Corrosion Performance of UNS S31000 under Batch-mode Hydrothermal Liquefaction (HTL) Conversion of Different Biomass
Bibliographic record
Abstract
Abstract Hydrothermal liquefaction (HTL) is an important thermochemical technology which uses hot pressurized water to convert wet biomass or biowaste feedstocks into biocrude oils and other marketable bio-chemicals. The presence of hot pressurized water, aggressive catalyst, and organic products can lead to serious corrosion damage and even stress corrosion cracking risk on the HTL reactors. Up to now, very limited information is available about the corrosion of HTL reactor alloys under HTL processes. In this study, the corrosion of a candidate constructional steel (UNS S31000) was investigated under the batch-mode HTL conversion of different biomass feedstocks, including bamboo (a typical lignocellulosic biomass) and black liquor (a common industrial biowaste). The bio-oil produced from black liquor had higher contents of organic acids and phenols compared to that converted from bamboo. The corrosion rate of the steel in the HTL of black liquor was about twenty-five times higher than that in the HTL of bamboo. The corrosion layer formed in the HTL of black liquor is spalling.
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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".