Low-Cost Inorganic Strontium Ferrite a Novel Hole Transporting Material for Efficient Perovskite Solar Cells
Bibliographic record
Abstract
Perovskite solar cells attract significant interest due to their high-power conversion efficiencies. The replacement of charge-transporting layers using inorganic materials is an effective approach for improving stability and performance, as these materials are low-cost, highly durable, and environmentally friendly. This work focuses on the inorganic hole and electron transport layers (HTL and ETL), strontium ferrite (SrFe2O4), and zinc oxide (ZnO), respectively, to enhance the efficiency of perovskite solar cells. Favorable band alignment and high charge-collection capability make these materials promising. Experimental and computational studies revealed that the power conversion efficiency of the fabricated device is 7.80% and 8.83%, respectively. Investigating electronic properties and interface charge transfer through density functional theory calculations further corroborated that SrFe2O4 is a good HTL candidate. Our numerical device modeling reveals the importance of optimizing the thickness (100 nm and 300 nm) of the HTL and perovskite layers and defect density (1016 cm−3) of the absorber to achieve better solar cell performance.
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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".