Stability assessment of <scp>PTB7</scp>‐Th and a quinoxaline‐based polymer in both organic thin film transistors and in organic photovoltaic devices
Bibliographic record
Abstract
Abstract Herein, we perform a stability assessment of two conjugated polymers that are conventionally used as electron donor polymers in the active layer of organic photovoltaic (OPV). More specifically, the impact of thermal annealing, a post‐treatment commonly applied in the OPV community, is evaluated in terms of device performance and stability. The two polymers are PTB7‐Th and QX1, and they are respectively blended with a non‐fullerene electron acceptor, herein a derivative of N‐annulated perylene diimide, that is, tPDI2N‐EH. These blends are targeted for their relatively high power conversion efficiency in outdoor conditions, but also for their potential as efficient active layer in low‐intensity (indoor) conditions—while these blends have been reported, no study on the impact of thermal annealing on their stability has been performed yet. The performance stability of these devices, tracked via the open circuit voltage, the short‐circuit current, the fill factor, and the power conversion efficiency metrics, were evaluated each day for 2 weeks and correlated to an evaluation of the microstructure of the active layer, evaluated using atomic force microscopy and UV–visible absorbance spectroscopy. Finally, transistors were prepared using only the two electron donor polymers, PTB7‐Th and QX1, to assess if some correlations could be made between the behaviour of the OPV devices and that of the electronic charge mobilities. Results contribute to identify which molecular structures and which post‐treatments are ideal to promote the stability of the active layers in the context of OPV devices.
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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 | 0.001 |
| 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".