Polymer–solute interactions in solid–liquid two‐phase partitioning bioreactors
Bibliographic record
Abstract
Abstract BACKGROUND: Biphasic systems with immiscible solvents have been studied for in situ product removal, and have shown improvements in bioreactor performance, however, problems associated with solvent biocompatibility, bioavailability and operation have been identified. One alternative is the solid–liquid system in which polymer beads are used, absorbing and removing target compounds from the aqueous phase while maintaining equilibrium conditions. This work aims to identify polymer properties that may be important in polymer selection for selected biotransformation molecules including 2‐phenylethanol, cis‐1,3‐indandiol, iso‐butanol, succinic acid and 3‐hydroxybutyrolactone. RESULTS: Relatively hydrophobic compounds (e.g. 2‐phenylethanol) tend to be absorbed by polymers better than hydrophilic ones (e.g. iso‐butanol) based on partition coefficient tests; values as high as 80 were obtained for the former and < 3 for the latter. Owing to the presence of polar functional groups on these compounds, polar polymers such as Hytrel® performed better than non‐polar ones such as Kraton®. Crystallinity and intermolecular hydrogen‐bonding were also found to be important polymer properties. CONCLUSION: Polymers showed excellent results in absorbing hydrophobic compounds such as aromatic alcohols, and positive results in absorbing hydrophilic compounds but to a lesser extent. Grafting hydrophilic functional groups onto polymers may be a promising approach for extending polymer uptake capabilities and is currently being investigated. Copyright © 2009 Society of Chemical Industry
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".