Molybdenum-Oxysulfide-Functionalized MgAl-Layered Double Hydroxides─A Sorbent for Selenium Oxoanions
Bibliographic record
Abstract
Effective removal of chemically toxic selenium oxoanions at high-capacity and trace levels from contaminated water remains a challenge in current scientific pursuits. Here, we report the functionalization of the MgAl layered double hydroxide with molybdenum-oxysulfide (MoO 2 S 2 ) anion, referred to as LDH-MoO 2 S 2, and its potential to sequester Se VI O 4 2– and Se IV O 3 2– from aqueous solution. LDH-MoO 2 S 2 nanosheets were synthesized by an ion exchange method in solution. Synchrotron X-ray pair distribution function (PDF) and extended X-ray absorption fine structure (EXAFS) revealed an unexpected transformation of the MoO 2 S 2 2– to Mo 2 O 2 S 6 2– like species during the intercalation process. LDH-MoO 2 S 2 is remarkably efficient in removing SeO 4 2– and SeO 3 2– ions from the ppm to trace level (≤10 ppb), with distribution constant ( K d ) ranging from 10 4 to 10 5 mL/g. This material showed exceptionally high sorption capacities of 237 and 358 mg/g for SeO 4 2– and SeO 3 2–, respectively. Furthermore, LDH-MoO 2 S 2 demonstrates substantial affinity and efficiency to remove SeO 3 2– /SeO 4 2– even in the presence of competitive ions from contaminated water. Hence, the removal of selenium (VI/IV) oxoanions collectively occurs through reductive precipitation and ion exchange mechanisms. This work provides significant insights into the chemical structure of the MoO 2 S 2 anion into LDH and emphasizes its exceptional potential for high-capacity selenium removal and positioning it as a premier sorbent for selenium oxoanions.
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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) | 0.000 | 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) | 0.001 | 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".