Error-Oblivious Sample Preparation With Digital Microfluidic Lab-on-Chip

Author(s):  
Sudip Poddar ◽  
Robert Wille ◽  
Hafizur Rahaman ◽  
Bhargab B. Bhattacharya
2016 ◽  
Vol 22 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Sudip Poddar ◽  
Sarmishtha Ghoshal ◽  
Krishnendu Chakrabarty ◽  
Bhargab B. Bhattacharya

2022 ◽  
Vol 27 (1) ◽  
pp. 1-21
Author(s):  
Sudip Poddar ◽  
Sukanta Bhattacharjee ◽  
Shao-Yun Fang ◽  
Tsung-Yi Ho ◽  
B. B. Bhattacharya

Microfluidic lab-on-chips offer promising technology for the automation of various biochemical laboratory protocols on a minuscule chip. Sample preparation (SP) is an essential part of any biochemical experiments, which aims to produce dilution of a sample or a mixture of multiple reagents in a certain ratio. One major objective in this area is to prepare dilutions of a given fluid with different concentration factors, each with certain volume, which is referred to as the demand-driven multiple-target (DDMT) generation problem. SP with microfluidic biochips requires proper sequencing of mix-split steps on fluid volumes and needs storage units to save intermediate fluids while producing the desired target ratio. The performance of SP depends on the underlying mixing algorithm and the availability of on-chip storage, and the latter is often limited by the constraints imposed during physical design. Since DDMT involves several target ratios, solving it under storage constraints becomes even harder. Furthermore, reduction of mix-split steps is desirable from the viewpoint of accuracy of SP, as every such step is a potential source of volumetric split error. In this article, we propose a storage-aware DDMT algorithm that reduces the number of mix-split operations on a digital microfluidic lab-on-chip. We also present the layout of the biochip with -storage cells and their allocation technique for . Simulation results reveal the superiority of the proposed method compared to the state-of-the-art multi-target SP algorithms.


2013 ◽  
Vol 336-338 ◽  
pp. 523-527
Author(s):  
Tao Dong ◽  
Matteo Molino ◽  
Danilo Demarchi

In this study, a lab-on-chip (LOC) system is designed for the cell sensors to provide a high-efficient continuous analysis platform of acute toxicants in water environment. The chip is composed of three domains, including counter-flow micromixers, a T-junction droplet generator and time delay channels (TD-Cs). Water sample and bioluminescent bacterium Vibrio Fischeri (VF) are imported into the micromixers before that the droplet generator encapsulates them inside aqueous droplets separated by air. Air flow is the disperse medium, which can guarantee sufficient oxygen supply for the cells in droplets. The system shows high reliability and stability through numerical and experimental investigations.


2018 ◽  
Vol 17 (2) ◽  
pp. 1-12 ◽  
Author(s):  
Sukanta Bhattacharjee ◽  
Yi-Ling Chen ◽  
Juinn-Dar Huang ◽  
Bhargab B. Bhattacharya

Biosensors ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 117 ◽  
Author(s):  
Faye M. Walker ◽  
Kuangwen Hsieh

Advances in nucleic acid amplification technologies have revolutionized diagnostics for systemic, inherited, and infectious diseases. Current assays and platforms, however, often require lengthy experimental procedures and multiple instruments to remove contaminants and inhibitors from clinically-relevant, complex samples. This requirement of sample preparation has been a bottleneck for using nucleic acid amplification tests (NAATs) at the point of care (POC), though advances in “lab-on-chip” platforms that integrate sample preparation and NAATs have made great strides in this space. Alternatively, direct NAATs—techniques that minimize or even bypass sample preparation—present promising strategies for developing POC diagnostic tools for analyzing real-world samples. In this review, we discuss the current status of direct NAATs. Specifically, we surveyed potential testing systems published from 1989 to 2017, and analyzed their performances in terms of robustness, sensitivity, clinical relevance, and suitability for POC diagnostics. We introduce bubble plots to facilitate our analysis, as bubble plots enable effective visualization of the performances of these direct NAATs. Through our review, we hope to initiate an in-depth examination of direct NAATs and their potential for realizing POC diagnostics, and ultimately transformative technologies that can further enhance healthcare.


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