NextM Seminar: Derya Tansel and David Guirguis

Next Manufacturing Center seminars are open to Center members, as well as other interested members of the CMU community. Next Manufacturing Center Consortium members are able to participate online.

Aerosol-jet printing of interconnect and chip-level stiffness gradients for stretchable electronics

Speaker: Derya Tansel, postdoctoral appointee, Sandia National Lab

The need for stretchable electronics arises from the demand for flexible and deformable electronic devices that can conform to curved surfaces, withstand mechanical strain, and enable new applications in areas such as wearable technology, healthcare modeling, robotics, and electronic skins. Stretchable electronics offer the potential to enhance comfort, enable seamless integration with the human body, and open new avenues for innovation in electronic systems. Aerosol jet printing (AJP) offers advantages for the fabrication of stretchable electronics including conformal deposition, high resolution, design flexibility, and integration capabilities.

AJP is used to study two significant areas in the development of stretchable devices: (1) fabricating stretchable substrates with reliable circuitry and (2) creating stiffness gradients in the stretchable substrate (e.g. polydimethyldisiloxane (PDMS)) toward reliable mechanical connection of chips to the substrate. With the high resolution capabilities of AJP, one- and two-layer stretchable devices with embedded circuitry are achieved. These stretchable devices are thin (< 100 µm), biocompatible, and capable of surviving high strain. Additionally, multi-layered electrocardiogram (ECG) patches are successfully fabricated and demonstrated. Stiffness gradients are needed in the PDMS to prevent premature failure at the chip-PDMS interface to survive high strains needed in biomedical and robotics applications. Producing these stiffness gradients are explored by testing AJP to print PDMS curing agent and, alternatively, to print polyimide directly onto PDMS, with the latter technique showing promise. The utilization of the AJP to fabricate direct-customized multi-layered stretchable devices with embedded stiffness gradients surrounding rigid components will significantly enhance accessibility, enabling quick prototyping in diverse applications, especially in the biomedical field.

Simulated annealing-based computational framework for hybrid lattice support structure design in LPBF additive manufacturing

Speaker: David Guirguis, postdoctoral associate, Beuth Laboratory

The variability in the printing outcome of additive manufacturing of metals is a major obstacle that hinders the reliance on the quality of printed parts and thus the potential for full production. In-situ monitoring coupled with machine learning can save labor-intensive costs and time-consuming ex-situ work by enabling accelerated process design that targets consistent printing quality.

In this talk, we will present our recent work on smart monitoring at the melt-pool scale and part scale through high-speed imaging and IR thermal imaging for the process development, identification of defects formation, and analysis of the balling formation mechanism.

We start by looking into the global effect of heat accumulation and monitoring the process at the part scale by using IR thermal imaging. An unsupervised machine learning-based method is developed to detect heat accumulation in real time without the need to spend a long time labeling millions of images. Finally, we zoom into the process and track the molten pool of metal as the laser moves to dive into the local aspects of the process.