Grafting of Polycaprolactone on Oxidized Nanocelluloses by Click Chemistry
Bibliographic record
Abstract
The main objective of this work is the grafting of polycaprolactone diol (PCL) on the surface of oxidized nanocelluloses (ONC) in order to enhance the compatibility between the hydrophilic cellulose nanofibres and the hydrophobic polymer matrix. This grafting was successfully realized with a new strategy known as click chemistry. In this context, the oxidized nanocelluloses bearing alkyl groups (ONC-PR) were prepared by reacting amino groups of propargylamine (PR) with carboxyl groups of ONC. In parallel, PCL was converted into azido-polycaprolactone (PCL-N3) in two steps: (i) tosylation of polycaprolactone (PCL-OTs) and (ii) conversion of PCL-OTs into PCL-N3 by nucleophilic displacement using sodium azide. Finally, ONC-PR was reacted with PCL-N3 in heterogeneous conditions through click chemistry in order to prepare polycaprolactone grafted oxidized nanocellulose (ONC-g-PCL), which could be suitable for improving the interfacial adhesion in the composite materials. The grafted samples were characterized by transmission electron microscopy and by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and Carbon-13 nuclear magnetic resonance spectroscopy (13C-NMR) spectroscopic techniques.
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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".