Uptake of Methylene Blue from Aqueous Solution by Pectin–Chitosan Binary Composites
Bibliographic record
Abstract
To address the need to develop improved hybrid biopolymer composites, we report on the preparation of composites that contain chitosan and pectin biopolymers with tunable adsorption properties. Binary biopolymer composites were prepared at variable pectin–chitosan composition in a solvent directed synthesis, dimethyl sulfoxide (DMSO) versus water. The materials were characterized using complementary methods (infrared spectroscopy, thermal gravimetric analysis, pH at the point-of-zero charge, and dye-based adsorption isotherms). Pectin and chitosan composites prepared in DMSO yielded a covalent biopolymer framework (CBF), whereas a polyelectrolyte complex (PEC) was formed in water. The materials characterization provided support that cross-linking occurs between amine groups of chitosan and the –COOH groups of pectin. CBF-based composites had a greater uptake of methylene blue (MB) dye over the PEC-based composites. Composites prepared in DMSO were inferred to have secondary adsorption sites for enhanced MB uptake, as evidenced by a monolayer uptake capacity that exceeded the pectin–chitosan PECs by 1.5-fold. This work provides insight on the role of solvent-dependent cross-linking of pectin and chitosan biopolymers. Sonication-assisted reactions in DMSO favor CBFs, while cross-linking in water yields PECs. Herein, composites with tunable structures and variable physicochemical properties are demonstrated by their unique dye adsorption properties in aqueous media.
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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) | 0.000 | 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 | 0.001 |
| 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 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".