Co-design of programmable material systems
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.
Authors
- Xiaojia Shelly Zhang (ORCID: https://orcid.org/0000-0003-4878-8637)
- Ruike Renee Zhao (ORCID: https://orcid.org/0000-0002-9292-5267)
- Bolin Chen (ORCID: https://orcid.org/0000-0002-7230-7197)
- Ying-Kuan Tsai (ORCID: https://orcid.org/0009-0005-8853-2216)
- Dex Doksoo Lee
- Jay Sim
- Liwei Wang
- Wei Chen
Institutions
- Northwestern University (US)
- University of Illinois Urbana-Champaign (US)
- National Center for Supercomputing Applications (US)
- Carnegie Mellon University (US)
- Stanford University (US)
Publication Details
- Journal
- npj Metamaterials
- Published
- 2026-09-04
- DOI
- https://doi.org/10.1038/s44455-026-00039-4
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- National Aeronautics and Space Administration
- Materials Research Science and Engineering Center, Harvard University
- Materials Research Science and Engineering Center, Northwestern University
- Division of Materials Research
- Division of Civil, Mechanical and Manufacturing Innovation
- Division of Electrical, Communications and Cyber Systems
- Air Force Office of Scientific Research