Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation
Abstract Mechanical metamaterials represent a distinct category of engineered materials characterized by their tailored density distributions to have unique properties. It is challenging to create continuous density distributions to design a smooth mechanical metamaterial sequence in which each meta...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Advanced Science |
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| Online Access: | https://doi.org/10.1002/advs.202410428 |
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| author | Yunkai Zhao Lili Wang Xiaoya Zhai Jiacheng Han Winston Wai Shing Ma Junhao Ding Yonggang Gu Xiao‐Ming Fu |
| author_facet | Yunkai Zhao Lili Wang Xiaoya Zhai Jiacheng Han Winston Wai Shing Ma Junhao Ding Yonggang Gu Xiao‐Ming Fu |
| author_sort | Yunkai Zhao |
| collection | DOAJ |
| description | Abstract Mechanical metamaterials represent a distinct category of engineered materials characterized by their tailored density distributions to have unique properties. It is challenging to create continuous density distributions to design a smooth mechanical metamaterial sequence in which each metamaterial possesses stiffness close to the theoretical limit in all directions. This study proposes three near‐isotropic, extreme‐stiffness, and continuous 3D mechanical metamaterial sequences by combining topology optimization and data‐driven design. Through innovative structural design, the sequences achieve over 98% of the Hashin–Shtrikman upper bounds in the most unfavorable direction. This performance spans a relative density range of 0.2–1, surpassing previous designs, which fall short at medium and higher densities. Moreover, the metamaterial sequence is innovatively represented by the implicit neural function; thus, it is resolution‐free to exhibit continuously varying densities. Experimental validation demonstrates the manufacturability and high stiffness of the three sequences. |
| format | Article |
| id | doaj-art-f65602ff1f714023b8eb37c0f7757f89 |
| institution | Kabale University |
| issn | 2198-3844 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advanced Science |
| spelling | doaj-art-f65602ff1f714023b8eb37c0f7757f892025-01-20T13:04:18ZengWileyAdvanced Science2198-38442025-01-01123n/an/a10.1002/advs.202410428Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural RepresentationYunkai Zhao0Lili Wang1Xiaoya Zhai2Jiacheng Han3Winston Wai Shing Ma4Junhao Ding5Yonggang Gu6Xiao‐Ming Fu7Department of Mathematical Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaDepartment of Mathematical Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaDepartment of Mathematical Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaDepartment of Mathematical Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaDepartment of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong ChinaDepartment of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong ChinaExpertmental Center of Engineering and Material Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaDepartment of Mathematical Sciences University of Science and Technology of China Hefei Anhui 230026 ChinaAbstract Mechanical metamaterials represent a distinct category of engineered materials characterized by their tailored density distributions to have unique properties. It is challenging to create continuous density distributions to design a smooth mechanical metamaterial sequence in which each metamaterial possesses stiffness close to the theoretical limit in all directions. This study proposes three near‐isotropic, extreme‐stiffness, and continuous 3D mechanical metamaterial sequences by combining topology optimization and data‐driven design. Through innovative structural design, the sequences achieve over 98% of the Hashin–Shtrikman upper bounds in the most unfavorable direction. This performance spans a relative density range of 0.2–1, surpassing previous designs, which fall short at medium and higher densities. Moreover, the metamaterial sequence is innovatively represented by the implicit neural function; thus, it is resolution‐free to exhibit continuously varying densities. Experimental validation demonstrates the manufacturability and high stiffness of the three sequences.https://doi.org/10.1002/advs.202410428extreme stiffnessimplicit neural representationisotropic metamaterialsmetamaterial sequences |
| spellingShingle | Yunkai Zhao Lili Wang Xiaoya Zhai Jiacheng Han Winston Wai Shing Ma Junhao Ding Yonggang Gu Xiao‐Ming Fu Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation Advanced Science extreme stiffness implicit neural representation isotropic metamaterials metamaterial sequences |
| title | Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation |
| title_full | Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation |
| title_fullStr | Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation |
| title_full_unstemmed | Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation |
| title_short | Near‐Isotropic, Extreme‐Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation |
| title_sort | near isotropic extreme stiffness continuous 3d mechanical metamaterial sequences using implicit neural representation |
| topic | extreme stiffness implicit neural representation isotropic metamaterials metamaterial sequences |
| url | https://doi.org/10.1002/advs.202410428 |
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