Adsorption of Uranyl Species onto the Rutile (110) Surface: A Periodic DFT Study
Bibliographic record
Abstract
To model the structures of dissolved uranium contaminants adsorbed on mineral surfaces and further understand their interaction with geological surfaces in nature, we have performed periodic density funtional theory (DFT) calculations on the sorption of uranyl species onto the TiO(2) rutile (110) surface. Two kinds of surfaces, an ideal dry surface and a partially hydrated surface, were considered in this study. The uranyl dication was simulated as penta- or hexa-coordinated in the equatorial plane. Two bonds are contributed by surface bridging oxygen atoms and the remaining equatorial coordination is satisfied by H(2)O, OH(-), and CO(3)(2-) ligands; this is known to be the most stable sorption structure. Experimental structural parameters of the surface-[UO(2)(H(2)O)(3)](2+) system were well reproduced by our calculations. With respect to adsorbates, [UO(2)(L1)(x)(L2)(y)(L3)(z)](n) (L1=H(2)O, L2=OH(-), L3=CO(3)(2-), x≤3, y≤3, z≤2, x+y+2z≤4), on the ideal surface, the variation of ligands from H(2)O to OH(-) and CO(3)(2-) lengthens the U-O(surf) and U-Ti distances. As a result, the uranyl-surface interaction decreases, as is evident from the calculated sorption energies. Our calculations support the experimental observation that the sorptive capacity of TiO(2) decreases in the presence of carbonate ions. The stronger equatorial hydroxide and carbonate ligands around uranyl also result in U=O distances that are longer than those of aquouranyl species by 0.1-0.3 Å. Compared with the ideal surface, the hydrated surface introduces greater hydrogen bonding. This results in longer U=O bond lengths, shorter uranyl-surface separations in most cases, and stronger sorption interactions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".