Sample Preparation with Free-Flowing Biochips using Microfluidic Binary-Tree Network

Banerjee, Tapalina; Poddar, Sudip; Bhattacharjee, Sukanta; Song, Yong-Ak; Orozaliev, Ajymurat; Bhattacharya, Bhargab B.

doi:10.1109/iscas45731.2020.9180795

Cited by 3 publications

(7 citation statements)

References 22 publications

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“…We also present a new architecture based on Farey sequence that supports programmability, and at the same time, obviates the need for different injection velocities and precise online injection timing. This improves upon other free-flowing fluidic architectures proposed earlier [4], [20], [21]. We construct a 3D-model of the proposed channel architecture considering shear stress between the wall and fluid layer as well as those between adjacent fluid layers in both parallel and perpendicular directions, and study its behavior via COMSOL simulation framework.…”

Section: Motivationmentioning

confidence: 97%

“…Any defect in elastic micro-valves or micro-pumps may also introduce various microfluidic errors in valvebased CFMBs [2], [3]. Free-flowing programmable architectures that obviate the need for valves as well as split operations were proposed in [4], [20], [21] to overcome these limitations. The work in [4] studies a 2D microfluidic network for implementing dilution on a free-flowing biochip.…”

Section: Preliminaries Of Sample Preparationmentioning

confidence: 99%

“…These designs, however, need variable injection-velocities at input ports and precise timing sequence for fluid injection, which again are hard to implement in practice. Free-flowing biochips resembling a binary tree was proposed in [21] to mitigate these problems. However, on the negative side, they require a special set of concentration values to be fed as inputs.…”

Section: Preliminaries Of Sample Preparationmentioning

confidence: 99%

“…, n denoting the accuracy level [4], [20], [21]. We call this as binarized sequence BS of order n (i.e., BSn).…”

Section: A Representation Of Cf-values Using Farey Sequencementioning

confidence: 99%

“…As a consequence, in most of the SP-algorithms, a target-CF is first approximated as an n-bit binary fraction, where n is a positive integer that determines the desired accuracy of CFs. The reliability of sample preparation depends on the correctness of (1:1) mixing steps and balancing of split operations during implementation [17]- [21]. SP-algorithms usually aim to minimize the number of mix-split operations (assaytime) [9], reactant-usage (cost) [11], or waste production [22], and their complexities largely depend on the value of n, the required output volume, and the availability of physical resources on-chip.…”

Section: Introductionmentioning

confidence: 99%

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Sample Preparation Meets Farey Sequence: A New Design Technique for Free-Flowing Microfluidic Networks

Banerjee¹,

Poddar²,

Ho³

et al. 2021

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Design of microfluidic biochips has led to newer challenges to the EDA community due to the availability of various flow-based architectures and the need for catering to diverse applications such as sample preparation, personalized medicine, point-of-care diagnostics, and drug design. The ongoing Covid-19 pandemic has increased the demand for low-cost diagnostic lab-on-chips manifold. Sample preparation (dilution or mixing of biochemical fluids) is an indispensable step of any biochemical experiment including sensitive detection and successful assay execution downstream. Although for valve-based microfluidic biochips various design automation tools are currently available, they are expensive, and prone to various manufacturing and operational defects. Additionally, many problems are left open in the domain of free-flowing biochips, where only a single layer of flow-channels is used for fluid-flow devoid of any kind of control layer/valves. In this work, we present a methodology for designing a free-flowing biochip that is capable of performing fluid dilution according to user's requirement. The proposed algorithm for sample preparation utilizes the Farey-sequence arithmetic of fractions that are used to represent the concentration factor of the target fluid. We also present the detailed layout design of a free-flowing microfluidic architecture that emulates the dilution algorithm. The network is simulated using COMSOL multi-physics software accounting for relevant hydrodynamic parameters. Experiments on various test-cases support the efficacy of the proposed design in terms of accuracy, convergence time, reactant cost, and simplicity of the fluidic network compared to prior art.

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Section: Motivationmentioning

confidence: 97%