Simultaneous Determination of Seven Anions of Interest in Raw <i>Jatropha curcas</i> Oil by Ion Chromatography
Bibliographic record
Abstract
Various ions are of interest to the quality of biodiesel feedstock and products. In this study, a simple and labor-saving analytical method was developed to directly and simultaneously measure seven anions of interest in oil, utilizing an ion chromatography system with function of sample matrix elimination. Various eluent profiles were explored and calibration curves were made to analyze 13 raw Jatropha curcas oils for their contents of formate, acetate, nitrite, nitrate, sulfite, sulfate and phosphate. A 23 min program was found to sufficiently separate all the ions, and linear correlation higher than 99% was achieved for all the ions except formate (98.6%). High diversity was found in both the presence and concentration range of these ions. Formate, nitrate, and phosphate were more prevalent among the ions tested, such that 12, 10, and 11 samples showed their presence, respectively. Nitrite was found in only two samples with the concentrations lower than 10 mg kg –1 . Formate concentration ranged from 0 to over 3000 mg kg –1, and nitrate and phosphate showed ranges of 0 to 100 and 0 to 300 mg kg –1, respectively. Acetate was less common than formate, and its concentration was universally lower (0 to 500 mg kg –1 ). In addition, the occurrence of acetate and nitrite seemed to be correlated to that of formate and nitrate, respectively, whereas sulfite and sulfate showed mutual exclusion. This method showed reasonably good detection limits and reproducibility, that concentrations of around 0.2 mg L –1 can be detected in the organic samples, and in most cases the ratio of standard deviation to average was below 25%. However, for phosphate, the accuracy and reproducibility need further improvement, possibly by decreasing sample dilution ratio and optimizing eluent profile.
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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".