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Jamming the flow to enable memory in quantum materials

Jamming the flow to enable memory in quantum materials

phys.org 14.10.2026 16:00 6 views
Understanding and controlling phase transitions are fundamental to physics and central to many technological revolutions. There is currently strong interest in materials with coupled structural and electronic phase trans

This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Understanding and controlling phase transitions are fundamental to physics and central to many technological revolutions. There is currently strong interest in materials with coupled structural and electronic phase transitions, where controlling the transition plasticity naturally yields built-in memory—a key step in emulating neurons and synapses for "neuromorphic" or brain-like computing technologies.

A team of UC San Diego researchers led by physics professor Oleg Shpyrko developed a new approach to coherent X-ray diffraction—a microscopy technique that is highly sensitive to specific nanoscale domain configurations—that allowed them to observe dynamics within a neuristor (a man-made device that mimics the brain's neurons) made of vanadium dioxide while electricity was applied. By taking measurements while operating the neuristor, they discovered a strategy to make the material learn and forget a specific state, opening an avenue toward developing energy-efficient brain-inspired hardware. The study is published in the journal Nature Communications.

The physical phenomenon that enables this control is a phase transition from a liquid-like state to a jammed (or glassy) state. This is somewhat similar to passengers waiting for a train. When there are few people on the platform, they can move independently of each other.

When the platform is crowded, the movements of one person can affect others. In the case of the neuristor, jamming the flow enables learning, and restoring free flow erases memory. The findings have practical implications for the development of energy-efficient neuromorphic devices and for fundamental materials science.

Finding a way to control how neuristors can "learn" and "forget" is central to the operation of neuromorphic devices. Nicolò D'Anna et al., Jamming-controlled stochasticity in metal-insulator switching, Nature Communications (2026). DOI: 10.1038/s41467-026-76844-2 Journal information: Nature Communications Provided by University of California - San Diego Swati Mestri holds a bachelor's degree in Electronics Engineering and has worked as a content editor since 2019.

She has experience editing research documents across technology, health care, and materials science, and has a particular interest in technology and space. Full profile → Bachelor's in mathematical biology, Master's in creative writing. Well-traveled with unique perspectives on science and language.

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