Development of a Multi-scale Mathematical Model for Chip-based Chromatography

标题：芯片色谱多尺度数学模型的开发 摘要 本申请的目标是开发一个多尺度的数学模型，用于基于芯片的毛细管 电动色谱（CEC）系统，应用于床旁技术。产生 在芯片实验室平台上分析的样品数量及其复杂性的快速增长， 有效的化学和生物化学分离成为芯片实验室系统的关键要素， 实现即时护理所承诺的快速、高通量、可靠和具有成本效益的操作目标 技术. CEC既具有毛细管电泳（CE）的高效性，又具有选择性和样品选择性 包装的高效液相色谱（HPLC）的容量。CEC似乎是最简单的 实现快速、高效分离。然而，一个主要问题，驱动流耦合到 柱的性质使得选择性和流动产生的独立优化是不可能的， 阻碍了CEC的广泛工业应用。因此，数学建模工具能够 对分离过程进行预测，对于充分开发和利用CEC的潜力至关重要 系统.如今，为了理解底层物理，数值模拟成为最重要的方法之一， 重要的工具。这对于CEC系统尤其重要，因为同时优化两种选择性 流场的研究对于实验研究来说是一个挑战。但通常直接数值模拟是时间- 消耗大、成本高，并且由于问题的复杂性，通常仅应用于相对较短的列。从而 为了克服上述与直接数值模拟相关的缺点，我们建议开发 一个多尺度数学模拟工具，以减少许多数量级的计算成本。 数值模拟也是一种重要的现代设计工具。计算研究可以促进和加快 设计过程中节省时间和成本，缩小最佳的设计解决方案，通过虚拟样机， 在制造原型之前的系统。

Title: Development of a Multi-scale Mathematical Model for Chip-based Chromatography ABSTRACT The goal of this application is to develop a multi-scale mathematical model for chip-based Capillary Electrokinetic Chromatography (CEC) systems with applications to point-of-care technologies. Arising from the rapid growth of the number of samples to analyze and of their complexity on a lab-on-a-chip platform, effective and efficient chemical and biochemical separation becomes a pivotal element of lab-on-a-chip systems to achieve the goal of fast, high-throughput, reliable, and cost-effective operations promised by point-of-care technologies. CEC has both the efficiency of the Capillary Electrophoresis (CE) and the selectivity and sample capacity of the packed High Performance Liquid Chromatography (HPLC). CEC appears to be the simplest answer to realize fast and high-efficiency separation. However, one main issue that the driven flow is coupled to the properties of the column makes independent optimization of selectivity and flow generation impossible, preventing the widely industrial implementation of CEC. Therefore, a mathematical modeling tool capable of predicting the separation process, in advance, becomes critical to fully explore and exploit the potential of CEC systems. Nowadays, to understand the underlying physics, numerical simulation becomes one of the most important tools. It is particularly essential for CEC systems as the simultaneous optimization of both selectivity and flow field is challenging for experimental studies alone. But often direct numerical simulations are time- consuming, costly, and usually only applied for relatively short columns due to problem complexity. Thus to overcome the aforementioned shortcomings associated with direct numerical simulations, we propose to develop a multi-scale mathematical simulation tool to reduce the computational cost by many orders of magnitude. Numerical simulation is a key modern design tool as well. Computational studies can facilitate and speed up the design process by saving the time and cost to narrow down the optimal design solution via virtual prototyping of systems prior to fabrication of prototypes.