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ACS Sensors

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ACS Sensors


December 26, 2025

Volume 10, Issue 12

Pages 9105-9466



Trap-Based Microfluidic Device with Retrievable Droplet for the Analysis of Pollutants from Slurry Solutions


Liquid–liquid microextraction (LLME) is a cost-effective sample pretreatment method for the analysis of trace analytes in various samples, such as water, blood, urine, and others. In LLME, the high surface area-to-volume ratio of the extractant enables fast accumulation of analytes from the sample into the extractant. The analyte-loaded extractant can easily be analyzed by using common analytical instruments such as liquid or gas chromatography, mass spectrometry, and others. However, a critical drawback of LLME is that when the sample contains solid fragments, microextraction must be preceded by a removal step, which can result in the loss of the analyte and compromise the detection. In this work, we demonstrate microextraction of analytes from a slurry solution without the need for an additional pretreatment step using a trap-based microfluidic device with a retrievable extractant. The extractant, 1-Octanol, is loaded into a microchamber that is in contact with a microchannel that continuously introduces the sample solution. As the solution flows in the microchannel, the intimate contact of the solution with the extractant enables the fast extraction of analytes. Using Nile red (NR) as a model analyte, we demonstrate the influence of the analyte concentration and the flow rate of the sample solution on the extraction. As a proof-of-concept, we show successful extraction of trace amounts of perfluorooctanoic acid (PFOA) from water. More importantly, the device enables one-step extraction of target analytes, e.g., carbamazepine (CBZ), from a concentrated sand suspension. The extracted CBZ is easily analyzed by using high-performance liquid chromatography, eliminating the need to remove the solid content prior to extraction. The approach shown in this work can potentially be applied to various fields, such as drug detection, environmental pollution monitoring, or food safety for pesticide residue analysis.

  • Sung Wook Choi
  • Dong Hyeong Kim
  • Soo-Hwan Jeong
  • Ju Hyeon Kim
  • Jae Bem You


https://pubs.acs.org/doi/10.1021/acssensors.5c01878


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