Robotic automation of droplet microfluidics

Abstract

Droplet microfluidics enables powerful analytic capabilities but often requires workflows involving macro- and microfluidic processing steps that are cumbersome to perform manually. Here, we demonstrate the automation of droplet microfluidics with commercial fluid-handling robotics. The workflows incorporate common microfluidic devices including droplet generators, mergers, and sorters and utilize the robot's native capabilities for thermal control, incubation, and plate scanning. The ability to automate microfluidic devices using commercial fluid handling will speed up the integration of these methods into biological workflows.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2022
Source ID
10.1063/5.0064265

Entities

People

  • Adam R. Abate
  • Cyrus Modavi
  • Samuel Kim
  • Tuan M. Tran

Organizations

  • California Institute for Quantitative Biosciences
  • Chan Zuckerberg Biohub
  • Chan Zuckerberg Initiative
  • Defense Advanced Research Projects Agency
  • Division of Intramural Research, National Institute of Allergy and Infectious Diseases
  • National Human Genome Research Institute
  • National Institute of Arthritis and Musculoskeletal and Skin Diseases
  • National Institute of Biomedical Imaging and Bioengineering
  • National Science Foundation
  • United States Department of Energy
  • University of California, San Francisco

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Nanoscale Plasmonic Nanotechnology

Technology Areas

  • AI & ML
  • Autonomy