Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis. The "digital" microfluidic biochips are manipulating liquids not as a continuous flow, but as discrete droplets, and hence they are highly reconfigurable and scalable. A digital biochip is composed of a two-dimensional array of cells, together with reservoirs for storing the samples and reagents. Several adjacent cells are dynamically grouped to form a virtual device, on which operations are executed. During the execution of an operation, the virtual device can be reconfigured to occupy a different group of cells on the array. In this paper, we present a Tabu Search metaheuristic for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determines the allocation, resource binding, scheduling and placement of the operations in the application. In our approach, we consider moving the modules during their operation, in order to improve the completion time of the biochemical application. The proposed heuristic has been evaluated using three real-life case studies and ten synthetic benchmarks.
Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis. The "digital" microfluidic biochips are manipulating liquids not as a continuous flow, but as discrete droplets, and hence they are highly reconfigurable and scalable. A digital biochip is composed of a two-dimensional array of cells, together with reservoirs for storing the samples and reagents. Several adjacent cells are dynamically grouped to form a virtual device, on which operations are performed. So far, researchers have assumed that throughout its execution, an operation is performed on a rectangular virtual device, whose position remains fixed. However, during the execution of an operation, the virtual device can be reconfigured to occupy a different group of cells on the array, forming any shape, not necessarily rectangular. In this paper, we present a Tabu Search metaheuristic for the synthesis of digital microfluidic biochips, which, starting from a biochemical application and a given biochip architecture, determines the allocation, resource binding, scheduling and placement of the operations in the application. In our approach, we consider changing the device to which an operation is bound during its execution, to improve the completion time of the biochemical application. Moreover, we devise an analytical method for determining the completion time of an operation on a device of any given shape. The proposed heuristic has been evaluated using a real-life case study and ten synthetic benchmarks.
Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis. The "digital" biochips are manipulating liquids as discrete droplets on a two-dimensional array of electrodes. Basic microfluidic operations, such as mixing and dilution, are performed on the array, by routing the corresponding droplets on a series of electrodes. So far, researchers have assumed that these operations are executed on virtual rectangular devices, formed by grouping several adjacent electrodes. One drawback is that all electrodes are considered occupied during the operation execution, although the droplet uses only one electrode at a time. Moreover, the operations can actually be performed by routing the droplets on any sequence of electrodes on the microfluidic array. Hence, in this paper, we eliminate the concept of virtual devices and allow the droplets to move on the chip on any route during operation execution. Thus, the synthesis problem is transformed into a routing problem. We develop an algorithm based on a Greedy Randomized Adaptive Search Procedure (GRASP) and we show that routing-based synthesis leads to significant improvements in the application completion time compared to traditional synthesis based on virtual devices. However, the disadvantage of the routing-based approach is that it may contaminate larger areas of the biochip, when synthesizing applications containing liquids which may adsorb on the surface of the microfluidic array. We have extended the GRASP-based algorithm to consider contamination avoidance during routing-based synthesis. Several real-life examples and synthetic benchmarks are used to evaluate the proposed approaches.
Microfluidic biochips represent an alternative to conventional biochemical analyzers. A digital biochip manipulates liquids not as continuous flow, but as discrete droplets on a two-dimensional array of electrodes. Several electrodes are dynamically grouped to form a virtual device, on which operations are executed by moving the droplets. So far, researchers have ignored the locations of droplets inside devices, considering that all the electrodes forming the device are occupied throughout the operation execution. In this article, we consider a droplet-aware execution of microfluidic operations, which means that we know the exact position of droplets inside the modules at each time-step. We propose a Tabu Search-based metaheuristic for the synthesis of digital biochips with droplet-aware operation execution. Experimental results show that our approach can significantly reduce the application completion time, allowing us to use smaller area biochips and thus reduce costs.
Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the basic functions for biochemical analysis. The "digital" microfluidic biochips are manipulating liquids not as a continuous flow, but as discrete droplets on a two-dimensional array of electrodes. Basic microfluidic operations, such as mixing and dilution, are performed on the array, by routing the corresponding droplets on a series of electrodes. So far, researchers have assumed that these operations are executed on rectangular virtual devices, formed by grouping several adjacent electrodes. One drawback is that all electrodes are considered occupied during the operation execution, although the droplet uses only one electrode at a time. Moreover, the operations can actually execute by routing the droplets on any sequence of electrodes on the array. Hence, in this paper, we eliminate the concept of virtual modules and allow the droplets to move on the chip on any route during operation execution. Thus, the synthesis problem is transformed into a routing problem. We propose an approach derived from a Greedy Randomized Adaptive Search Procedure (GRASP) and we show that by considering routing-based synthesis, significant improvements can be obtained in the application completion time.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.