Multicomponent Hollow Tubules Formed Using Phytosterol and γ-Oryzanol-Based Compounds: An Understanding of Their Molecular Embrace
Bibliographic record
Abstract
The formation kinetics of self-assembling tubules composed of phytosterol:gamma-oryzanol mixtures were investigated at the Canadian Light Source on the mid-IR beamline using synchrotron radiation and Fourier transform infrared spectroscopy (FT-IR). The Avrami model was fitted to the changing hydrogen bonding density occurring at 3450 cm(-1). The nucleation process was found to be highly dependent on the molecular structure of the phytosterol. The nucleation event for cholesterol:gamma-oryzanol was determined to be sporadic whereas 5alpha-cholestan-3beta-ol:gamma-oryzanol and beta-sitosterol:gamma-oryzanol underwent instantaneous nucleation. One-dimensional growth occurred for each phytosterol:gamma-oryzanol mixture and involved the evolution of highly specific intermolecular hydrogen bonds. More detailed studies on the cholesterol:gamma-oryzanol system indicated that the nucleation activation energy, determined from multiple rate constants, obtained using the Avrami model, was at a minimum when the two compounds were at a 1:1 weight ratio. This resulted in drastic differences to the microscopic structures and affected the macroscopic properties such as turbidity. The formation of the phytosterol:gamma-oryzanol complex was due to intermolecular hydrogen bonding, which was in agreement with the infrared spectroscopic evidence.
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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".