EXAFS study on arsenite(V) adsorption onto goethite and hematite
Bibliographic record
Abstract
BackgroundArsenic (As) is one of the most toxic pollutants in the environment. Its adsorption on the surface of iron oxyhydr (oxides) is an important factor affecting its migration and transformation behavior. Goethite and hematite are ubiquitous in soil, groundwater and aquatic sediments. They all have the characteristics of small particle size, large specific surface area, and many active groups, thus can be used as adsorbents for As.PurposeThis study aims to investigate the behaviors of As(V) adsorbed on these two minerals, and determine its complex structures by extended X-ray absorption fine structure spectroscopy (EXAFS).MethodsFirst of all, adsorbents made from goethite and hematite were prepared for experimental measurement of As adsorption at different pH values and Fe/As molar ratios. Then the content of As in the solid phase after adsorption was measured by X-ray fluorescence spectrometer while the surface morphology of the adsorbent was characterized by scanning electron microscope (SEM). Finally, extended X-ray absorption fine structure spectroscopy (EXAFS), obtained at BioXAS beamline of Canadian synchrotron radiation source, was used to detect the coordination numbers of As and Fe adsorbed on the two adsorbents.ResultsThe results show that the adsorption capacity of these two adsorbents for As(V) under acidic pH is greater than that of the adsorbent under alkaline conditions. The adsorption capacity of the two adsorbents decreases with the increase of the Fe/As molar ratio. As(V) adsorption capacity of goethite is larger than that of hematite under the same adsorption pH and Fe/As molar ratio. The EXAFS data shows that the coordination numbers of As-Fe in both goethite and hematite are close to 1, and the distance of As-Fe in different samples is in the range of 3.29~3.31 Å.ConclusionsArsenic mainly forms monodentate-mononuclear complexes after adsorption on the surface of goethite and hematite, which is independent of the experimental pH values and the Fe/As molar ratios.
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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".