Improved utilization of crude glycerol from biodiesel industries: Synthesis and characterization of sustainable biobased polyesters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Crude glycerol from biodiesel facilities was used as biopolyester precursor. • Impurities in crude glycerol were found to create heterogeneous synthesis products. • Technical glycerol yielded elastomeric biopolyesters similar to pure glycerol based ones. • It was shown that only highly purified glycerol from biodiesel production could replace pure glycerol in biomaterial synthesis with comparable results. The present work describes the synthesis of biobased polyesters using glycerol of different purities and sources with the aim of understanding how glycerol composition can influence the resulting structure and properties of biobased polyesters. Glycerol and succinic acid based polyesters were synthesized using crude and technical grade glycerol obtained from biodiesel producing facilities. It was shown that the presence of impurities in crude glycerol can greatly decrease the yield of reaction and also lead to products with different chemical structure and composition than those derived from pure glycerol. In particular, the presence of fatty acids and soaps was shown to produce incorporation of fatty acid residues and formation of carboxylate residues in the polymer backbone respectively. The products synthesized from industrial technical grade glycerol with 95 wt% purity were similar to those formulated from pure glycerol, showing rubbery behavior at room conditions. The materials synthesized from crude glycerol showed different thermal and chemical properties due to incorporation of impurities from the glycerol source to the polymer backbone. It was concluded that technical glycerol could be used as an alternative to pure glycerol on the synthesis of polyesters without inducing major changes on the synthesis products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 it