Metamaterials are specially designed materials with unique 3D structures at the micro- and nanoscale, giving them properties not found in nature.
By carefully engineering their internal structure, these materials can remarkably interact with waves like light, sound, or even seismic waves. For example, they can bend light in unusual directions, enabling technologies like invisibility cloaks or superlenses that reveal tiny details beyond normal limits.
In the last decade, metamaterials have shown great promise for solving tough engineering challenges where conventional materials fail. However, their full potential is still limited by difficulties in designing, manufacturing, and testing them.
MIT scientists are paving the way for more intelligent, adaptive materials with their latest research on multiscale architected materials. The study dives into cutting-edge methods for designing, fabricating, and understanding these engineered materials while addressing existing gaps in knowledge and presenting exciting opportunities for the future.
A significant highlight of their work is the proposed roadmap for accelerating discoveries in architected materials with programmable properties. By combining experimental techniques and computational advancements, they aim to unlock the full potential of these materials.
Software tool can help architects to design efficient buildings
Carlos Portela, a leading expert at MIT, emphasized that progress in scalable fabrication, high-throughput testing, and AI-driven design optimization could transform material science and mechanics. He envisions breakthroughs that redefine engineering challenges and influence technologies we use in everyday life.
To push boundaries further, Portela highlights the need for innovation across multiple scales—from nano to macro—and a deeper understanding of material behavior over varying time scales, such as slow deformation or dynamic impact.
The study outlines a plan to speed up the development of architected materials with programmable properties by combining advanced experimentation and computational tools. It highlights the use of AI and machine learning to design and optimize these materials.
Techniques like miniaturized high-throughput experiments, non-contact methods, and extreme-condition testing will provide valuable data, enabling faster discovery and enhancement of metamaterials with exceptional capabilities.
Journal Reference
Surjadi, J. U., & Portela, C. M. (2025). Enabling three-dimensional architected materials across length scales and timescales. Nature Materials, 1-13. DOI: 10.1038/s41563-025-02119-8