Dr. Kim had attended 2026 International Conference on Nonlinear Elastic Materials (ICNEM). He gave a presentation on the compressibility measurement of cells and particles in nonlinear, acoustophoretic, microfluidic channels.
Title: Compressibility Measurement of Cells and Particles in Nonlinear, Acoustophoretic, Microfluidic Channels
Presenter: Yong-Joe Kim, Ph.D., Associate Professor, Director of the Acoustics and Signal Processing Laboratory, Department of Mechanical Engineering, Texas A&M University, College Station, Texas, USA.
Author 1: Han Wang, Tsinghua University
Author 2: Zhongzheng Niu, TDK InvenSense
Author 3: Arum Han, Texas A&M University
Abstract: Compressibility of particles and cells is an interesting physical property that can be utilized in label-free separation; in particular, compressibility-dependent cell separation modalities have gained significant interest since red blood cells (RBCs) and cancer cells are observed to have different compressibility compared to benign cells. Specifically, it has been known that a cancer cell with the higher metastatic potential has the higher compressibility. However, systems capable of continuous and simultaneous label-free separation of particles and cells based on their sizes and compressibility at high throughput have been rarely investigated. Acoustophoresis-based microfluidic separation utilizes intrinsic differences in vibro-acoustic properties of target samples under nonlinear acoustic excitations, and can be achieved using simple microfluidic systems without need for cumbersome sample preparation steps. Thus, this approach has gained significant interest as the most viable label-free separation method in terms of its strong force generation, high throughput, high specificity, and low capital and operation cost. However, the design of state-of-the-art acoustophoretic microfluidic systems has been mainly derived from a simplistic analytical acoustic model in a “static” fluid medium with uniform temperature distribution. Therefore, it is difficult to consider the real-world effects of “moving” fluid media, viscous boundary layers, and locally elevated temperature that significantly influence the motion of particles and cells. In this presentation, a numerical modeling method is introduced to address these deficiencies, significantly improving the predictability and specificity of the acoustophoretic separation. As an application of the numerical method, a camera with a microscope was used to record the trajectories of cancer cell motions under nonlinear acoustic excitation in a microfluidic channel. Then, the experimental trajectories were curve fitted to the predicted ones to identify the compressibility of the cells. The cells with the highest metastatic potential showed the highest compressibility, which is consistent with previously reported clinical observations.