Exploring the Long‐term Catalytic Mechanism of Catalase‐Like Nanozymes Prepared by Flow Chemistry
Bibliographic record
Abstract
ABSTRACT Despite of the rapid development of nanozymology, the long‐term catalysis of nanozymes, which reflects their hidden catalytic mechanism and sustainability is still overlooked. Herein, we systematically investigate the prolonged catalase (CAT)‐like activity of nanozymes prepared by flow chemistry. Through a rational control on the reaction conditions in micro‐channel, fast synthesis of a library of common CAT‐like nanozymes, including Prussian blue (PB), manganese Prussian blue (Mn‐PB), Fe 3 O 4 , CeO 2 , Pt, and Au is realized. The mass production capability of the developed synthetic device is validated with a high yield of 60.5 g uniform PB nanozymes in 115 min. A precise definition of s nano value is then proposed, quantitively expressing the long‐term catalytic behavior of the as‐prepared nanozymes with self‐increasing or self‐depleting activity. Taking Mn‐PB, Fe 3 O 4, and Pt as representative models, the irreversible oxidation effect of H 2 O 2 is demonstrated to endow them with abundant oxygenated groups during the prolonged catalysis and regulate their reaction energy profiles, thus varying their catalytic activities. Our results reveal the superiority of flow synthesis for the nanozymes preparation and the guiding significance of long‐term catalysis for the mechanism study and the efficient application of nanozymes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".