制作
3D打印
熔融沉积模型
计算机科学
材料科学
构造(python库)
喷嘴
运动规划
路径(计算)
墨水池
纳米技术
形态发生剂
沉积(地质)
微流控
分布式计算
堆栈(抽象数据类型)
忠诚
异构网络
机械工程
涂层
工程制图
流量(数学)
扩散
作者
Wenyu Ning,Fei Duan,Lily Raymond,Weikang Lv,Jiangtao Hao,Yang Yang,Wenbo Jin,Jian Yang,Shijun Li,Sai Ma,Cheng Zhang,Prof. Yifei Jin,Danyang Zhao
标识
DOI:10.1088/1758-5090/ae36f8
摘要
Abstract Multi-nozzle 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.
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