A Bottom-up Route to a Chemically End-to-End Assembly of Nanocellulose Fibers
Bibliographic record
Abstract
In this work, we take advantage of the rod-like structure of electrosterically stabilized nanocrystalline cellulose (ENCC, with a width of about 7 nm and a length of about 130 nm), which has dicarboxylated cellulose (DCC) chains protruding from both ends, providing electrosterical stability for ENCC particles, to chemically end-to-end assemble these particles into nanocellulose fibers. ENCC with shorter DCC chains can be obtained by a mild hydrolysis of ENCC with HCl, and subsequently the hydrolyzed ENCC (HENCC, with a width of about 6 nm and a length of about 120 nm) is suitable to be assembled into high aspect ratio nanofibers by chemically cross-linking HENCC from one end to another. Two sets of HENCC were prepared by carbodiimide-mediated formation of an alkyne and an azide derivative, respectively. Cross-linking these two sets of HENCC was performed by a click reaction. HENCCs were also end-to-end cross-linked by a bioconjugation reaction, with a diamine. From atomic force microscopy (AFM) images, about ten HENCC nanoparticles were cross-linked and formed high aspect ratio nanofibers with a width of about 6 nm and a length of more than 1 μm.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".