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Heme Cofactor-Resembling Fe-N Single Site Embedded Graphene as Nanozymes to Selectively Detect H2O2 with High Sensitivity

Authors
Kim, Min SuLee, JunsangKim, Hye SuCho, AraShim, Kyu HwanLe, Thao NguyenAn, Seong Soo A.Han, Jeong WooKim, Moon IlLee, Jinwoo
Issue Date
Jan-2020
Publisher
WILEY-V C H VERLAG GMBH
Keywords
cofactor-embedded graphene; density functional theory; Fe-N single site; nanozymes; substrate specificity
Citation
ADVANCED FUNCTIONAL MATERIALS, v.30, no.1
Journal Title
ADVANCED FUNCTIONAL MATERIALS
Volume
30
Number
1
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17683
DOI
10.1002/adfm.201905410
ISSN
1616-301X
Abstract
Over the past decade, the catalytic activity of nanozymes has been greatly enhanced, but their selectivity is still low and considered a critical issue to overcome. Herein, Fe-N-4 single site embedded graphene (Fe-N-rGO), which resembles the heme cofactor present in natural horseradish peroxidase, shows a marked enhancement in peroxidase-like catalytic efficiency of up to approximate to 700-fold higher than that of undoped rGO as well as excellent selectivity toward target H2O2 without any oxidizing activity. Importantly, when Fe or N is doped alone or when Fe is replaced with another transition metal in the Fe-N-4 site, the activity is negligibly enhanced, showing that mimicking the essential cofactor structure of natural enzyme might be essential to design the catalytic features of nanozymes. Density functional theory results for the change in Gibbs free energy during the peroxide decomposition reaction explain the high catalytic activity of Fe-N-rGO. Based on the high and selective peroxidase-like activity of Fe-N-rGO, trace amounts of H2O2 produced from the enzymatic reactions from acetylcholine and cancerous cells are successfully quantified with high sensitivity and selectivity. This work is expected to encourage studies on the rational design of nanozymes pursuing the active site structure of natural enzymes.
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BioNano Technology (Department of BioNano Technology)
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