Investigation of Uranyl Sulfate Complexation under Hydrothermal Conditions by Quantitative Raman Spectroscopy and Density Functional Theory
Bibliographic record
Abstract
Abstract Quantitative first and second formation constants of aqueous uranyl sulfate complexes were obtained from Raman spectra of solutions in fused silica capillary cells at 25 MPa, at temperatures ranging from 25 to 375 °C. Temperature-dependent values of the symmetric O–U–O vibrational frequencies of UO22+(aq), UO2SO40(aq), and UO2(SO4)22–(aq) were determined from the high-temperature spectra. Temperature-independent Raman scattering coefficients of UO22+(aq) were calculated directly from uranyl triflate spectra from 25 to 300 °C, while those of UO2SO40(aq) and UO2(SO4)22–(aq) were derived from spectroscopic data at 25 °C and concentrations calculated using the formation constants of Tian and Rao ( J. Chem. Thermodyn.2009, 41, 569−574.), together with the Specific Ion Interaction Theory (SIT) activity coefficient model. Chemical structures and vibrational frequencies predicted from Density Functional Theory (Gaussian 09) were employed to interpret the Raman spectra. Values of the cumulative formation constants ranged from log β1 = 3.23 ± 0.08 and log β2 = 4.22 ± 0.15 at 25 °C, to log β1 = 12.35 ± 0.22 and log β2 = 14.97 ± 0.02 at 350 °C. This is the first reported use of high-pressure fused silica capillary cells to determine formation constants of metal ligand complexes from their reduced isotropic Raman spectra under hydrothermal conditions.
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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".