Autonomous codesign and fabrication of multistimuli-responsive material systems

Responsive materials offer solutions to complex engineering challenges by enabling systems to adapt their shapes or properties in response to external stimuli. To fully harness the potential of responsive materials, inverse design methods that integrate multiple types of stimuli and manufacturing processes are necessary. We present a unified, autonomous codesign framework that simultaneously optimizes structure, manufacturing, materials, and stimuli for responsive material systems, achieving target shape morphing under multiple stimuli without relying on human heuristics or expertise. It integrates generalized topology optimization with hybrid data-physics differentiable simulations to achieve flexible, manufacturing-aware designs for network-like responsive material systems. We showcase our framework with a multimaterial three-dimensional printing process with high material tunability, which we use to fabricate liquid crystal elastomer systems that morph into different forms in response to heat and light. The exceptional flexibility and efficiency of our method will advance shape-morphing applications spanning soft robotics to drug delivery.

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Publication Details

Journal
Science Advances
Published
2025-09-12
DOI
https://doi.org/10.1126/sciadv.adx4409
Citations
5
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
4.77
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article

Autonomous codesign and fabrication of multistimuli-responsive material systems

Ryan L. Truby, Liwei Wang, Alexander L. Evenchik, Wei Chen et al.
5 citations
Science Advances
Topology Optimization in Engineering
4.77
article

Autonomous codesign and fabrication of multistimuli-responsive material systems

Ryan L. Truby, Liwei Wang, Alexander L. Evenchik, Wei Chen, J.M. Yang
article en
5 citations

Abstract

Responsive materials offer solutions to complex engineering challenges by enabling systems to adapt their shapes or properties in response to external stimuli. To fully harness the potential of responsive materials, inverse design methods that integrate multiple types of stimuli and manufacturing processes are necessary. We present a unified, autonomous codesign framework that simultaneously optimizes structure, manufacturing, materials, and stimuli for responsive material systems, achieving target shape morphing under multiple stimuli without relying on human heuristics or expertise. It integrates generalized topology optimization with hybrid data-physics differentiable simulations to achieve flexible, manufacturing-aware designs for network-like responsive material systems. We showcase our framework with a multimaterial three-dimensional printing process with high material tunability, which we use to fabricate liquid crystal elastomer systems that morph into different forms in response to heat and light. The exceptional flexibility and efficiency of our method will advance shape-morphing applications spanning soft robotics to drug delivery.

Science AdvancesVol. 11(37)
Northwestern University (US), Carnegie Mellon University (US)
Openalex Percentile: Top 5%
Topology Optimization in Engineering
4.77
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