Investigation of yields and qualities of pyrolysis products obtained from oil palm biomass using an agitated bed pyrolysis reactor
Bibliographic record
Abstract
Oil palm biomass is a non-woody lignocellulosic biomass that has a high potential at the south of Thailand for biofuels and bioenergy applications. Pyrolysis of oil palm biomass to produce biofuels such as bio-oil, biochar, and pyrolysis gas is still challenging. The aim of this study was therefore to investigate the yields and qualities of pyrolysis products obtained from oil palm trunk (OPT), oil palm fronds (OPF), and oil palm shell (OPS) using an agitated bed pyrolysis reactor. These biomasses were pyrolyzed at pyrolysis temperatures of 400, 450, and 500°C while the other operating parameters were fixed. The results showed that the different types of oil palm biomass and pyrolysis temperatures affected the product yields and qualities. The OPF pyrolyzed at 500°C provided the highest liquid yield. The liquid product contained a relatively high water content with a low pH value, leading to highly-oxygenated compounds as indicated by gas chromatography-electron ionization/mass spectroscopy technique (GC-EI/MS). The higher heating value (HHV) of the liquid product was 18.95-22.52 MJ/kg. The biochar had a relatively high HHV ranging from 25.14 to 28.45 MJ/kg. Scanning electron microscopy (SEM) indicated that the resultant biochar had a porous structure surface with a surface area of 1.15-4.43 m2/g as indicated by BET. The pyrolysis gas contained a low composition of combustible gases, leading to a low HHV.
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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) | 0.000 | 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 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".