Upgrading of Hydrothermal Liquefaction Biocrude from Forest Residues Using Solvents and Mild Hydrotreating for Use as Co-processing Feed in a Refinery
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The presence of a variety of reactive oxygen compounds in biocrudes derived from thermochemical conversion of biomass creates challenges for their co-processing with petroleum in a refinery. In this work, we explore two different technology approaches to upgrade a biocrude produced by hydrothermal liquefaction of forest residues, to the level at which it becomes compatible for co-processing in a refinery. The first approach consisted of using solvents to reject petroleum-insoluble oxygen components in the biocrude, whereas the second one was catalytic hydrotreating under relatively mild conditions. The biocrude had 11.3 wt % oxygen and was completely immiscible in the reference petroleum feedstock (vacuum gas oil). Upgrading using solvents (toluene, dichloromethane, ethyl acetate, and n -pentane) resulted in the rejection of high boiling components, but the concentration of oxygen components in the resulting extract did not change significantly. While the biocrudes treated with n -pentane and toluene were miscible in the reference petroleum feedstock, the mass rejected by these solvents from the biocrude was significant (>35%). Hydrotreating the biocrude was effective at reducing oxygen content down to 2.9 wt % and converting high boiling fractions, while preserving more than 90% of the biocrude’s mass as the liquid product. At this level of deoxygenation, the biocrude was fully miscible in the reference petroleum feedstock and the blend was stable over 7 days. NMR spectroscopy provided insights into the structural changes taking place upon hydrotreating the biocrude. In general, it was found that after hydrotreating the biocrude became more saturated in nature and thus more miscible in petroleum.
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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) | 0.000 | 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".