Breaking the pH Limitation of Nanozymes: Mechanisms, Methods, and Applications
Bibliographic record
Abstract
Although nanozymes have drawn great attention over the past decade, the activities of peroxidase-like, oxidase-like, and catalase-like nanozymes are often pH dependent with elusive mechanism, which largely restricts their application. Therefore, a systematical discussion on the pH-related catalytic mechanisms of nanozymes together with the methods to overcome this limitation is in need. In this review, various nanozymes exhibiting pH-dependent catalytic activities are collected and the root causes for their pH dependence are comprehensively analyzed. Subsequently, regulatory concepts including catalytic environment reconstruction and direct catalytic activity improvement to break this pH restriction are summarized. Moreover, applications of pH-independent nanozymes in sensing, disease therapy, and pollutant degradation are overviewed. Finally, current challenges and future opportunities on the development of pH-independent nanozymes are suggested. It is anticipated that this review will promote the further design of pH-independent nanozymes and broaden their application range with higher efficiency.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".