A comparison of three first principles methods for predicting solute–polymer affinity, and the simultaneous biodegradation of phenol and butyl acetate in a two‐phase partitioning bioreactor
Bibliographic record
Abstract
Abstract BACKGROUND Solid–liquid two‐phase partitioning bioreactors ( TPPBs ) use polymers as the sequestering phase to reduce the concentration of substrates to sub‐inhibitory levels and enhance biodegradation performance. Polymer selection for TPPBs is challenging due to the almost infinite variety of target substrates to be degraded, and the variability and complexity of polymer composition and structure. RESULTS Three different polymer selection criteria, based on either solubility parameters or activity coefficients, were assessed via experimental partitioning coefficients ( PCs ) for phenol and butyl acetate, two substantially different target contaminant molecules, and the relative ability of the three methods to predict effective polymers was assessed. The best method was also applied to predict which waste polymers would be effective for sequestering these molecules, and TPPB degradation tests were conducted to confirm the effectiveness of a single identified polymer and selected waste polymers. CONCLUSION An effective polymer selection criterion was identified and the identified polymer showed a high capacity to absorb both phenol and butyl acetate. Both substrates were successfully degraded in solid–liquid TPPBs using the selected polymer and using mixtures of waste polymers. © 2013 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".