| Autor: |
Mengjie Zhang, Xiru Fan, Le Dong, Chengru Jiang, Oliver Weeger, Kun Zhou, Dong Wang |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Advanced Science, Vol 11, Iss 28, Pp n/a-n/a (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2198-3844 |
| DOI: |
10.1002/advs.202309932 |
| Popis: |
Abstract Grayscale digital light processing (DLP) printing is a simple yet effective way to realize the variation of material properties by tuning the grayscale value. However, there is a lack of available design methods for grayscale DLP 3D‐printed structures due to the complexities arising from the voxel‐level grayscale distribution, nonlinear material properties, and intricate structures. Inspired by the dexterous motions of natural organisms, a design and fabrication framework for grayscale DLP‐printed soft robots is developed by combining a grayscale‐dependent hyperelastic constitutive model and a voxel‐based finite‐element model. The constitutive model establishes the relationship between the projected grayscale value and the nonlinear mechanical properties, while the voxel‐based finite‐element model enables fast and efficient calculation of the mechanical performances with arbitrarily distributed material properties. A multiphysics modeling and experimental method is developed to validate the homogenization assumption of the degree of conversion (DoC) variation in a single voxel. The design framework is used to design structures with reduced stress concentration and programmable multimodal motions. This work paves the way for integrated design and fabrication of functional structures using grayscale DLP 3D printing. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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