Catalytic conversion of chicken fats into fuel grade hydrocarbons
Bibliographic record
Abstract
Fatty acid is considered as a renewable source for producing transportation fuel. As there is an ongoing price hike of diesel and kerosene as well as a lack of sustainable fuel to mitigate global climate change, the current study developed a one-step process of fuel grade hydrocarbons production from low-grade chicken fats (as a fatty acid source) using NiO/γ-Al2O3 catalysts. Results showed that straight-chain hydrocarbons were obtained through deoxygenation of chicken fats at different temperatures (350 to 400 °C) and reaction times (0.25 to 1 h). 65% liquid yield and 87% degree of deoxygenation were obtained at the optimum reaction conditions (400 °C and 1 h) using 5 wt%NiO/γ-Al2O3 catalyst, whereas the liquid product contains 18.7% C8 to C15 alkanes, 38.5% hexadecane, 39% heptadecane and 3.8% C18 to C20 alkanes. Liquid product has a similar high heating value (HHV) and density as a commercial fuel such as diesel. This work opens a new research window in the field of green energy to improve global energy security.
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 | 0.000 | 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".