Effects of O<sub>2</sub> and SO<sub>2</sub> on Water Chemistry Characteristics and Corrosion Behavior of X70 Pipeline Steel in Supercritical CO<sub>2</sub> Transport System
Bibliographic record
Abstract
The water chemistry characteristics of supercritical CO 2 streams and the corrosion behavior of X70 steel in a supercritical CO 2 system containing O 2 and/or SO 2 impurities were investigated by thermodynamic simulation and corrosion testing. The results show that O 2 concentration in supercritical CO 2 streams contributes to the negligible influence on the water chemistry characteristics, corresponding to a slight change in the corrosion rate, whereas the rising SO 2 concentration noticeably deteriorates the water chemistry characteristics, in accordance with a remarkable increase in the corrosion rate. The coexistence of O 2 and SO 2 synergistically accelerates the corrosion of X70 steel due to the fact that the formation of H 2 SO 4 makes the condensed water highly acidified. The corrosion products were further characterized by surface analysis techniques. It is found that O 2 and/or SO 2 remarkably affects the corrosion film characteristics by changing the chemistry characteristics of condensed water. The corrosion model corresponding to this phenomenon was proposed.
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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".