Session: 17-01-01: Research Posters

Paper Number: 150341

150341 - A Meshfree Phase-Field Model for Simulating the Sintering Process of Metallic Particles for Printed Electronics 

Printed electronics are usually developed with printed electrodes from nanoparticle-based inks, which need a post-printing sintering process to enable the high conductivity required for the devices. Currently, most sintering processes in printed electronics are based on the try-and-error method or previous experience and estimation. To improve the efficiency and effectiveness of the sintering process for nanoparticle-based printed electrodes, a highly efficient numerical model and simulation method is crucial to optimize the sensing conditions for different applications to reduce manufacturing costs and save energy. In this work, we propose a meshfree phase-field sintering model using the node-material point framework implemented in Hot Optimal Transform Meshfree (HOTM) method. This framework employs the Local Maximum Entropy (LME) shape function and two optimization methods to achieve accurate predictions of void distribution and porosity in printed electronics. The sintering behaviors of both 2D and 3D cases are evaluated in comparison with experimental observation. 

Printed electronics are usually developed with printed electrodes from nanoparticle-based inks, which need a post-printing sintering process to enable the high conductivity required for the devices. Currently, most sintering processes in printed electronics are based on the try-and-error method or previous experience and estimation. To improve the efficiency and effectiveness of the sintering process for nanoparticle-based printed electrodes, a highly efficient numerical model and simulation method is crucial to optimize the sensing conditions for different applications to reduce manufacturing costs and save energy. In this work, we propose a meshfree phase-field sintering model using the node-material point framework implemented in Hot Optimal Transform Meshfree (HOTM) method. This framework employs the Local Maximum Entropy (LME) shape function and two optimization methods to achieve accurate predictions of void distribution and porosity in printed electronics. The sintering behaviors of both 2D and 3D cases are evaluated in comparison with experimental observation. 

Printed electronics are usually developed with printed electrodes from nanoparticle-based inks, which need a post-printing sintering process to enable the high conductivity required for the devices. Currently, most sintering processes in printed electronics are based on the try-and-error method or previous experience and estimation. To improve the efficiency and effectiveness of the sintering process for nanoparticle-based printed electrodes, a highly efficient numerical model and simulation method is crucial to optimize the sensing conditions for different applications to reduce manufacturing costs and save energy. In this work, we propose a meshfree phase-field sintering model using the node-material point framework implemented in Hot Optimal Transform Meshfree (HOTM) method. This framework employs the Local Maximum Entropy (LME) shape function and two optimization methods to achieve accurate predictions of void distribution and porosity in printed electronics. The sintering behaviors of both 2D and 3D cases are evaluated in comparison with experimental observation.

Presenting Author: Changyong Cao Case Western Reserve University

Presenting Author Biography: Dr. C. Chase Cao is an Assistant Professor in Mechanical and Aerospace Engineering, and Electrical, Computer and Systems Engineering at Case Western Reserve University (CWRU), directing the Laboratory for Soft Machines and Electronics at Case School of Engineering. He is also an Investigator of the Advanced Platform Technology (APT) Center at Louis Stokes Cleveland VA Medical Center. His current research interests include self-powered soft/flexible electronic systems, soft robotics, physical intelligence, and 3D/4D printing of multifunctional materials and structures. Dr. Cao has published over 80 scientific papers (Total Citation: >4500, h-index: 34) in peer-reviewed journals, and holds 7 US patents. He is serving as an Associate Editor for: IEEE Robotics and Automation Letters (RA-L), Frontiers in Robotics and AI, and Frontiers in Mechanical Engineering, and editorial board member of several journals such as Advanced Electronic Materials, Soft Science, Micromachines, and Sensors.

Authors:

Changyong Cao Case Western Reserve University
Md Shariful Islam Case Western Reserve University