Effects of temperature, reaction time, atmosphere, and catalyst on hydrothermal liquefaction of Chlorella
Bibliographic record
Abstract
Abstract Hydrothermal liquefaction (HTL) is the direct conversion of wet biomass into bio‐oil at high temperature (200–400°C) and high pressure (10–25 MPa). In this work, we investigated HTL with 4.5 g of Chlorella and 45 ml of water/ethanol (1:1 vol. ratio) in a 100 ml reactor. Bio‐oils produced are characterized via elemental analysis, thermogravimetric analysis, and gas chromatography–mass spectrometry (GC–MS). HTL of Chlorella was investigated at 240 and 250°C for 0 and 15 min under an air or H 2 atmosphere and with and without 5% zeolite Y. Temperature increased the bio‐oil yield from 38.75% at 240°C to 43.04% at 250°C for 15 min reaction time. Longer reaction time increased the bio‐oil yield at 250°C from 39.14% for 0 min to 43.04% for 15 min. The H 2 atmosphere had a significant effect for HTL at 240°C. Zeolite Y increased the bio‐oil yield significantly from 32.03% to 43.06% at 250°C for 0 min. The carbon content of bio‐oil increased with the temperature while the oxygen content decreased. The boiling point distribution of bio‐oils in the range of 110–300°C varies with temperature, and atmosphere. At 240°C for 15 min, the 110–300°C range increased from 31.19% in air (240‐15‐air) to 39.25% in H 2 (240‐15‐H 2 ). The H 2 atmosphere increased the content of hydrocarbons, alcohols, and esters from 69.61% in air (240‐0‐air) to 82.83% in H 2 (240‐0‐H 2 ). Overall, temperature, reaction time, atmosphere, and catalyst all significantly influenced the yield and/or quality of bio‐oils from HTL of Chlorella.
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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 | 0.001 |
| 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) | 0.001 | 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".