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Updated: Feb 1, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
Published on: April 12, 2019
An Adaptive Trimodal Bioanalysis System via Heterogeneous Interface Engineering and Enzyme-Powered Molecular Machines
Lin Sun1, Wan-Zhen Xie2, Yu Ya3
1Key Laboratory of Optic-electric Chemo/Biosensing and Molecular Recognition (Guangxi Minzu University), Education Department of Guangxi Zhuang Autonomous Region; Key Laboratory of Chemistry and Engineering of Forest Products, State Ethnic Affairs Commission; School of Chemistry and Chemical Engineering, Guangxi Minzu University, Nanning 530006, China.
None:
This study reports a trimodal biosensing platform centered on an adaptive signal-fusion strategy for the ultrasensitive detection of pathogens, developed through the strategic integration of heterogeneous interface engineering and enzyme-powered molecular machines. The platform is built on a Ni-MOF-on-Co-MOF heterostructure, where precise interface modulation and pore channel engineering significantly enhance the specific surface area and electron-transport efficiency (1.55-fold higher enzyme-loading capacity), complemented by a novel Au@Ni/Co ZIF@PDA with a remarkable 38.1% photothermal conversion efficiency. For the detection mechanism, the system synergistically combines exonuclease III-mediated target cycling with a dual-output toehold-mediated strand displacement-DNA Walker cascade amplification strategy, which achieves exponential signal amplification by releasing double the signal probes per reaction cycle. This integrated design enables electrochemical, colorimetric, and photothermal trimodal output, with exceptional detection limits (LOD, S/N = 3) of 31.4 aM, 1.32 fM, and 1.14 fM respectively, alongside built-in self-verification and correction for enhanced reliability. Practical validation with real samples shows strong agreement with qPCR results, high spiked recovery rates (96.1-103.4%), excellent repeatability, and outstanding stability. Consequently, this trimodal system presents a novel, robust approach for pathogen detection and, via its adaptive intelligent multisignal cross-checking, offers a highly promising technological platform for complex sample analysis in early agricultural disease diagnosis, food safety monitoring, and clinical diagnostics.
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