Under pressure: A new theory lets us predict when soft materials will
fail
Major implications for polymer engineering

Date:
February 28, 2022
Source:
University of Massachusetts Amherst
Summary:
Researchers recently announced a major theoretical and
experimental breakthrough that allows scientists to predict, with
an unprecedented precision, when a soft material will crack and
fail. The findings have immediate implications for the engineering
and manufacture of a wide range of polymers. They also provide
insights into how natural soft materials -- such as the connective
tissues in our bodies and even our brains -- break down.



FULL STORY ========================================================================== Researchers led by a team from the University of Massachusetts Amherst
recently announced a major theoretical and experimental breakthrough
that allows scientists to predict, with an unprecedented precision,
when a soft material will crack and fail. The findings, published in
the Proceedings of the National Academy of Sciences, have immediate implications for the engineering and manufacture of a wide range of
polymers. They also provide insights into how natural soft materials --
such as the connective tissues in our bodies and even our brains --
break down.


==========================================================================
It has proved devilishly complex to predict when a soft material, such
as a gel or elastomer, will crack and fail. "It's been a mystery,"
says Alfred Crosby, professor of polymer science and engineering at
UMass Amherst and one of the paper's senior authors. Because scientists
haven't been able to accurately predict when a soft material will
fail, designers typically over-engineer their products and recommend
replacing them earlier rather than later, just to be safe. "But if
we could predict exactly when a product would fail, and under what
conditions," says Crosby, "we could engineer materials in the most
efficient way to meet those conditions." Cracking this particular
nut, which was supported by the Office of Naval Research's Naval Force
Health Protection program, involved a multi-disciplinary effort between
Alfred Crosby, Gregory Tew, also a professor of polymer science at UMass Amherst, and Robert Riggleman, professor of chemical and biomolecular engineering at the University of Pennsylvania. With a combination of
highly precise chemistry, detailed and innovative computer modeling,
and fine-grained experimental data, the group modified an older theory,
called the Lake-Thomas Theory, with the help of a newer molecular model
known as Real Elastic Network Theory (RENT). "As a result," says Ipek
Sacligil, graduate student in polymer science at UMass Amherst, and one
of the paper's co-lead authors, "using only the molecular ingredients,
we can now accurately predict when a soft material will fail at both the molecular and product levels." Christopher Barney, one of the paper's
other co-lead authors and a graduate student at UMass at the time he
completed this research says that "this project highlights the importance
of addressing modern scientific problems from multiple perspectives. By combining our efforts, we were able to craft a comprehensive story that
is far greater than the sum of its parts." "This advance provides a
missing link between chemistry and materials science and engineering for polymer networks," says Crosby, who notes that this research is part of
a much larger, ongoing project to understand the mechanics of cavitation
or the sudden, unstable crack-causing expansions within soft materials
and tissues.

========================================================================== Story Source: Materials provided by
University_of_Massachusetts_Amherst. Note: Content may be edited for
style and length.


========================================================================== Journal Reference:
1. Christopher W. Barney, Ziyu Ye, Ipek Sacligil, Kelly R. McLeod, Han
Zhang, Gregory N. Tew, Robert A. Riggleman, Alfred
J. Crosby. Fracture of model end-linked networks. Proceedings of
the National Academy of Sciences, 2022; 119 (7): e2112389119 DOI:
10.1073/pnas.2112389119 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220228150639.htm

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