Predictive descriptor unlocks high-performance nanozymes for peroxidase-like activity

In a new study, Professor Hui Wei and coworkers have introduced a predictive descriptor—t2 occupancy—to guide the design of spinel oxide-based nanozymes with enhanced peroxidase-like (POD) activity.
Nanozymes, functional nanomaterials with enzyme-like properties, have found applications in biosensing, environmental monitoring, and medical diagnostics. While thousands of nanozymes have been discovered, the lack of predictive descriptors has hindered their systematic development.
The paper, published in Angewandte Chemie International Edition, reveals how t2 occupancy—a key electronic characteristic of tetrahedral crystal sites in spinel oxides—can serve as an effective and predictive tool to optimize POD-like activity in nanozymes.
The research focuses on a series of chromium-based spinel oxides (ACr2O4), where transition metal elements occupy tetrahedral sites, exhibiting varying POD-like activities. By calibrating t2 occupancy and correlating it with specific activities, the team observed a “volcanic” curve, demonstrating a peak in activity when t2 occupancy is between 3.7 and 4.9.
Notably, CuCr2O4, with a t2 occupancy near 4.4, exhibited the highest activity, confirming the descriptor’s predictive power. Further optimization of the t2 occupancy through calcination temperature adjustments led to materials exhibiting even higher performance, including a hundredfold increase in activity compared to earlier materials.
Expanding on the dual descriptor strategy, the researchers introduced surface oxygen (Oβ) content as a secondary factor, refining the prediction of activity when t2 occupancy alone was insufficient. The team demonstrated that by optimizing both tetrahedral and octahedral sites in the spinel structure, they could surpass the limitations of the volcanic curve and achieve significant performance breakthroughs.
This strategy, applied to the CuCo2O4 nanozyme, yielded a material with twice the activity of previous benchmarks, marking a significant leap in nanozyme performance. These findings, supported by density functional theory (DFT) calculations, promise to accelerate the design of nanozymes with high catalytic efficiency for a wide range of applications.
More information:
Jiang Du et al, t2 Occupancy as an Effective and Predictive Descriptor for the Design of High‐Performance Spinel Oxide Peroxidase‐like Nanozymes, Angewandte Chemie International Edition (2025). DOI: 10.1002/anie.202421790
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Nanjing University
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Predictive descriptor unlocks high-performance nanozymes for peroxidase-like activity (2025, January 20)
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