Cover Picture: Influence of Polymer Electronics on Selective Dispersion of Single‐Walled Carbon Nanotubes (Chem. Eur. J. 41/2016)
Bibliographic record
Abstract
In the pursuit of next-generation polymers for the selective dispersion and purification of single-walled carbon nanotubes (SWNTs), understanding the key parameters dictating polymer selectivity is imperative. Simple modification of a poly(fluorene-co-pyridine) backbone, such that it is transformed from being electron-rich to -poor, has a significant impact on the electronic nature of the SWNTs dispersed. The unmodified copolymer bearing an electron-rich fluorene co-monomer preferentially forms stable colloids with sc-SWNTs, while the methylated copolymer bearing electron-withdrawing cationic charges produces dispersions that are more enriched with m-SWNTs. This work provides a clear indication that polymer electronics plays an important role. More information can be found in the Full Paper by A. Adronov et al. on page 14560 ff.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.160 | 0.056 |
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".