Cellulose Hollow Annular Nanoparticles Prepared from High-Intensity Ultrasonic Treatment
Bibliographic record
Abstract
Cellulose nanomaterials, such as cellulose nanocrystals (CNCs), have received enormous attention in various material research fields due to their unique properties and green/sustainable nature, among other qualities. Herein, we report hollow-type annular cellulose nanocrystals (HTA-CNCs), which are generated by following a high-intensity ultrasonic treatment. The advanced aberration-corrected transmission electron microscopy results reveal that HTA-CNCs exhibit ring structures with a typical diameter of 10.0-30.0 nm, a width of 3.0-4.0 nm, and a thickness of 2.0-5.0 nm, similar to those of elementary crystallites. The X-ray diffraction measurements show that the as-prepared HTA-CNCs maintain the cellulose I structure. The changes in structure and hydrogen-bonding characteristics of HTA-CNCs are further determined based on the FT-IR results after deconvolution fitting, showing that three types of hydrogen bonds decrease and the content of free OH increases in HTA-CNCs compared with those in the original CNCs. Furthermore, molecular dynamics simulation is carried out to support the experimental study. The formation of HTA-CNCs might be attributed to the structural change and entropy increase. The hollow-type annular CNCs may have broad value-added applications as cellulose nanomaterials in different fields.
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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".