Modification of Nanocrystalline Cellulose for Bioactive Loaded Films
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the use of petrochemical derived packaging, many problems such as browning and food spoilage still happen in food after harvesting. There is an increasing consumers concern for food shelf life to be extended as much as possible along with a big interest in green and bioactive materials, that could be used in direct contact with aliments. In order to reach public demand, biopolymers coming from natural sources such as plants or animals have been used to replace synthetic materials. Even though natural polymers are biodegradable, they do not reach regulations required with respect to mechanical properties in commercial applications. However, the mechanical properties can be improved when reinforced with nanoparticles. Several reinforcing nanoparticules such as clays, silica or silver have been used for industrial applications, but cellulose nanocrystals (CNCs) are a better choice for food industry due to their biodegradable and biocompatible nature as well as their outstanding potential in improving mechanical and barrier properties of nanocomposites. CNCs consist of anhydroglucopyranose units (AGU) linked together and several functional hydroxyl groups found on its surface. Modifications of the CNC surface chemistry can give to cellulose new functionalities that open the way to the development of new bioactive reinforcement in food packaging. The present review will be focused on covalent and non covalent modifications that can be achieved on surface CNC with the aim of adding functionalities to be applied for food industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it