Using volatile additives to alter the morphology and performance of active layers in thin-film molecular photovoltaic devices incorporating bulk heterojunctions
Bibliographic record
Abstract
Thin-film photovoltaic devices composed of polymers or small molecules have an exciting future as sources of renewable energy because they can be made in large sizes on flexible surfaces by inexpensive techniques of fabrication. Significant progress in developing new molecular photovoltaic materials and device architectures has been achieved in the last decade. The identity of molecular components in active layers and their individual optoelectronic properties obviously help determine the properties of devices; in addition, however, the behavior of devices depends critically on the nature of the local organization of the components. Recent studies have shown that the morphology of active layers can be tuned by adjusting various parameters, including the solvent used to cast the layer, thermal annealing, and special processing additives. In this review, we summarize the effect of volatile additives on the nanoscale morphology of molecular blends, and we show how these effects can improve the performance of devices. Although we focus on the behavior of mixtures of the type used in current molecular thin-film photovoltaic devices, the subject of our review will interest researchers in all areas of science and technology requiring materials in which separate phases must form intimate long-lived intermixtures with defined structures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".