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Encoding many properties in one material via 3D printing

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Encoding many properties in one material via 3D printing
High operating temperature-direct ink writing of square spirals. Credit: Lewis Lab

A class of synthetic soft materials called liquid crystal elastomers (LCEs) can change shape in response to heat, similar to how muscles contract and relax in response to signals from the nervous system. 3D printing these materials opens new avenues to applications, ranging from soft robots and prosthetics to compression textiles.

Controlling the material’s properties requires squeezing this elastomer-forming ink through the nozzle of a 3D printer, which induces changes to the ink’s internal structure and aligns rigid building blocks known as mesogens at the molecular scale. However, achieving specific, targeted alignment, and resulting properties, in these shape-morphing materials has required extensive trial and error to fully optimize printing conditions. Until now.

In a new study, researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), Princeton University, Lawrence Livermore National Laboratory, and Brookhaven National Laboratory worked together to write a playbook for printing liquid crystal elastomers with predictable, controllable alignment, and hence properties, every time.

By using an X-ray characterization method during the printing process that enables quantification of mesogen alignment at the microscale, the researchers have established a fundamental framework to guide their rapid design and fabrication across multiple scales.

By tuning the microscale nozzle design, printing speed, and temperature, one can induce the desired molecular-scale alignment, which translates into prescribed shape-morphing and mechanical behavior at the macroscale.

Published in Proceedings of the National Academy of Sciences, the study’s senior author is Jennifer Lewis, the Hansjörg Wyss Professor of Biologically Inspired Engineering at Harvard SEAS. Lewis’s lab has decades of experience in molecular and nanoscale design of 3D printing inks for new, functional materials. The study was co-led by former Harvard postdoctoral researcher Emily Davidson, now a faculty member at Princeton University, with expertise in the design, nanoscale assembly, X-ray characterization, and 3D printing of soft materials.

Encoding many properties in one material via 3D printing
The researchers used an X-ray microbeam, during printing, to locally measure liquid crystal alignment and direction inside the printer nozzle. Credit: Harvard John A. Paulson School of Engineering and Applied Sciences

Liquid crystal elastomers exhibit their best shape-morphing and mechanical properties when individual chains composed of liquid crystalline parts are aligned with each other. The researchers printed these liquid crystalline chains through fine nozzles, driving their flow-induced alignment.

“When this project began, we simply didn’t have a good understanding of how to precisely control liquid crystal alignment during extrusion-based 3D printing,” said first author Rodrigo Telles, a SEAS graduate student, Academic Cooperation Program scholar and collaborator with Lawrence Livermore National Laboratory. “Yet it is their degree of alignment that gives rise to varying amounts of actuation and contraction when heated.”

To investigate alignment of molecules during printing, the researchers used different-shaped nozzles—tapered and hyperbolic. The nozzle shape affected how the ink flowed out, which in turn controlled molecular alignment. By varying extrusion speed and nozzle shape, they were able to create two types of filaments: one with an outer layer of well-aligned molecules surrounding a poorly aligned core, and another with uniform alignment throughout.

Their calculations and experiments showed that the distribution of flow type and speed inside the nozzle determined the filament type. While there were many factors that mattered, the researchers showed they could combine most of these into a single parameter called a Weissenberg number to describe how different printing conditions align the molecules.

Encoding many properties in one material via 3D printing
The researchers demonstrated on-the-fly control of liquid crystal molecular alignment by printing ‘H’ shapes. Red consists of highly aligned molecules while black consists of poorly aligned molecules. Credit: Harvard John A. Paulson School of Engineering and Applied Sciences

“In the 3D printing community, most of us use a relatively small number of commercially available printheads. This study showed us that it’s important to pay attention to the details of both nozzle geometry and flow—and that we can exploit them to control material properties,” Davidson said.

The team worked with researchers at a wide-angle X-ray scattering beamline at the Department of Energy’s Brookhaven National Laboratory to take detailed X-ray measurements during 3D printing. This method allowed them to look inside the nozzles to visualize LCE alignment using different nozzle geometries and flow conditions.

The X-ray measurements helped them determine the precise degree of alignment of the liquid crystalline molecules at any given position within the nozzles, providing a road map for their flow-induced alignment that is linked to tunable nozzle designs and printing parameters.

Among their results was that a nozzle with a hyperbolic shape created better and more uniform alignment than conventional nozzles.

The work opens new avenues for fabricating LCE structures with programmed shape morphing and mechanics, for use in applications such as adaptive structures and artificial muscles.

“The ability to ‘see’ into liquid crystal elastomers and quantify their alignment at the microscale during printing via wide angle X-ray scattering measurements has provided a fundamental framework of their processing-structure-property relationships for the first time,” Lewis said.

More information:
Rodrigo Telles et al, Spatially programmed alignment and actuation in printed liquid crystal elastomers, Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2414960122

Provided by
Harvard John A. Paulson School of Engineering and Applied Sciences


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Encoding many properties in one material via 3D printing (2025, February 3)
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