Large-Scale, Two-Photon, Three-Dimensional Printing Enabled by Metaoptics

Executive Summary

We will utilize machine-learning-designed metaoptic arrays to scale up two-photon, three-dimensional printing for wafer-scale additive manufacturing, offering submicron resolution and substantially faster printing throughput. If successful, project outcomes will open doors to a vast, unexplored application space of micro/nano-architected materials, which can be rationally designed, computationally optimized, and additively manufactured for enhanced and novel functionalities in high-strain-rate mechanics, high-energy-density physics, energy storage, carbon reduction, and microelectronics. 

Publications, Presentations, and Patents

Xia, Xiaoxing, Christopher M. Spadaccini, and Julia R. Greer. "Responsive materials architected in space and time." Nature Reviews Materials 7, no. 9 (2022): 683-701.

Oliva, Sergi Bernaus, Felix T. Bölle, A. T. Las, Xiaoxing Xia, and Ivano E. Castelli. "Reinforcement learning-based design of shape-changing metamaterials." Journal of Materials Chemistry A (2023).

Xia, Xiaoxing. “Controlling Phase Transition and Multi-phase Boundaries in Architected Materials.” The 2023 Gordon Research Conference on Micro and Nanoscale Phase Change Phenomena (2023).

Xia, Xiaoxing. “Functionality by Design: Architected Materials and Devices Enabled by Two-Photon 3D Printing.” UCSD Department of Mechanical and Aerospace Engineering Seminar (2023).