Chemical Stabilization behind Cardamom Pickering Emulsion Using Nanocellulose
Bibliographic record
Abstract
Cardamom essential oil (EO) is a rare oil of high scientific and economic interest due to its biofunctionality. This work aims to stabilize the EO by Pickering emulsions with nanocellulose, in the form of nanocrystals (CNC) or nanofibers (CNF), and to investigate the stability and chemical and physical interactions involved in the process. The emulsions were characterized by droplet size, morphology, stability, surface charges, Fourier transform infrared spectroscopy, FT-Raman, nuclear magnetic resonance, and scanning electron microscopy. Stable emulsions were prepared with cellulose morphologies and CNCs resulted in a 34% creaming index, while CNFs do not show instability. Emulsions indicate a possible interaction between nanocellulose, α-terpinyl acetate, and 1,8-cineole active essential oil compounds, where α-terpinyl acetate would be inside the drop and 1,8-cineole is more available to interact with cellulose. The interaction intensity depended on the morphology, which might be due to the nanocellulose’s self-assembly around oil droplets and influence on oil availability and future application. This work provides a systematic picture of cardamomum derived essential oil Pickering emulsion containing nanocellulose stabilizers’ formation and stability, which can further be extended to other value-added oils and can be an alternative for the delivery of cardamom essential oil for biomedical, food, cosmetics, and other industries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".