Issue 25, 2016

Microfluidic flow-injection thermal-lens microscopy for high-throughput and sensitive analysis of sub-μL samples

Abstract

An analytical method combining microfluidic flow-injection analysis (μFIA) with thermal-lens microscopy (TLM) was developed for high-throughput and sensitive analysis of sub-μL samples. The performance of μFIA-TLM was validated for detection of hexavalent chromium [Cr(VI)] in water samples. At different sample injection volumes, detection positions, and flow rates, the influence of the reaction time and the diffusion of Cr–diphenylcarbazone (DPCO) complexes on the μFIA-TLM signal were investigated. Photodegradation of the Cr–DPCO complex was clearly observed when the absorbed photons per Cr–DPCO molecule were above 1600. After optimization of TLM with respect to rapid flows (up to 10 cm s−1), we achieved a limit of detection of 0.6 ng mL−1 for Cr(VI) in a 50 μm deep channel. The impacts of interfering ions [V(V), Mo(VI), and Fe(III)] on Cr(VI) determination were found to be small. Cr(VI) contents in real samples from a cement factory were determined and found to be in good agreement with the results of spectrophotometry. This μFIA-TLM shows advantages over its conventional counterpart, such as eliminating additional sample conditioning, reducing by over 100 times the sample consumption to sub-μL volumes, and reducing by over 10 times the time required for one sample injection to a few seconds (up to 20 samples per min). The optimized μFIA-TLM setup can be applied for fast and sensitive analysis of nonfluorescent sub-μL samples in rapidly flowing mediums.

Graphical abstract: Microfluidic flow-injection thermal-lens microscopy for high-throughput and sensitive analysis of sub-μL samples

Article information

Article type
Paper
Submitted
31 မတ် 2016
Accepted
23 မေ 2016
First published
25 မေ 2016

Anal. Methods, 2016,8, 5053-5060

Microfluidic flow-injection thermal-lens microscopy for high-throughput and sensitive analysis of sub-μL samples

M. Liu, S. Malovrh and M. Franko, Anal. Methods, 2016, 8, 5053 DOI: 10.1039/C6AY00932H

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