A Single-Step Solid Acid-Catalyzed Process for the Production of Biodiesel from High Free Fatty Acid Feedstocks
Bibliographic record
Abstract
Biodiesel is a nontoxic, renewable, and biodegradable alternative green fuel for petroleum-based diesel. However, the major obstacle for the commercial production of biodiesel is the high cost of raw material, i.e., refined vegetable oils. This problem can be addressed using low-cost feedstocks, such as waste oils and fats. However, these feedstocks contain a high amount of free fatty acids (FFAs), which cannot be used for the production of biodiesel using a traditional homogeneous alkali-catalyzed transesterification process. A solid acid catalyst based on a supported heteropolyacid catalyst (PSA) was evaluated for the production of biodiesel from soybean oil (SBO) containing up to 25 wt % palmitic acid (PA). It was demonstrated that this solid acid catalyst catalyzed simultaneously esterification and transesterification. The total glycerin, ester content, and acid numbers were determined according to ASTM D 6584, EN 14103, and ASTM D 974, respectively. It was found that at 200 °C, 1:27 oil/alcohol molar ratio, and 3 wt % catalyst, a high-quality biodiesel with an ester content of 93.95 mass % was produced from a feedstock (SBO containing 10% PA) in 10 h. The PA and chemically bound glycerin (CBG), which includes triglyceride (TG), diglyceride (DG), and monoglyceride (MG), conversions of 92.44 and 99.38% were obtained, respectively. The effect of process parameters, such as catalyst amount, oil/alcohol molar ratio, and FFA content in the feedstock, has been investigated. This single-step solid acid-catalyzed process has potential for industrial-scale production of biodiesel from high FFA feedstocks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".