Insights into the Surface Complexation of Dimethylarsinic Acid on Iron (Oxyhydr)oxides from ATR-FTIR Studies and Quantum Chemical Calculations
Bibliographic record
Abstract
The surface chemistry of methylated arsenicals with ubiquitous geosorbents and industrial catalysts is poorly understood. These arsenic compounds pose both a health and an environmental risk in addition to being a challenge to the energy industry. We report herein a detailed spectroscopic analysis of the surface structure of dimethylarsinic acid (DMA) adsorbed on hematite and goethite using attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Spectra of adsorbed DMA, DMA(ads), were collected in situ as a function of pH and ionic strength, using both H(2)O and D(2)O at 298 K in flow mode. Experimental data were complemented with DFT calculations of geometries and frequencies of hydrated DMA-iron oxide clusters. Results indicate the simultaneous formation of inner- and outer-sphere complexes with distinct spectral components. Desorption behavior of DMA due to chloride and phosphate was studied as a function of time from the decrease in the absorbance of apparent spectral features. The impact of our studies on the environmental fate of DMA in geochemical environments and the design of technologies to reduce arsenic content in fuels are 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 | 0.001 |
| Open science | 0.001 | 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".