Controlling C<inf>60</inf> fullerene nanocolumn morphology for organic photovoltaic applications
Bibliographic record
Abstract
We investigate nanostructuring approaches in inverted organic photovoltaic cells to increase exciton harvesting. Conventional bulk heterojunctions (BHJs) have disordered morphologies which increase exciton dissociation. However, in BHJs free charge carriers can be trapped in pocket domains and dead ends. Using glancing angle deposition (GLAD) we fabricate vertical nanocolumns to increase heterointerface area while improving charge transport. Nanostructured C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> columns have been fabricated using GLAD on transparent indium tin oxide coated glass substrates. GLAD can control intercolumn spacing, column shape, film thickness and other properties. When depositing at constant substrate rotation vertical C <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> columns were achieved. Intercolumn spacing was controlled by the deposition angle between substrate and source. To further approach the ideal nanostructure for organic photovoltaic cells (OPVs), the column diameter was controlled through a substrate motion algorithm called phi-sweep. The engineered GLAD nanomorphology yielded a fivefold increase in short-circuit current when compared to planar devices and a two-fold increase in short-circuit current when compared with bulk heterojunctions.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".