Nanozyme catalysis in a crowded environment: the impact of diffusion and surface shielding
Bibliographic record
Abstract
Nanozymes are widely used in various applications as nanosized catalysts for replacing enzymes. An accurate estimation of the catalytic activity of nanozymes in real conditions is critical. In this article, for the first time, we systematically studied the effect of macromolecular molecules co-existing in the real system on the oxidoreductase (peroxidase, oxidase, and catalase)-mimicking nanozymes made of a gold nanoparticle core and a platinum shell, Prussian Blue, Mn2O3 and CoO nanoparticles. Comparisons were made with horseradish peroxidase. We distinguished two main mechanisms of the negative impact of macromolecules on nanozyme catalysis–slowed diffusion and surface shielding of nanoparticles. While the first mechanism is typical for enzymes, the second one is specific only for nanozymes. Understanding the mechanisms is essential for developing approaches to reduce the unavoidable impact of macromolecules for various analytical and biomedical applications.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".