Chitosan and Whey Protein Bio-Inks for 3D and 4D Printing Applications with Particular Focus on Food Industry
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
The application of chitosan (CS) and whey protein (WP) alone or in combination in 3D/4D printing has been well considered in previous studies. Although several excellent reviews on additive manufacturing discussed the properties and biomedical applications of CS and WP, there is a lack of a systemic review about CS and WP bio-inks for 3D/4D printing applications. Easily modified bio-ink with optimal printability is a key for additive manufacturing. CS, WP, and WP-CS complex hydrogel possess great potential in making bio-ink that can be broadly used for future 3D/4D printing, because CS is a functional polysaccharide with good biodegradability, biocompatibility, non-immunogenicity, and non-carcinogenicity, while CS-WP complex hydrogel has better printability and drug-delivery effectivity than WP hydrogel. The review summarizes the current advances of bio-ink preparation employing CS and/or WP to satisfy the requirements of 3D/4D printing and post-treatment of materials. The applications of CS/WP bio-ink mainly focus on 3D food printing with a few applications in cosmetics. The review also highlights the trends of CS/WP bio-inks as potential candidates in 4D printing. Some promising strategies for developing novel bio-inks based on CS and/or WP are introduced, aiming to provide new insights into the value-added development and commercial CS and WP utilization.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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