La spirale turbulente : motif de grande longueur d'onde dans les écoulements cisaillés turbulents
Bibliographic record
Abstract
Biocatalytic treatment with oxidoreductase enzymes, especially laccases are an environmentally benign method for biodegradation of pharmaceutical compounds, such as carbamazepine to less harmful compounds. However, enzymes are required to be immobilized on supports to be reusable and maintain their activity. Functionalization of support prior to immobilization of enzyme is highly important because of biomolecule-support interface on enzyme activity and stability. In this work, the effect of oxidation of nanobiochar, a carbonaceous material produced by biomass pyrolysis, using HCl, H<sub>2</sub>SO<sub>4</sub>, HNO<sub>3</sub> and their mixtures on immobilization of laccase has been studied. Scanning electron microscopy indicated that the structure of nanobiochars remained intact after oxidation and Fourier transform infrared spectroscopy confirmed the formation of carboxylic groups because of acid treatment. Titration measurements showed that the sample treated with H<sub>2</sub>SO<sub>4</sub>/HNO<sub>3</sub> (50:50, v/v) had the highest number of carboxylic groups (4.7mmol/g) and consequently the highest efficiency for laccase immobilization. Additionally, it was observed that the storage, pH and thermal stability of immobilized laccase on functionalized nanobiochar was improved compared to free laccase showing its potential for continuous applications. The reusability tests towards oxidation of 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) showed that the immobilized laccase preserved 70% of the initial activity after 3cycles. Finally, using immobilized laccase for degradation of carbamazepine exhibited 83% and 86% removal in spiked water and secondary effluent, respectively.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".