Thermoresponsive Starch Nanoparticles for the Extraction of Bitumen from Oil Sands
Bibliographic record
Abstract
Starch nanoparticles (SNPs) useful for the extraction of bitumen from oil sands were obtained by modification with thermoresponsive poly(di(ethylene glycol) methyl ether methacrylate) (PMEO2MA) segments through RAFT (Reversible Addition–Fragmentation chain Transfer) grafting. Since PMEO2MA exhibits a Lower Critical Aggregation Temperature (LCAT), the polymer-grafted SNPs are amphiphilic above the LCAT of the thermoresponsive polymer and can interact efficiently with bitumen in the oil sands, facilitating its extraction. The PMEO2MA-grafted SNPs form micellar aggregates that remain dispersed in water but can shuttle the bitumen component out of the sand and silt mixture in the extraction process above the LCAT. Upon cooling, the hydrophobic PMEO2MA domains become hydrophilic again and the grafted SNPs remain in the water phase, while the extracted oil floats on the aqueous phase and can be skimmed off. The aqueous polymer solution may be reused in other extraction cycles. Extraction by tumbling of the oil-water-SNP mixtures in vials at 45 °C reached over 80% efficiency. The synthetic methods used provide easy control over the characteristics of the grafted SNPs (number and length of grafted PMEO2MA segments), and therefore over their hydrophilic-lipophilic balance (HLB). The SNP-g-PMEO2MA samples were characterized by 1H NMR, UV-visible spectroscopy and dynamic light scattering analysis, and the grafted PMEO2MA chains were cleaved from the starch substrates for analysis by gel permeation chromatography.
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.
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) | 0.001 | 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".