Jeevan Maddala

Traffic of pairs of drops in microfluidic ladder networks with fore-aft structural asymmetry

We investigate the dynamics of pairs of drops in microfluidic ladder networks with slanted bypasses, which break the fore-aft structural symmetry of the network. Our analytical results indicate that unlike symmetric ladder networks, structural asymmetry introduced by a single slanted bypass can be used to modulate the relative drop spacing, enabling them to contract, synchronize, expand, or even flip at the ladder exit. Our experiments confirm all these behaviors predicted by theory. Numerical analysis further shows that while ladder networks containing several identical bypasses are limited to nearly linear transformation of input delay between drops, combination of forward and backward slanted bypasses can cause significant nonlinear transformation enabling coding and decoding of input delays.

Design of multi-functional microfluidic ladder networks to passively control droplet spacing using genetic algorithms

Abstract Accelerated progress in the use of droplet-based microfluidics for high throughput screening and biochemical analysis will require development of devices that are robust to experimental uncertainties and which offer multiple functionalities. Achieving precise functionalities in microfluidic devices is challenging because droplets exhibit complex dynamic behavior in these devices due to hydrodynamic interactions and discontinuities that are a result of discrete decision-making at junctions. For example, even a simple loop device can show transitions from periodic to aperiodic/chaotic behavior based on input conditions. Hence, rational design frameworks that handle this complexity are required to move this field from labs to industrial practice. Two main challenges that need to be confronted in the realization of such a rational design framework are: (i) computational science related to rapid simulation of very large networks; development of predictive models that will form the basis for characterizing droplet motion through interconnected and intricate large-scale networks, and (ii) conceptualization of a design approach that is generic in nature and not very narrowly defined limiting its application potential. In this paper, we develop a GA approach for the design of ladder networks that are used to control the relative droplet distance at the exit. Through several case studies, the potential of the proposed GA approach in designing exquisite ladder structures for multiple functions is demonstrated. A recently proposed network model is used as the basis for all the computational studies reported in this paper.

A Genetic Algorithm (GA) based rational approach for design of discrete microfluidic networks

Abstract Droplet based microfluidic devices are widely used in protein crystallization, high throughput screening and biochemical assays. These devices are complex with even a simple loop device exhibiting varied nonlinear behavior. Therefore, any approach for engineering optimal multi-functional devices has to deal with the vast design space that has to be potentially explored for a solution. As a result, there is a need for efficient algorithms that can handle this complexity. In this paper, GA is proposed as a promising solution approach for this problem. We demonstrate the power of the proposed GA methodology in designing multi-functional ladder devices that are extremely difficult to uncover using expensive experimental trial-and-error loops. The GA methodology can be further enhanced for designing other complex microfluidic systems.

Sort-synchronization control in microfluidic loop devices with experimental uncertainties using a model predictive control (MPC) framework

Abstract Droplet microfluidic devices are being used in several applications. Increasing sophistication of these applications require precise control of the droplet behavior in such devices. However, it has been shown that even the simplest loop devices (a channel that splits into two arms and subsequently recombines) can demonstrate nonlinear behavior like period doubling, bifurcations and chaos. This behavior of the droplets makes control using traditional methods difficult. In this paper, a model based control algorithm is proposed for active sort-synchronization control in microfluidic devices. A recently proposed network model is used in this control. The control concepts are demonstrated on simulation studies using a prototypical loop device.

Modeling and Control Challenges in the development of Discrete Microfluidic Devices

Abstract Droplet-based microfluidics is an emerging area that has important applications in chemical engineering and several other disciplines. For example, these devices have applications in the areas of bubble computers, cancer diagnostics and development of microfactories on a chip. Some of the challenges that need to be overcome to realize the potential of this area are related to experimental uncertainties and development of devices that offer multiple functionalities, thereby reducing the footprint and aiding in miniaturization. Achieving precise functionalities in microfluidics is challenging because droplets exhibit complex dynamic behavior in these devices due to hydrodynamic interactions and discontinuities that are a result of discrete decision-making at junctions. Remarkably, transitions from periodic to aperiodic/chaotic behavior based on input conditions can be witnessed even in a simple loop device. Hence rational design frameworks that handle this complexity are required to make significant progress. Further, passive designs that achieve such functionalities might entail large footprint. As a result, active control might become a necessity for developing efficient device designs. The main purpose of this paper is the identification of the challenges and opportunities for the PSE community in this area of emerging importance. Further, our work in the area model predictive control (MPC) for active control in a microfluidic loop device will also be briefly described.