Physicists Get Three Times More Work From a Glass Bead Using Hidden Memory

Physicists have built a real-world version of Maxwell's demon, a famous thought experiment, and used it to pull out up to three times as much work as the theoretical limit for a comparable system without hidden memory, according to ScienceAlert. The work was published in Nature Physics.

The result does not yet power any useful machine. It does show that memory stored in a surrounding fluid, which researchers cannot see directly, can still be exploited as a source of energy at microscopic scales.

The demon that has puzzled physicists since 1867

In 1867, physicist James Clerk Maxwell proposed a thought experiment involving a tiny, intelligent “demon” stationed at a door between two chambers of gas. By letting only fast particles into one side and slow particles into the other, the demon would leave one chamber warm and the other cool.

That appears to reduce entropy, which the second law of thermodynamics says cannot happen in an isolated system without an increase elsewhere. The demon seems to manage this without doing any work.

ScienceAlert notes that the original paradox has long since been resolved. The demon's trick is not free, because information is physical and processing it carries thermodynamic costs that keep the second law intact. The resolution also revealed something useful: information about a physical system can itself be used to extract work from that system.

How the experiment worked

Physicist Clemens Bechinger of the University of Konstanz in Germany and his colleagues demonstrated the idea with a laser that trapped a microscopic glass bead in a liquid. Even held by the laser, the bead kept jiggling at random because molecules around it constantly jostled it, a phenomenon known as Brownian motion.

By watching the bead's position, the team could decide when to shift the laser trap to take advantage of its movements and gain a little energy. This is the basic principle of an information engine: using knowledge about a system to turn random motion into useful work.

There is a catch. An information engine can only use the information it can reach, and in real systems some of that information is hidden.

A hidden network that remembers

This is where the experiment goes beyond the standard demon. The liquid was packed with spaghetti-like strands of molecules called micelles, which form a microscopic network. The researchers could not observe that network directly.

The strands tangled and rearranged themselves as the bead moved, keeping traces of its past motion that could influence where it went next. Although the network itself was out of view, the bead's movements gave the team a way to learn about it.

Instead of measuring the bead's position once, the researchers measured it twice, with a carefully timed gap between the two readings. Timing mattered. Measurements taken too close together revealed little about the liquid's hidden dynamics. Measurements taken too far apart came after the network had begun to forget the bead's earlier movements. The team found a sweet spot at an interval of around one second.

Comparing the two readings let the researchers infer how the surrounding network had been disturbed and how it might affect the bead's next move. They could then time their adjustments to the laser trap better and extract energy that would otherwise have been out of reach.

ScienceAlert offers a mental picture: a meatball held in place in a vat of invisible spaghetti soup. The meatball is watched twice to work out what the spaghetti is doing, and that knowledge is used to move the trap so it draws extra energy from the soup's hidden dynamics.

Why it matters

For now, the practical payoff is limited. According to ScienceAlert, the researchers have not built a tiny machine that performs a useful task. What they have shown is a new way to extract energy from a microscopic system, which advances understanding of what information engines can achieve.

The finding could matter for future technologies that operate at microscopic scales, especially in complex settings such as biological fluids, where the interactions between particles and their surroundings are hard to predict. Rather than treating those interactions as an obstacle, the study suggests they could serve as an extra source of useful energy.

The authors put it this way: they say their results establish “environmental memory as an experimentally accessible thermodynamic resource.”

The result comes from a laboratory demonstration with a single bead in a specially prepared liquid, so how well it carries over to other systems remains to be seen.

Around Prague, based on reporting by ScienceAlert