Researchers at Penn State University have unveiled a novel method for material memory storage, akin to the mechanics of a combination lock. This innovative approach, termed return-point memory, allows materials to retain information through alternating positive and negative deformations.
Nathan Keim, an associate professor of physics leading the research, explained, "With a lock, rotating the dial in a specific sequence yields a result that depends on how the dial was moved." Similarly, materials with return-point memory can imprint and erase information based on the forces applied.
The study reveals that these principles could extend to various systems, including the magnetization of computer hard drives and the structural integrity of solid rocks. The research team utilized computer simulations to explore how different parameters, such as force magnitude and orientation, influence memory formation.
Key to their findings are 'hysterons', which represent elements in a system that may not respond immediately to external conditions. Travis Jalowiec, a former undergraduate who contributed to the research, noted, "Hysterons can interact cooperatively or non-cooperatively, affecting how sequences are stored and retrieved."
One significant discovery involves 'frustrated hysterons', which resist one another and enable sequence storage even under asymmetric driving conditions. Keim illustrated this concept using a bendy straw analogy, explaining how a slight pull can trigger a change in one part of the system, relieving stress elsewhere.
The researchers believe their insights could lead to the development of artificial systems capable of sophisticated memory storage, potentially paving the way for new mechanical systems that can sense their environment and perform computations without electricity. "If you can create a system that stores a sequence of memories, you can use it like a combination lock to verify a specific history," Keim added.
This groundbreaking work, supported by the U.S. Department of Energy and other institutions, opens avenues for advanced information storage and retrieval methods, with implications for diagnostics and forensic applications.