Asset Details
Do you wish to reserve the book?
Mining extreme properties from a large metamaterial database
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Mining extreme properties from a large metamaterial database
Do you wish to request the book?
Mining extreme properties from a large metamaterial database
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Mining extreme properties from a large metamaterial database
2025
Overview
Truss metamaterials exhibit a wide range of properties due to their unique node-strut architectures, which are artificially engineered through a delicate design process. However, their advanced applications are presently constrained by limited architectures and property ranges. Here, we propose a framework that systematically encodes architectural topologies and generates a comprehensive architecture-property database of over 1.8 million truss metamaterials. This database reveals numerous architectures with extreme properties, including Young’s moduli near the Voigt bound, programmable Poisson’s ratios from extremely negative to positive, and exceptional isotropic bi-mode. Moreover, we introduce the concept of mechanical isomerism. This mechanical isomerism uncovers the underlying mapping from symmetric and asymmetric architectures to extreme properties through the study of architectural variations. Our findings bridge theoretical design and engineering requirements in mining extreme properties from truss metamaterials, further enabling data-driven design, shape optimization, and advanced manufacturing.
This work mines extreme mechanical properties in 2D truss metamaterials via an architecture design method and a large database. Main findings include extreme Young’s modulus, a wide range of Poisson’s ratio, extreme bi-mode, and mechanical isomerism.
