Design of NiO<i><sub>x</sub></i>/Carbon Heterostructure Interlayer to Improve Hole Extraction Efficiency of Inverted Perovskite Solar Cells
Bibliographic record
Abstract
Abstract An efficient hole transport layer (HTL) with desirable charge separation and hole extraction efficiency is crucial for inverted perovskite solar cells. However, the interfacial trap recombination loss and mismatched band alignment limit the actual performance of device, especially the open‐circuit voltage (VOC). To address this issue, a unique NiOx/carbon heterostructure is designed as efficient anode interlayer for optimizing the interfacial charge transport dynamics between HTL and perovskite. Such a buffer interlayer can significantly contribute to the improved hole conductivity and hole extraction efficiency at HTL/perovskite interface. Moreover, the more favorable gradient energy level alignment can be formed to increase the interfacial electric field, inhibit the nonradiative recombination, and minimize the VOC loss. Therefore, the champion device achieves 19.51% efficiency with high VOC of 1.13 V, close to the highest power conversion efficiencies of MAPbI3 device. This work suggests that interface design can be an alternative approach to fabricate efficient inverted NiO‐based devices.
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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) | 0.000 | 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".