Deep within a lab at Boston University's College of Engineering, a remarkable robot arm is relentlessly pushing the boundaries of energy absorption efficiency. Dubbed MAMA BEAR (Mechanics of Additively Manufactured Architectures Bayesian Experimental Autonomous Researcher), this autonomous system has evolved through over three years of continuous experimentation to design and test an unprecedented 25,000 unique 3D-printed structures.

Its quest? To autonomously discover the most efficient shape for absorbing impact energy – a breakthrough that could revolutionize everything from protective gear to shipping materials. And in January 2023, MAMA BEAR achieved the unprecedented, creating a four-pointed structure with thin petal-like protrusions that broke the known efficiency record at 75%.

"When we started out, we didn't know if there was going to be this record-breaking shape," said Kelsey Snapp, the Ph.D. student overseeing MAMA BEAR. "Slowly but surely we kept inching up, and broke through."

The robot's modus operandi is remarkably methodical yet ingenious. It 3D prints a small plastic structure, analyzes its shape and size, then crushes it with the force of an Arabian horse standing on it. Meticulously recording the energy absorbed and deformation details, MAMA BEAR iterates through machine learning, tweaking design parameters in a process called Bayesian optimization to inch closer to perfection with each attempt.

"We're excited that there's so much mechanical data here, that we're using this to learn lessons about design more generally," noted Keith Brown, the associate mechanical engineering professor whose lab created MAMA BEAR. Before this robot, the best observed impact absorption efficiency was just 71%.

While MAMA BEAR's record-setter optimizes energy dampening, the lab is already applying their vast dataset to real-world applications. Brown's team collaborated with the U.S. Army to design and test new impact-absorbing helmet padding using a different, more comfort-focused 3D printed structure.

MAMA BEAR is the flagship of Brown's growing autonomous research robot fleet, which includes "nano BEAR" studying materials at the molecular scale and PANDA BEAR optimizing polymer battery components. "The philosophy is that they're using machine learning together with automation to help us do research much faster," Brown explained.

For Snapp, who enabled MAMA BEAR's machine vision and self-cleaning capabilities, the robots transcend mere acceleration: "You can do things you couldn't normally do. We can reach a structure or goal that we wouldn't have been able to achieve otherwise, because it would have been too expensive and time-consuming."

Despite shattering the efficiency ceiling, Brown believes MAMA BEAR's work is far from over. "We have no ability to know if we've reached the maximum efficiency," he stated. The lab intends to continue iterating novel applications for their 25,000-structure dataset while exploring recycling the crushed pieces for further experiments.

"Mechanical efficiency, like so many other material properties, is only accurately measured by experiment," Brown said. "Using self-driving labs helps us pick the best experiments and perform them as fast as possible."

With MAMA BEAR's record-breaking design ushering in a new frontier of energy absorption potential, Boston University's autonomous researchers are pioneering a future where robots blaze past human limitations to unlock transformative material breakthroughs. One crush-tested structure at a time, MAMA BEAR is redefining what's possible through intelligent, untiring iteration.