摘要
In this study,we developed a single-beam optical trap-based surface-enhanced Raman scattering(SERS)optofluidic molecular fingerprint spectroscopy detection system.This system utilizes a single-beam optical trap to concentrate free silver nanoparticles(AgNPs)within an optofluidic chip,significantly enhancing SERS performance.We investigated the optical field distribution characteristics within the tapered fiber using COMSOL simulation software and established a MATLAB simulation model to validate the single-beam optical trap's effectiveness in capturing AgNPs,demonstrating the theoretical feasibility of our approach.To verify the particle capture efficacy of the system,we experimentally controlled the optical trap's on-off state to manage the capture and release of particles precisely.The experimental results indicated that the Raman signal intensity in the capture state was significantly higher than in the non-capture state,confirming that the single-beam optical trap effectively enhances the SERS detection capability of the optofluidic detection system.Furthermore,we employed Raman mapping techniques to investigate the impact of the capture area on the SERS effect,revealing that the spectral intensity of molecular fingerprints in the laser-trapping region is significantly improved.We successfully detected the Raman spectrum of crystal violet at a concentration of 10^(−9)mol/L and pesticide thiram at a concentration of 10^(−5)mol/L,further demonstrating the ability of the single-beam optical trap in enhancing the molecular fingerprint spectrum identification capability of the SERS optofluidic chips.The optical trapping SERS optofluidic detection system developed in this study,as a key component of an integrated optoelectronic sensing system,holds the potential for integration with portable high-power lasers and high-performance Raman spectrometers.This integration is expected to advance highly integrated technologies and significantly enhance the overall performance and portability of optoelectronic sensing systems.
基金
financial supports from National Natural Science Foundation of China(62175023).
