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Proceedings ArticleDOI

A Design Optimization for Pin-Constrained Paper-based Digital Microfluidic Biochips Integrating Fluid-Control Co-Design Issues

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TLDR
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.
Abstract
Paper-based digital microfluidic biochips (PDMFBs) are becoming highly effective among the microfluidic platforms due to its low-cost and in-place fabrication. The designed electrodes and wiring can be fabricated on a piece of paper by an inkjet printer and conductive ink containing carbon nanotube particles (CNTs). However, due to induced control interference, the wires cannot pass by an arbitrary electrode. Each wire that is to be routed possesses its conflict electrode group, which must be avoided for a feasible droplet movement. 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. Observably, design gaps exist among the sub-tasks of the fluid-level, control-level, and fluid-control as a whole, due to their separate considerations. It indeed introduces many design cycles lengthening the design process, and thus increases the overall cost. In this context, this work integrates the sub-tasks as a prior need to obtain a low cost and efficient platform. Several benchmarks have been studied to evaluate the performance.

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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.
References
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Principles of Artificial Intelligence

TL;DR: This classic introduction to artificial intelligence describes fundamental AI ideas that underlie applications such as natural language processing, automatic programming, robotics, machine vision, automatic theorem proving, and intelligent data retrieval.
Proceedings ArticleDOI

Broadcast electrode-addressing for pin-constrained multi-functional digital microfluidic biochips

TL;DR: A broadcast-addressing-based design technique for pin-constrained multi-functional biochips that provides high throughput for bioassays and it reduces the number of control pins by identifying and connecting control pins with "compatible" actuation sequences.
Journal ArticleDOI

Active digital microfluidic paper chips with inkjet-printed patterned electrodes.

TL;DR: Active, paper-based, microfluidic chips driven by electrowetting are fabricated and demonstrated for reagent transport and mixing, which should allow point-of-care production and diagnostic activities in the future.
Journal ArticleDOI

Paper-Based Biochip Assays and Recent Developments: A Review

TL;DR: Paper-based biochips have become of much interest for development of biomolecule sensing as discussed by the authors, and they have become a biomarker for diagnosis of diseases, and they can be used to detect biomolecules in human body.
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