Studies of Sample Compartmentalization By Microfluidic Methods

Abstract

Miniaturization of reaction volumes into nanoliter sized droplets makes today's chemical analysis cheaper, faster, and more sensitive. These droplets can be generated by a variety of microfluidic methods that provide great control over size and composition, and can be performed at high speed. Other methods for droplet mixing and docking have been developed to allow droplet manipulation and subsequent analysis in continuous flow. These methods are designed to be modular systems, allowing the user to interchange or combine different methods in a "Lab on a Chip". The coupling of droplet generation, droplet manipulation, and analysis modules can be challenging if there is a mismatch between droplet generation frequency and time required to perform additional tasks in separate modules. As a result, droplet microfluidic methods can be very complex and can be less attractive for end-user applications, in particular in the biological sciences. During the past years, a new generation of microfluidic droplet platforms emerged which is called self-digitization and is novel for its simplicity. In this method an aqueous sample is compartmentalized into smaller droplets by an immiscible phase and stored on-site. Self-digitization does not require complex microfluidic design or complex pumping and valving technologies to generate droplets. The volume of these droplets is predefined by the geometry of microfluidic wells and this gives rise to loss-less filling of large arrays of nanoliter wells. The droplets can then be addressed and monitored over time as their positions are registered in an array of static droplets. This thesis summarizes the progress in the development of sample self-digitization in microfluidic arrays of side chambers and bottom wells, and provides a perspective view of the potential applications of this next generation droplet platform.