
< (From left) Ph.D candidate Changhwan Kim, Ph.D candidate Seunghwan Kim , Ph.D candidate Namwook Hur, Professor Joonki Suh, Ph. D candidate Youngseok Cho>
As artificial intelligence advances, computers demand faster and more efficient memory. The key to ultra-high-speed, low-power semiconductors lies in the "switching" principle—the mechanism by which memory materials turn electricity on and off. A South Korean research team has successfully captured the elusive moment of switching and its internal operational principles by momentarily melting and freezing materials within a nanoscale electronic device. This study provides a foundational blueprint for designing next-generation memory materials that are faster and consume less power based on fundamental principles.
On February 8th, the research team led by Professor Joonki Suh from our department (Chemical and Biomolecular Engineering), in collaboration with Professor Tae-Hoon Lee’s team from Kyungpook National University, announced the development of an experimental technique capable of real-time monitoring of electrical switching processes and phase changes within nano-devices—phenomena that were previously difficult to observe.
To verify the electrical switching, the team applied a method of instantaneous melting followed by rapid cooling (quenching). Through this, they succeeded in stably implementing amorphous tellurium (a-Te)—a state where tellurium is disordered like glass—within a nano-device much smaller than a human hair. Tellurium is typically sensitive to heat and changes properties easily when current is applied; however, in its amorphous state, it is garnering significant attention as a core material for next-generation memory due to its speed and energy efficiency. *Tellurium (Te): A metalloid element possessing properties of both metals and non-metals.

< Illustration of the experiment involving instantaneous melting and freezing in a memory electronic device (AI-generated image) >
Through this study, the team specifically identified the threshold voltage and thermal conditions at which switching begins, as well as the segments where energy loss occurs. Based on these findings, they observed stable and high-speed switching even while reducing heat generation. This enables "principle-based" memory material design, allowing researchers to understand exactly why and when electricity starts to flow.
The results confirmed that microscopic defects within amorphous tellurium play a crucial role in electrical conduction. When the voltage exceeds a certain threshold, the corresponding current does not rise all at once; instead, it follows a two-step switching process: initially, a rapid current increase along the defects occurs primarily during the abrupt electrical switching, followed by heat accumulation that causes the material to melt.
Furthermore, the team successfully implemented a "self-oscillation" phenomenon—where voltage spontaneously increases and decreases—by conducting experiments that maintained the amorphous state without excessive current flow. This demonstrates that stable electrical switching is possible using only the single element of tellurium, without the need for complex material combinations.

< Electrical characteristics of amorphous tellurium created through rapid cooling from a liquid state within an electronic device >
This research is a significant achievement as it implements amorphous tellurium—a next-generation memory material—within an actual electronic device and systematically elucidates the fundamental principles of electrical switching. These findings are expected to serve as essential guidelines for designing semiconductor materials to realize faster and more energy-efficient memory in the future.
"This is the first study to implement amorphous tellurium in a real-world device environment and clarify the switching mechanism," said Professor Joonki Suh. "It sets a new standard for research into next-generation memory and switching materials."
The study, with Namwook Hur as the first author and Seunghwan Kim as the second author, and Professor Joonki Suh (KAIST) as the corresponding author, was published online on January 13th in the international academic journal Nature Communications.
Meanwhile, this research was supported by the National Research Foundation of Korea (NRF) through the PIM (Processor-in-Memory) AI Semiconductor Core Technology Development Project, the Excellent Young Researcher Program funded by the Ministry of Science and ICT, and Samsung Electronics.
<(From Left) Dr. Minju Jeong,(UCSD), Prof. Byung Kook Lim (UCSD), Prof. Se-Bum Paik (KAIST)> Drug addiction carries an extremely high risk of relapse, as cravings can be reignited by minor stimuli even long after one has stopped using. Previously, this phenomenon was attributed to a decline in the function of the prefrontal cortex (PFC), which regulates impulses. However, a joint international research team has recently revealed that the cause of addiction relapse is not a simple decli
2026-03-10< (From Left) M.S candidate Dongwon Lee from School of Electrical Engineering, Ph.D candidate Jaehun Han from Graduate School of Quantum Science and Technology > "Team Yangja-jorim," consisting of Dongwon Lee, Gyungjun Kim and Jaehun Han , has been honored with the Grand Prize at the '2026 2nd Global Quantum AI Competition.' The event was hosted and organized by NORMA, a specialized quantum computing company. This global competition was designed to expand hands-on experience with quant
2026-03-10<(From Left) Dr. Subin Yoon, Ph.D candidate Hyeonggon Cho, Prof. Jae-Hwan Nam, Prof. Young-suk Lee> Since the COVID-19 pandemic, mRNA vaccines have gained attention as a next-generation pharmaceutical technology. mRNA therapeutics work by delivering genetic instructions that enable cells to produce specific proteins for therapeutic effects. However, their efficacy has been reported to decline in elderly individuals or patients with obesity. To address this limitation, Korean researchers
2026-03-10<(From Left) Ph.D candidate Hyojin Son, Professor Gwan-su Yi> Proteins in our body function like switches. When a drug binds to a protein, the structure at the binding site changes, and this structural change propagates throughout the protein, turning its function on or off. Google DeepMind’s AlphaFold3 successfully predicted whether drugs bind to proteins and the three-dimensional structure of binding sites. However, it could not predict how signals propagate inside the protein a
2026-03-09<(From Left) Sumin Lee, Sungwon Park, Prof. Jihee Kim, Prof. Meeyoung Cha, Prof. Jeasurk Yang> "Cities don't even know where their slums (impoverished areas) are located." In many developing nations, the most vulnerable citizens are invisible to the state simply because their homes don't appear on any official map. Today, a breakthrough using Artificial Intelligence (AI) is changing that. A joint research team from KAIST and Chonnam National University in South Korea and MPI-SP in Ger
2026-03-08