Algal Polysaccharides-Based Hydrogels: Extraction, Synthesis, Characterization, and Applications
Bibliographic record
Abstract
Hydrogels are three-dimensional crosslinked hydrophilic polymer networks with great potential in drug delivery, tissue engineering, wound dressing, agrochemicals application, food packaging, and cosmetics. However, conventional synthetic polymer hydrogels may be hazardous and have poor biocompatibility and biodegradability. Algal polysaccharides are abundant natural products with biocompatible and biodegradable properties. Polysaccharides and their derivatives also possess unique features such as physicochemical properties, hydrophilicity, mechanical strength, and tunable functionality. As such, algal polysaccharides have been widely exploited as building blocks in the fabrication of polysaccharide-based hydrogels through physical and/or chemical crosslinking. In this review, we discuss the extraction and characterization of polysaccharides derived from algae. This review focuses on recent advances in synthesis and applications of algal polysaccharides-based hydrogels. Additionally, we discuss the techno-economic analyses of chitosan and acrylic acid-based hydrogels, drawing attention to the importance of such analyses for hydrogels. Finally, the future prospects of algal polysaccharides-based hydrogels are outlined.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".