FY05 LDRD Final Report A Computational Design Tool for Microdevices and Components in Pathogen Detection Systems Page: 4 of 22
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There are several MEMS CAD capabilities currently available that have evolved from
industry design tools for integrated circuits coupled with mechanical simulation
capabilities. Furthermore, many, if not all, biosensors will have significant fluidic
components because of the biochemical nature of the assays. While some of the CAD
packages have rudimentary fluid dynamics modeling capabilities, for advanced
design and optimization of biodetection systems it will be necessary to develop an
advanced modeling capability to address and understand the fundamental physics
and chemistry associated with complex biological flow in micro-environments.
Complex biological fluids at the microscale. One of the fundamental research
problems in this project is polymeric fluid dynamics at the microscale. The
biochemical nature of biosensing and detection requires micro-processing of
macromolecules (polymers) such as DNA or proteins via polymerase chain reaction
(PCR) or immunoassay, respectively. In a standard amplification and sequencing
microprocessor 1010 molecules of bacterial DNA, each of which is approximately 1-2
mm long when stretched out in solution, will have to pass through channels with
characteristic length scales of 100 m or less. This flow regime presents new fluid
mechanical issues, different from macro-scale flows, because (1) surface-to-volume
ratios are extremely large in microchannels; (2) biological fluids demonstrate
complex, non-Newtonian behavior; and (3) characteristic lengths of the
macromolecules/cells approach those of the fluid channels.
Modeling complex biological fluids is a challenge because their non-Newtonian
constitutive behavior is not easily represented. For example, a highly concentrated
solution of suspended polymer molecules such as DNA may be represented at large,
system-level scales with a continuum viscoelastic constitutive model. This flow
scenario is typical of a post-amplification process in a PCR device where it is
computationally prohibitive to discretely represent every DNA molecule. However,
when the inter-polymer spacing is comparable to geometry length scales as in a
microscale flow, a continuum approximation is no longer appropriate. Instead, a
discrete molecular approximation is needed, but at a computational expense. On the
other hand, in a pre-amplification detection environment very few DNA molecules
may be present in the flow as a result of some collected air sample that has been
fluidized; downstream, only a single molecule needs to be captured for amplification.
In this case a discrete molecular approximation is appropriate, but smaller scale
chemistry must be included in the model for the capture process. Figures 3 and 4
demonstrate these continuum and molecular behaviors, respectively.
Figure 3 is experimental evidence obtained in this project (discussed in more detail
later) that proves the hypothesis that the presence of long-chain polymers in a
Newtonian solvent (e.g., Boger fluid, DNA) can cause a bulk fluid to demonstrate
both viscous and elastic behavior even at micro-molar concentrations. This behavior
is drastically different from canonical flows as seen in the vortex enhancement in re-
entrant corners. One potential problem scenario of this phenomenon occurring in a
biosensor is the diffusion of a macromolecule across streamlines into one of these
large recirculation zones, then degradation or even breaking of the molecule in the
vortex due to shear and finally diffusion back across streamlines to be processed
downstream without full character. It is important to be able to predict this type of
behavior in a device where there is a need to control the working fluid and
simultaneously manipulate and detect biological species in the fluid.
Figure 4 demonstrates the conformational changes of DNA molecules as they move
through a micro-valve . Experiments show that long-chain polymers migrate
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Trebotich, D. FY05 LDRD Final Report A Computational Design Tool for Microdevices and Components in Pathogen Detection Systems, report, February 7, 2006; Livermore, California. (digital.library.unt.edu/ark:/67531/metadc878012/m1/4/: accessed November 13, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.