Corrosion of Candidate Alloys in Supercritical Water Gasification (SCWG) Reactor under Batch-mode Operation
Bibliographic record
Abstract
Abstract Supercritical Water Gasification (SCWG) is a promising thermochemical conversion technology in which supercritical water (SCW) is used as a conversion medium to gasify wet biomass feedstocks, such as raw forest biomass, black liquor, crude bio-oils and biowastes, into syngas (a mixture of CO and H2). Despite that considerable studies have been done on the development of SCWG technology, the optimum SCWG conversion conditions have not yet been well defined due to the complexity of raw feedstocks and conversion chemistry. From the corrosion perspective, few information is available to determine which alloys are suitable for the construction of SCWG core components (e.g., reactor and gas lines) to avoid catastrophic disaster under harsh operating conditions, e.g., high temperature (>450°C) and high pressure (>22.1MPa). Thus, the corrosion of two candidate alloys with high Cr contents > 20% (UNS S31000 and UNS N06625), which exhibit high corrosion resistance in SCW environments, were investigated in a batch SCWG reactor containing supercritical water and a typical biomass model compound at 500 °C and 34.4 MPa. To obtain reliable results, a test of 12 SCWG cycles was completed, and the duration of each cycle was one hour. The gasification products were collected and analyzed to advance the fundamental understanding of how the organic compounds released during the conversion affect the corrosion performance of the alloys in the SCWG environments. CO2 was found to be the main gas product, along with certain amounts of H2 and CH4, and a trace contents of CO and C2H4. Acidic phenolic compounds are the major volatile compounds. Both alloys exhibited general and nodular oxidation. Furthermore, UNS N06625 alloy experienced more obvious localized oxide breakdown.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".