Sorption properties of peroxidase-catalysed polyphenolic resin enable aromatics’ capture
Bibliographic record
Abstract
Soybean peroxidase catalyses the removal of many phenols and anilines through polymerisation and precipitation. The precipitates might sorb other wastewater compounds simultaneously through a hydrophobic interaction. To model this interaction, phenol was chosen as the substrate and 4-(phenylazo)benzoate as the sorbate, and the system was quantitatively evaluated with the Langmuir isotherm. Sorption occurred either during or after enzymatic conversion of phenol (dynamic or static, respectively). The two systems showed Langmuir association constants of 0·088 and 0·13 l/mg and maximum sorption capacities of 51 and 16 mg/g, respectively. Both parameters compare favourably with those for the sorption of benzene, toluene and xylenes on activated carbon. A composite Langmuir parameter, (maximum capacity/dissociation constant), is suggested as the criterion for evaluating potential sorbent–sorbate couples. The model system demonstrates the feasibility of using enzymatically generated phenolic precipitates to remove toxic hydrophobic aromatic non-substrates from wastewater, when they co-occur with a substrate such as phenol. In the future, the use of polyaryl sorbents for aryl sorbates should be more broadly characterised and the criterion used for comparison should be the composite Langmuir parameter.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".