Medium composition effects on solute partitioning in solid–liquid two‐phase bioreactors
Bibliographic record
Abstract
Abstract Biphasic systems such as two‐phase partitioning bioreactors (TPPBs) have been used to alleviate biological inhibition by sequestering inhibitory compounds within an immiscible phase. The use of solid polymer beads as this auxiliary phase provides a fully biocompatible alternative to potentially toxic organic solvents. While guidelines exist for the rational selection of the polymer phase, the effect of the aqueous phase composition on molecular sequestration has not been explored in the literature. This work aims to identify aspects of medium composition that influence the partitioning of target molecules into the sequestering phase. Using benzaldehyde as the target molecule and Hytrel G3548L (DuPont) as the polymer phase, pH, temperature, salt and glucose concentrations, as well as ethanol concentrations, were examined for their effects on the partition coefficient. pH and temperature were observed to have no significant effect on benzaldehyde partitioning. Salt and glucose additions increased the partition coefficient by 173% and 30%, respectively, compared with pure reverse osmosis (RO) water, while increasing ethanol concentration was found to decrease the partition coefficient from 44 ( ± 1.6) to 1 ( ± 0.3). Strategic changes to the aqueous phase can be made to improve affinity of the sequestering phase for target molecules. This provides a simple and cost‐effective method to potentially improve TPPB system performance. Copyright © 2010 Society of Chemical Industry
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".