Evidence map›Paper›PMID 42807580›Full record

ArticleResearch (Washington, D.C.)2026

Geometry-Mechanics Compatibility Enables Interpretable Inverse Design of Non-Rigid Origami.

Yucong Sun, Keyao Song, Yiqiu Wang, Wenshi Xue, Yang Li, Xiang Zhou

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Yucong SunSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID https://orcid.org/0009-0005-5473-555X
Keyao SongSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID https://orcid.org/0000-0001-7504-1040
Yiqiu WangSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID https://orcid.org/0009-0008-3139-116X
Wenshi XueSchool of Integrated Circuits, Wuhan University, Wuhan, Hubei 430072, China.ORCID https://orcid.org/0009-0000-5585-3295
Yang LiSchool of Integrated Circuits, Wuhan University, Wuhan, Hubei 430072, China.ORCID https://orcid.org/0000-0002-4939-8174
Xiang ZhouSchool of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID https://orcid.org/0000-0003-1317-2912

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-rigid origami offers a geometric route to programmable mechanical and kinematic functions in metamaterials, deployable structures, and robotic mechanisms. Yet, its inverse design remains constrained by a fundamental modeling dilemma: High-fidelity nonlinear simulations become prohibitively expensive when repeatedly applied across large design spaces, whereas reduced models are efficient but often rely on pattern-specific assumptions whose validity is difficult to assess across crease patterns. Here, we introduce a compatibility-guided inverse-design framework that uses a geometry-mechanics test to determine when a parameterized design family can be reliably represented by a single-degree-of-freedom (1-DOF) kinematic model. Once qualified, the reduced model enables rapid and interpretable exploration of the admissible design space, while incompatible cases remain evaluated using high-fidelity analysis. We demonstrate the framework by designing origami metamaterials with programmable multistability and multi-plateau mechanical responses, enabled by the identification and removal of key geometric constraints. Its broader applicability is further illustrated through target-shape morphing and task-specific robotic motion programming. By turning model reduction from an assumed approximation into an explicit design decision, this framework provides a geometry-driven route from target functions to manufacturable non-rigid origami while reducing reliance on simulation-intensive search.

Identifiers

PMID42807580
PMCPMC13617216

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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.