By Topic

Automated Cell Transport in Optical Tweezers-Assisted Microfluidic Chambers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
Chowdhury, S. ; Dept. of Mech. Eng., Univ. of Maryland, College Park, MD, USA ; Svec, P. ; Chenlu Wang ; Seale, K.T.
more authors

In this paper, we present a physics-aware, planning approach for automated transport of cells in an optical tweezers-assisted microfluidic chamber. The approach can be used for making a uniform distribution of cells inside the chamber to allow the study of a variety of biological processes, including cell signaling. Fluid forces inside the chamber, modeled using computational fluid dynamics, are incorporated into the widely used Langevin equation to simulate the motion of cells. The developed simulator was used for building a map that contains probabilities of a cell successfully reaching one of the outlets of the chamber from different locations under the influence of the fluid flow. The developed planner not only generates collision-free paths that exploit the fluid flow inside the chamber but also utilizes the offline generated simulation data to decide suitable locations for releasing the cells. This ensures fast and robust cell transport, while minimizing the required laser power and operational time. The planner is based on the heuristic D* Lite algorithm that employs a specific cost function for searching over a novel state-action space representation. The effectiveness of the planning algorithm is demonstrated using both simulation and physical experiments in a microfluidics-optical tweezers hybrid manipulation setup.

Published in:

Automation Science and Engineering, IEEE Transactions on  (Volume:10 ,  Issue: 4 )