EHDprint dataset ver2

Abstract

Advances in high resolution electrohydrodynamic inkjet (EHD) printing of functional materials are poised to enable additive and scalable large-area manufacturing for optical metasurfaces and flexible electronics. This would provide a fully additive, scalable pathway for the fabrication of flexible optoelectronics that rivals and even exceeds the performance of conventional subtractive electronics processing technologies. EHD printing moves additive printing of functional materials from the domain of conventional printing resolutions of >20 microns down to single micron and even submicron regimes that exceed the patterning resolution for large area lithography used in thin film silicon on glass processing for displays. There are, however, improvements in the technique that are required to make this a manufacturable technology of use to a broader range of materials and applications spanning electronics, photonic and optical metasurfaces, and interconnects. Process monitoring, optimization of new inks, and design for EHD are challenging due to the extremely small, high velocity femtoliter droplet sizes that are 1000X smaller than conventional inkjet droplets and high droplet velocities and are beyond the limits of conventional droplet and imaging approaches. To achieve high throughput and reproducibility in the EHD inkjet’s complex process space, proven in-situ laser diffraction, in-situ imaging and characterization strategies will be used to optimize, train, and deploy machine learning models specialized in prediction and control of complex dynamical systems. By providing reproducible feature control at the micron and even submicron scale, this ML-guided manufacturing approach will make deployment of large-area photonic, sensing and high resolution flexible printed circuit and photonic technologies with features sizes approaching the wavelength of light feasible at scale. With this collaboration between the University of Washington, Iowa State University, and small businesses, we form an interdisciplinary team with members in different backgrounds and expertise in printed electronics, metasurface design, materials, printing hardware and applications. We expect the project to have a disruptive impact on advanced ultralight optical materials, additive manufacture of micron-scale interconnects and functional devices, and data-driven process control. The proposed work directly addresses Part E. of the FlexTech/SEM RFP, specifically advancing the development of optical metamaterials and AI for process optimization. The work, as a sustainable, additive manufacturing alternative to subtractive semiconductor processing, addresses Part C. Lastly, this project also addresses a key scope area for Part D – Heterogeneous packaging as it applies to FHE- Heterogeneous Integration, specifically in that it provides an additive processing with fine lines and pads with pads separation of <10um. The industrial collaborators provide a pathway for manufacturing and product commercialization of this work.