Over the past few decades, surface-enhanced Raman spectroscopy (SERS) has garnered respect as an analytical technique with significant chemical and biological applications. SERS is important for the life sciences because it can provide trace level detection, a high level of structural information, and enhanced chemical detection. However, creating and successfully implementing a sensitive, reproducible, and robust SERS active substrate continues to be a challenging task. Herein, we report a novel method for SERS that is based upon using multiplexed microfluidics (MMFs) in a polydimethylsiloxane platform to perform parallel, high throughput, and sensitive detection/identification of single or various analytes under easily manipulated conditions. A facile passive pumping method is used to deliver Ag colloids and analytes into the channels where SERS measurements are done under nondestructive flowing conditions. With this approach, SERS signal reproducibility is found to be better than 7%. Utilizing a very high numerical aperture microscope objective with a confocal-based Raman spectrometer, high sensitivity is achieved. Moreover, the long working distance of this objective coupled with an appreciable channel depth obviates normal alignment issues expected with translational multiplexing. Rapid evaluation of the effects of anion activators and the type of colloid employed on SERS performance are used to demonstrate the efficiency and applicability of the MMF approach. SERS spectra of various pesticides were also obtained. Calibration curves of crystal violet (non-resonant enhanced) and Mitoxantrone (resonant enhanced) were generated, and the major SERS bands of these analytes were observable down to concentrations in the low nM and sub-pM ranges, respectively. While conventional random morphology colloids were used in most of these studies, unique cubic nanoparticles of silver were synthesized with different sizes and studied using visible wavelength optical extinction spectrometry, scanning electron microscopy, and the MMF-SERS approach.
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