Solubility of bio-sourced feedstocks in ‘green’ solvents
Bibliographic record
Abstract
A group of 14 different bio-sourced, renewable feedstocks (homoserine, 1; glutamic acid, 2; aspartic acid, 3; 2,5-furandicarboxylic acid, 4; fumaric acid, 5; oxalacetic acid, 6; tartaric acid, 7; malic acid, 8; succinic acid, 9; levulinic acid, 10; γ-hydroxybutyrolactone, 11; xylitol, 12; mannitol, 13; sorbitol, 14) have been examined for their solubility/miscibility in a variety of ‘green’ solvents, including water, supercritical carbon dioxide (scCO2), and ionic liquids. Two other bio-based compounds 5-hydroxymethylfurfural, 15, and D-xylose, 16, were studied in selected solvents. Trends in solubility have been assessed so that these data may be extrapolated to help predict solubilities of other related compounds. For example, 10, 11 and 15 all demonstrated appreciable solubility in scCO2, as they possess weak intermolecular interactions. The dicarboxylic acids studied (4–9) all proved soluble in modified scCO2 (by use of MeOH as a cosolvent). While the polyols (12–14) and 1 were insoluble in scCO2 but water of various pHs and ionic liquids proved adept at their dissolution. Some of the amino acids studied (2 and 3) were only soluble in water with an adjustment of pH.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".