journal article·2025-03Open access

4D Printing of Electrically Activated Reversible Deformation Composite Actuators

Nan Wang, Xingzhi Xiao, Tingting Liu, Changdong Zhang, Mingfei Gu, Ximeng Qi

Advanced Materials Technologies· Volume 10· Issue 6

Abstract

Abstract 4D printing of shape memory polymers combines smart materials and 3D printing technology enabling transformations in shape, properties, and functionalities. However, existing research predominantly addresses unidirectional deformation, necessitating the application of external force for reprogramming after each deformation. This limitation impedes the realization of continuous reversible deformation, posing challenges to meet the demands of reversible deformation in complex scenarios. This study introduces an innovative method for fabricating electrically activated reversible composite actuators by 4D printing. The composite actuator's structure comprises conductive ink and shape memory PEEK. Upon current excitation, the composite actuator attains controlled and reversible deformation, attributed to the electro‐thermal sintering properties of the conductive ink, combined with the shape memory effect and phase transition of PEEK. The actuator's deformation performance is validated by subjecting the composite actuator to varying high‐low current excitations, modifying the excitation circuit's configuration, and refining the PEEK printing process. Concurrently, the reversible deformation performance of the actuator is evaluated through the application of cyclic current excitation. Additionally, an inchworm‐like crawling robot is fabricated to demonstrate validation, achieving a speed exceeding 8 mm min −1 . The 4D printing technique for composite actuators developed in this study expands potential applications in fields such as reversible actuators, soft robotics, and deployable structures.
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Research context

OpenAlex topics: Advanced Materials and Mechanics · Polymer composites and self-healing · Surface Modification and Superhydrophobicity

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Mechanical Engineering Nanjing University of Science and Technology Nanjing 210094 China

Funding

National Key Research and Development Program of China

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