Genetic Algorithm for the Design of Microchip Flow Cytometers

, , , , , ,

Keywords: , , , ,

Robot designers and artificial-intelligence researchers have long been inspired by living things. Now, we are trying to mimic some of the most fundamental features of life while designing micro devices. In this paper we proved that the design of a micro system can evolve through the genetic algorithm (GA), a digital Darwinism. Partly due to its short history of the lab-on-a-chip industry, design problems have been solved by trial-and-error dictated by design specifications and guided by the experience and intuition of the designer. This time, we suggest a robust methodology for optimizing microchannel devices. We adopted the GA while optimizing two types of commercial microchip flow cytometers. One detects signal with spatial imaging in a single channel and the other detects fluorescence intensity of particles with a spot laser in a focusing channel. The GA has been implemented to run in parallel on multiple computers. By making it as a JAVA applet, anyone who can access the internet through any kinds of web browsers can participate in our project by just visiting our web page. With this publicity, our parallel implementation gets rid of the burden of economical and computational cost for massive calculation loops.

PDF of paper:

Journal: TechConnect Briefs
Volume: 3, Technical Proceedings of the 2007 NSTI Nanotechnology Conference and Trade Show, Volume 3
Published: May 20, 2007
Pages: 93 - 95
Industry sector: Sensors, MEMS, Electronics
Topic: MEMS & NEMS Devices, Modeling & Applications
ISBN: 1-4200-6184-4