Chip Scale Optical Microresonator Sensors Integrated With Embedded Thin Film Photodetectors on Electrowetting Digital Microfluidics Platforms

Liu, Lin; Royal, Matthew; Evans, R.D.; Fair, Richard B.; Jokerst, N.M.

doi:10.1109/jsen.2011.2179027

Cited by 48 publications

(31 citation statements)

References 20 publications

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“…In [26] a chip scale sensing system, made up of a planar integrated optical microdisk resonator and a thin film InGaAs photodetector, is integrated with a digital microfluidic system. The integrated optical system with the EWOD DFMS was able to detect changes in index of refraction as presented by glucose solutions in small droplets with different concentrations that were delivered by the DFMS.Another contribution reported in [27] where using the integrated device described in [22][23] a digital microfluidic system comprising of multiple DMFB has been designed. The system implements result based sequential execution of multiple bioassay protocols on different DMFBs controlled through a centralized timer and controller circuit.…”

Section: Previous Workmentioning

confidence: 99%

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Feedback based automated detection analysis in Digital Microfluidic Biochip Systems

Roy

Bal

Patra

et al. 2013

2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE)

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Detection and analysis are major tasks for biochemical analysis required to be performed in digital microfluidic systems. With the development of heterogeneous photonic component integration technologies it has become possible to integrate miniaturized optical sensing technologies with the Microfluidic systems. This enables complex optical detection functions to be incorporated within the microfluidic platform. In this paper we proposed a design of a digital microfluidic system that uses a feedback based detection and analysis technique using multiple homogeneous sample based detection analyzers. The analyzers are connected in a feedback loop to discrete Biochips for dedicated majority based detection on specified bioassays. The initial detection is carried out on different individual samples in a centralized digital microfluidic biochip. Based on the initial detection results for each sample feedback signals have been generated. Such signals are employed for initiatiation of independent confirmatory detection of lower degree of presence of targeted parameters on individual bioassays separately. The experiment has been carried out for Bioassays involving detection of blood Glucose, Lactate and Pyruvate. The simulation results for the design along with automated detection analysis results are found to be encouraging.

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Section: Previous Workmentioning

confidence: 99%

“…It has been found that in the last work [27] an attempt has been made to perform automated result based detection analysis in DMFBs. In the proposed work we have used a new design of the analyzer based on the principle mentioned in [27] to develop a multiple Biochip system.…”

Section: Previous Workmentioning

confidence: 99%

Feedback based automated detection analysis in Digital Microfluidic Biochip Systems

Roy

Bal

Patra

et al. 2013

2013 International Conference on Control, Automation, Robotics and Embedded Systems (CARE)

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“…Applications are wide ranging and include "Lab-on-Chip" devices were there is an increasing interest in MEMS integration due to the improved sensitivity and faster response which have been well documented [20] [21]. Of special interest are technologies capable of integrating microfluidics with electronic sensing, actuation, control and processing.…”

Section: Introductionmentioning

confidence: 99%

A Housekeeping Prognostic Health Management Framework for Microfluidic Systems

Khan

Al-Gayem

Richardson

2017

IEEE Trans. Device Mater. Relib.

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Abstract--Micro-electro-mechanical Systems and microfluidics are becoming popular solutions for sensing, diagnostics and control applications. Reliability and validation of function is of increasing importance in the majority of these applications. Online testing strategies for these devices have the potential to provide real-time condition monitoring information. It is shown that this information can be used to diagnose and prognose the health of the device. This information can also be used to provide an early failure warning system by predicting the remaining useful life. Diagnostic and prognostic outcomes can also be leveraged to improve the reliability, dependability and availability of these devices. This work has delivered a methodology for a "lightweight" prognostics solution for a microfluidic device based on real-time diagnostics. An oscillation based test methodology is used to extract diagnostic information that is processed using a Linear Discriminant Analysis based classifier. This enables the identification of current health based on pre-defined health levels. As the deteriorating device is periodically classified, the rate at which the device degrades is used to predict the devices remaining useful life. I. INTRODUCTIONA novel implementation of a prognostics function for a microfluidic device based on MEMS technology is presented. The term "prognostics" has been defined in various different ways depending on context [1], this research considers the definition given by ISO13381-1 as the most comprehensive. It states that prognostics is not only the prediction of the time to failure but also the risk of one or more existing or future failure modes [2].Studies have revealed some excellent Prognostic and Health Management (PHM) solutions that provide deep and detailed prognostic capabilities for micro-devices with a high level of accuracy. The use of machine learning [3] and physics based prognostics [4] is being actively explored. PHM solutions similar to these are designed from the ground up in a device specific framework with the prognostics modules being tightly coupled with the physics of failure of the device. While these PHM systems perform very well in conjunction with their target devices, flexibility and wide scale adoption in other MEMS devices is quite challenging.The onus of most PHM frameworks is to provide prognosis at the highest possible confidence level thus providing the most reliable Remaining Useful Life (RUL) predictions [5] [6] [7]. However, this comes at a cost, be it a heavy processing requirement or the aforementioned rigidity or complexity, to name two. This work proposes a "Housekeeping" Prognostics and Health Management (HPHM) framework that has a conservative prognostic mandate. Such a framework caters strictly for wear during normal use and evolving faults. This affords the usage of simpler models that are easy to adapt, implement and use.The scope of this HPHM is to predict patterns of low intensity failures and drift due to gradual aging and noncatastrophic faults du...

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“…The first integration of microring sensors on digital microfluidic chips has already been demonstrated [21,22], although these systems rely on very complex fabrication procedures for making integrated optical detectors and bulky optical fiber connections to couple light into the system.…”

Section: Introductionmentioning

confidence: 99%

Silicon photonic sensors incorporated in a digital microfluidic system

et al. 2012

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Label-free biosensing with silicon nanophotonic microring resonator sensors has proven to be an excellent sensing technique for achieving high-throughput and high sensitivity, comparing favorably with other labeled and label-free sensing techniques. However, as in any biosensing platform, silicon nanophotonic microring resonator sensors require a fluidic component which allows the continuous delivery of the sample to the sensor surface. This component is typically based on microchannels in PDMS or other materials which add cost and complexity to the system. The use of microdroplets in a digital microfluidic system, instead of continuous flows, is one of the recent trends in the field, where micro-to picoliter-sized droplets are generated, transported, mixed and split, thereby creating miniaturized reaction chambers which can be controlled individually in time and space. This avoids cross-talk between samples or reagents and allows fluid plugs to be manipulated on reconfigurable paths, which cannot be achieved using the more established and more complex technology of microfluidic channels where droplets are controlled in series. It has great potential for high-throughput liquid handling, while avoiding on-chip cross contamination.We present the integration of two miniaturized technologies: label-free silicon nanophotonic microring resonator sensors and digital microfluidics, providing an alternative to the typical microfluidic system based on microchannels. The performance of this combined system is demonstrated by performing proof-of-principle measurements of glucose, sodium chloride and ethanol concentrations. These results show that multiplexed real-time detection and analysis, great flexibility, and portability make the combination of these technologies an ideal platform for easy and fast use in any laboratory.

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Chip Scale Optical Microresonator Sensors Integrated With Embedded Thin Film Photodetectors on Electrowetting Digital Microfluidics Platforms

Cited by 48 publications

References 20 publications

Feedback based automated detection analysis in Digital Microfluidic Biochip Systems

Feedback based automated detection analysis in Digital Microfluidic Biochip Systems

A Housekeeping Prognostic Health Management Framework for Microfluidic Systems

Silicon photonic sensors incorporated in a digital microfluidic system

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