Journal ArticleDOI
A New Fluid-Chip Co-Design for Digital Microfluidic Biochips Considering Cost Drivers and Design Convergence
Arpan Chakraborty,Piyali Datta,Rajat Kumar Pal +2 more
- Vol. 4, Iss: 4, pp 548-564
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TLDR
This paper aims to propose a fluid-chip co-design methodology in dealing with the consideration of the fluid- chip cost drivers, while reducing the design cycles in between.Abstract:
The design process for digital microfluidic biochips (DMFBs) is becoming more complex due to the growing need for essential bio-protocols. A number of significant fluid- and chip-level synthesis tools have been offered previously for designing an efficient system. Several important cost drivers like bioassay schedule length, total pin count, congestion-free wiring, total wire length, and total layer count together measure the efficiency of the DMFBs. Besides, existing design gaps among the sub-tasks of the fluid and chip level make the design process expensive delaying the time-to-market and increasing the overall cost. In this context, removal of design cycles among the sub-tasks is a prior need to obtain a low-cost and efficient platform. Hence, this paper aims to propose a fluid-chip co-design methodology in dealing with the consideration of the fluid-chip cost drivers, while reducing the design cycles in between. A simulation study considering a number of benchmarks has been presented to observe the performance.read more
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Proceedings ArticleDOI
A Design Optimization for Pin-Constrained Paper-based Digital Microfluidic Biochips Integrating Fluid-Control Co-Design Issues
TL;DR: This paper presents a fluid-control co-design considering several important cost-driving issues like minimization of schedule length, control pin count, and wirelength, together with congestion-free and conflict-free wiring.
Journal ArticleDOI
An Integrated Co-Design of Flow-Based Biochips Considering Flow-Control Design Issues and Objectives
TL;DR: With increasing effectiveness of flow-based microfluidic biochips in the field of biochemical experiments and point-of-care diagnosis, design automation demands enormous attention to integrate the technology into the design process.
Journal ArticleDOI
A Predictive Model for Fluid-Control Codesign of Paper-Based Digital Biochips Following a Machine Learning Approach
TL;DR: A machine learning-based model is built to predict violation in control design beforehand and accordingly guides the fluid-control codesign to tackle important cost-driving issues while attaining congestion- and conflict-free wiring and effectively eliminates the design cycles producing a low-cost platform.
Journal ArticleDOI
Attack-Detection and -Recovery: An Integrated Approach Towards Attack-Tolerant Cyber-Physical Digital Microfluidic Biochips
TL;DR: In this article , an attack-tolerant synthesis is proposed with two-way security through integrating attack-detection and attack-recovery from various Denial of Service attacks.
References
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