Evidence map›Paper›PMID 42701396›Full record

ReviewNPJ metamaterials2026

Co-design of programmable material systems.

Dex Doksoo Lee, Liwei Wang, Bolin Chen, Ying-Kuan Tsai, Jay Sim, Ruike Renee Zhao, Xiaojia Shelly Zhang, Wei Chen

Abstract readReview
In one paragraph

Review in NPJ metamaterials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

8 authors.

Dex Doksoo Lee *Department of Mechanical Engineering, Northwestern University, Evanston, IL USA.
Liwei Wang *Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA USA.
Bolin ChenDepartment of Mechanical Engineering, Northwestern University, Evanston, IL USA.
Ying-Kuan TsaiDepartment of Mechanical Engineering, Northwestern University, Evanston, IL USA.
Jay SimDepartment of Mechanical Engineering, Stanford University, Stanford, CA USA.
Ruike Renee ZhaoDepartment of Mechanical Engineering, Stanford University, Stanford, CA USA.
Xiaojia Shelly ZhangDepartment of Civil and Environmental Engineering, University of Illinois Urbana-Champaign, Urbana, IL USA.
Wei ChenDepartment of Mechanical Engineering, Northwestern University, Evanston, IL USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in manufacturing, stimuli-responsive materials, and actuation technologies have fueled the development of programmable material systems (PMS) that can change their functional states in response to external stimuli. This functional switch is instrumental for applications that demand adaptability and robustness under dynamic environments such as wearable electronics, haptic interfaces, and soft robots. In principle, achieving an interesting degree of programmability in material systems is a challenging design problem as it requires careful consideration of geometry, material, stimulus, and process amidst dynamic environments. This task becomes even more challenging when compounded by multifunctionality requirements, multiphysics modeling, coupling among the design entities, and resource-intensive performance evaluation. In practice, prevailing approaches often heuristically fix some entities or decouple their interactions, which significantly limits achievable performance and generalizability of the design approach. Motivated by this gap between promise and practice, we present a co-design formalism that highlights shared design considerations across prior works and categorizes design strategies for managing complexity. With the proposed lens, we reveal common threads in existing design approaches, identify opportunities and open research questions for co-design to achieve better performance and generalization. Through this perspective article, we aim to lay a design foundation for boosting progress in this emerging interdisciplinary field.

Indexed as

EngineeringMaterials scienceMathematics and computing

Identifiers

PMID42701396
PMCPMC13545007

What OpenQuestion holds

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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.