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pH‐Responsive DNA‐Functionalized Liquid Metal–Organic Frameworks (L‐MOFs) as Molecular Sponges for Ultrasensitive and Label‐Free SERS Detection of Folic Acid
Author(s) -
Liu Xu,
Glazutdinova Liliia,
Wu Guangrun,
Yang Wenxu,
Liu Hongbo,
Shen Yifu,
Zhang Siyao,
Wu Jing,
Ji Haoyu,
Gao Lixin,
Gao Xinlu,
Zhao Jiayi,
Li Yang,
Liu Yu
Publication year - 2025
Publication title -
small
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.785
H-Index - 236
eISSN - 1613-6829
pISSN - 1613-6810
DOI - 10.1002/smll.202412267
Subject(s) - biomolecule , detection limit , raman spectroscopy , materials science , folic acid , nanotechnology , metal organic framework , combinatorial chemistry , chemistry , chromatography , organic chemistry , medicine , adsorption , physics , optics
Abstract Although “hotspots” have been utilized to enhance Raman signals for detecting various biomolecules, precisely regulating “hotspot” dimensions within enhancement substrates remains a significant challenge. This study introduces a novel, easily fabricated surface‐enhanced Raman spectroscopy sensor, T 6 (OH⁻)/Ag@CC. This platform employs single‐stranded DNA of adjustable lengths to mediate the self‐assembly of silver nanoparticles (Ag NPs), resulting in a uniformly enhanced substrate with a spatially organized metal–organic frameworks architecture. The DNA‐mediated self‐assembly exhibits pH‐responsive characteristics, enabling precise control over “hotspot” distribution. Comprehensive characterization and Raman enhancement experiments demonstrate that optimal self‐assembly and signal amplification are achieved under alkaline conditions. The sensor demonstrates excellent reproducibility and sensitivity, enabling the label‐free detection of folic acid with a detection limit as low as 0.1 ng mL −1 . Validation using real‐world food and biological samples highlights its ability to accurately detect and identify folic acid fingerprints in spinach, chicken liver, and various human biological fluids, including breast milk, serum, erythrocytes, and urine. The analysis of characteristic peak intensities underscores the potential of this method as a versatile and unified approach for folic acid detection across diverse sample matrices.
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