Insight into Morphology Change of Chitin Microspheres using Tertiary Butyl Alcohol/H<sub>2</sub>O Binary System Freeze‐Drying Method
Bibliographic record
Abstract
Abstract The morphology of materials usually plays a significant role in their applications; the mechanical properties of the materials and characteristics such as specific surface area, surface energy, adsorbability, and wettability are dependent on the morphology. This study is focused on studying the effects of different tertiary butyl alcohol (TBA) aqueous solutions on the freeze‐dried morphologies of chitin microspheres (CMs). By constructing a TBA/H2O phase diagram, the underlying mechanisms of morphology change are explored. It is found that by freeze drying the CMs with 20 and 100 wt% TBA, a fine nanofiber weaved pore structure can be obtained. Away from these two ratios, the nanofibers are oppressed by the large crystals formed during the precool process or bind together due to the existence of water in the secondary drying stage, poor morphology and pore characteristics appearing. Moreover, the 20 wt% TBA freeze‐drying route is conducive to split the CMs and other polysaccharide (PS) microspheres. The split method is also helpful for exploring the internal structure of the microspheres. Therefore, this study makes it possible to simplify the morphology control of CMs, which helps in the characterization of porous PS‐based microspheres.
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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".