KAIST Reveals How Information Is Written in Ferroelectric Memory at the Nanoscale
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KAIST Reveals How Information Is Written in Ferroelectric Memory at the Nanoscale


What happens at the nanoscale when information is written to memory? Researchers at KAIST have shown how tiny regions with a new polarization direction form while previously formed regions continue to expand in a promising ferroelectric material. By linking these nanoscale changes to electrical measurements, the team developed a model that captures both processes, offering a basis for designing faster and more stable memory.

KAIST (President Choongsik Bae) announced on October 8 that a team led by Professor Seungbum Hong from the Department of Materials Science and Engineering had identified how information is recorded in hafnium zirconium oxide (HZO), a promising material for next-generation memory. The study was conducted in collaboration with Professor Byung Jin Cho’s team at KAIST’s School of Electrical Engineering and researchers at NaMLab/TU Dresden in Germany.

The research team focused on ferroelectrics. Ferroelectric materials can retain their electrical polarization after an applied voltage is removed. Reversing this orientation allows the material to store information as 0s and 1s. The electrical state in which positive and negative charges inside a material are aligned in a particular direction is called polarization.
HZO combines hafnium oxide, a material widely used in semiconductor manufacturing, with zirconium oxide. Its compatibility with existing semiconductor manufacturing processes makes it attractive for nonvolatile memory, which retains data without power.

When a voltage is applied to a ferroelectric, tiny regions called domains, each with a uniform polarization direction, begin to change. As new domains form and existing domains expand into the surrounding area, the overall polarization direction reverses and information is recorded.
Researchers have traditionally described this switching behavior using models that emphasize either nucleation, the formation of new domains, or growth, the expansion of existing domains.

In hafnia-based thin films such as HZO, however, switching occurs across many nanometer-sized crystal grains. Nucleation and growth interact with grain boundaries and other structural features, making it difficult for models that emphasize either process alone to fully capture the observed behavior.

Using high-resolution piezoresponse force microscopy (PFM), the researchers directly observed how nanometer-scale domains (one nanometer is one billionth of a meter) change as the applied voltage increases. They then compared these observations with the electrical switching behavior of the full devices.

The combined results showed that new domains continued to form while existing domains expanded. In other words, information is recorded through two simultaneous processes: new changes begin, and changes already under way spread.

To describe this behavior, the team introduced a simultaneous nucleation and growth (SNG) model. The model accounts for both the continuing formation of new domains and the cumulative expansion of those already present, bringing the two processes together in a single framework.

The team also linked the nanoscale changes seen under the microscope directly to the electrical behavior of real memory devices. This makes it possible to explain not only how quickly the memory switches, but also where information writing begins and how it spreads.

The findings can also be used to improve the performance of next-generation memory. Once researchers understand how domains form and spread, they can adjust a material's structure or manufacturing process so that information is written more quickly and uniformly.

This understanding could help researchers improve memory performance by adjusting material structures and fabrication conditions to make switching faster and more uniform. The findings could also guide the development of more reliable, energy-efficient nonvolatile memory and neuromorphic devices for AI. Neuromorphic devices mimic aspects of the brain’s information processing and storage, offering potential applications in low-power AI hardware.

“When information is written in a ferroelectric material, which retains its electrical state even without power, small changes begin at multiple sites while those already under way spread into the surrounding regions,” said Professor Hong. “This study reveals how these two processes work together to write information, providing a new basis for designing faster and more reliable next-generation memory.”

Batzorig Buyantogtokh, a postdoctoral researcher in KAIST’s Department of Materials Science and Engineering, is the study’s first author. The paper was published in Nano Letters on June 15, 2026, and was selected for a journal cover.
Paper: “Nucleation-to-Propagation Switching Modes in Ferroelectric Hf₀.₅Zr₀.₅O₂ Capacitors”
DOI: https://doi.org/10.1021/acs.nanolett.6c01580

This research was supported by the National Research Foundation of Korea (NRF), with funding from the Ministry of Science and ICT (MSIT), under grant numbers RS-2026-25487626, RS-2026-25468150, and RS-2023-00272257.
Author: Batzorig Buyantogtokh, a postdoctoral researcher in KAIST’s Department of Materials Science and Engineering, is the study’s first author.
Journal: Nano Letters (June 15, 2026, selected for a journal cover)
Paper: “Nucleation-to-Propagation Switching Modes in Ferroelectric Hf₀.₅Zr₀.₅O₂ Capacitors”
DOI: https://doi.org/10.1021/acs.nanolett.6c01580
Angehängte Dokumente
  • Figure 1. The cover of Nano Letters (Volume 26, Issue 33, August 26, 2026) featuring the research.
  • Figure 2. Ferroelectric domains spread differently depending on the bottom electrode. With a niobium nitride (NbN) electrode, switched regions stay within individual grains. With a titanium nitride (TiN) electrode, they spread across grain boundaries, which leads to faster switching.
  • Figure 3. Pulsed switching measurements show that the switching speed and uniformity of the ferroelectric depend on the electrode material. The simultaneous nucleation and growth (SNG) model developed by the research team accounts for both the formation of new domains and their growth, providing guidelines for the design of fast memory devices.
Regions: Asia, South Korea, Europe, Germany
Keywords: Applied science, Artificial Intelligence, Computing, Engineering, Nanotechnology, Technology

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