Germafluorenes: New Heterocycles for Plastic Electronics
Bibliographic record
Abstract
The synthesis and characterization of new heterofluorene derivatives based on germanium are described. These germafluorene monomers have been polymerized with different aromatic comonomers. The resulting homopolymers and alternating copolymers have been characterized by size exclusion chromatography, thermal analyses (TGA and DSC), UV−vis−NIR absorption spectroscopy, X-ray diffraction, and cyclic voltammetry. These homopolymers and copolymers are air-stable and present bandgaps ranging from 3.0 to 1.6 eV. Some copolymers were tested in field-effect transistors (FETs) and bulk heterojunction photovoltaic cells (PCs). Best results in FETs were obtained with poly[2,7-(9,9-di- n -butylgermafluorene)- alt -3,6-bis(thiophen-5-yl)-2,5-dioctylpyrrolo[3,4-]pyrrole-1,4-dione], which shows a hole mobility up to 0.04 cm 2 (V·s) −1 with an I on / I off ratio of 1.0 × 10 6 . For photovoltaic applications, the best results were obtained with poly[2,7-(9,9-di- n -octylgermafluorene)- alt -5,5-(4′,7′-di-2-thienyl-2′,1′,3′-benzothiadiazole)] with a power conversion efficiency (PCE) of 2.8%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".