Novel 3D printing method a 'game changer' for discovery, manufacturing
of new materials

Date:
May 18, 2023
Source:
University of Notre Dame
Summary:
Researchers have created a novel 3D printing method that produces
materials in ways that conventional manufacturing can't match.


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FULL STORY ==========================================================================
The time-honored Edisonian trial-and-error process of discovery is slow
and labor-intensive. This hampers the development of urgently needed
new technologies for clean energy and environmental sustainability,
as well as for electronics and biomedical devices.

"It usually takes 10 to 20 years to discover a new material," said
Yanliang Zhang, associate professor of aerospace and mechanical
engineering at the University of Notre Dame.

"I thought if we could shorten that time to less than a year -- or
even a few months -- it would be a game changer for the discovery
and manufacturing of new materials." Now Zhang has done just that,
creating a novel 3D printing method that produces materials in ways that conventional manufacturing can't match. The new process mixes multiple aerosolized nanomaterial inks in a single printing nozzle, varying the
ink mixing ratio on the fly during the printing process. This method
-- called high-throughput combinatorial printing (HTCP) -- controls
both the printed materials' 3D architectures and local compositions
and produces materials with gradient compositions and properties at
microscale spatial resolution.

His research was just published in Nature.

The aerosol-based HTCP is extremely versatile and applicable to a broad
range of metals, semiconductors and dielectrics, as well as polymers
and biomaterials. It generates combinational materials that function as "libraries," each containing thousands of unique compositions.

Combining combinational materials printing and high-throughput
characterization can significantly accelerate materials discovery, Zhang
said. His team has already used this approach to identify a semiconductor material with superior thermoelectric properties, a promising discovery
for energy harvesting and cooling applications.

In addition to speeding up discovery, HTCP produces functionally graded materials that gradually transition from stiff to soft. This makes
them particularly useful in biomedical applications that need to bridge
between soft body tissues and stiff wearable and implantable devices.

In the next phase of research, Zhang and the students in his Advanced Manufacturing and Energy Lab plan to apply machine learning and artificial intelligence-guided strategies to the data-rich nature of HTCP in order
to accelerate the discovery and development of a broad range of materials.

"In the future, I hope to develop an autonomous and self-driving process
for materials discovery and device manufacturing, so students in the
lab can be free to focus on high-level thinking," Zhang said.

* RELATED_TOPICS
o Matter_&_Energy
# Materials_Science # Civil_Engineering #
Engineering_and_Construction # 3-D_Printing # Electronics
# Weapons_Technology # Nanotechnology # Physics
* RELATED_TERMS
o Knot_theory o Materials_science o Pyroelectricity o
Radiocarbon_dating o Carbon-14 o Resonance_(chemistry) o
Metallurgy o Tissue_engineering

========================================================================== Story Source: Materials provided by University_of_Notre_Dame. Original
written by Karla Cruise. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Minxiang Zeng, Yipu Du, Qiang Jiang, Nicholas Kempf, Chen Wei,
Miles V.

Bimrose, A. N. M. Tanvir, Hengrui Xu, Jiahao Chen, Dylan
J. Kirsch, Joshua Martin, Brian C. Wyatt, Tatsunori Hayashi,
Mortaza Saeidi-Javash, Hirotaka Sakaue, Babak Anasori, Lihua Jin,
Michael D. McMurtrey, Yanliang Zhang. High-throughput printing of
combinatorial materials from aerosols.

Nature, 2023; 617 (7960): 292 DOI: 10.1038/s41586-023-05898-9 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2023/05/230518120903.htm

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