Thick honey spreads slowly across a plate. In such a world, where friction suppresses inertia, motion is governed not by force but by viscosity. This is how many soft materials behave: polymer gels, colloidal suspensions, the contents of living cells. The researchers asked: can we locally change viscosity so that a material responds differently to stress at different points?
They developed a method based on the idea of 'directed aging': just as muscles strengthen with exercise, a material 'trains' to alter its resistance in response to local deformations. Using a mathematical approach that describes energy losses in a viscous medium, the authors derived rules for updating viscosity at each point. These rules allow the material to gradually adapt to a desired mechanical behavior.
To test the idea, the scientists simulated a disordered Maxwell material — a substance that behaves like an elastic solid under rapid forces but flows like a liquid under slow ones. They found that by locally changing viscosity, they could control the Poisson's ratio — a measure of how much a material contracts in one direction when stretched in another. For example, they could make a material that, when compressed, does not expand sideways but remains unchanged or even contracts.
This approach resembles training a neural network, but instead of adjusting connection weights, local viscosities are tuned. The material itself 'learns' the desired behavior by adapting to external conditions. This opens the way to smart gels that change stiffness in response to touch, or polymers that adapt to loads.
as written by the authors arXiv:2602.19122
In regimes where inertia is negligible, the temporal evolution is governed by overdamped dynamics. This limit is particularly relevant in soft-matter contexts, such as polymers, colloidal suspensions, and processes occurring at the cellular scale. Being able to manipulate the dynamics of such many-particle systems would enable control over rate-dependent elastic responses, time-dependent material properties, relaxation processes, and perhaps the hydrodynamics of suspensions. In this work, we develop a framework for manipulating overdamped dynamics through local, physically motivated update rules. Our approach is inspired by ideas from physical learning and directed aging, in which microscopic parameters adapt autonomously to endow a material with a desired function. Using the Rayleighian formulation, whose minimization reproduces the overdamped equations of motion, we derive approximate directed-aging and equilibrium-propagation rules tailored to dissipative systems. To demonstrate these ideas, we study a disordered Maxwell material that behaves elastically at short times but flows at long times. By locally modifying the viscous damping, we show that one can tune the viscous Poisson's ratio and shape local mechanical responses. These results illustrate how materials can be trained to exhibit targeted rate-dependent elastic and viscous behaviors.
The Poisson's ratio of ordinary cork is close to zero: when compressed, it barely expands sideways, which is why it's easy to push a cork into a bottle.