Bibliographic record
Abstract
Bio-oil is chemically and thermally unstable during storage and transportation. For that reason, it is necessary to evaluate the changes in the properties (chemical and physical) of bio-oil during storage to understand its chemical instability, which will further assist researchers in stabilization strategies. This paper describes the evaluation of an accelerated aging process on the physical and chemical properties of bio-oil from fast pyrolysis of ash and birch woods using two different pyrolyzers, a pilot scale (auger) and lab scale (tube furnace), respectively. The produced oils (freshly made) were aged at 80 °C over different periods (1, 3, and 7 days) in sealed nitrogen-purged Nalgene vessels. Fresh oil was analyzed alongside aged oils. Bio-oils were characterized by viscometer, Karl Fischer titration (H 2 O), pyrolysis–gas chromatography/mass spectrometry (GC/MS), thermogravimetric analysis (TGA), photo-microscopy, 13 C nuclear magnetic resonance (NMR), and Fourier transform infrared spectroscopy (FTIR). The water content, viscosity, decomposition temperature (TGA) and ash content levels in bio-oil samples all increased as the aging period lengthened. GC/MS analysis showed a major reduction in GC-analyzable components. The mass of residue remaining after pyrolysis–GC/MS increased, and the structures of pyrolysis products of this non-volatile residue along with NMR and FTIR data suggest the following aging processes; some of the reactive compounds undergo polymerization or reaction with other compounds, including olefins, alcohols, and aldehydes. Some possible reaction mechanisms are given. The oils remained as a single phase throughout the initial study period; however, on day 7, a clear phase separation was observed by photo-microscopy.
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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".