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• W4386497282 startingPage "341792" @default.
• W4386497282 abstract "Combining microfluidics with mass spectrometry (MS) analysis has great potential for enabling new analytical applications and simplifying existing MS workflows. The rapid development of 3D printing technology has enabled direct fabrication of microfluidic channels using consumer grade 3D printers, which holds great promise to facilitate the adoption of microfluidic devices by the MS community. However, photo polymerization-based 3D printed devices have an issue with chemical leeching, which can introduce contaminant molecules that may present as isobaric ions and/or severely suppress the ionization of target analytes when combined with MS analysis. Although extra cure and washing steps have alleviated the leeching issue, many such contaminant peaks can still show up in mass spectra. In this work, we report a simple surface modification strategy to isolate the chemical leachates from the channel solution thereby eliminating the contaminant peaks for MS analysis. The channel was prepared by fabricating a layer of polydimethylsiloxane graft followed by wetting the graft using silicone oil. The resulting liquid infused surface (LIS) showed significant reduction in contaminant peaks and improvement in the signal intensity of target analytes. The coating showed good stability after long-term usage (7 days) and long-term storage (∼6 months). Finally, the utility of the coating strategy was demonstrated by printing herringbone microfluidic mixers for studying fast reaction kinetics, which obtained comparable reaction rates to literature values. The effectiveness, simplicity, and stability of the present method will promote the adoption of 3D printed microdevices by the MS community." @default.
• W4386497282 created "2023-09-07" @default.
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• W4386497282 date "2023-10-01" @default.
• W4386497282 modified "2023-10-15" @default.
• W4386497282 title "Unlocking the potential of 3D printed microfluidics for mass spectrometry analysis using liquid infused surfaces" @default.
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• W4386497282 doi "https://doi.org/10.1016/j.aca.2023.341792" @default.
• W4386497282 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37827686" @default.
• W4386497282 hasPublicationYear "2023" @default.
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