Our home: Bergeron Center for Engineering Excellence

Electronics Additive Manufacturing Lab (E-AM)

Research Projects

We are constantly working on new ideas for electronics additive manufacturing. Our goal is to fabricate and deploy electronics in new ways for innovative applications. Some of our current projects are:

Integration of 3D printing with printed electronics

3D printing and printed electronics are both hot topics with large promise. Combining the two will be a significant step in the field of additive manufacturing and towards the Internet of Things (IoT). Many biomedical applications such as personalized prosthetics will benefit from electronics, especially sensors, being integrated with customized 3D printed components. Surprisingly little progress has been made towards printing advanced semiconductor devices such as transistors onto 3D printed surfaces. In this project, we study non-idealities that occur when printing micro-electronics onto 3D printed surfaces and the processing steps needed to create such devices.

Structural composites with integrated electronics for structural health monitoring

Carbon fiber composites are becoming increasingly prevalent in structural applications such as automotive, aerospace, defense or health. Structural health monitoring (SHM) to sense strain and damage is a key challenge for such structures. The goal of this project is to electrically functionalize fibers for SHM and add functionality such as light emission at the same time. This project is a collaboration with Prof. Garrett Melenka from Mechanical Engineering.

Micro-inkjet printed pattern optimization using machine learning

The goal of this project is to eliminate non-idealities in micro-inkjet printed patterns. After ink is deposited onto a substrate, micron-scale patterns can be distorted due to uncontrollable fluid flow. We have developed a new method to supress this flow by changing the order in which droplets are placed on the substrate. We are extending this approach to general patterns by using machine learning.