Adsorption of Phosphate Dianions by Hybrid Inorganic–Biopolymer Polyelectrolyte Complexes: Experimental and Computational Studies
Bibliographic record
Abstract
Hybrid inorganic–biopolymer polyelectrolyte complexes (HIB-PECs) consisting of chitosan, alginate, and an aluminum-based cross-linking agent were prepared at variable chitosan and alginate mass ratios. IR spectral results indicate that chitosan and alginate undergo PEC formation according to the spectral shifts of the −NH 3 + and COO – groups for chitosan and alginate, respectively. Evidence of Al–O–R (where R = alkyl group) and Al–OH bonds are supported by XPS, PXRD, and NMR spectra. Computational studies provide additional support that aluminum undergoes cross-linking with the carboxylate groups of alginate of the PEC. SEM and pH pzc results provide support of variable product morphology and surface charge for the HIB-PECs over the pristine biopolymers. Equilibrium adsorption studies of the hydrogen phosphate dianion at pH 8.5 reveal that chitosan with alginate at a 1:1 (w/w) ratio afforded an HIB-PEC with an optimal adsorption capacity ( Q m = 152 ± 44 mg/g). The Sips isotherm model accounts for the adsorption data, where the uptake parameters indicate a heterogeneous adsorbent surface with physisorption uptake properties. Increased temperatures led to reduced uptake capacity of the HIB-PECs, where competitor anion species had no apparent effects. Computational studies revealed that the −OH sites of the aluminum complex in the HIB-PECs serve as the preferred active site for phosphate anion uptake. Regeneration of the HIB-PECs over four adsorption–desorption cycles did not show any attenuation of the adsorption capacity. This study presents a first example of the application of HIB-PECs for the adsorption of phosphate species in aqueous solution, where the computational and experimental studies provided complementary support that the −OH sites of the aluminum complex serve as the key active adsorption site for the phosphate anion species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".