A Route to Selective Arsenate Adsorption in Phosphate Solutions via Ternary Metal Biopolymer Composites
Bibliographic record
Abstract
With the increased need for improved adsorbents for efficient water treatment, sodium alginate (NaAlg) and chitosan (Chi) represent promising platform biopolymers for the preparation of biocomposite adsorbents for the effective removal of waterborne oxyanion (arsenate (Asi) and orthophosphate (Pi)) contaminants. The TMCs were characterized by spectroscopy (infrared (IR), SEM with an energy dispersive X-ray (SEM-EDX)), point-of-zero-charge (PZC) measurements, and dye adsorption by employing p-nitrophenol at variable pH. Based on dye adsorption results, the adsorbent surface area (SA) was 271 m2/g for Al-TMC, 286 m2/g for Fe-TMC, and 311 m2/g for Cu-TMC. This indicates the role of adsorbent pore structure and swelling in water. Further, the role of either aluminum (Al), copper (Cu), or iron (Fe) for the preparation of TMCs for the selective Asi removal in the presence of Pi as a competitor anion was evaluated. While Al, Fe, and Cu coordinate to the biopolymer framework at C=O sites, only Fe coordinates to –NH2 sites. While Al coordinated via Al-O and interfacial hydroxy groups, Cu showed the formation of Cu2(OH)3NO3 in contrast to Fe, which observed FeOOH formation. Adsorption of Asi was highest for Al-TMC (80 mg/g), followed by Fe-TMC (77 mg/g) and Cu-TMC (31 mg/g). Adsorption of Pi was highest for Al-TMC (93 mg/g), followed by Fe-TMC (66 mg/g) and Cu-TMC (17 mg/g). While Al-TMC showed the highest adsorption capacity overall, only Fe-TMC (followed by Cu-TMC) showed strong arsenate selectivity over orthophosphate. The selectivity toward Asi in presence of Pi was determined and the binary separation factor (αt/c) and the selectivity coefficient (βt) were calculated, where Cu-TMC (αt/c = 6.1; βt = 4.4) and Fe-TMC (αt/c = 8.3; βt = 5.0) exceeded Al-TMC (αt/c = 1.5; βt = 1.2). This work contributes to the field of oxyanion-selective adsorbents via judicious selection of the metal salt precursor during the synthetic design of the ternary biocomposite systems, as demonstrated herein.
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.
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 | 0.001 |
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".