Fluorinated Thiophene-Based Synthons: Polymerization of 1,4-Dialkoxybenzene and Fluorinated Dithieno-2,1,3-benzothiadiazole by Direct Heteroarylation
Bibliographic record
Abstract
The incorporation of fluorine atoms along the conjugated polymer backbone is an effective strategy to tune the electro-optical properties of donor–acceptor based copolymers. We report here an efficient way to synthesize and purify new mono-fluorinated thiophene derivatives for the synthesis of fluorinated dithienobenzothiadiazole (DTBT) comonomers. It was observed that the reactivity and regioselectivity of the direct (hetero)arylation polymerization (DHAP) were modified upon the amount and the positioning of the fluorine atoms on the DTBT moiety. Indeed, the polymerization time went from 66 h (for non-fluorinated DTBT, M1 ) to only 11 min (for tetra-fluorinated DTBT, M2 ). In addition to enhanced reactivity, the degree of fluorination of the flanking thiophene of the DTBT moiety also modulates the electro-optical properties, lowering both the bandgap and stabilizing the ionization energy level. Indeed, P1 (with non-fluorinated flanking thiophene) has a bandgap of 1.73 eV and an ionization energy (IE) of 4.96 eV while a bandgap of 1.65 eV and a IE of 5.20 eV were obtained for P4 (with the fluorine atom facing the 1,4-alkoxyphenylene moiety).
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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".