Researchers on a team led by University of Michigan unveiled that phase separation, alongside oxygen diffusion, crucially supports the long-term retention of information in memristors, specifically in resistive random access memory (RRAM). This discovery challenges previous models that suggested limited retention capabilities, highlighting potential applications in energy-efficient AI and rad-hard memory chips for space exploration.<\/p>\n
Phase separation, when molecules part like oil and water, works alongside oxygen diffusion to help memristors\u2014electrical components that store information using electrical resistance\u2014retain information even after the power is shut off, according to a University of Michigan-led study recently published in the scientific journal Matter<\/em>.<\/p>\n Until now, explanations have not fully grasped how memristors retain information without a power source, known as nonvolatile memory, because models and experiments do not match up.<\/p>\n \u201cWhile experiments have shown devices can retain information for over 10 years, the models used in the community show that information can only be retained for a few hours,\u201d said Jingxian Li, U-M doctoral graduate of materials science and engineering and first author of the study.<\/p>\n To better understand the underlying phenomenon driving nonvolatile memristor memory, the researchers focused on a device known as resistive random access memory or RRAM, an alternative to the volatile RAM used in classical computing, and are particularly promising for energy-efficient artificial intelligence applications.<\/p>\n The specific RRAM studied, a filament-type valence change memory (VCM), sandwiches an insulating tantalum oxide layer between two platinum electrodes. When a certain voltage is applied to the platinum electrodes, a conductive filament forms a tantalum ion bridge passing through the insulator to the electrodes, which allows electricity to flow, putting the cell in a low resistance state representing a \u201c1\u201d in binary code. If a different voltage is applied, the filament is dissolved as returning oxygen atoms react with the tantalum ions, \u201crusting\u201d the conductive bridge and returning to a high resistance state, representing a binary code of \u201c0.\u201d<\/p>\n It was once thought that RRAM retains information over time because oxygen is too slow to diffuse back. However, a series of experiments revealed that previous models have neglected the role of phase separation.<\/p>\n \u201cIn these devices, oxygen ions prefer to be away from the filament and will never diffuse back, even after an indefinite period of time. This process is analogous to how a mixture of water and oil will not mix, no matter how much time we wait, because they have lower energy in a de-mixed state,\u201d said Yiyang Li, U-M assistant professor of materials science and engineering and senior author of the study.<\/p>\n To test retention time, the researchers sped up experiments by increasing the temperature. One hour at 250\u00b0C is equivalent to about 100 years at 85\u00b0C\u2014the typical temperature of a computer chip.<\/p>\n Using the extremely high-resolution imaging of atomic force microscopy, the researchers imaged filaments, which measure only about five nanometers or 20 atoms wide, forming within the one micron wide RRAM device.<\/p>\n \u201cWe were surprised that we could find the filament in the device. It\u2019s like finding a needle in a haystack,\u201d Li said.<\/p>\n The team found that different-sized filaments yielded different retention behavior. Filaments smaller than about 5 nanometers dissolved over time, whereas filaments larger than 5 nanometers strengthened over time. The size-based difference cannot be explained by diffusion alone.<\/p>\n Together, experimental results and models incorporating thermodynamic principles showed the formation and stability of conductive filaments depend on phase separation.<\/p>\n The research team leveraged phase separation to extend memory retention from one day to well over 10 years in a rad-hard memory chip\u2014a memory device built to withstand radiation exposure for use in space exploration.<\/p>\n Other applications include in-memory computing for more energy-efficient AI applications or memory devices for electronic skin\u2014a stretchable electronic interface designed to mimic the sensory capabilities of human skin. Also known as e-skin, this material could be used to provide sensory feedback to prosthetic limbs, create new wearable fitness trackers or help robots develop tactile sensing for delicate tasks.<\/p>\n \u201cWe hope that our findings can inspire new ways to use phase separation to create information storage devices,\u201d Li said.<\/p>\n