Aerospace & Defense Technology - October 2024 - 34

Tech Briefs
Using AI, Ramprasad's team and their
collaborators have made significant
advancements in diverse fields, including
energy storage, filtration technologies,
additive manufacturing, and recyclable
materials.
Polymer Progress
One notable success, described in the
Nature Communications paper, involves
the design of new polymers for capacitors,
which store electrostatic energy.
These devices are vital components in
electric and hybrid vehicles, among
other applications. Ramprasad's group
worked with researchers from the University
of Connecticut.
Current capacitor polymers offer either
high energy density or thermal stability,
but not both. By leveraging AI tools, the
researchers determined that insulating
materials made from polynorbornene
and polyimide polymers can simultaneously
achieve high energy density and
high thermal stability. The polymers
can be further enhanced to function in
demanding environments, such as aerospace
applications, while maintaining
environmental sustainability.
" The new class of polymers with high
energy density and high thermal stability
is one of the most concrete examples
of how AI can guide materials discovery, "
said Ramprasad. " It is also the result of
years of multidisciplinary collaborative
work with Greg Sotzing and Yang Cao
at the University of Connecticut and
sustained sponsorship by the Office of
Naval Research. "
Industry Potential
The potential for real-world translation
of AI-assisted materials development
is underscored by industry
participation in the Nature Reviews
Materials article. Co-authors of this
paper also include scientists from Toyota
Research Institute and General Electric.
To further accelerate the adoption
of AI-driven materials development in
industry, Ramprasad co-founded Matmerize
Inc., a software startup company
recently spun out of Georgia Tech.
Their cloud-based polymer informatics
software is already being used by companies
across various sectors, including
energy, electronics, consumer products,
chemical processing, and sustainable
materials.
" Matmerize has transformed our
research into a robust, versatile, and
industry-ready solution, enabling
users to design materials virtually with
enhanced efficiency and reduced cost, "
Ramprasad said. " What began as a curiosity
has gained significant momentum,
and we are entering an exciting new era
of materials by design. "
This work was performed by a team of
researchers from Georgia Tech University.
For more information, download the
Technical Support Package (free white
paper) at mobilityengineeringtech.
com/tsp under the Materials category.
Machine Learning Unlocks Secrets to Advanced Alloys
An MIT team uses computer models to measure atomic patterns in metals, essential for designing
custom materials for use in aerospace, biomedicine, electronics, and more.
Massachusetts Institute of Technology, Cambridge, MA
T
he concept of short-range order
(SRO) - the arrangement of atoms
over small distances - in metallic alloys
has been underexplored in materials
science and engineering. But the past
decade has seen renewed interest in
quantifying it, since decoding SRO is a
crucial step toward developing tailored
high-performing alloys, such as stronger
or heat-resistant materials.
Understanding how atoms arrange
themselves is no easy task and must
be verified using intensive lab experiments
or computer simulations based
on imperfect models. These hurdles have
made it difficult to fully explore SRO in
metallic alloys.
But Killian Sheriff and Yifan Cao,
graduate students in MIT's Department
of Materials Science and Engineering
(DMSE), are using machine learning to
quantify, atom-by-atom, the complex
34
This artistic illustration shows the unique arrangement
of atoms in high-entropy alloys, which have
subtle patterns. Machine-learning techniques helped
MIT researchers accurately measure these patterns.
(Image: MIT)
mobilityengineeringtech.com
chemical arrangements that make up
SRO. Under the supervision of Assistant
Professor Rodrigo Freitas, and with the
help of Assistant Professor Tess Smidt
in the Department of Electrical Engineering
and Computer Science, their
work was recently published in The
Proceedings of the National Academy
of Sciences.
Interest in understanding SRO is linked
to the excitement around advanced
materials called high-entropy alloys,
whose complex compositions give them
superior properties.
Typically, materials scientists develop
alloys by using one element as a base
and adding small quantities of other
elements to enhance specific properties.
The addition of chromium to nickel,
for example, makes the resulting metal
more resistant to corrosion.
Unlike most traditional alloys, high-entropy
alloys have several elements, from
three up to 20, in nearly equal proportions.
This offers a vast design space. " It's
like you're making a recipe with a lot
more ingredients, " says Cao.
Aerospace & Defense Technology, October 2024

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Aerospace & Defense Technology - October 2024

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