Digital Twins for Printed Electronics for 3D Packaging, High-performance Sensors, and High-capacity Batteries

[]Printed electronics has emerged as a versatile technique for on-demand fabrication of passives, interconnects, and active devices. Our group has recently extended this technique to create freeform devices in Three-Dimensional space that have opened exciting application areas for this technology. The manufacturing process for printed electronics, however, can suffer from process drifts and does not have an active feedback loop to fix errors. In this research, we develop a digital twin for aerosol jet 3D printing, a jetting-based method to create printed electronics to address this concern. This work, done in collaboration with an ECE faculty at CMU, matches observations with outcomes expected from a physics-based process model, and continuously updates the hidden variables to minimize this error via probabilistic estimation techniques.
We then use the aerosol jet 3D printing to demonstrate devices with extraordinary performances that cannot be achieved by any other method. Specifically, we show 3D electrodes by this technique that enable detection of pathogens and breast cancer biomarkers in 10-12 seconds at femtomolar levels (fastest detection yet reported). We also show fully customizable brain-computer interfaces (BCIs) that record electrical signals between neurons at densities of thousands of electrodes/cm2, which is 5-10× the current state-of-the-art technologies. We also demonstrated the printing of high-capacity Li-ion batteries and thin flexible robotic skins with embedded sensors.
Speaker(s): Rahul Panat,
Virtual: https://events.vtools.ieee.org/m/481231