As artificial intelligence (AI) continues to evolve, researchers at POSTECH (Pohang University of Science and Technology) have made a discovery that could help AI technologies become faster and more efficient.
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Professor Seyoung Kim and Dr. Hyunjeong Kwak from POSTECH’s Departments of Materials Science & Engineering and Semiconductor Engineering, in collaboration with Dr. Oki Gunawan from the IBM T.J. Watson Research Center, are the first to uncover the hidden operating mechanisms of Electrochemical Random-Access Memory (ECRAM*¹), a promising next-generation technology for AI. Their findings were recently published in the international journal Nature Communications.
As AI systems become more advanced, the demand for data processing has surged. Yet, traditional computing architectures separate data storage (memory) from data processing (processors), leading to significant time and energy losses as data moves between the two. To overcome this, researchers have developed the concept of "In-Memory Computing."
"In-Memory Computing" enables calculations to happen directly within memory itself, eliminating the need for data transfers and allowing for much faster and more energy-efficient operations. ECRAM plays a central role in making this possible. Unlike traditional memory devices, ECRAM stores and processes information using ionic movement, enabling continuous, analog-style data storage. However, challenges in understanding its complex structure and high-resistance oxide materials have slowed its path toward commercialization.
To tackle these challenges, the POSTECH team developed a multi-terminal structured ECRAM device using tungsten oxide and applied the ‘Parallel Dipole Line Hall System,' which allowed them to observe internal electron dynamics across a wide temperature range—from ultra-low temperatures (-223 °C, or 50 K) up to room temperature (300 K).
For the first time, they discovered that oxygen vacancies inside the ECRAM form shallow donor states (~0.1 eV), creating "shortcuts" that allow electrons to move freely. Rather than merely increasing the number of electrons, the ECRAM naturally fosters an environment that promotes easier electron transport. Importantly, this mechanism remained stable even at extremely low temperatures, highlighting the robustness and durability of the device.
This research is significant as it experimentally clarified the switching mechanism of ECRAM across various temperatures. Commercializing this technology could lead to faster AI performance and extended battery life in devices such as smartphones, tablets, and laptops.
Seyoung Kim, Professor, Pohang University of Science and Technology
This study was supported by K-CHIPS (Korea Collaborative & High-tech Initiative for Prospective Semiconductor Research), funded by Korea’s Ministry of Trade, Industry & Energy (MOTIE).
Journal Reference:
Kwak, H., et al. (2025) Unveiling ECRAM switching mechanisms using variable temperature Hall measurements for accelerated AI computation. Nature Communications. doi.org/10.1038/s41467-025-58004-0