Open AccessHigh-performance surface-enhanced Raman spectroscopy chip integrated with a micro-optical system for the rapid detection of creatinine in serum
Author(s) -
Feng Yang,
Ping Wen,
Gang Li,
Zhisen Zhang,
Changrong Ge,
Li Chen
Publication year - 2021
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.434053
Subject(s) - surface enhanced raman spectroscopy , detection limit , materials science , raman spectroscopy , raman scattering , substrate (aquarium) , lens (geology) , chip , nanotechnology , optoelectronics , optics , chemistry , computer science , chromatography , telecommunications , physics , oceanography , geology
To improve the sensitivity of disease biomarker detection, we proposed a high-performance surface-enhanced Raman spectroscopy (SERS) chip integrated with a micro-optical system (MOS). The MOS, which is based on the micro-reflecting cavity and the micro-lens, optimizes the optical matching characteristics of the SERS substrate and the Raman detection system, and greatly improves the SERS detection sensitivity by improving the collection efficiency of the Raman scattering signal. A uniform single layer of silver nanoparticles on a gold film was prepared as the SERS substrate using a liquid-liquid interface self-assembly method. The micro-reflecting cavity and micro-lens were prepared using micro-processing technology. The SERS chip was constructed based on the MOS and the Au film-based SERS substrate, and experimental results showed an EF of 1.46×10 8 , which is about 22.4 times higher than that of the Si-based SERS substrate. The chip was used for the detection of creatinine and the detection limit of creatinine in aqueous solution was 1 µM while the detection limit in serum was 5 µM. In addition, SERS testing was conducted on serum samples from normal people and patients with chronic renal impairment. Principal component analysis and linear discriminant analysis were used for modeling and identification, and the results showed a 90% accuracy of blind sample detection. These results demonstrate the value of this SERS chip for both research and practical applications in the fields of disease diagnosis and screening.