アコースティック流体技術を用いたニコチン酸の高感度・高速SERS検出
Lei Wu1, Wenjing Zhang1, Zefan Xu1
1Advanced Photonics Center, School of Electronic Science and Engineering, Southeast University, 2 Sipailou, Nanjing, 210096, China.
Abstract:
The growing demand for sensitive and rapid detection of small biochemical molecules, ranging from spanning metabolites, toxins to active pharmaceutical ingredients, has driven significant advancements in analytical sciences. Surface enhanced Raman spectroscopy (SERS) stands out as a powerful molecular sensing tool because it delivers unique vibrational fingerprints that enable label-free identification and quantification. However, the full potential of SERS technique is frequently hindered by the slow mass transport and the inefficient adsorption of target molecules onto the plasmonic substrates. This study proposes an innovative solution by integrating acoustofluidic technology with SERS to enhance the detection efficiency. Specifically, theoretical analysis and experimental validation were systematically combined to clarify how acoustic streaming influences the adsorption kinetics of target molecules onto SERS substrates, and how these changes result in improved detection efficiency and sensitivity. Through the activation of acoustic streaming, the microfluidic chip demonstrates significantly improved molecular dynamics and signal amplification. Experimental findings reveal a marked reduction in reaction time from 30 to 12 min and a tenfold improvement in the limit of detection to 100 nM. The real-world applicability of this integrated approach is validated through the analysis of nicotinic acid in Gynostemma pentaphyllum, a common health supplement. This work pioneers the seamless on-chip coupling of acoustofluidic streaming with a standard SERS substrate, significantly improving the detection performance. The SERS-acoustofluidic platform constitutes a highly promising molecular sensor for rapid and ultrasensitive biochemical analysis, with broad translational potential across food-safety assurance and healthcare-monitoring applications.
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