Molecularly imprinted 3D SERS sensor with inorganic frameworks for specific and recyclable SERS sensing application.

Area of Science:

• Materials Science
• Nanotechnology
• Analytical Chemistry

Background:

• Surface-enhanced Raman spectroscopy (SERS) faces challenges in selectivity and reusability with traditional Au/Ag nanostructures for real sample analysis.
• Developing robust SERS sensors with specific analyte recognition and regeneration capabilities is crucial for practical applications.

Purpose of the Study:

• To design and fabricate a novel, reusable three-dimensional (3D) SERS sensor with dual functions of selective trapping and photocatalytic degradation.
• To achieve sensitive and selective detection of specific molecules, such as rhodamine 6G (R6G), in complex matrices like food samples.

Main Methods:

• Preparation of a 3D SERS substrate using silicon nanowires array decorated with Au-Ag bimetallic nanoparticles (SiNWs-AuAg).
• Synthesis and immobilization of silicon-based inorganic-framework molecularly imprinted TiO2 (TiO2@SiMIP) onto the SiNWs-AuAg substrate using R6G as a template.
• Evaluation of the sensor's performance for R6G detection, including sensitivity, selectivity, and reusability through photocatalytic degradation.

Main Results:

• The fabricated SiNWs-AuAg/TiO2@SiMIP sensor demonstrated excellent SERS performance and specific affinity for R6G.
• Sensitive detection of R6G in food samples was achieved with a low limit of detection (LOD) of 0.27 nM.
• The sensor exhibited high reusability, with imprinted cavities maintaining good selectivity after regeneration via UV-induced photocatalytic degradation of residual templates.

Conclusions:

• The developed 3D SERS sensor effectively addresses the limitations of poor selectivity and reusability in traditional SERS substrates.
• The dual functionality of selective trapping and photocatalytic degradation enables sensitive, selective, and repeatable detection of target analytes.
• This novel sensor platform holds significant promise for reliable and sustainable SERS-based detection in real-world applications, particularly in food safety analysis.