Computer design of microfluidic mixers for protein/RNA folding studies

Kinetic studies of biological macromolecules increasingly use microfluidic mixers to initiate and monitor reaction progress. A motivation for using microfluidic mixers is to reduce sample consumption and decrease mixing time to microseconds. Some applications, such as small-angle x-ray scattering, also require large ( \u3e 10 micron) sampling areas to ensure high signal-to-noise ratios and to minimize parasitic scattering. Chaotic to marginally turbulent mixers are well suited for these applications because this class of mixers provides a good middle ground between existing laminar and turbulent mixers. In this study, we model various chaotic to marginally turbulent mixing concepts such as flow turning, flow splitting, and vortex generation using computational fluid dynamics for optimization of mixing efficiency and observation volume. Design iterations show flow turning to be the best candidate for chaotic/marginally turbulent mixing. A qualitative experimental test is performed on the finalized design with mixing of 10 M urea and water to validate the flow turning unsteady mixing concept as a viable option for RNA and protein folding studies. A comparison of direct numerical simulations (DNS) and turbulence models suggests that the applicability of turbulence models to these flow regimes may be limited

Turbulent mixers for protein folding experiments

Protein folding studies require the development of micro-mixers that require less sample, mix at faster rates, and still provide a high signal to noise ratio. Chaotic to marginally turbulent micro-mixers are promising candidates for this application. In this study, various turbulence and unsteadiness generation concepts are explored that avoid cavitation. The mixing enhancements include flow turning regions, flow splitters, and vortex shedding. The relative effectiveness of these different approaches for rapid micro-mixing is discussed. Simulations found that flow turning regions provided the best mixing profile. Various turbulence models are simulated to determine appropriate model of the design requirements. Experimental validation of the optimal design is verified through laser confocal microscopy experiment

Five unsteady/turbulent mixer designs tested in this work.

<p>(A) flow-turning inlets, (B) vortex shedding inlets (side channels are twice the width of other concepts, centre channel is same width as other channels, buffer solution flow rate in side channels of 9 m/s), (C) flow-splitting inlets, (D) T-junction flow-turning inlets, (E) T-junction swirled flow-turning inlets.</p

Operating conditions shown on first design concept in Fig 2A, but applicable to all design concepts except that in Fig 2B.

<p>Operating conditions shown on first design concept in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g002" target="_blank">Fig 2A</a>, but applicable to all design concepts except that in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g002" target="_blank">Fig 2B</a>.</p

α profiles where mixing is complete experimentally (0.9mm).

<p>The position of the slices is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g001" target="_blank">Fig 1</a> (“Fully Mixed Point”). (A) Temporally averaged DNS, (B) Instantaneous snapshot of DNS.</p

Temporally averaged DNS results at end of diffuser.

<p>The position of the slices is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g001" target="_blank">Fig 1</a> (“End of Diffuser”). (A) Velocity Magnitude, (B) α.</p

Pressure, velocity magnitude and <i>α</i> simulation results using the <i>k</i> − <i>ω</i> SST turbulence model.

<p>(A) Flow-turning inlets, (B) Vortex shedding inlets, (C) Flow-splitting inlets, (D) T-junction flow-turning Inlets, (E) T-junction swirled flow-turning Inlets.</p

Qualitative experimental test of 10-fold dilution of 10 M urea with water visualized using Schlieren optical inhomogeneity induced by the mixing process to determine the mixing time of the reference design (Fig 2A).

<p>Qualitative experimental test of 10-fold dilution of 10 M urea with water visualized using Schlieren optical inhomogeneity induced by the mixing process to determine the mixing time of the reference design (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g002" target="_blank">Fig 2A</a>).</p

α profiles at 0.9mm downstream from the inlets.

<p>The position of the slices is shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198534#pone.0198534.g001" target="_blank">Fig 1</a> (“Fully Mixed Point”). (A) Spalart-Allmaras, (B) k-ω SST, (C) Realizable k-ε, (D) Launder-Sharma low Reynolds number k-ε.</p

Streamlines tracking velocity and shaded by velocity magnitude in the diffuser of reference design.

<p>(A) k-ω SST, (B) Temporally averaged direct numerical simulation (DNS).</p