A layer of soap bubbles remembers its past

A system that’s out of equilibrium can retain a memory about how it got where it is. A soft amorphous solid, such as the bubble raft shown in the figure, is such a system. Because the bubbles are different sizes, they can’t settle into a configuration with crystalline order, and because they’re packed together, they can’t readily explore all the possible disordered configurations to find the one lowest in energy. The system, therefore, is perpetually out of equilibrium.

Now Rajesh Ganapathy and colleagues at the Jawaharlal Nehru Centre for Advanced Scientific Research in Bangalore, India, have shown experimentally that a bubble-raft memory can be written and read like a computer bit. They placed soap bubbles in a Couette cell, the annular region between an inner disk (visible on the left edge of the figure) and outer ring (not shown). Rotating the disk alternately clockwise and counterclockwise applies an oscillating shear strain.

The quantity the system remembers is the amplitude γ of the shear oscillations. When subjected to repeated oscillations at a particular γ, the bubbles work their way into a configuration that’s relatively unresponsive to shearing at the same amplitude: Each subsequent oscillation rearranges the bubbles less and less. But the response to other amplitudes, whether greater or less than γ, is unaffected. So once they’ve encoded the memory through a dozen or so shear cycles at a particular γ, the researchers can read it by scanning the shearing amplitude and looking for the value with the diminished response.

Surprisingly, it doesn’t matter whether γ is above or below the system’s yield strain, the boundary between regimes of elastic and plastic deformation. In fact, the memory is most pronounced for γ values in the neighborhood of the yield strain, whether just above or just below.

Although the bubble memory can persist for several minutes or more, it’s unlikely to find application in practical data storage. Rather, researchers are interested in mechanical memory in part because of the connections it might reveal between seemingly unrelated materials—for example, soft matter and ferromagnets—whose memories work in similar ways. (S. Mukherji et al., Phys. Rev. Lett. 122, 158001, 2019 .)