Atomic-Dispersed and Iron-Doped Carbon Dots by Efficient One-Pot Synthesis for High Peroxidase-like Catalytic Activity

Abstract Carbon-based nanozymes are expected to reach the catalytic performance of natural enzymes, but their multiparameter synthesis resists rational design. We combined a deep neural network trained on 59 formulations with a differential evolution search algorithm to predict a synthetic route outside the training space, and the measured mass-normalized efficiency matched the prediction. The optimized VS-1 showed a particle size of 2.2 nm, with Fe atoms dispersed and coordinated to approximately 7–8 light atoms (N/O). The optimized VS-1 exhibits a Michaelis constant (Km) of 0.149 mM and a maximum reaction velocity of 2.67 × 10–6 M s–1, demonstrating a substrate affinity approximately three times higher than that of natural horseradish peroxidase. Furthermore, mechanistic investigations based primarily on electron paramagnetic resonance spectroscopy, supported by radical-scavenger trends, identify the superoxide anion radical as the dominant reactive species for substrate oxidation. This work provides a highly active carbon-based catalytic carbon dot for sensing.

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Publication Details

Journal
Nano Letters
Published
2026-11-03
DOI
https://doi.org/10.1021/acs.nanolett.6c04331
Primary Topic
Advanced Nanomaterials in Catalysis
Type
article
Field-Weighted Citation Impact
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article

Atomic-Dispersed and Iron-Doped Carbon Dots by Efficient One-Pot Synthesis for High Peroxidase-like Catalytic Activity

Jiangxiong Zhu, Hao Yin, Yun Deng, Yu Zhong et al.
Nano Letters
Advanced Nanomaterials in Catalysis
article

Atomic-Dispersed and Iron-Doped Carbon Dots by Efficient One-Pot Synthesis for High Peroxidase-like Catalytic Activity

Jiangxiong Zhu, Hao Yin, Yun Deng, Yu Zhong, Xueqing Geng, Huanning ZHANG, Ruilong Luo
article en

Abstract

Abstract Carbon-based nanozymes are expected to reach the catalytic performance of natural enzymes, but their multiparameter synthesis resists rational design. We combined a deep neural network trained on 59 formulations with a differential evolution search algorithm to predict a synthetic route outside the training space, and the measured mass-normalized efficiency matched the prediction. The optimized VS-1 showed a particle size of 2.2 nm, with Fe atoms dispersed and coordinated to approximately 7–8 light atoms (N/O). The optimized VS-1 exhibits a Michaelis constant (Km) of 0.149 mM and a maximum reaction velocity of 2.67 × 10–6 M s–1, demonstrating a substrate affinity approximately three times higher than that of natural horseradish peroxidase. Furthermore, mechanistic investigations based primarily on electron paramagnetic resonance spectroscopy, supported by radical-scavenger trends, identify the superoxide anion radical as the dominant reactive species for substrate oxidation. This work provides a highly active carbon-based catalytic carbon dot for sensing.

Nano Letters
Shanghai Jiao Tong University (CN)
Openalex Percentile: Top 30%
Advanced Nanomaterials in Catalysis
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