Related Experiment Video
Updated: Jan 14, 2026

Multimodal 3D Printing of Phantoms to Simulate Biological Tissue
Published on: January 11, 2020
High-precision path planning for multi-material 3D bioprinting of complex structures
Wenyu Ning1, Fei Duan1, Lily Raymond2
1State Key Laboratory of High-Performance Precision Manufacturing, School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, People's Republic of China.
Abstract:
Multi-nozzle (MN) collaborative bioprinting enables high-precision fabrication of complex tissue and organ models through synchronous deposition of heterogeneous bioinks within a shared substrate, offering a promising solution for efficient construct generation. However, challenges remain, including nozzle motion interference and inconsistent geometric fidelity when printing asymmetric structures with heterogeneous materials. This study proposes a multi-nozzle collaborative and alternating printing path (MN-CAPP) planning strategy that integrates intra-layer repartitioning with adaptive mode switching to optimize the fabrication of complex heterogeneous tissues. By printing two Y-shaped vascular models with distinct interfaces, MN-CAPP preserves the efficiency advantages of collaborative printing for symmetric regions, improving printing efficiency by 32.4% and 33.0%, respectively, compared with single-nozzle printing. Furthermore, MN-CAPP adaptively regulates printing strategies for regions with significant nozzle step differences based on ink rheology and printing parameters. During the fabrication of size-differentiated scaffolds, the proposed path effectively suppresses edge material stack in small-scale scaffolds, resulting in a 33.8% improvement in pore diffusion degree relative to conventional collaborative printing. Finally, successful fabrication of a heterogeneous rabbit hepatobiliary model demonstrates a deviation of ⩽4% in critical feature dimensions from design specifications, confirming MN-CAPP's effectiveness in enhancing both printing precision and dimensional reproducibility for complex asymmetric structures.

