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Although developing artificial enzymes has made great progress, there isstill a gap between artificial enzymes and natural enzymes in catalyticperformance. Designing and constructing efficient artificial biocatalysts isextremely desirable because of their high stability, low cost and easy storage.Here, we report a synthesized amino-functionalized graphene quantum dots-basedmanganese single atom catalyst (SAC) Mn-N4, which exhibits POD-, CAT, SOD-likeactivities, especially the superior SOD-like activity. Recent studies havereported Mn-based SAzymes, however, the multi-enzyme mimicking catalyticmechanisms for Mn-N4 are not comprehensive and in-depth enough. Therefore, wecombine density functional theory (DFT) calculations and machine learning (ML)to validate the performance of the multi-enzyme mimicking activities. The DFTsimulations show that Mn-N4 owns a highly effective SOD in the "one-sideadsorption" with a very low energy barrier of 0.077 eV, which can be attributedto variation of the preferred spin states of Mn-O2.- system and its "spinflip-collection lock" in the SOD-like catalytic procedure. Furthermore, spinrelated charge distributions on Mn-N4 configurations by machine learning (ML)analysis suggest that the pattern of spin and natural charge/valence electrondistribution will exhibit similarity in the structures of multiple intermediatesteps of multi-enzyme mimicking activities. This work not only puts forward thecatalytic mechanisms of Mn-N4 SAzymes, but also provides essential guidance forfuture design of highly performance artificial enzymes.

Spin Cooperated Catalytic Activities in Mn-N4 based Single-atom Nanozyme: Mechanisms and a Brief Charge-spin Model