Regioselective Protection and Deprotection of Nanocellulose Molecular Design Architecture: Robust Platform for Multifunctional Applications
Bibliographic record
Abstract
Regioselectively substituted nanocellulose was synthesized by protecting the primary hydroxyl group. Herein, we took advantage of the different reactivities of primary and secondary hydroxyl groups to graft large capping structures. This study mainly focuses on regioselective installation of trityl protecting groups on nanocellulose chains. The elemental analysis and nuclear magnetic resonance spectroscopy of regioselectively substituted nanofibrillated cellulose (NFC) suggested that the trityl group was successfully grafted in the primary hydroxyl group with a degree of substitution of nearly 1. Hansen solubility parameters were employed, and the binary system composed of an ionic liquid and pyridine as a base was revealed to be the optimum condition for regioselective functionalization of nanocellulose. Interestingly, the dissolution of NFC in the ionic liquid and the subsequent deprotection process of NFC substrates hardly affected the crystalline structure of NFC (3.6% decrease in crystallinity). This method may provide endless possibilities for the design of advanced engineered nanomaterials with multiple functionalities. We envisage that this protection/deprotection approach may lead to a bright future for the fabrication of multifunctional devices based on nanocellulose.
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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) | 0.001 | 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".