In the human body, connective tissues, like ligaments and tendons, contain gradients with varying mechanical properties at different points. The hard will be more rigid, while the soft will be more flexible. This endows the tissue with a useful pliancy that engineers have lately begun harnessing by manufacturing tools with similar mechanical gradients.
“We want to use, design, and leverage these types of materials in some way. Helmets, for example, could really benefit from a hard-to-soft gradient material for shock absorption,” said Jon Estrada, associate professor of mechanical engineering. “The problem that is especially prominent in the field though is that there is no standard way to test that what you wanted to make is actually what you got.”
Estrada has received an NSF CAREER Award for his project, “Informed Testing: From Full-Field Characterization of Mechanically Graded Soft Materials to Student Equity in the Classroom,” which aims to create a protocol for testing newly-designed mechanically graded soft materials.
“For testing right now, you tend to have a standard geometry and you manipulate it following a protocol that has been established for many, many years,” said Estrada. “But if you want to test something that you’ve just created to accomplish something specific, there’s no obvious way for you to do that.”
With standard geometries, manipulations – like pulling and twisting – will yield approximately uniform behavior throughout a material, but throughout mechanically graded soft materials, each point along the geometry may exhibit distinct properties. Each of these points must be considered to understand how a material will perform overall.
To accomplish this, Estrada and his lab will manufacture a series of tools made from a compliant silicone that will be mechanically graded and then work to “assess internal deformations and determine how the gradient is spatially laid out” by largely adapting established testing methods.
“There’s an optimization procedure that can happen where we can measure all of the deformation happening inside a sample, but if we want to pick up a gradient somewhere, how should we make the geometry of that sample going in?” Estrada asked.
Traditionally, a material may be tested by taking a standard dog bone or dumbbell shaped tool, deforming it, and assessing how the material responds to determine its mechanical properties. Through this project, Estrada is seeking to determine such an optimal geometry for testing mechanically graded materials.
“And the other side of this is figuring out how to grip it,” said Estrada. “You could start pulling on it or twisting it. There’s a lot of things you could be doing to test the material.”
To determine an optimization procedure for deforming a sample, Estrada will be rigging an MRI machine to allow his team to pull and twist their samples while monitoring and measuring the behavior of each at different points along its geometry.
Comparing these data with surface-level measurements and theory, the team will be able to most fully characterize each material and develop informed testing procedures that will bring mechanically graded soft materials closer to their many possible industry applications.
“If you have a way to reliably test these materials, then you can say, the problem is the process now,” said Estrada. “So let’s go back to the process and try to optimize that. In that way, we get closer and closer to achieving whatever it is that a material is designed to achieve.”
In addition to this research focus, Estrada and his team will work to improve testing in his classes. By integrating an open-source PrairieLearn platform into his core course curricula and focus area of Solid Mechanics, he will provide an avenue for students to concentrate their practice outside of the classroom.
“With PrairieLearn, if you want to just practice multivariable calculus before going into Intro to Solid Mechanics, you can,” said Estrada. This way, students, regardless of social pressures or constraints on their schedules, will have more flexibility to learn.
When asked how he felt about receiving funding for this project, Estrada said, “It’s a tremendous honor. The CAREER award recognizes contributions in all of the facets of what we do—research, teaching, and service—and the universally positive reviews were especially validating. I’m humbled, grateful to the review panel and my students who produced such rich preliminary data, and eager to get this work going.”
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“The Faculty Early Career Development (CAREER) Program is a Foundation-wide activity that offers the National Science Foundation’s most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.”
