. Additionally, simulation results corroborate the experimental findings, revealing optimized intermolecular interactions and charge transfer between MAPbI 3– x Cl x and the columnar mesogens. These results highlight the potential of incorporating an interfacial columnar layer to improve the performance of the PSC. This approach can be used in state-of-the-art solar cell technology to enhance efficiency and wider viability close to commercialization.
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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".