Evidence map›Paper›PMID 41309821›Full record

ArticleScientific reports2025

Inverse design framework for 4D printed structures using the finite element method.

Zaiyang Liu, Kusuma Betha Cahaya Imani, Mengtao Wang, Shugen Ma, Hidemitsu Furukawa, Shinichi Hirai, Zhongkui Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Zaiyang LiuDepartment of Robotics, Ritsumeikan University, Shiga, 525-8577, Japan.
Kusuma Betha Cahaya ImaniDepartment of Robotics, Ritsumeikan University, Shiga, 525-8577, Japan.
Mengtao WangDepartment of Electronic and Computer Engineering, Ritsumeikan University, Shiga, 525-8577, Japan.
Shugen MaRobotics & Autonomous Systems Thrust, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, 511453, China.
Hidemitsu FurukawaDepartment of Mechanical Systems Engineering, Yamagata University, Yonezawa, 992-8510, Japan.
Shinichi HiraiDepartment of Robotics, Ritsumeikan University, Shiga, 525-8577, Japan.
Zhongkui WangDepartment of Robotics, Ritsumeikan University, Shiga, 525-8577, Japan. wangzk@fc.ritsumei.ac.jp.

Funding

China Scholarship Council CSC202106220079New Energy and Industrial Technology Development Organization JPNP14004
6 · The paper itself

Abstract

In this paper, we present an inverse design framework based on the finite element method (FEM) tailored for 4D printed structures capable of undergoing programmable, stimulus-responsive shape transformations over time. In contrast to conventional forward simulations, which predict deformation from a given initial configuration, our inverse approach seeks to determine the required printed geometry that will evolve into a desired final shape under specific external stimuli. The proposed framework incorporates viscoelasticity, geometric nonlinearity and time-dependent behavior into the FEM solver, formulating the inverse design task as an optimization problem. It enables users to specify custom target shapes and boundary conditions, thereby providing the flexibility needed to address a wide range of design scenarios. A comprehensive implementation workflow of the framework is also presented. To demonstrate the versatility and feasibility of our approach, we present two representative case studies: a classic bilayer actuator with 4D-printed normal hydrogel and a soft gripper with electrically responsive hydrogel. The results confirm the framework's accuracy and adaptability to different external stimulus, highlighting its potential as a practical computational design tool for the inverse design of 4D printed structures.

Indexed as

4D printingFinite element methodGeometrical nonlinearityInverse designSoft gripper

Identifiers

PMID41309821
PMCPMC12660970

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Registered trials

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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.