AI–Guided 4D Printing of Carnivorous Plants–Inspired Microneedles for Accelerated Wound Healing
Abstract
ABSTRACT Artificial intelligence (AI) integrated with bioinspired design enables the development of materials that adapt and dynamically respond to biological cues. In this study, a Drosera capensis –inspired thermo‐responsive microneedle (MN) platform was developed, integrating motion, surface, and functional mimicry through AI‐guided 4D printing. Shape memory polymers (SMPs) composed of tert‐butyl acrylate (tBA) and 1,6‐hexanediol diacrylate (HDDA) were designed to exhibit reversible shape recovery upon thermal stimulation. The complex shape‐memory behavior was quantitatively modeled using multiple machine learning (ML) algorithms, including support vector regression (SVR), extreme gradient boosting (XGB), and Gaussian process regression (GPR). Among them, GPR demonstrated superior predictive accuracy ( R 2 > 0.99) and provided predictive means and 95% confidence intervals, highlighting its reliability in modeling nonlinear thermal recovery behavior and its potential for guiding process parameter optimization. The resulting MNs exhibited Drosera capensis ‐like coiling and grasping motions, enabling self‐actuating wound closure. Furthermore, the MNs were functionalized with adhesive DNA (aDNA) and Zn nanolayers via sputtering‐based plasma immersion ion implantation (S‐PIII). The Zn nanolayers facilitated sustained DNA release and endowed the MNs with intrinsic antibacterial activity. In diabetic wound models, the AI‐optimized biomimetic MN (BMMN) system significantly enhanced epithelial regeneration, collagen remodeling, and neovascularization, demonstrating adaptive and intelligent wound healing materials.
Article Details
Authors (22)
Hyun Lee
Moon‐Jo Kim
Research Institute of Intelligent Manufacturing & Materials Technology Korea Institute of Industrial Technology Incheon Republic of Korea
DongEung Kim
Research Institute of Intelligent Manufacturing & Materials Technology Korea Institute of Industrial Technology Incheon Republic of Korea
Chan Ho Moon
Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea
Seojoon Bang
Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea
Hyeong Seok Kang
Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea
Ju Yeong Gwon
Department of Bioengineering Hanyang University Seoul Republic of Korea
Jong Hwa Seo
Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea
Junhyub Jeon
Research Institute of Intelligent Manufacturing & Materials Technology Korea Institute of Industrial Technology Incheon Republic of Korea
Junhyuk Son
Research Institute of Intelligent Manufacturing & Materials Technology Korea Institute of Industrial Technology Incheon Republic of Korea
Munwon Lim
Research Institute of Intelligent Manufacturing & Materials Technology Korea Institute of Industrial Technology Incheon Republic of Korea
Minho Kang
Dong Yun Lee
Donghyun Lim
Chemical Biology and Therapeutics Science Program
Jung‐Hoon Park
Department of Convergence Medicine, Asan Medical Center University of Ulsan College of Medicine Seoul Republic of Korea
Gi Doo Cha
Department of Systems Biotechnology Chung‐Ang University Anseong‐si Gyeonggi‐do Republic of Korea
Soo‐Hong Lee
Department of Biomedical Engineering Dongguk University Seoul Republic of Korea
Tae‐Sik Jang
School of Biomedical Convergence Engineering Pusan National University Yangsan Republic of Korea
Kisuk Yang
Division of Bioengineering, College of Life Sciences and Bioengineering Incheon National University Incheon Republic of Korea
Yunho Jeong
Department of Organic and Nano Engineering, Human‐Tech Convergence Program Hanyang University Seoul Republic of Korea
Youngho Eom
Hyun‐Do Jung
Division of Materials Science and Engineering Hanyang University Seoul Republic of Korea