Determining the acid number of biodiesel
Bibliographic record
Abstract
Abstract Commerical biodiesel is composed of FAME. It may also contain small amounts of FA, which are quantified by an acid number, expressed as milligrams of potassium hydroxide required to neutralize 1 g of sample. In 2006, the ASTM D 6751 biodiesel acid‐number limit was harmonized with the European biodiesel value of 0.50. ASTM D 664 is the standard reference method for measuring the acid number of both ASTM biodiesel and petroleum‐derived diesel. This potentiometric method cites acceptable repeatability and mediocre reproducibility, but no information on accuracy. ASTM D 974 is a non‐aqueous colorimetric titration that uses potassium hydroxide in isopropanol as the titrant and p‐naphtholbenzein as indicator. It was designed for petroleum products and is suitable for colored samples. It has been tested on nine palmitic acid/soybean oil standards in the acid‐number range of 0.198 to 1.17. All accuracies were within 3.3%. The repeatability was approximately 6% at an acid number of 0.5. The reproducibility appears to be only slightly greater than the repeatability at an acid number of 0.5. It is concluded that ASTM D 974 is a good method for evaluating the acid‐number compliance of biodiesel samples.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 0.001 |
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".