Home Research & Education Tsinghua researchers develop DLP 3D printing process for complex magnetic soft robots

Tsinghua researchers develop DLP 3D printing process for complex magnetic soft robots

Picture: Jiadao Wang, State Key Laboratory of Tribology in Advanced Equipment, Department of Mechanical Engineering, Tsinghua University

A research team from Tsinghua University has introduced an advanced 3D printing method based on Digital Light Processing (DLP) technology. This approach enables, for the first time, the fabrication of complex magnetic structures composed of different materials in a single manufacturing step. The results were published on February 26, 2025, in the journal Cyborg and Bionic Systems.

According to study author Jiadao Wang, conventional methods for creating magnetic structures—such as mold-based forming or UV lithography—face significant limitations. These techniques are often restricted in terms of geometry and material diversity, and they typically require uniform material compositions, which complicates the development of multifunctional magnetic components. The new process addresses these issues by enabling the simultaneous printing of hard magnetic and superparamagnetic materials in a single step.

As part of the study, the researchers developed a soft robot composed of a composite material combining hard magnetic and superparamagnetic elements. In addition to mechanical and magnetic characterization, practical applications were demonstrated: the robots were able to navigate solid surfaces, overcome obstacles, grasp and transport objects, and swim in liquid environments. The researchers used multiphysics simulations to analyze swimming behavior.

Challenges such as magnetic particle adhesion to carrier films, reduced curing depth, and particle sedimentation were systematically addressed throughout the project. Following successful biocompatibility testing, the printed structures may also find application in medical fields, such as targeted drug delivery via capsule robots. The research was funded by the National Natural Science Foundation of China.


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