3D-Printed Array Helical Monolithic Column Chip with Hierarchical Porous Structure for High-Throughput ICP-MS Analysis of Trace Rare-Earth Elements

作者
Cheng Lei,Man He,Beibei Chen,Bin Hu
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:97 (37): 20389-20398 被引量:1
标识
DOI:10.1021/acs.analchem.5c03633
摘要

Three-dimensional printing (3DP) technology enables the flexible fabrication of integrated monolithic microextraction chips for high-throughput sample pretreatment. Meanwhile, the extraction performance of 3DP-based channels is largely limited by printer resolution and the commercially available printing materials. In this work, a 3DP array monolithic microextraction chip (AMC) was fabricated by integrating 26-array helical monolithic microextraction channels for sample pretreatment and 52-array gas valves for fluid control. 3DP with a liquid crystal display, switching between flexible and rigid resins, was employed to fabricate fluid-control valves and helical microchannels, respectively. Hierarchical porous monolithic column in microchannels was obtained by in-situ polymerization of a high internal phase Pickering emulsion, with carbonyl-containing covalent organic frameworks (COFs) employed for the first time as both emulsifier and stabilizer. The amphiphilic COFs with balanced hydrophilic carbonyl groups and hydrophobic benzene rings was selected to facilitate the emulsion template formation for the monolith's porous structure while providing effective functional sites for adsorption. The helical shape and internal hierarchical porous structure of the monolithic column both help to improve mass transfer during adsorption and desorption. Based on the above facts, a method by online coupling 3DP-AMC with inductively coupled plasma-mass spectrometry (ICP-MS) detection was developed for the analysis of rare-earth elements (REEs) in environmental samples. The developed method has a high sample throughput (30 h-1), a wide linear range (0.001-50 μg L-1), low limits of detection (0.3-0.8 ng L-1), and good precisions (relative standard deviations of 2.7%-9.4%). Its application potential was demonstrated by analyzing trace/ultratrace REEs in different samples with complicated matrix, including atmospheric particulate matter, environmental water, soil, human urine, and human hair.
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