Surface Interactions of Aromatic Organoarsenical Compounds with Hematite Nanoparticles Using ATR-FTIR: Kinetic Studies
Bibliographic record
Abstract
Aromatic organoarsenicals p-arsanilic acid (pAsA) and roxarsone (ROX) are used as feed additives in developing countries that allow the use of arsenic-containing compounds in their poultry industry. These compounds are introduced to the environment through the application of contaminated poultry litter. Little is known about the surface chemistry of these organoarsenicals on the molecular level with reactive components in soils. We report herein the first in situ and surface-sensitive rapid kinetic studies on the adsorption and desorption of pAsA to/from hematite nanoparticles at pH 7 using ATR-FTIR. Values for the apparent initial rates of adsorption and desorption were extracted from experimental data as a function of spectral components. Hydrogen phosphate was used as a desorbing agent due to its ubiquitous presence in litter, and its adsorption kinetics was investigated on surfaces with and without surface arsenic. Initial first-order pseudo-adsorption rate constant for pAsA was lower by a factor of 1.6 than that of iAs(V), suggesting an average behavior for the formation of quantitatively more weakly bonded monodentate or hydrogen-bonded complexes for the former relative to strongly bonded bidentate surface complexes for the latter under our experimental conditions. Initial first-order pseudo-adsorption rate constants for hydrogen phosphate decrease in this order: fresh hematite > pAsA/hematite ≈ phenylarsonic acid (PhAs)/hematite > iAs/hematite by factors 1.5 and 3 relative to fresh films, respectively. Initial desorption kinetics of aromatic organoarsenicals due to flowing hydrogen phosphate proceed with a nonunity overall order, suggesting a complex mechanism, which is consistent with the existence of more than one type of surface complexes. The impact of our studies on the environmental fate and transport of aromatic organoarsenicals in geochemical environments and their overall surface chemistry with iron (oxyhyr)oxides is discussed.
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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".