Bimetallic Ti3C2Tx with three synergistic catalytic pathways and enhanced dual enzyme activities for a visual sensing platform

Abstract

Nano-enzymes are increasingly used in forensic identification, biochemical testing, food regulation, environmental pollution monitoring and other fields. However, the construction of enzyme cascade catalytic systems based on nano-enzymes with multiple enzyme activities presents both opportunities and challenges. Ti3AlC2 is a common MXene with a graphene-like structure, which has the features of a large specific surface area, good electrical conductivity, excellent catalytic properties, and easy functionalization. Moreover, after being functionalized, Ti3AlC2 can exhibit excellent peroxidase-like activity. Therefore, in this work, a bimetallic Fe–Ni@Ti3C2Tx nano-enzyme with both peroxidase-like and oxidase-like activities was synthesized, and three synergistic catalytic mechanisms of Fe–Ni@Ti3C2Tx were verified. A colorimetric sensor was constructed based on Fe–Ni@Ti3C2Tx for the detection of H2O2 to test its feasibility for practical applications. The prepared colorimetric sensor had a wide linear range (50–6000 µM) and a low detection limit (14.606 µM). In addition, the selectivity, stability and reproducibility of the prepared colorimetric sensor were acceptable. This study laid a foundation for the simple preparation and practical application of a bimetallic nano-enzyme with various enzyme activities.

Graphical abstract: Bimetallic Ti3C2Tx with three synergistic catalytic pathways and enhanced dual enzyme activities for a visual sensing platform

Supplementary files

Article information

Article type
Paper
Submitted
03 Oct 2025
Accepted
01 Dec 2025
First published
18 Dec 2025
This article is Open Access
Creative Commons BY-NC license

Nanoscale Adv., 2026, Advance Article

Bimetallic Ti3C2Tx with three synergistic catalytic pathways and enhanced dual enzyme activities for a visual sensing platform

Z. Zhou, L. Zou, P. Zhang, J. Dong, J. Zhou, H. Jiang, H. Ren, Z. Li, H. Niu, H. Liao, X. Zhang, S. An, F. Ren, X. Ge, L. Cheng, F. Yang, H. Pan, S. Rong and H. Ma, Nanoscale Adv., 2026, Advance Article , DOI: 10.1039/D5NA00939A

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