Session: Research Posters

Paper Number: 173017

Layerless 3d Printing of Metal and Multi-Metal Structures via Continuous Liquid Interface Production (Clip) 

The field of metal additive manufacturing (MAM) has become the current state-of-the-art technology for fabricating intricately complex and high-quality metal components with a wide range of industrial applications such as aerospace parts, biomedical devices, and electronics. A digital model representing the overall net shape of the part is utilized to construct the metal or alloy component in a layer-by-layer manner by selectively fusing metal particles, within a powder bed or material feed system, using high energy thermal sources. However, the layer-based manufacturing of metal components give rise to “staircasing effects” that result in anisotropic physical properties, poor surface quality, limited resolution control, and long printing times. Furthermore, specialized atmospheric conditions, metal nanoparticles, and complex industrial equipment are required to achieve high-quality prints which lead to a large operational cost.  In this work, we developed a low-cost and ultra-fast layerless metal AM process for producing metal, alloy, and multi-metal structures that exhibit excellent surface quality and overall performance compared with traditional metal 3D printing. To facilitate the layerless printing of metal precursors through the continuous liquid interface production (CLIP) printing approach, a low viscosity resin was formulated that allows for a high solid loading concentration of metal precursors while providing superb rheological properties. Based on experimental findings, the printing speed of metal precursor structures with mesoscale and microscale features using this approach exceeds 120 µm/s which is orders of magnitude faster than commercial technologies such as selective laser melting (SLM), wire-arc AM (WAAM), and binder jetting (BJ). Because the low viscosity resin has great flowability, multi-metal objects with smooth transitional gradients can be produced by carefully depositing fresh metal precursors through a material exchange process during printing. Utilizing the proposed printing approach, a wide variety of multi-metal structures consisting of both pure metal and alloy can be realized for unique applications such as functionally graded materials (FGMs). Since 3D objects are printed continuously, the microstructure of the final metal or alloy printed part exhibits a uniform grain distribution in both the XY and XZ plane leading to isotropic physical properties in contrast to heterogeneous microstructures observed in traditional fabrication methods. Moreover, during post-heat treatment the process parameters, such as sintering temperature, can be adjusted to realize both highly porous and dense metal microstructures allowing for a high degree of control and flexibility over the final physical properties. Comparison between the layer-based and layer-less based printing process was conducted to assess the improvement to the overall cost and surface quality of monolithic alloy and metal structures. Consequently, the proposed ultrafast metal precursor 3D printing process aims to open new and intriguing prospectives in metal additive manufacturing to circumvent emerging science and engineering endeavors within the aerospace, automotive, and biomedical sectors.

Presenting Author: Dylan Joralmon Arizona State University

Presenting Author Biography: Dylan Joralmon is a second year Ph.D. student in Mechanical Engineering from Arizona State University and his research focuses primarily on developing innovative and low cost metal additive manufacturing (AM) technologies for a wide range of applications including aerospace and biomedical devices. In addition to his research at ASU he has also worked on developing an optical bench for a NASA terahertz balloon borne telescope and was part of a research team at Sandia National Laboratory working on printing soft metamaterial using a machine learning optimization approach. His primary research goals include data- and physic-driven optimization approaches, computational mechanics, biomimetic structures, process development, and engineering education.

Authors:

Dylan Joralmon Arizona State University
Soham Khairnar ASU
Tengteng Tang ASU
Xiangjia Li ASU