Single-step batch fabrication of microfluidic paper-based analytical devices with a 3D printer and their applications in nanoenzyme-enhanced visual detection of dopamine

• Published in: Analytical and bioanalytical chemistry Vol. 416; no. 18; pp. 4131 - 4141
• Main Authors: Yan, Yongkang, Huang, Xueer, Yuan, Lili, Tang, Yiyue, Zhu, Wenli, Du, Hancong, Nie, Jinfang, Zhang, Lang, Liao, Shan, Tang, Xuehui, Zhang, Yun
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2024; Springer Nature B.V
• Subjects: 3-D printers; Analytical Chemistry; Biochemistry; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Colorimetry; Dopamine; Fabrication; Food safety; Food Science; Laboratory Medicine; Metal-organic frameworks; Microfluidics; Monitoring/Environmental Analysis; Nanosensors; Polyethylene; Polyethylenes; Poultry feed; Printing; Research Paper; Waxes; Paper-based microfluidics; Colorimetric assay; Metal-organic frameworks; Smartphone; 3D printing
• ISSN: 1618-2642; 1618-2650
• DOI: 10.1007/s00216-024-05337-2

Wax printing is the most widely used method for fabricating microfluidic paper-based analytical devices (μPADs), but it still suffers from disadvantages like discontinuation of wax printers and need for additional equipment for heating treatment. To address these issues, this work initially describes a new class of wax printing approach for high-precision, batch fabrication of μPADs using a household 3D printer. It only involves a one patterning step of printing polyethylene wax into rice paper body. Under optimized parameters, a fabrication resolution, namely the minimum hydrophilic channel width, down to ~189 ± 30 μm could be achieved. In addition, the analytical applicability of such polyethylene wax-patterned μPADs was demonstrated well with enhanced colorimetric detection of dopamine as a model analyte by combining metal-organic framework (MOF) based nanoenzymes (ZIF-67) with a smartphone (for portable quantitative readout). The developed nanosensor could linearly detect dopamine over a concentration range from 10 to 1000 μM, with a detection limit of ca. 2.75 μM (3σ). The recovery results for analyzing several real samples (i.e., pig feed, chicken feed, pork and human serum) were between 91.82 and 102.79%, further validating its good detection accuracy for potential practical applications in food safety and medical diagnosis. Graphical Abstract