High-speed multinozzle additive manufacturing and extrusion modeling of large-scale microscaffold networks

2021 
Abstract In this work, a six-degree-of-freedom (6-DOF) robotic infrastructure is used for the high-speed additive manufacturing (AM) of large-scale networks of high-resolution scaffolds made of microfilaments, referred as microscaffold networks. The use of a multinozzle printhead, featuring an extrusion nozzle array of 26 cylindrical nozzles of 250 µm inner diameter, enabled the AM of microscaffolds with very high flow rate (i.e., > 300 mm³/s) and printing speed (i.e., up to 250 mm/s) while preserving fine features. A Multinozzle Extrusion Prediction Model (MEPM), based on capillary rheometry, was developed to predict the extrusion pressure gradient and the overall total volumetric flow rate of the printing process. The MEPM predictions are made as a function of the material used, printing speed and multinozzle printhead configuration (i.e., nozzles inner diameter and number of nozzles). Experimental pressures and flow rates strongly match the MEPM predictions for a printing speed range of 0–250 mm/s. The MEPM is also used to explore the design of other multinozzle configurations. The advantages of the high-speed multinozzle AM infrastructure is demonstrated through four case studies. The high-speed printing of microscaffold network demonstrated a printing speed of up to 250 mm/s, with flow rate of ~ 319.4 mm³ /s. The 6-DOF of the robot are used to manufacture a variable pore size microscaffold network, which shows an achievable inter-filaments spacing of 0–750 µm. The printing of a large-scale partitioned microscaffold network spans over an area of ~ 9 × 104 mm2. Finally, a relatively thick partitioned microscaffold network is manufactured up to 50 layers (~ 10 mm thick). Findings of this work contribute to the development of multinozzle printheads, high-speed 3D printing and high-resolution microscaffold manufacturing, which could be targeted for a wide range of applications including sound absorption, smart materials, and tissue engineering.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    32
    References
    0
    Citations
    NaN
    KQI
    []