CS<sub>2</sub> Formation in the Claus Reaction Furnace: A Kinetic Study of Methane−Sulfur and Methane−Hydrogen Sulfide Reactions
Bibliographic record
Abstract
Improving the understanding of reaction kinetics of CS 2 formation in the Claus plant front-end reaction furnace (RF) is a key step in developing strategies to reduce CS 2 formation and, consequently, the environmental impact of Claus plants. Specifically, experiments were carried out in a high-temperature flow reactor with pressures of 101−150 kPa, temperatures of 800−1250 °C, and residence times of 90−1400 ms to study the kinetics of CH 4 −S 2 and CH 4 −H 2 S reactions; these conditions are typical of those encountered in the Claus RF. The reaction between methane and sulfur was found to be very rapid, resulting in complete consumption of sulfur in less than 100 ms at 1100 °C with formation of CS 2 and H 2 S as the primary sulfur-containing products. At higher temperature (>1000 °C), the produced H 2 S decomposes with a proportional increase in CS 2 formation. A simple rate expression for CS 2 formation was obtained, and a kinetic model was developed to describe H 2 S formation/consumption in the CH 4 −S 2 system. In the CH 4 −H 2 S reacting system, H 2 S thermal decomposition appears to be the rate-limiting step for CS 2 formation. The consumption of H 2 S in the CH 4 −H 2 S system proceeds at a rate characteristic of thermal decomposition of H 2 S, i.e., at a rate independent of any reaction of H 2 S with methane.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".