Steering H2O2 lysis pathway for ROS generation in Prussian blue nanozymes via alkali cation doping
Bibliographic record
Abstract
Prussian blue nanoparticles (PBNPs) have emerged as versatile nanozymes with reactive oxygen species (ROS)-scavenging capabilities, predominantly applied in antioxidant therapies. In this work, we present a combined theoretical and experimental study demonstrating that modulating Fe coordination environments can fundamentally reconfigure PBNPs’ catalytic properties, enabling ROS generation and pro-oxidative functionality. Ab initio molecular dynamics revealed different H2O2 lysis mechanisms at Fe sites with varying coordination numbers: Low-coordinated center (FeN4) induced hydrogen atom transfer to form Fe=O species, while high-coordinated FeN5 generated ·OH radicals via H+-assisted homolysis under acidic conditions. Guided by calculations, Cs-doped PBNPs (Cs-PBs) with elevated coordination numbers were synthesized via alkali cation stoichiometric control, leveraging high distribution coefficient and low hydration energy of Cs+. Experimental results confirmed radical generation in Cs-PBs aligned with theoretical predictions. The size-optimized Cs-PBs demonstrated ultrahigh peroxidase-like activity (1182.26 U·mg-1) and outperformed ROS generating properties in both pollutant degradation and chemodynamic therapy. This work redefines PBNPs’ catalytic potential beyond conventional antioxidant roles, and lays the foundation for innovative environmental and therapeutic solutions. While Prussian blue (PB) nanozymes are typically employed as antioxidants, their reactive oxygen species-generating capability remains unexplored. Here, the authors predict by molecular dynamics and identify explicit hydroxyl radical generation in highly crystalline cesium-doped PBs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".