A first principles approach to identifying polymers for use in two‐phase partitioning bioreactors
Bibliographic record
Abstract
Abstract BACKGROUND: Two‐phase partitioning bioreactors (TPPBs) employ an immiscible phase to partition toxic substrates/products to/away from cells to reduce cytotoxicity and improve bioprocess performance. Initially, immiscible organic solvents were used as the sequestering phase, and their selection included consideration of solute–solvent affinity, which can be predicted through first principles consideration of solute activity and phase equilibrium thermodynamics. Polymers can replace organic solvents in such systems, however, their selection has largely been via heuristic means, and a more fundamental approach is necessary for future success in rational polymer identification. RESULTS: Material properties (polymer crystallinity, solubility parameter, and glass transition temperature Tg) were examined across several polymers and polyaromatic hydrocarbons as target solutes. All were shown to influence solute–polymer affinity. CONCLUSION: This first attempt at identifying physical/chemical properties that affect solute–polymer partitioning has been able to demonstrate some clear trends, and has allowed us to formulate a polymer selection guide, based on first principles, to facilitate the selection of solute–polymer pairs for solid–liquid TPPB applications. Copyright © 2012 Society of Chemical Industry
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".