Session: 04-23-01: Functional Soft Composites - Design, Mechanics, and Manufacturing

Paper Number: 149530

149530 - Digital Light Process 3d Printing of Free-Form Voxelated Liquid Crystalline Elastomers 

Liquid crystalline elastomers (LCEs) are lightly crosslinked polymer networks retaining liquid crystallinity, integrating anisotropy and viscoelasticity. These properties support their potential in soft robotics, impact resistance, optics, and energy applications. The synthesis, alignment, deformation mechanics, and physics of LCEs have been extensively documented, with recent research advancements facilitated by novel materials chemistries that enable straightforward LCE preparation and alignment via surface-enforced, mechanical, and shear force methods. Shear force alignment, particularly through direct ink write (DIW) 3D printing, involves extruding a viscous LC oligomer melt through a nozzle, where shear forces impart alignment, which is then fixed by photopolymerization. Despite these advancements, DIW printing can only prepare flat objects that actuate into 3D structures.

An increasingly popular additive manufacturing technique, digital light processing (DLP), allows for the creation of complex 3D LCE structures by photopolymerizing an LC oligomer resin layer by layer. While DLP has achieved high-resolution LCE lattices, ideal for energy-absorbing materials, these structures are unaligned , which diminishes the primary benefits of LCEs. Attempts to address alignment in DLP include specialized printers that shear and photopolymerize LC resin layers, but a versatile alignment method integrated into existing DLP processes remain a challenge.

Other alignment techniques, such as photopatterned and electric field alignment, offer solutions but with limitations. Electric field alignment requires high-strength fields, complicating integration with DLP. Magnetic field alignment, leveraging liquid crystals' diamagnetic susceptibility, shows promise but has seen limited use, mainly aligning side-chain LCEs with some success in aligning main-chain LCEs under high-strength fields. Main-chain LCEs, preferred for their superior actuation and viscoelastic properties, are the focus of our research.

We explore the preparation of thick, aligned LCE free-forms, achieving up to 70 layers and 7 mm in height, using a low-strength (100 mT) magnetic field generated by a Halbach array integrated with a commercial DLP printer. This method employs a dual-stage thiol-acrylate/thiol-ene chemistry in a liquid crystalline solvent (4-Cyano-4'-pentylbiphenyl, 5CB). We systematically examine the relationship between director orientation and variables like field strength, alignment time, and layer thickness.  These experiments were carried out using a range of characterization techniques including Dynamic Mechanical Analysis (DMA), small angle x-ray scattering (SAXS), and polarized optical microscopy (POM).  This fundamental understanding supports the development of 3D-printed LCE structures with tailorable variation in spatial and hierarchical director orientation. This work represents a significant advance in the application of DLP-printed LCEs to form complex 3D free-forms, offering a transformational development for the production of next-generation soft robotics, biomedical devices, and energy absorption systems.

Presenting Author: Devin Roach Oregon State University

Presenting Author Biography: Devin is an Assistant Professor in the Mechanical, Industrial, and Manufacturing Department at Oregon State University (OSU). Prior to his time at OSU, he was a Senior Member of the Technical Staff at Sandia National Laboratories leading a research group focusing on applied machine learning methods for real-time monitoring and autonomous optimization of additive manufacturing systems. He received his PhD from Georgia Institute of Technology under the direction of Prof. H Jerry Qi.
His research interest lie at the cross-section of additive manufacturing, materials, and structural design. He is particularly interested in the development and manufacturing of smart/active materials such as shape memory polymers (SMP) and liquid crystal elastomers (LCE) for applications in biomedical devices, soft robotics, and energy harvesting devices. Additionally, he is interested in how artificial intelligence can be applied to improve and even automate additive manufacturing processes to eliminate user error.

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