Thermogravimetric Studies on Pyrolysis and Combustion Behavior of a Heavy Oil and Its Asphaltenes
Bibliographic record
Abstract
A thermogravimetric analyzer (TGA) was used to obtain information on the pyrolysis and combustion behavior of both crude oil (Neilburg) and its asphaltenes, each mixed with reservoir sand. Of all the saturate, aromatic, resin, and asphaltene fractions, asphaltenes contribute the most to the formation of coke (fuel). Temperature-ramped as well as the isothermal pyrolysis experiments on whole oil and asphaltenes were analyzed to determine the temperature at which coke formation was maximized. Furthermore, isothermal combustion curves for coke derived from whole oil and asphaltenes were obtained to provide reliable data for calculating the kinetics of the reactions. The classical Arrhenius model was applied, and the activation energy for the combustion of coke formed from pure asphaltenes and from the whole oil was calculated. The results showed that the Arrhenius model fitted the data well in the entire range of temperatures the experiments were conducted. The source material for the coke led to modest differences in its reactivity. The observed activation energy for asphaltenes was 117.7 kJ/mol, and for the whole oil it was 129.5 kJ/mol, which indicates that they were in close agreement. Also, the combustion of coke from asphaltenes showed a reaction order of 0.4 at 375°C, which gradually increased to 0.9 at 525°C. For whole oil, it increased from 0.5 at 375°C to 0.7 at 500°C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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".