Correlating the Phase Behavior with the Device Performance in Binary Poly-3-hexylthiophene: Nonfullerene Acceptor Blend Using Optical Probes of the Microstructure
Bibliographic record
Abstract
The performance of photovoltaic devices based on blends of conjugated polymers with nonfullerene acceptors depends on the phase behavior and microstructure of the binary, which in turn depends on the chemical structures of the molecular components and the blend composition. We investigate the correlation between the molecular structure, composition, phase behavior, and device performance of a model system consisting of semicrystalline poly-3-hexylthiophene (P3HT) as the donor polymer and three nonfullerene acceptors, two of which (O-IDTBR/EH-IDTBR) have a planar core with different side chains and one (O-IDFBR) of which has a twisted core. We combine differential scanning calorimetry with optical measurements including UV–Vis spectroscopy, photoluminescence, spectroscopic ellipsometry, and Raman spectroscopy and photovoltaic device performance measurements, all at varying blend composition. For P3HT:IDTBR blends, the crystallinity of polymer and acceptor is preserved over a wide composition range and the blend displays a eutectic phase behavior, with the optimum solar cell composition lying close to the eutectic composition. For P3HT:IDFBR blends, increasing acceptor content disrupts the polymer crystallinity, and the optimum device composition appears to be limited by polymer connectivity rather than being linked to the eutectic composition. The optical probes allow us to probe both the crystalline and amorphous phases, clearly revealing the compositions at which component mixing disrupts crystallinity.
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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".