Synergistic effect of carotenoid and silicone-based additives for photooxidatively stable organic solar cells with enhanced elasticity
Bibliographic record
Abstract
Photochemical and mechanical stability are critical in the production and application of organic solar cells. While these factors can individually be improved using different additives, there is no example of studies on the combined effects of such additive-assisted stabilization. In this study, the properties of PTB7:[70]PCBM organic solar cells are studied upon implementation of two additives: the carotenoid astaxanthin (AX) for photochemical stability and the silicone polydimethylsiloxane (PDMS) for improved mechanical properties. A newly designed additive, AXcPDMS, based on astaxanthin covalently bonded to PDMS was also examined. Lifetime tests, produced in ISOS-L-2 conditions, reveal an improvement in the accumulated power generation (APG) of 10% with pure AX, of 90% when AX is paired with PDMS, and of 140% when AXcPDMS is added in the active layer blend, as compared to the control devices. Singlet oxygen phosphorescence measurements are utilized to study the ability of AX and AXcPDMS to quench singlet oxygen and its precursors in the films. The data are consistent with the strong stabilization effect of the carotenoids. While AX and AXcPDMS are both efficient photochemical stabilizers, the improvement in device stability observed in the presence of AXcPDMS is likely due to a more favorable localization of the stabilizer within the blend. The mechanical properties of the active layers were investigated by tensile testing and cohesive fracture measurements, showing a joint improvement of the photooxidative stability and the mechanical properties, thus yielding organic solar cell devices that are promising for flexible photovoltaic applications.
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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) | 0.001 | 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 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".