Production and Characterization of Pyrolysis Oil from Sawmill Residues in an Auger Reactor
Bibliographic record
Abstract
In this study, the significant process variables of a pilot auger reactor (i.e., temperature, feed flow rate, and the vacuum fan speed) are investigated to optimize pyrolysis oil (py-oil) yield and properties. The auger reactor uses steel shot as a heat carrier and operates without inert carrier gas. For the pyrolysis of softwood shavings, the optimum conditions are 450–475 °C temperature, a 4 kg/h feed flow rate, and a 2415 rpm vacuum fan speed producing an oil yield of 53%. The water content of the oil was minimized under these conditions to 24–26% and produced a single phase liquid. Hardwood sawdust (HW), Softwood shavings (SW), and Softwood Bark (SB) were pyrolyzed at these conditions to compare py-oil yield and chemical and physical characteristics, such as chemical composition, water content, total acid number (TAN), pH, density, viscosity, solids content, and HHV. The chemical components in py-oil were identified by GC-MS.
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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 | 0.001 |
| 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".