Investigating the Thermal Stability and Corrosivity of Biocrude Oil at FCC Feeding Temperatures for Co-processing Applications
Bibliographic record
Abstract
Abstract Co-processing biocrude oils in existing fluid catalytic cracking (FCC) units can significantly expand the use of renewable bioenergy resources with acceptable capital expenditures. Considering the instability and high corrosivity of bio-oils, extensive studies have been done on the aging of bio-oil and corrosion of low-alloy and stainless steels under transportation and storage conditions at temperatures < 80 °C, which is much lower than the FCC feeding temperatures of 100–300 °C. In this work, the thermal stability and corrosivity of pinewood-derived bio-oil were evaluated by aging at 150 °C and immersion experiments at temperatures of 80, 150, and 220 °C. Phase separation was observed in aged samples. Viscosity measurements and thermogravimetric analysis were conducted on the aged bio-oil samples. In parallel, the corrosion modes and extents of two structural materials (UNS K02600 carbon steel and UNS S30403 stainless steel) were evaluated using microscopy and mass change measurements after immersion tests. UNS S30403 exhibited an acceptable corrosion rate of 0.29 mm/y at 80 °C, but its corrosion rate increased by one order of magnitude when increasing the temperature to 150 and 220 °C. UNS K02600 behaved more poorly at each testing temperature. Thermogravimetric analysis of aged bio-oil and bio-oil from immersion tests revealed a combined effect caused by lixiviated metal ions on facilitating bio-oil aging and phase separation on increasing bio-oil corrosivity. Post-characterizations were performed to identify the corroded surface morphology.
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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".