Magnetic-assisted surface-enhanced Raman spectroscopy of Fe3O4@C/Ag nanostructures for non-invasive, enzyme-free and ultrasensitive detection of glucose in urine for clinical diagnostics
Year: 2025
Type: article
Abstract: Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique capable of directly detecting target molecules with ultrasensitivity down to the single-molecule level via their characteristic vibrational fingerprints. While SERS has achieved significant success in detecting various analytes such as organic dyes, pesticides, explosives, and bacteria, the direct detection of glucose – a vital biomarker for diabetes diagnosis and management – remains challenging due to its low affinity for bare metal surfaces and inherently weak Raman scattering cross-section. Despite these limitations, SERS offers a promising alternative to traditional enzyme-based glucose detection methods, which require invasive blood sampling and are highly susceptible to environmental fluctuations such as pH and temperature. In this work, we report the design of Fe 3 O 4 @C/Ag nanostructures as a high-performance SERS substrate for non-invasive, enzyme-free, and ultrasensitive glucose detection in artificial urine. The carbon shell provides good glucose adsorption, while the Ag coating ensures strong plasmonic enhancement. Notably, we introduce a magnetic-assisted SERS (MA-SERS) strategy in which the Fe 3 O 4 @C/Ag nanostructures are dispersed into urine samples to capture glucose and subsequently magnetically retrieved for SERS analysis. This platform enables direct glucose detection at concentrations as low as 0.21 mM, significantly below the clinical prediabetes threshold (5.6 mM), with excellent recovery values ranging from 92 % to 109 %. These results demonstrate the strong potential of the MA-SERS approach as a practical, non-invasive, and enzyme-free diagnostic tool for early detection and monitoring of diabetes.
Source: Nano-Structures & Nano-Objects
Authors: Thi Hanh Trang Dang, Quan-Doan Mai, Thi Linh Dong, Trung Thanh Nguyen, Thi Loan Ngo, Thi Lan Nguyen, Xuan Quang Nguyen, Ta Ngoc Bach, Anh-Tuan Pham, Anh-Tuan Le
Language: English
Field: Materials Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,130
Funder: Trường Đại học PHENIKAA
OpenAlex ID: W7082969236