Light Management in Organic Photovoltaics Processed in Ambient Conditions Using ZnO Nanowire and Antireflection Layer with Nanocone Array
Bibliographic record
Abstract
Low carrier mobility and lifetime in semiconductor polymers are some of the main challenges facing the field of organic photovoltaics (OPV) in the quest for efficient devices with high current density. Finding novel strategies such as device structure engineering is a key pathway toward addressing this issue. In this work, the light absorption and carrier collection of OPV devices are improved by employment of ZnO nanowire (NW) arrays with an optimum NW length (50 nm) and antireflection (AR) film with nanocone structure. The optical characterization results show that ZnO NW increases the transmittance of the electron transporting layer as well as the absorption of the polymer blend. Moreover, the as-deposited polymer blend on the ZnO NW array shows better charge transfer as compared to the planar sample. By employing PC70BM:PV2000 as a promising air-stable active-layer, power conversion efficiencies of 9.8% and 10.1% are achieved for NW devices without and with an AR film, indicating 22.5% and 26.2% enhancement in PCE as compared to that of planar device. Moreover, it is shown that the AR film enhances the water-repellent ability of the OPV device.
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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".