Synthesis and Characterization of γ-Fe<sub>2</sub>O<sub>3</sub> for H<sub>2</sub>S Removal at Low Temperature
Why this work is in the frame
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Bibliographic record
Abstract
The performance of γ-Fe 2 O 3 as sorbent for H 2 S removal at low temperatures (20–80 °C) was investigated. First, γ-Fe 2 O 3 /SiO 2 sorbents with a three-dimensionally ordered macropores (3DOM) structure were successfully prepared by a colloidal crystal templating method. Then, the performance of the γ-Fe 2 O 3 -based material, e.g., reference γ-Fe 2 O 3 and 3DOM γ-Fe 2 O 3 /SiO 2 sorbents, for H 2 S capture was compared with that of α-Fe 2 O 3 and the commercial sorbent HXT-1 (amorphous hydrated iron oxide). The results show that γ-Fe 2 O 3 has an enhanced activity compared to that of HXT-1 for H 2 S capture at temperatures over 60 °C, whereas α-Fe 2 O 3 has little activity. Because of the large surface area, high porosity, and nanosized active particles, 3DOM γ-Fe 2 O 3 /SiO 2 sorbent shows the best performance in terms of sulfur capacity and utilization. Moreover, it was found that moist conditions favor H 2 S removal. Furthermore, it was found that the conventional regeneration method with air at high temperature was not ideal for the composite regeneration because of the transmission of some amount of γ-Fe 2 O 3 to α-Fe 2 O 3 . However, simultaneous regeneration by adding oxygen in the feed stream allowed the breakthrough sulfur capacity of FS-8 to increase up to 79.1%, which was two times the value when there was no O 2 in the feed stream.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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