Organic solar cell materials and active layer designs—improvements with carbon nanotubes: a review
Bibliographic record
Abstract
Abstract Organic solar cells offer an opportunity to diversify renewable energy sources owing to their low technological cost. They are amenable to large surfaces and can easily be integrated into buildings. It is necessary, however, to improve their energy efficiency and durability for the development of a sustainable technology. In these devices, photovoltaic conversion is based on the separation of photogenerated charges at an interface between electron donor and acceptor materials, which imposes some constraints on the photoactive layer of the cells. In this paper, which includes some of our studies, we address optimization of the active layer: absorption and exciton dissociation steps, the open‐circuit voltage and the active layer morphology. A promising direction proposed to improve the active layer morphology and cell efficiency is the incorporation of highly anisotropic nanoparticles such as carbon nanotubes, which may facilitate charge transport to the electrodes. Dispersion and orientation of the nanotubes in the organic matrix are discussed and we suggest an ideal model polymer solar cell which will maximize performance of the cells by using carbon nanotubes in the active layer. Copyright © 2012 Society of Chemical Industry
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".