A Spectroscopic Investigation of Halogen Bonding for the Adsorption Process of Grafted Chitosan With Fluorescein Versus Rose Bengal Dye Systems
Bibliographic record
Abstract
ABSTRACT Chitosan was modified by grafting of aniline via cross‐linking with urea and confirmed by spectroscopic (FT‐IR, 1 H‐NMR) and TGA results. Adsorption studies of chitosan and its grafted form were carried out in single‐component solutions of fluorescein (FL) and rose bengal (RB), along with their binary (FL+RB) mixtures. In single‐component dye solutions, grafted chitosan revealed enhanced uptake of FL and preferential uptake of RB. Dye adsorption selectivity employed a binary dye mixture (50:50 molar ratio), where nearly complete adsorption of RB, whereas FL remained in the aqueous phase. RB dye adsorption selectivity was accounted for by halogen bonding. The adsorption mechanism was investigated by 2D‐NOESY and fluorescence spectroscopy, which reveal the role of π–π interactions between the adsorbent and dyes. The role of halogen bonding between the amine, aniline rings, and carbonyl functional groups of the modified chitosan with RB was corroborated by XPS results. Halogen bonding was supported by 2D [ 1 H‐ 15 N] HMBC of glucosamine (as the chitosan monomer model) and Nʺ‐phenyl‐N‐β‐ d ‐glucopyranosyl urea (as the grafted chitosan monomer model), which was studied with and without RB, along with IR spectroscopy of RB supports the key role of halogen bonding in the adsorption mechanism.
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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 | 0.000 | 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) | 0.000 | 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 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".