Name
Abstract | ||
|---|---|---|
Many biomedical sensors combine micro fluidic, electronic capacitive, and/or photonic capabilities. Micro fluidic sensors involve sealed channels through which the sample fluid containing biomedical materials flows with capacitive or photonic sensors detecting parameters contained in the liquid. However micro fluidic devices are prone to faults occurring when foreign particles in the bioliquid, or fluid bubbles, get lodged in the paths blocking a channel, thereby changing the fluidic flow in the device and affecting the parameters to be sensed. Thus, these systems require defect tolerant design in the micro fluidic and knowledge of how these changes will affect the parameters being sensed. To achieve fault tolerance we investigate a Cathedral Chamber design, with pillars supporting the roof at regular intervals. This prevents single blockages from stopping fluid flow through the system in a channel, as there are many paths. We discuss the potential causes and effects of such blockages. Monte Carlo analysis and simulations based on both randomly placed blockages and blockages occurring in low flow areas show that the Cathedral Chamber design significantly increases lifetime of the system, an average of 6 times more particles are required before full blockage occurs compared to an array of parallel channels. Fluid flow modeling shows parallel channels show rapid rise of pressure with the number of blockages while the Cathedral chamber shows much slower rise, which reaches a plateau pressure until it is blocked. The impact of these defects on the sensed parameters, such as capacitive measurement of the fluid or photonic measurements, is discussed. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/DFT.2011.33 | DFT |
Keywords | Field | DocType |
fluid flow modeling,photonic biosensors,creating defect tolerance,micro fluidic,fluid flow,cathedral chamber design,fluidic flow,microfluidic capacitive,parallel channel,micro fluidic sensor,micro fluidic device,sample fluid,fluid bubble,material flow,monte carlo analysis,fault tolerance,fault tolerant,biomems,capacitive sensors,monte carlo methods,biosensors,low flow | Fluidics,Computer science,Flow (psychology),Microfluidics,Communication channel,Electronic engineering,Capacitive sensing,Fluid dynamics,Fault tolerance,Photonics | Conference |
ISSN | Citations | PageRank |
1550-5774 | 0 | 0.34 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Glenn H. Chapman | 1 | 167 | 34.10 |
| Bonnie L. Gray | 2 | 0 | 0.68 |
| Vijay K. Jain | 3 | 93 | 54.61 |