Rod- and sphere-shaped cellulose nanocrystals (CNCs) type-II derived from <i>Asclepias syriaca</i> stem residues: composition, morphology, and thermal properties
Bibliographic record
Abstract
Cellulose nanocrystals or nanoparticles (CNCs) have drawn a lot of attention due to their abundance, biocompatibility, renewability and their excellent mechanical properties paving the way to innovative and sustainable applications. In the present work, the stem residues of Asclepias syriaca L., better known as milkweed and generally regarded as a weed, was used for the first time to extract CNCs with a crystalline structure type-II (CNC-II). Structural, thermal, morphological, and mechanical properties of extracted CNC-II were characterized by means of Fourier transform infrared, X-ray diffraction, scanning electron microscopy, dynamic light scattering, thermogravimetric analysis, and atomic force microscopy (AFM). Asclepias syriaca stem fibers revealed quite similar cellulose content compared with other milkweed species, and stable suspensions made of nanosphere- and nanorod-shape CNC-II were successfully extracted from raw milkweed fibers. In addition, after conversion from cellulose-I to cellulose-II by mercerization, milkweed cellulose-II exhibited higher thermal resistance compared with cellulose-I with degradation temperatures at 328 °C and 310 °C, respectively. Finally, the transversal elastic modulus of individuals CNC-II, as measured by AFM, was found to be in the range of 3.5–27 GPa, which is consistent with reported values for CNC-I or -II in the literature.
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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".