Lentz Cody J, Hidalgo-Caballero Samuel, Lapizco-Encinas Blanca H
Microscale Bioseparations Laboratory, Rochester Institute of Technology, Rochester, New York 14623, USA.
Biomicrofluidics. 2019 Aug 29;13(4):044114. doi: 10.1063/1.5115153. eCollection 2019 Jul.
In this study, we demonstrate the use of cyclical low frequency signals with insulator-based dielectrophoresis (iDEP) devices for the separation of particles of similar characteristics and an experimental method for estimating particle DEP mobilities. A custom signal designer program was created using Matlab® and COMSOL Multiphysics® for the identification of specific low frequency signals aimed at separating particle mixtures by exploiting slight differences in surface charge (particle zeta potential) or particle size. For the separation by surface charge, a mixture of two types of 10 m particles was analyzed and effectively separated employing both a custom step signal and a sawtooth left signal. Notably, these particles had the same shape, size, and surface functionalization as well as were made from the same substrate material. For the separation by size, a sample containing 2 m and 5 m particles was successfully separated using a custom step signal; these particles had the same shape, surface functionalization, were made from the same substrate materials, and had only a small difference in zeta potential (10 mV). Additionally, an experimental technique was developed to estimate the dielectrophoretic mobility of each particle type; this information was then utilized by the signal designer program. The technique developed in this study is readily applicable for designing signals capable of separating micron-sized particles of similar characteristics, such as microorganisms, where slight differences in cell size and the shape of surface charge could be effectively exploited. These findings open the possibility for applications in microbial screening using iDEP devices.
在本研究中,我们展示了利用基于绝缘体的介电电泳(iDEP)装置的周期性低频信号来分离具有相似特性的颗粒,以及一种估计颗粒介电电泳迁移率的实验方法。使用Matlab®和COMSOL Multiphysics®创建了一个定制信号设计程序,用于识别特定的低频信号,旨在通过利用表面电荷(颗粒zeta电位)或颗粒大小的微小差异来分离颗粒混合物。对于基于表面电荷的分离,分析了两种10μm颗粒的混合物,并使用定制的阶跃信号和锯齿左信号有效地进行了分离。值得注意的是,这些颗粒具有相同的形状、大小和表面功能化,并且由相同的基底材料制成。对于基于大小的分离,使用定制的阶跃信号成功分离了包含2μm和5μm颗粒的样品;这些颗粒具有相同的形状、表面功能化,由相同的基底材料制成,并且zeta电位仅有微小差异(10mV)。此外,还开发了一种实验技术来估计每种颗粒类型的介电电泳迁移率;信号设计程序随后利用了这些信息。本研究中开发的技术很容易应用于设计能够分离具有相似特性的微米级颗粒的信号,例如微生物,其中细胞大小和表面电荷形状的微小差异可以得到有效利用。这些发现为使用iDEP装置进行微生物筛选的应用开辟了可能性。