Elucidation of the structure of poly(γ-benzyl-l-glutamate) nanofibers and gel networks in a helicogenic solvent
Bibliographic record
Abstract
The synthesis, characterization, self-assembly, and gel formation of poly(γ-benzyl-l-glutamate) (PBLG) in a molecular weight range from ca. 7,000-100,000 g/mol and with narrow molecular weight distribution are described. The PBLG is synthesized by the nickel-mediated ring-opening polymerization and is characterized by size-exclusion chromatography coupled with multiple-angle laser light scattering, NMR, and Fourier transform infrared spectroscopy. The self-assembly and thermoreversible gel formation in the helicogenic solvent toluene is investigated by transmission electron microscopy, atomic force microscopy, small-angle X-ray scattering, and synchrotron powder X-ray diffraction. At concentrations significantly below the minimum gelation concentration, spherical aggregates are observed. At higher concentrations, gels are formed, which show a 3D network structure composed of nanofibers. The proposed self-assembly mechanism is based on a distorted hexagonal packing of PBLG helices parallel to the axis of the nanofiber. The gel network forms due to branching and rejoining of bundles of PBLG nanofibers. The network exhibits uniform domains with a length of 200 ± 42 nm composed of densely packed PBLG helices.
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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) | 0.000 | 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".