Biodiesel production from <scp> <i>Nannochloropsis</i> </scp> microalgal biomass‐derived oil: An experimental and theoretical study using <scp>the RSM‐CCD</scp> approach
Bibliographic record
Abstract
Abstract Biodiesel production from Nannochloropsis is investigated in the current study. Based on the extraction studies, the used biomass is composed of 50% saponifiable lipids, which turns this species to a vulnerable feedstock for biodiesel production. It should also be noted that the acidity of the obtained crude bio‐oil is higher than 2 mg KOH/g, hence it was attempted to survey the biodiesel production from the obtained oil through the esterification reaction with the aid of response surface methodology (RSM). According to the data, the highest biodiesel yield (99.5%) from the bio‐oil is obtained at a reaction temperature of 69°C, a reaction time of 30 min, a methanol to oil molar ratio of 9:1, and an H 2 SO 4 concentration of 0.13 wt.%. In the next step, the in‐situ extraction and esterification of Nannochloropsis were investigated at the observed optimum reaction conditions. Based on the analysis, biodiesel yield from the dry cell weight of the biomass is considered to be 16%, which accounts for 99% conversion of bio‐oil to biodiesel.
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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) | 0.000 | 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 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".