New Class of Metamaterials Changes Physical Properties in Seconds

Mechanical metamaterials can have their rigidity tuned, offering a new approach to soft robotics

3 min read
A researcher demonstrates the ability to adjust a metamaterial's rigidity on the fly by removing a magnetic field.
A researcher demonstrates the ability to adjust a metamaterial's rigidity on the fly by removing a magnetic field.

Metamaterials seem like a technology out of science fiction. Because of the way these materials affect electromagnetic phenomena and physical attributes of materials, they can render objects invisible, leaving the observer in disbelief.

While invisibility cloaks are a gee-whiz application, metamaterials now offer real-world commercial applications such as new antenna technologies for mobile phones. To get to the point where metamaterials are not just a curiosity but also a viable commercial technology, they have had to evolve a new set of tricks.

One example is the work of a team of researchers from Lawrence Livermore National Laboratory (LLNL) and the University of California, San Diego (UCSD).  They have used so-called mechanical metamaterials—which exhibit unique mechanical properties that do not exist in nature—to create a novel material that can change from rigid to flexible in response to a magnetic field. The researchers expect this new material could usher in new approaches to smart wearables and soft robotics.

Today’s mechanical metamaterials have demonstrated their worth with attractive properties such as negative thermal expansion and high strength and stiffness at low weight. However, once they are built, you are stuck with their properties and cannot change or tune them.

“We sought to create a mechanical metamaterial with on-the-fly tunable mechanical properties via a facile application of a magnetic field without inducing significant shape change (which is common amongst origami and buckling materials),” said Christopher Spadaccini, director of the Center for Engineered Materials, Manufacturing and Optimization at LLNL.

To create their tunable mechanical metamaterials, the researchers turned to so-called four-dimensional printing. It gets its name from the fact that such 3D printed objects change form or shape over time, with time being the fourth dimension. Typically, a structure of this type responds to a stimulus (e.g., heat, hydration, or magnetic field) that causes it to change shape.

The field-responsive metamaterials (FRMMs) developed by the researchers change their properties in response to a variation in a magnetic field. However, unlike typical 4D printed materials, they do not change their overall shape but instead change their stiffness.

“We explicitly tried to create materials where properties change but form does not, thus classifying this work outside of the 4D printed realm,” said Spadaccini.

The creation of FRMMs is relatively simple, according to Spadaccini. The first step is to 3D print a mechanical metamaterial that is constructed out of hollow beams instead of the typical solid beams. Once the hollow tubular metamaterial is printed, magnetorheological (MR) fluid is injected into the beams’ cores, completing the fabrication process for the FRMM.

It’s in the MR fluid where the magneto-mechanical effect happens. MR fluid is constructed of magnetic particles, suspended in a nonmagnetic medium. When the fluid is in the presence of a magnetic field, the magnetic particles align into chains along the magnetic field lines, increasing the stiffness of the fluid and thus simultaneously increasing the overall stiffness of the structures. When the magnetic field is removed, the MR fluid behaves as a liquid and is able to flow freely.

“What’s really important is this [magneto-mechanical effect] is not just an on and off response; the stiffness of the structures can be tuned with applied magnetic field strength,” explained Spadaccini. “By carefully choosing the tubular structure we used, the mechanical properties of our FRMMs can display up to a 318 percent increase in tensile stiffness in less than a second.”

Spadaccini believes that FRMMs could be used as variable stiffness joints in soft robotics and could be integrated into smart wearables that are flexible in the absence of a magnetic field and then change properties to absorb an impact or vibration when an incoming threat is sensed.

The technology is not there yet, however. Spadaccini recognizes that getting field-responsive metamaterials into the field would require faster, more reliable manufacturing methods. Furthermore, those manufacturing methods would need to be scaled up in size, and more sophisticated designs would need to be developed.

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How the U.S. Army Is Turning Robots Into Team Players

Engineers battle the limits of deep learning for battlefield bots

11 min read
Robot with threads near a fallen branch

RoMan, the Army Research Laboratory's robotic manipulator, considers the best way to grasp and move a tree branch at the Adelphi Laboratory Center, in Maryland.

Evan Ackerman
LightGreen

“I should probably not be standing this close," I think to myself, as the robot slowly approaches a large tree branch on the floor in front of me. It's not the size of the branch that makes me nervous—it's that the robot is operating autonomously, and that while I know what it's supposed to do, I'm not entirely sure what it will do. If everything works the way the roboticists at the U.S. Army Research Laboratory (ARL) in Adelphi, Md., expect, the robot will identify the branch, grasp it, and drag it out of the way. These folks know what they're doing, but I've spent enough time around robots that I take a small step backwards anyway.

This article is part of our special report on AI, “The Great AI Reckoning.”

The robot, named RoMan, for Robotic Manipulator, is about the size of a large lawn mower, with a tracked base that helps it handle most kinds of terrain. At the front, it has a squat torso equipped with cameras and depth sensors, as well as a pair of arms that were harvested from a prototype disaster-response robot originally developed at NASA's Jet Propulsion Laboratory for a DARPA robotics competition. RoMan's job today is roadway clearing, a multistep task that ARL wants the robot to complete as autonomously as possible. Instead of instructing the robot to grasp specific objects in specific ways and move them to specific places, the operators tell RoMan to "go clear a path." It's then up to the robot to make all the decisions necessary to achieve that objective.

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