Polymer Selection for Biphenyl Degradation in a Solid-Liquid Two-Phase Partitioning Bioreactor
Bibliographic record
Abstract
The commercially available thermoplastic polymer Hytrel was selected as the delivery phase for the hydrophobic model compound biphenyl in a solid-liquid two-phase partitioning bioreactor (TPPB), and 2.9 g biphenyl could successfully be degraded in 1-L TPPBs by a pure culture of the biphenyl-degrading bacterium Burkholderia xenovorans LB400 in 50 h and by a mixed microbial consortium isolated from contaminated soil in 45 h. TPPBs consist of an aqueous cell-containing phase and an immiscible second phase that partitions toxic and/or poorly soluble substrates (in this case biphenyl) on the basis of maintaining a thermodynamic equilibrium. This paper illustrates a rational strategy for selecting a suitable solid polymeric substance for the delivery of the poorly water-soluble model compound biphenyl. The partitioning of biphenyl between the selected polymers and water was analogous to partitioning of solutes between two immiscible liquid phases. The partitioning coefficients varied between 180 for Nylon 6.6 and 11,000 for Desmopan, where the later numerical value is comparable to biphenyl partitioning coefficients between water and organic solvents. Employing a solid delivery phase enabled the utilization of a surfactant-producing microbial mixed culture, which could not be cultivated in liquid-liquid TPPBs and thereby extended the range of biocatalysts that can be employed in TPPBs.
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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".