Materials that can sense and respond are essential to advancing biomedical and defense technology. Metamaterials, or architected materials, have microstructure geometries designed from first principles that enable extraordinary, tunable behaviors—lightweight yet strong, resilient in extreme environments, and tailorable to specific applications in sensing, biomedical applications, and micro-electromechanical systems. However, moving metamaterials towards physical intelligence in devices requires careful design and innovative fabrication driven by theoretical and computational efforts to fully predict their behavior and inform their application.
I use solid mechanics principles to design, fabricate, and characterize physically intelligent materials to transform how we use engineering materials in complex engineering problems across medical, defense, and robotics applications.
Sun, R.*, Chen, A.*, Ji, Y., Yee, D., Portela, C. (2025). Magnetically Responsive Microprintable Soft Nanocomposites with Tunable Nanoparticle Loading. arXiv. DOI.
* indicates equal contribution
Magnetic remote actuation of soft materials has been demonstrated at the macroscale using hard-magnetic particles for applications such as transforming materials and medical robots. However, due to manufacturing limitations, few microscale magnetically responsive devices exist and remain difficult to fabricate at the microscale. Even so, among successfully fabricated microscale soft-magnetic composites, limited control over magnetic-particle loading, distribution, and matrix-phase stiffness has hindered their functionality.
This work combines two-photon lithography (microscale 3D printing) with iron-oxide nanoparticle co-precipitation (nanoparticle growth) to fabricate 3D-printed microscale nanocomposites having features down to 8 µm with spatially tunable nanoparticle distribution. Using uniaxial compression experiments and vibrating sample magnetometry, we characterize the mechanical and magnetic properties of the composite, achieving millimeter-scale elastic deformations. We control nanoparticle content by modulating laser power of the print to imbue complex parts with magnetic functionality, demonstrated by a soft robotic gripper and a bistable bit register and sensor. This approach enables precise control of structure and functionality, advancing the development of microscale metamaterials and robots with tunable mechanical and magnetic properties.
Sun, R., Lem, J., Kai, Y., DeLima, W., Portela, C. (2024). Tailored Ultrasound Propagation in Microscale Metamaterials via Inertia Design. Science Advances. DOI.
The quasi-static properties of micro-architected (meta)materials have been extensively studied over the past decade, but their dynamic responses, especially in acoustic metamaterials with engineered wave propagation behavior, represent a new frontier. However, challenges in miniaturizing and characterizing acoustic metamaterials in high-frequency (MHz) regimes have hindered progress toward experimentally implementing ultrasonic-wave control.
This work presents an inertia design framework based on positioning microspheres to tune responses of 3D microscale metamaterials. We demonstrate tunable quasi-static stiffness by up to 75% and dynamic longitudinal-wave velocities by up to 25% while maintaining identical material density. Using noncontact laser-based dynamic experiments of tunable elastodynamic properties and numerical demonstrations of spatio-temporal ultrasound wave propagation, we explore the tunable static and elastodynamic property relation. This design framework expands the quasi-static and dynamic metamaterial property space through simple geometric changes, enabling facile design and fabrication of metamaterials for applications in medical ultrasound and analog computing.
Kai, Y., Dhulipala, S.*, Sun, R.*, Lem, J., DeLima, W., Pezeril, T., Portela, C. (2023). Dynamic Diagnosis of Metamaterials via Laser-Induced Vibrational Signatures. Nature. DOI, Nature Briefing Article.
* indicates equal contribution
Mechanical metamaterials at the microscale exhibit exotic static properties owing to their engineered building blocks, but their dynamic properties have remained substantially less explored. Their design principles can target frequency-dependent properties and resilience under high-strain-rate deformation, making them versatile materials for applications in lightweight impact resistance acoustic waveguiding or vibration damping. However, accessing dynamic properties at small scales has remained a challenge owing to low-throughput and destructive characterization or lack of existing testing protocols.
This work demonstrates a high-throughput, non-contact framework that uses MHz-wave-propagation signatures within a metamaterial to non-destructively extract dynamic linear properties, omnidirectional elastic information, damping properties and defect quantification. Using rod-like tessellations of microscopic metamaterials, we report up to 94% direction-dependent and rate-dependent dynamic stiffening at strain rates approaching 102 1/s, as well as damping properties three times higher than their constituent materials. We also show that frequency shifts in the vibrational response allow for characterization of invisible defects within the metamaterials and that selective probing allows for the construction of experimental elastic surfaces, which were previously only possible computationally. Our work provides a route for accelerated data-driven discovery of materials and microdevices for dynamic applications such as protective structures, medical ultrasound or vibration isolation.
Liu, K., Sun, R., Daraio, C. (2022). Growth Rules for Irregular Architected Materials with Programmable Properties. Science. DOI.
Biomaterials display microstructures that are geometrically irregular and functionally efficient. Understanding the role of irregularity in determining material properties offers a new path to engineer materials with superior functionalities, such as imperfection insensitivity, enhanced impact absorption, and stress redirection.
We uncover fundamental, probabilistic structure–property relationships using a growth-inspired program that evokes the formation of stochastic architectures in natural systems. This virtual growth program imposes a set of local rules on a limited number of basic elements. It generates materials that exhibit a large variation in functional properties starting from very limited initial resources, which echoes the diversity of biological systems. We identify basic rules to control mechanical properties by independently varying the microstructure’s topology and geometry in a general, graph-based representation of irregular materials.