Evidence map›Paper›PMID 39601118›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Near-Isotropic, Extreme-Stiffness, Continuous 3D Mechanical Metamaterial Sequences Using Implicit Neural Representation.

Yunkai Zhao, Lili Wang, Xiaoya Zhai, Jiacheng Han, Winston Wai Shing Ma, Junhao Ding, Yonggang Gu, Xiao-Ming Fu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Highly Efficient Discovery of 3D Mechanical Metamaterials via Monte Carlo Tree Search.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yunkai ZhaoDepartment of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Lili WangDepartment of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Xiaoya ZhaiDepartment of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.ORCID https://orcid.org/0000-0002-5209-8738
Jiacheng HanDepartment of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Winston Wai Shing MaDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Junhao DingDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Yonggang GuExpertmental Center of Engineering and Material Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.
Xiao-Ming FuDepartment of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, 230026, China.

Funding

the national natural science fundation of china 62402467the Open Project Program of the State Key Laboratory of CAD\&CG, Zhejiang university A2303the Strategic Priority Research Program of the Chinese Academy of Sciences, China XDB0640000USTC Research Funds of the Double First-Class Initiative YD0010002010
6 · The paper itself

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.

Indexed as

extreme stiffnessimplicit neural representationisotropic metamaterialsmetamaterial sequences

Identifiers

PMID39601118
PMCPMC11744521

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.