Adsorption of (Poly)vanadate onto Ferrihydrite and Hematite: An <i>In Situ</i> ATR–FTIR Study
Bibliographic record
Abstract
Vanadium (V) geochemistry offers insight into Earth’s global biogeochemical cycles over geologic time. Additionally, increasing anthropogenic release of this redox-sensitive metal has led to elevated V concentrations in soils, sediments, and waters. Although Fe (oxyhydr)oxides are important sinks for aqueous V in soils and sediments, our understanding of adsorption mechanisms is currently limited to mononuclear species (i.e., H x VO 4 (3– x )– ). Here, we use in situ attenuated total reflectance–Fourier transform infrared spectroscopy to examine the sorption mechanisms for (poly)vanadate attenuation by ferrihydrite and hematite from pH 3 to 6. Adsorption isotherms illustrate the low affinity of polyvanadate species for ferrihydrite surfaces compared to that for hematite. Mononuclear V species (i.e., [H x VO 4 ] (3– x )– and VO 2 + ) were present at all experimental conditions. At low surface loadings and pH values of 5 and 6, H 2 VO 4 – adsorption onto ferrihydrite and hematite surfaces results in the formation of inner-sphere complexes. At [V] T above 250 μM, adsorbed polynuclear V species in this study include H 2 V 2 O 7 2– and V 4 O 12 4–, whereas, HV 10 O 28 6–, H 3 V 10 O 28 5–, and NaHV 10 O 28 4– are the predominant adsorbed species at pH values of 3 and 4 and elevated [V] T ’s. Surface polymers were identified on hematite at all experimental pH values, whereas polymeric adsorption onto ferrihydrite was limited to pH values of 3 and 4. Results also suggest that hematite is a more suitable substrate for polymer complexation than ferrihydrite. Our results demonstrate the pH- and concentration-dependent removal of (poly)vanadate species by Fe(III) (oxyhydr)oxides, which has implications for understanding V mobility, behavior, and fate in the environment.
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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".