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3D Printing of Microfluidics for Point of Care Diagnosis

[+] Author Affiliations
John P. Sibbitt, Mei He

Kansas State University, Manhattan, KS

Paper No. MSEC2017-2778, pp. V004T05A002; 8 pages
  • ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing
  • Volume 4: Bio and Sustainable Manufacturing
  • Los Angeles, California, USA, June 4–8, 2017
  • Conference Sponsors: Manufacturing Engineering Division
  • ISBN: 978-0-7918-5075-6
  • Copyright © 2017 by ASME


Microfluidic lab-on-a-chip (MLOC) technology is a promising approach for point-of-care (POC) diagnosis; low reagent consumption, high sensitivity and quick analysis time are the most prominent benefits. However, microfabrication of MLOCs utilizes specialized techniques and infrastructure, making conventional fabrication time consuming and difficult. While relatively inexpensive production techniques exist for POC diagnoses, such as replication of polymer-based (e.g., PDMS) microfluidic POC devices on lithographic molds, this approach has limitations including: further hydrophilic surface modifications of PDMS, inability to change lithographic mold Z dimensions, and slow prototyping. In contrast, stereo-lithographical (SLA) printing can integrate all of the necessary fabrication resources in one instrument, allowing highly versatile microfluidic devices to be made at low cost. In this paper, we report two microfabrication approaches of microfluidics utilizing (SLA) 3D printing technology: I) Direct SLA printing of channels and structures of a monolithic microfluidic POC device; II) Indirect fabrication, utilizing SLA 3D printed molds for PDMS based microfluidic device replication. Additionally, we discuss previous work providing a proof of concept of applications in POC diagnosis, using direct 3D printing fabrication (approach I). The robustness and simplicity of these protocols allow integrating 3D design and microfabrication with smartphone-based disease diagnosis as a stand-alone system, offering strong adaptability for establishing diagnostic capacity in resource-limited areas and low-income countries.

Copyright © 2017 by ASME



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