SGER: Flow field quantification in microfluidic mixing systems by single-molecule detection methods

CBET-0820745Su微尺度流体系统在生物分析中广泛存在，也出现在燃料电池等能源系统中。这种体系中的雷诺数很低，因此分子混合增强不能利用湍流效应。相反，有必要应用混沌平流的概念，这种概念在大尺度层流中很常见。这种SGER将解决被动、稳定流动的微型混合器，尽管一般方法也将适用于通过机械驱动等产生非稳定流动的有源混合器。有许多旨在产生混沌平流的微混合器设计，它们通常是将二维(2D)混沌流动几何结构适配到三维(3D)微通道。从概念上讲，通过将三维通道的连续横截面等同于二维流动中的时间序列来比较流动轨迹。现有的量化微通道流动的努力依赖于使用诸如Micro-PIV等技术的单点或现场流速测量。然而，这种测量从根本上与基于二维混沌流动类比的流动配置不匹配，因为许多用于分析混沌流动的工具依赖于粒子轨迹(或条纹)及其到低维空间的映射的知识。根据速度测量确定轨迹或条纹需要了解三维速度场的时间演变，这对Micro-PIV仍然具有挑战性。PI将展示一种新的方法来量化沟道型微混合设备中的流场，该方法使用单分子检测技术来直接测量流动条纹。与速度场测量相比，流线测量固有地提供了对混合的更直接的了解，因为它允许访问现有的混沌流动分析工具。例如，PI将能够构建Poincare截面，通过考虑初始近端条纹的发散或固定点的属性等来明确地评估微通道流的混沌特性。这些测量最终将为微混合设备的设计和表征提供严格而直观的框架。

CBET-0820745SuMicroscale fluid systems are widespread in bioanalysis, and also appear in energy systems such as fuel cells. Reynolds numbers in such systems are very low, so molecular mixing enhancement cannot exploit turbulent effects. Instead, it is necessary to apply concepts of chaotic advection, which are familiar in macroscale laminar flows. This SGER will address passive, steady-flow micromixers, though the general approach will also be applicable to active mixers that generate unsteady flows through, for example, mechanical actuation. There are numerous micromixer designs that aim to generate chaotic advection, which are often adaptations of two-dimensional (2-D) chaotic flow geometries to three-dimensional (3-D) microchannels. Conceptually, flow trajectories are compared by treating successive transverse sections of 3-D channels equivalently to temporal series in 2-D flows Existing efforts to quantify microchannel flows rely on single-point or field measurements of flow velocities, using techniques such as micro-PIV. Such measurements are fundamentally mismatched with flow configurations based on 2-D chaotic flow analogies, however, because many tools for analyzing chaotic flows rely on knowledge of particle trajectories (or streaklines), and of their mappings into lower-dimensional space. Determining trajectories or streaklines from velocity measurements requires knowledge of the temporal evolution of the 3-D velocity field, which remains challenging for micro-PIV. The PI will demonstrate a new method for quantifying flow fields in channel-type micromixing devices, where the method employs single-molecule detection techniques to measure flow streaklines directly. Streakline measurements inherently offer more direct insight into mixing than velocity field measurements, by allowing access to established tools of chaotic flow analysis. For example, The PI will be able to construct Poincare sections explicitly to assess the chaotic properties of microchannel flows by considering the divergence of initially proximal streaklines, or the properties of fixed points, etc. These measurements will eventually provide a rigorous, yet intuitive framework for the design and characterization of micromixing devices.