Microbial Biodiesel Production by Direct Transesterification of Rhodotorula glutinis Biomass
Bibliographic record
Abstract
(1) Background: Lipids derived from oleaginous microbes have become promising alternative feedstocks for biodiesel. This is mainly because the lipid production rate from microbes is one to two orders of magnitude higher than those of energy crops. However, the conventional process for converting these lipids to biodiesel still requires a large amount of energy and organic solvents; (2) Methods: In this study, an oleaginous yeast, Rhodotorula glutinis, was used for direct transesterification without lipid pre-extraction to produce biodiesel, using sulfuric acid or sodium hydroxide as a catalyst. Such processes decreased the amount of energy and organic solvents required simultaneously; (3) Results: When 1 g of dry R. glutinis biomass was subject to direct transesterification in 20 mL of methanol catalyzed by 0.6 M H2SO4 at 70 °C for 20 h, the fatty acid methyl ester (FAME) yield reached 111%. Using the same amount of biomass and methanol loading but catalyzed by 1 g/L NaOH at 70 °C for 10 h, the FAME yield reached 102%. The acid-catalyzed process showed a superior moisture tolerance; when the biomass contained 70% moisture, the FAME yield was 43% as opposed to 34% of the base-catalyzed counterpart; (4) Conclusions: Compared to conventional transesterification, which requires lipid pre-extraction, direct transesterification not only simplifies the process and shortens the reaction time, but also improves the FAME yield.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".