Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants

Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants

Current limitations in implant design often lead to trade-offs between minimally invasive surgery and achieving the desired post-implantation functionality. Here, we present an artificial intelligence inverse design paradigm for creating deployable implants as planar and tubular thermal mechanical m...

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Bibliographic Details
Main Author: Pengcheng Jiao (8017532) (author)
Other Authors: Chenjie Zhang (11328211) (author), Wenxuan Meng (20496077) (author), Jiajun Wang (512021) (author), Daeik Jang (20496080) (author), Zhangming Wu (12580546) (author), Nitin Agarwal (179363) (author), Amir H. Alavi (20496083) (author)
Published: 2025
Subjects:
Biophysics
Genetics
Neuroscience
Cancer
Science Policy
Hematology
Space Science
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
various cell structures
guided inverse design
fully deployed states
enabling minimally invasive
clinically relevant factors
clinically viable implants
minimally invasive surgery
metamaterial implants based
creating deployable implants
metamaterial implants
personalized surgery
deployable thermo
tracheal stents
temperature changes
subsequently developed
sectional area
results demonstrate
proposed vision
prioritizes biocompatibility
precision simultaneously
optimal microstructure
neural network
model allows
large database
implantation functionality
evolutionary algorithm
desired post
desired performance
designing patient
demonstrated using
broader vision
bending stiffnesses
automatic determination
artificial intelligence
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