Selective Adsorption of Thiols Using Gold Nanoparticles Supported on Metal Oxides
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Bibliographic record
Abstract
Selective capture of thiols from a synthetic hydrogen sulfide containing mixture using supported nanogold materials has been explored for the potential removal of thiols from sour gas production fluids. In this research, TiO2-, Al2O3-, SiO2-, and ZnO-supported gold nanoparticles have been studied for their usage as regeneratable adsorbents to capture CH3SH, C2H5SH, and i-C3H7SH. Au/TiO2 and Au/Al2O3 showed promising properties for removing the thiols efficiently from a gas-phase mixture; however, Au/Al2O3 did catalyze some undesirable side reactions, e.g., carbonyl sulfide formation. It was found that a mild temperature of T = 200 °C was sufficient for regeneration of either Au/TiO2 or Au/Al2O3 adsorbent. The metal oxide mesopores played an important role for accommodating gold particles and chemisorption of the thiols, where smaller pore sizes were found to inhibit the agglomeration/growth of gold particles. The nature of thiol adsorption and the impact of multiple adsorption-desorption cycles on the adsorbents have been studied using electron microscopy, XPS, XRD, GC, and physi/chemiadsorption analyses.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it