t2 Occupancy as an Effective and Predictive Descriptor for the Design of High-Performance Spinel Oxide Peroxidase-like Nanozymes

Nanozymes are next generation of enzyme mimics. Due to the lack of activity descriptors, most nanozymes were discovered through trial-and-error strategies or by accident. While eg occupancy in an octahedral crystal field was proven as an effective descriptor, the t2 in a tetrahedral crystal field has rarely been explored. Here, we first identified t2 occupancy as an effective and predictive descriptor. Then, we predicted and demonstrated that spinel oxide nanozymes (AB2O4) with a t2 occupancy of around 4.4 at A site had the highest activity. Furthermore, we introduced Oβ content as a secondary descriptor. The dual descriptor strategy resulted in a three-dimensional volcanic curve, converging at a vertex. To surpass the limitations of volcanic curves, a dual site optimizing strategy was proposed, guiding the optimization of both A and B sites as Cu and Co, respectively. The designed CuCo2O4 exhibited the highest activity, achieving around 100- and 2-fold enhancement compared to initial material and the state-of-the-art spinel oxide nanozyme LiCo2O4, respectively. Density functional theory calculations provided a theoretical basis for the catalytic process. This work provides a new strategy for the rational design of nanozymes, and t2 occupancy may also be applicable to the design of other catalysts.