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Development of Dream Battery Material: Air-Stable and Fast-Charging All-Solid-State Battery
<(Bottom row, from left) Dr. Jae-Seung Kim (Seoul National University), Prof. Dong-Hwa Seo (KAIST), Researcher Heeju Park (KAIST), Researcher Jiwon Seo, Researcher Jinyeong Choe.
(Top row, from left) Researcher Hae-Yong Kim (Dongguk University), Prof. Eunryeol Lee (Chungbuk National University), Prof. Kyung-Wan Nam (Dongguk University), Prof. Yoon Seok Jung (Yonsei University)>
Expectations are rising for all-solid-state batteries—the "dream battery" with low fire risk—not only for electric vehicles but also for various fields such as robotics and Urban Air Mobility (UAM). A research team at our university has presented a new design principle that simultaneously overcomes the limitations of solid electrolytes, which were previously vulnerable to air exposure and suffered from low performance. This technology is gaining significant attention as it can enhance both battery safety and charging speeds, demonstrating the feasibility of commercializing next-generation all-solid-state batteries.
KAIST announced on April 16th that a research team led by Professor Dong-Hwa Seo from the Department of Materials Science and Engineering, through joint research with teams from Dongguk University (President Jae-Woong Yoon), Yonsei University (President Dong-Sup Yoon), and Chungbuk National University (Acting President Yu-Sik Park), has developed a design technology for solid electrolytes used in all-solid-state batteries. This technology maintains structural stability even when exposed to air while dramatically increasing ionic conductivity.
Unlike conventional lithium-ion batteries that use liquid electrolytes, all-solid-state batteries are spotlighted as next-generation batteries due to their low fire risk. Among these, halide-based solid electrolytes—which contain halogen elements such as chlorine (Cl) and bromine (Br)—are advantageous in terms of performance due to their high ionic conductivity. However, they are known to be difficult materials to manufacture and handle because they are highly vulnerable to moisture in the air, which easily degrades their performance.
To solve this problem, the research team introduced a new structure called "Oxygen Anchoring." This method involves stably bonding oxygen inside the electrolyte to strengthen its structural intergrity, a process in which the element Tungsten plays a key role.
< Research image on tungsten-based oxygen fixation strategy >
As a result, it was confirmed that the electrolyte maintains a stable structure without collapsing, even in air-exposed environments.
Furthermore, the research team improved battery performance in addition to stability. The changes in the internal structure of the electrolyte widened the pathways for lithium ions, allowing them to move more smoothly and increasing the ion migration speed. It was confirmed that the oxygen-incorporated material exhibited an ionic conductivity approximately 2.7 times higher than that of conventional zirconium (Zr)-based halide solid electrolytes.
Another feature of this technology is that it is not limited to a specific material. The research team applied the same strategy to various halide solid electrolytes, including those based on zirconium (Zr), indium (In), yttrium (Y), and erbium (Er), and confirmed similar effects. This demonstrates that it is a "universal design principle" applicable to a wide range of battery materials.
< Research image (AI-generated image) >
The research team expects this technology to contribute to the development of solid electrolytes that possess both air stability and high performance.
Professor Dong-Hwa Seo stated, "This study presents a new material design principle that optimizes multiple performances through a structural design strategy that simultaneously improves air stability and ionic conductivity. It will serve as a key indicator for future all-solid-state battery research and process development."
This study involved Jae-Seung Kim (formerly KAIST, now SNU), Heeju Park, and Hae-Yong Kim as joint first authors. The research included contributions from Eunryeol Lee, Heewon Kim, Soeul Lee, Jinyeong Choe, Jiwon Seo, Hyeon-Jong Lee, Hojoon Kim, Jemin Yeon, and Yoon Seok Jung. The findings were published on March 6, 2026, in the international academic journal Advanced Energy Materials.
Paper Title: Universal Oxychlorination Strategy in Halide Solid Electrolytes for All-Solid-State Batteries
DOI: https://doi.org/10.1002/aenm.202506744
This research was conducted with support from the Samsung Electronics Future Technology Promotion Center and the Nano and Materials Technology Development Program of the National Research Foundation of Korea. Computational studies were performed using the resources of the National Supercomputing Center.
2026.04.16 View 129 -
Breakthrough in Data Processing via Light Control... Enhancing AI Accelerators and Quantum Communication
< (From left) Undergraduate researcher Taewon Kim and Professor Sangsik Kim >
A new technology has been developed that allows light to be "designed" into desired forms, potentially making Artificial Intelligence (AI) and communication technologies faster and more accurate. A KAIST research team has developed an "integrated photonic resonator"—a core component of next-generation optical integrated circuits that process data using light. The research is particularly significant as it was led by an undergraduate student. This technology is expected to serve as a key foundation for next-generation security technologies such as high-speed data processing and quantum communication.
KAIST announced on the 15th that a research team led by Professor Sangsik Kim from the School of Electrical Engineering, in collaboration with Professor Jae Woong Yoon’s team from the Department of Physics at Hanyang University (President Kigeong Lee), has developed a new integrated photonic resonator structure capable of freely controlling optical signals by utilizing light interference (the phenomenon where two light waves meet and influence each other).
Photonic Integrated Circuits (PICs) process data at ultra-high speeds and with low power consumption using light. They are garnering significant attention as a fundamental platform technology for next-generation fields such as AI, data centers, and quantum information processing.
The core of this technology lies in the precision with which light can be controlled. Specifically, the ability to freely adjust the spectrum (color or wavelength distribution) and phase response (timing or wave position) of optical signals is essential for implementing high-performance optical communication and computing. However, conventional methods have faced fundamental limitations.
The integrated photonic resonator (optical resonator) focused on by the research team is a key optical device that traps light in a specific space to amplify it or select specific colors (wavelengths), similar to how the body of a musical instrument amplifies sound. However, existing single-bus resonators have had limitations in precisely adjusting the phase and spectrum of optical signals.
To overcome these challenges, the research team introduced a "dual-bus" structure. This design allows light that has passed through the resonator to recombine with light that has not, enabling precise control over interference. This allows for the free design of optical signals into desired forms, making it possible to control various types of light signals that were previously difficult to implement.
By applying this technology, the research team secured new characteristics for more precise control of wavelength properties and presented new possibilities for non-linear frequency conversion research (changing the color of light). Utilizing this technology enables faster and more accurate data processing, which is expected to provide the groundwork for performance enhancements in future high-speed data centers, AI accelerators, and quantum communication systems.
This research is especially meaningful as it was led by an undergraduate student. Taewon Kim, an undergraduate student who conducted the study through the KAIST Undergraduate Research Program (URP), stated, "I was able to develop the resonator principles I learned in the Introduction to Integrated Optics class into actual device designs and a published paper."
< Research Image of the Dual-bus Resonator >
Professor Sangsik Kim remarked, "This study goes beyond proposing a new device; it demonstrates that by precisely analyzing previously overlooked optical characteristics, physical limitations can be overcome. We expect this to contribute broadly to the development of optics-based AI accelerators and optical communication technologies."
KAIST undergraduate student Taewon Kim participated as the lead author of this study, and the results were published on March 6th in the international optics journal, Laser & Photonics Reviews.
Paper Title: Dual-bus resonator for multi-port spectral engineering DOI: 10.1002/lpor.202502935 Authors: Taewon Kim, Mehedi Hasan, Yu Sung Choi, Jae Woong Yoon, and Sangsik Kim
This research was supported by the KAIST URP Program, the Institute of Information & Communications Technology Planning & Evaluation (IITP), the U.S. Asian Office of Aerospace Research and Development (AOARD), and the National Research Foundation of Korea (NRF).
2026.04.16 View 134 -
AI Fixed 'Temporal Errors'... Enhancing Reliability in Medical and Legal Fields
<Ph.D candidate Soyeon Kim, (From Left)Jindong Wang (Microsoft; currently at the College of William & Mary), Xing Xie (Microsoft), and Steven Euijong Whang (Professor at KAIST)>
What if ChatGPT answered with the name of a minister from a year ago when asked, "Who was the minister inaugurated last month?" This is a prime example of the limitations of AI that fails to properly reflect the latest information. Our university’s research team has developed a new evaluation technology that automatically reflects changing real-world information while catching "temporal errors" that may appear correct on the surface. This is expected to drastically improve AI reliability.
KAIST announced on April14th that a research team led by Professor Steven Euijong Whang from the School of Electrical Engineering, in joint research with Microsoft Research, has developed a system that automatically evaluates and diagnoses the temporal reasoning capabilities of Large Language Models (LLMs) using temporal database technology.
For AI to earn user trust, the ability to accurately understand real-world information that changes moment by moment is essential. However, existing evaluation methods only checked whether the answer matched or failed to sufficiently reflect complex temporal relationships, making it difficult to properly evaluate various question scenarios occurring in actual environments.
To solve this, the research team introduced "Temporal Database" design theory—which has been verified over the past 40 years—into AI evaluation for the first time. By utilizing the temporal flow and relational structure of data, the core of this technology is the automatic generation of 13 types of complex time-based problems from the database itself, without the need for humans to manually write evaluation questions.
<Schematic Diagram of the Evaluation Framework Proposed in This Study>
In particular, this technology is evaluated as a major innovation because it shifts from the traditional method where humans manually created problems to a method where evaluation questions are automatically generated based on data. Furthermore, by automating the entire process from problem generation to answer derivation and verification based on the database, the burden of maintenance can be drastically reduced without the need to manually modify questions as was previously required.
When real-world information changes, the evaluation questions, answers, and verification criteria are automatically updated simply by updating the corresponding content in the database. While the input of the latest information itself is handled by external data or administrators, this technology is structured to perform the overall evaluation automatically after such data is updated.
Additionally, moving beyond the existing method of simply judging whether the final answer is correct or incorrect, the research team introduced a new metric that verifies the logical validity of dates or periods presented during the answering process. Through this, they achieved a performance improvement in detecting "Temporal Hallucination" phenomena—where an answer appears correct but has the wrong temporal basis—by an average of 21.7% more accurately than before.
Applying this technology can significantly reduce evaluation maintenance costs since only the database needs to be updated when information changes, and it showed an effect of reducing the amount of input data by an average of 51% compared to previous methods.
<Future AI Evaluation System (AI-Generated Image)>
Professor Steven Euijong Whang stated, "This research is an example showing that classical database design theory can play a crucial role in solving the reliability issues of the latest AI. By converting vast amounts of professional data into evaluation resources, we expect this to become a practical foundation for verifying AI performance in various fields such as medicine and law in the future."
Soyeon Kim, a PhD student at KAIST, participated as the lead author of this study, and Jindong Wang (Microsoft Research, currently at William & Mary) and Xing Xie (Microsoft Research) participated as co-authors. The research results will be presented this April at ICLR 2026, the most prestigious academic conference in the field of artificial intelligence.
Paper Title: Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models
Paper Link: https://arxiv.org/abs/2508.02045
Meanwhile, this research was conducted with support from Microsoft Research, the National Research Foundation of Korea, and the Institute for Information & Communications Technology Planning & Evaluation (IITP) Global AI Frontier Lab projects (RS-2024-00469482, RS-2024-00509258).
2026.04.14 View 185 -
AI, Humanoid Robots, and Space Rovers to Gather: Experience Future Technologies at the Science Festival
<(From left) Photos of the KAIST Science Festival exhibition hall and booths from the previous year>
KAIST announced on April 10th that KAIST will participate in the ‘2026 Korea Science and Technology Festival,’ the largest science festival in the country, to mark Science Month in April. KAIST will operate ‘KAIST Play World,’ an interactive exhibition hall showcasing the pinnacle of AI and robotics. This year’s festival will be held in two parts: ‘2026 Korea Science Festival in Daejeon (April 17–19)’ and ‘2026 Korea Science Festival in Gyeonggi (April 24–26).’ KAIST will host consecutive exhibitions at the Daejeon DCC (Second Exhibition Hall) and KINTEX in Ilsan. Under the ‘Play World’ concept, KAIST plans to offer differentiated interactive content tailored to various generations. In particular, on-site events and souvenirs featuring the KAIST character ‘Nupjuk-i’ will be provided to enhance visitor engagement.
□ [Daejeon] From Humanoid Robots to Space Rovers and AI Semiconductor Friend ‘BROCA’ The exhibition at Daejeon DCC from April 17 to 19 will feature ‘Future Tech Experience Content’ centered on advanced robotics, space technology, and AI semiconductor technology, allowing visitors to experience KAIST's core research achievements firsthand. First, a humanoid robot equipped with control technology developed by Eurobotics Co., Ltd., a startup from Professor Myung Hyun’s research team in the School of Electrical Engineering, will be unveiled on the 17th. This robot is gaining attention as a next-generation platform capable of natural walking in both industrial and urban environments. Additionally, on the 19th, a humanoid robot from Professor Park Hae-won’s team in the Department of Mechanical Engineering will demonstrate high-difficulty human movements such as the duck walk and moonwalk, showcasing its potential for practical industrial use. Professor Lee Dae-young’s team in the Department of Aerospace Engineering will present the world’s first deployable lunar rover wheel based on origami technology. Visitors can touch the transformable wheel model and observe space rover demonstrations and displays by the co-developer, Unmanned Exploration Laboratory (UEL). Educational sessions for folding various space systems using origami will also be available. Along with this, visitors can experience advanced human-machine interaction through ‘BROCA,’ a mobile social AI agent that builds relationships with users beyond simple Q&A, and the voice-capable guide robot ‘On-Newro,’ developed by Professor Yoo Hoi-jun’s team at the AI Semiconductor Graduate School. The student startup ‘Liar Games’ will operate a trial zone for ‘Dual Focus,’ an abstract strategy board game where players compete 1:1 against AI. Similar to the deep strategic play of chess or Go, the rules are intuitive enough to learn in 5 minutes, which is expected to stimulate the challenge-seeking spirit of visitors.
< (Top row from left) Professor Park Hae-won’s humanoid robot, Professor Yoo Hoi-jun’s BROCA, (Bottom row from left) Eurobotics’ humanoid walking technology capable of overcoming any terrain based on a mobile kit, Professor Lee Dae-young’s storable and deployable rover for lunar exploration >
□ [Gyeonggi] ‘Raibo’ the Rough-Terrain Robot and AI-Based Future Experiences The Gyeonggi exhibition at KINTEX from April 24 to 26 will focus on ‘Life-Oriented Experience Content’ centered on AI and everyday technology. ‘Raibo,’ a quadrupedal robot developed by Professor Hwangbo Jemin’s team in the Department of Mechanical Engineering, is capable of high-speed movement on complex terrains such as sand, stairs, and debris, and is expected to be utilized for disaster relief and search missions. Visitors can experience Raibo’s driving technology directly at the site. The ‘Future Memories Studio’ from Professor Nam Tek-jin’s team in the Department of Industrial Design will provide a new experience where visitors can meet and talk to their future selves 10 years later, recreated using AI-generated visuals and voices. Participants will receive a four-cut photo capturing a moment that is the future for their current self but a memory for their future self. Professor Yun Yun-jin’s team at the KAIST Urban AI Research Center will present technology that analyzes the impact of climate change on small business sales through ‘AI-based Sight and Sound for Heatwave Consumption Index.’ They will showcase time-series AI-based sales prediction technology and generative AI technology that expresses this visually and audibly. Furthermore, Professor Yun’s lecture, “City Walk of Artificial Intelligence: Urban AI and the Future of Cities,” will be held on April 24 (Fri) at 15:00 in KINTEX Meeting Room 206. In addition, Professor Yoo Hoi-jun’s team from the AI Semiconductor Graduate School will continue from the Daejeon exhibition to operate an experience zone for various mobile AI agents based on AI semiconductors. Also, the student startup Rabbithole Company will introduce a new type of game where AI NPCs (Non-Player Characters) converse and cooperate to solve given problems. Visitors can participate by observing the process where AI characters create their own stories by being presented with situations or goals instead of being directly controlled.
< (Top row from left) Professor Hwangbo Jemin’s Raibo, Professor Nam Tek-jin’s team: Met My Future Self 10 Years Later, (Bottom row from left) Professor Yun Yun-jin’s Seeing and Hearing Heatwave Consumption Index through AI, Game image from CEO Kim Na-hoon’s Rabbithole Company >
Through the exhibitions in both regions, KAIST plans to operate various participatory programs to make science and technology easy and fun to approach, vividly conveying how technology from the laboratory transforms our lives. KAIST President Lee Kwang-hyung remarked, “This year’s science festival is a large-scale event connecting Daejeon and Gyeonggi, allowing more citizens to experience KAIST’s innovative research achievements firsthand.” He added, “I hope this will be a precious time for people to experience the future created by robots and AI, fostering their dreams and curiosity about science.”
2026.04.13 View 238 -
Development of Low-Frequency Wireless Sensor for Real-Time Monitoring of Arteriosclerosis Without Electromagnetic Interference Concerns
< (Top, left to right) Dr. Haerim Kim (KAIST), Ph.D. candidate Ji Hong Kim (Hanyang University), student Jaewon Rhee (KAIST); (Bottom, left to right) Prof. Seungyoung Ahn (KAIST), Prof. Do Hwan Kim (Hanyang University) >
Wireless sensors used in wearable smart devices and medical equipment must be capable of detecting minute changes while maintaining high operational stability. However, existing technologies often utilize excessively high frequencies, leading to electromagnetic interference (EMI) or potential health risks to the human body. To address these fundamental issues, a Korean research team has developed a low-frequency-based wireless sensor technology.
A joint research team, led by Professor Seungyoung Ahn from the KAIST Cho Chun Shik Graduate School of Mobility and Professor Do Hwan Kim from the Department of Chemical Engineering at Hanyang University, announced the development of "WiLECS" (Wireless Ionic-Electronic Coupling System), a low-frequency wireless electrochemical sensing platform that combines ion-based materials with wireless power transfer technology.
Conventional wireless sensors suffer from low capacitance (the ability to store electrical charge), requiring high frequencies in the megahertz (MHz) range to compensate. However, these high-frequency methods can cause tissue heating or signal instability, limiting their practical application in clinical medical settings.
To solve this, the Hanyang University team developed a biocompatible ionic material with high capacitance, leveraging the movement of ions to store significant amounts of electricity. The KAIST team then integrated this with a wireless LC resonance system—a circuit that exchanges energy wirelessly. The result is a wireless sensor that operates stably within the human body at low frequencies.
Specifically, the team designed the system such that ions are attached to the surface of gold nanoparticles, inhibiting their movement under normal conditions and releasing them only when pressure is applied. This design causes a significant change in electrical storage even under minor stimuli. By monitoring these changes through fluctuations in the wireless frequency, the sensor can detect extremely subtle variations in pressure. The system demonstrates excellent performance even in the sub-1 MHz frequency band and achieves a high Signal-to-Noise Ratio (SNR) due to reduced electromagnetic interference.
In experiments using an artificial blood vessel model, the research team successfully monitored real-time blood pressure changes associated with arteriosclerosis—a condition where blood vessels harden or narrow. This demonstrates the technology's strong potential for future cardiovascular disease monitoring.
< Schematic Diagram of a Wireless Blood Pressure Monitoring Platform (AI-Generated Image) >
This study is significant as it shifts away from the conventional approach of simply increasing frequency to improve performance. Instead, it solves the problem by fundamentally altering the physical mechanism of sensor operation. It is evaluated as opening a new path for the design of next-generation bio-devices where electromagnetic safety is paramount.
Professor Seungyoung Ahn stated, "This research is a result of a collaborative effort combining ionic materials and wireless technology, overcoming the limitations of existing high-frequency wireless sensors. It has great potential for expansion as a platform that enables stable wireless sensing while minimizing electromagnetic impact."
The study, with Haerim Kim (KAIST) and Ji Hong Kim (Hanyang University) as joint first authors, was published in the world-renowned academic journal Nature Communications on March 11.
Paper Title: Low-frequency ionic-electronic coupling for energy-efficient noise-resilient wireless bioelectronics
DOI: https://www.nature.com/articles/s41467-026-70331-4
Authors: Ji Hong Kim (Hanyang University, Co-first author), Haerim Kim (KAIST, Co-first author), Jaewon Rhee (KAIST, Co-author), Joo Sung Kim, Hanbin Choi, Won Hyuk Choi, Yoseph Park, Jong Hwi Kim, So Young Kim, Seungyoung Ahn (KAIST, Corresponding author), and Do Hwan Kim (Hanyang University, Corresponding author).
2026.04.13 View 176 -
Smart OLED Patch Uses Light to Automate Drug Delivery, Doubling Healing Speed
< (Left) Professor Kyung Cheol Choi, Researcher Hyejeong Yeon (Center) Researcher Sohyeon Yu, Dr. Daekyung Sung, Researcher Sangwoo Kim (Right) Researcher Minhyeok Lee, Professor Chan-Su Park >
Instead of applying ointment and attaching a bandage, a ‘smart patch that regulates treatment intensity on its own just by being attached’ has appeared. Our university's research team has developed a ‘self-regulating OLED wound healing patch’ that combines light and drugs to pull up the wound recovery speed by about twice. It is expected to develop into an intelligent treatment technology where light regulates drug release according to the patient's condition in the future.
KAIST announced on the 13th that a research team led by Professor Kyung Cheol Choi of the School of Electrical Engineering, together with Dr. Daekyung Sung of the Korea Institute of Ceramic Engineering and Technology (President Jong-seok Yoon) and Professor Chan-Su Park's team at Chungbuk National University (Acting President Yu-sik Park), developed a ‘self-regulating wound healing patch’ technology that combines Organic Light Emitting Diodes (OLED) and a Drug Delivery System (DDS).
Ointments can cause side effects when overused, and Photobiomodulation (PBM)* treatment, which helps cell regeneration using light, also had limitations in that its effect decreased if the appropriate amount was exceeded. *PBM (Photobiomodulation): A non-invasive treatment method that promotes the recovery of cells and tissues using low-intensity light.
< Schematic diagram of light-drug combined treatment using an OLED patch >
The research team focused on solving the limitations of existing treatment methods, which make it difficult to appropriately regulate treatment intensity. The core of this research is that ‘light regulates the medicine.’ When light is applied, Reactive Oxygen Species (ROS) are generated in the body, and this substance plays a role in stimulating nanoparticles so that drugs are released.
In other words, the amount of reactive oxygen species generated varies according to the intensity of light, and the amount of drug release is naturally regulated accordingly. When light is applied, cell regeneration is promoted, and at the same time, the ROS generated at this time acts as a ‘switch’ so that the drug is automatically released only as much as necessary. It is an ‘intelligent treatment method’ in which the treatment maintains its optimal level on its own even if a person does not regulate it separately. Simply put, it is a ‘self-regulating treatment patch’ where the medicine automatically comes out in an appropriate amount according to the intensity of the light when it is shone.
The research team produced a 630-nanometer (nm) wavelength OLED patch that closely adheres to the skin. This patch was designed to deliver light evenly to induce cell regeneration while releasing an appropriate amount of antioxidant drugs, such as Centella asiatica (commonly known as tiger grass) extract, a plant-derived ingredient well known for its skin regeneration effects.
In addition, it was produced in a wearable form that perfectly adheres to the curves of the skin to reduce light energy loss, and it maintains a temperature of about 31 degrees Celsius even during long-term use, allowing it to be used safely without the risk of low-temperature burns. Stability, maintaining performance for more than 400 hours, was also confirmed, securing the possibility of application to actual medical devices.
The effect was confirmed through experiments. In skin cell experiments, ‘combined treatment’ using light and drugs together showed faster recovery than single treatment. In mouse experiments, the wound recovery rate was 67% as of the 14th day of treatment, recording a healing speed about twice as fast as that of the control group (35%). The quality of healing was also significantly improved, such as skin thickness and barrier protein formation recovering to normal levels.
Professor Kyung Cheol Choi stated, “This research is an example of expanding OLED-based light treatment beyond the level of simply applying it to the role of regulating the treatment, and into a combined treatment platform where drug release is automatically regulated according to the wound status. We plan to develop it into an intelligent treatment technology that can be applied to various wounds and diseases and reacts on its own according to the patient's body condition.”
In this research, Hyejeong Yeon, a doctoral student at the KAIST School of Electrical Engineering, participated as the first author. It was published online in the international academic journal ‘Materials Horizons’ last January and was selected as the Front Cover Paper in March.
※ Paper title: A self-regulating wearable OLED patch for accelerated wound healing via photobiomodulation-triggered drug delivery, DOI: https://doi.org/10.1039/D5MH02129D (Authors: Hyejeong Yeon, Sohyeon Yu, Minhyeok Lee, Sangwoo Kim, Yongjin Park, Hye-Ryung Choi, Won Il Choi, Chang-Hun Huh, Yongmin Jeon, Chan-Su Park, Daekyung Sung, and Kyung Cheol Choi)
< Materials Horizons cover paper image >
This research was conducted with the support of the Future Discovery Convergence Science and Technology Development Program (2021M3C1C3097646) carried out through the National Research Foundation of Korea (NRF) of the Ministry of Science and ICT.
2026.04.13 View 216 -
KAIST Realizes Robots That See, Decide, and Move Like Humans
<Professor Hyun Myung>
A KAIST research team has developed quadrupedal robot technology that not only enables walking by estimating terrain without visual information, but also allows the robot to perceive its surroundings through cameras and LiDAR sensors and make its own decisions while walking, much like animals that visually examine terrain and adjust their steps. This technology is also expected to be extended to various robotic platforms such as wheeled-legged robots and humanoid robots.
KAIST (President Kwang Hyung Lee) announced that a research team led by Professor Hyun Myung from the School of Electrical Engineering, in collaboration with the lab’s startup EuRoboTics Co., Ltd., has developed “DreamWaQ++,” a quadrupedal robot control technology that recognizes terrain based on visual information and adjusts locomotion strategies in real time.
The previously developed “DreamWaQ” by this research team is a “blind locomotion” technology that estimates terrain using only proprioceptive sensing such as joint encoders and inertial sensors, enabling robust movement even without visual information. It allows stable walking even in environments where visual information is difficult to obtain, such as disaster situations, but has the limitation that the robot can only adjust its movement after its legs directly contact obstacles.
The newly developed DreamWaQ++ overcomes this limitation by combining proprioceptive sensing with exteroceptive sensing based on cameras and LiDAR. The key is that it enables “perception-based locomotion,” in which the robot recognizes obstacles in advance and proactively adjusts its walking strategy, going beyond simple reactive control to understanding and making decisions about the environment.
< (Representative image) (a) DreamWaQ++ walking on stairs (b) Terrain predicted by DreamWaQ++ compared with the ground truth (gray) >
To achieve this, the research team designed a multimodal reinforcement learning architecture and implemented it to enable real-time control based on lightweight computation. In addition, it simultaneously secured stability by automatically switching to locomotion based on other sensory modalities when sensor errors occur, and scalability that allows application to various robotic platforms.
Performance was also demonstrated through experiments. The robot equipped with DreamWaQ++ showed performance surpassing existing technologies in various challenging environments.
In stair locomotion experiments, it completed a course of 50 steps (30.03 m horizontally, 7.38 m vertically) in just 35 seconds, outperforming both blind locomotion controllers and commercial perception-based controllers.
< Locomotion controller trained with DreamWaQ++ >
In steep slope environments, it stably climbed a 35° incline, which is 3.5 times steeper than the training condition (10°), and actively adjusted its posture to reduce the rear leg motor torque by approximately 1.5 times compared to existing methods.
In addition, in various obstacle scenarios, it demonstrated learning-based perception capability by autonomously selecting more efficient paths without separate path planning, and in uncertain drop terrains, it exhibited “exploration behavior,” where it voluntarily stops to inspect the ground before moving.
Along with this, it demonstrated high agility by overcoming obstacles of 41 cm, exceeding the robot’s height, even while carrying a payload of 2.5 kg. In simulation, it was shown that it can handle obstacles up to 1.0 m with ANYmal-C (a representative quadrupedal robot developed at ETH Zurich) and up to 1.5 m with KAIST HOUND (a quadrupedal robot developed by Professor Hae-Won Park’s group at KAIST).
< DreamWaQ++ training process >
In particular, even though it was trained only on relatively low obstacles (27 cm), it achieved a success rate of about 80% on actual higher stairs of 42 cm. This means that the robot is not simply repeating learned situations but has the ability to adapt to new environments on its own.
The research team expects that this technology can be applied in environments where conventional wheeled robots have difficulty accessing, such as disaster response, industrial facility inspection, forestry, and agriculture.
< Racing and experiment scenes >
Professor Hyun Myung said, “This research shows that robots have advanced beyond simply moving to a level where they understand the environment and make decisions on their own,” adding, “We will further expand this into intelligent mobility technologies applicable in various real-world environments.”
This study was led by I Made Aswin Nahrendra (first author, current researcher at Krafton, KAIST PhD graduate), with co-authors Byeongho Yu (EuRoboTics Co., Ltd. CEO), Minho Oh (EuRoboTics Co., Ltd. CTO), Dongkyu Lee (EuRoboTics Co., Ltd. CTO), Seunghyun Lee (KAIST), Hyeonwoo Lee (KAIST), and Dr. Hyungtae Lim (MIT postdoctoral researcher). The study was published in February in the world-renowned robotics journal IEEE Transactions on Robotics (T-RO).
※ Paper title: DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learning (link to original Paper: https://arxiv.org/abs/2409.19709)
※ Videos demonstrating DreamWaQ++ operation and locomotion
● Main video: https://youtu.be/DECFbMdpfps
● Additional video: https://youtu.be/Img5a_yKjMs
● Humanoid application video of improved DreamWaQ: https://youtu.be/Kt5PgEiOijQ?si=I4O0flDSOV8ccX3d, https://www.youtube.com/watch?v=sWQY6prcQXw
● Wheeled-legged robot application video of improved DreamWaQ: https://youtu.be/7ruz6u5IhUE
● Project page: https://dreamwaqpp.github.io
This research was supported by the Korea Evaluation Institute of Industrial Technology (KEIT) under the Ministry of Trade, Industry and Energy (Project No. 20018216, “Development and Field Deployment of Mobility Intelligence Software for Autonomous Locomotion of Walking Robots in Dynamic and Unstructured Environments”), and by the Korea Forest Service (Korea Forestry Promotion Institute) through the Forest Science and Technology R&D Program (Project No. RS-2025-25424472).
2026.04.13 View 230 -
InnoCORE Research Group Successfully Achieves AI Protein Design with Nobel Laureate David Baker
< (From left) Professor Gyu Rie Lee, Professor David Baker >
Under the foundation of research cooperation established through the Ministry of Science and ICT's InnoCORE (InnoCORE) project, KAIST InnoCORE researchers have derived meaningful research results. Following a visit by Professor David Baker (University of Washington, USA), the 2024 Nobel Laureate in Chemistry, KAIST has revealed research findings on designing proteins that accurately recognize desired compounds using AI through joint research.
KAIST announced on April 9th that Professor Gyu Rie Lee of the Department of Biological Sciences—a researcher participating in the AI-CRED Innovative Drug InnoCORE Research Group—successfully designed artificial proteins that selectively recognize specific compounds using AI through joint research with Professor David Baker.
This research is characterized by using AI to design proteins that recognize specific compounds from scratch (de novo) and implementing them as functional biosensors. While the conventional approach mainly involved searching natural proteins or modifying some of their functions, this research is highly significant in that it ‘custom-built’ proteins with desired functions through AI-based design and even completed experimental verification.
In particular, the research team successfully designed a protein that selectively recognizes the stress hormone cortisol and implemented an AI-designed biosensor based on it. This is evaluated as a case that extends beyond protein design to actual measurable sensor technology, solving the long-standing challenge of small-molecule recognition in the field of protein design.
These research results are expected to be utilized in various fields such as disease diagnosis, new drug development, and environmental monitoring in the future. It can precisely detect biomarkers in the blood to diagnose diseases early and contribute to the development of targeted therapies through the design of proteins that selectively recognize specific molecules. Furthermore, it is expected that the implementation of customized biosensor technology will become possible, such as real-time monitoring of air and water quality through the development of sensors that detect environmental pollutants.
Designing new proteins (de novo proteins) that recognize compounds has been considered a challenge in the field of protein design for a long time because it requires precise calculations at the atomic level. The research team developed an AI model that precisely reflects protein-ligand interactions and successfully designed binding proteins using it.
As a result, artificial binding proteins were designed for six types of compounds, including metabolites and small-molecule drugs, and their functions were verified through experiments. In particular, a cortisol biosensor was developed by designing a chemical-induced dimer based on a new protein that binds with cortisol. A provisional patent for the relevant design technology has been filed in the United States.
Professor Gyu Rie Lee stated, “This research experimentally proves that AI can be used to design proteins that precisely recognize specific compounds,” and added, “We plan to expand this into protein design technology that can be utilized in various fields such as disease diagnosis, new drug development, and environmental monitoring in the future.”
Professor Gyu Rie Lee of the KAIST Department of Biological Sciences participated in this research as the first author, and Professor David Baker as the corresponding author. The study was published in the international academic journal Nature Communications on March 28, 2026. ※ Paper Title: Small-molecule binding and sensing with a designed protein family DOI: https://doi.org/10.1038/s41467-026-70953-8 Authors: Gyu Rie Lee, Samuel J. Pellock, Christoffer Norn, Doug Tischer, Justas Dauparas, Ivan Anishchenko, Jaron A. M. Mercer, Alex Kang, Asim K. Bera, Hannah Nguyen, Evans Brackenbrough, Banumathi Sankaran, Inna Goreshnik, Dionne Vafeados, Nicole Roullier, Hannah L. Han, Brian Coventry, Hugh K. Haddox, David R. Liu, Andy Hsien-Wei Yeh & David Baker
< Image of Research Content Summary >
Professor Gyu Rie Lee is a new professor who joined KAIST in February 2025 and leads the Protein Design Laboratory. She possesses world-class expertise in the field of precise protein complex design at the atomic level and is performing various research projects such as AI-based protein design, artificial enzyme design, and RNA-recognizing protein development. She is also participating as a mentor professor in the AI-CRED Innovative Drug Research Group of the InnoCORE project, conducting research on enzyme and peptide drug design.
Professor Lee conducted research as a postdoctoral researcher and Staff Scientist in Professor David Baker’s laboratory (University of Washington, USA, Howard Hughes Medical Institute) from 2018 to 2024. Professor David Baker is a world-renowned scholar in the field of protein structure prediction and design and was awarded the Nobel Prize in Chemistry in 2024.
Director Do-Heon Lee, a mentor professor of the AI-CRED Innovative Drug Research Group, stated, “This achievement is a meaningful result derived through cooperation between InnoCORE researchers and a global scholar,” and added, “We will further strengthen our research capabilities based on active research collaboration with postdoctoral researchers recruited through the InnoCORE project to continue creating innovative results in the AI drug development and bio-fields.”
Meanwhile, KAIST will host a lecture on Thursday, April 9th at 4 PM in the KI Building Fusion Hall featuring Professor David Baker and Professor Hannele Ruohola-Baker (University of Washington, USA) under the theme of ‘Advances in AI-powered protein design and biomedical science’ to mark Professor David Baker’s visit to Korea. This event is held with the support of the KAIST International Scholar Invitation Program, KAI-X, the InnoCORE AI-CRED Innovative Drug Group, and the Ministry of Science and ICT’s Overseas Excellent Research Institute Cooperation Hub Construction Project.
< Poster for Professor David Baker’s Invited Lecture >
KAIST President Kwang Hyung Lee stated, “Through cooperation with Nobel Laureate Professor David Baker, we have derived a meaningful achievement in AI-based protein design,” and added, “This research is an example showing that KAIST is leading innovative research alongside world-class research institutions.”
Meanwhile, the KAIST InnoCORE Research Group aims to accelerate AI-based scientific and technological innovation and promote global joint research by supporting top-tier domestic and international postdoctoral researchers to devote themselves to the development of AI convergence technology in a cutting-edge collective research environment. As the lead institution, KAIST operates the ▲Hyper-scale Large Language Model Innovation Research Group ▲AI-based Intelligent Design-Manufacturing Integration Research Group ▲AI-CRED Innovative Drug Research Group and ▲AI-Transformed Aerospace Research Group.
2026.04.09 View 469 -
KAIST Presents Roadmap for AFM Utilization in Next-Generation Semiconductor and Energy Materials Research
<(From Left) Ph. D candidate Yeongyu Kim, Professor Seungbum Hong, Ph.D candidate Kunwoo Park>
For smartphones and computers to become smaller and faster, technologies capable of precisely controlling electrical properties at the nanoscale—beyond what is visible to the naked eye—are essential. In particular, ferroelectric materials, which can maintain their electrical state without external power, are gaining attention as key components for next-generation memory and sensor technologies. However, due to their extremely small size, there have been limitations in precisely observing the internal changes occurring within these materials.
KAIST (President Kwang Hyung Lee) announced on the 4th of April that a research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering has published a review paper systematically outlining research strategies for ferroelectric materials based on atomic force microscopy (AFM), addressing these limitations.
The research team proposed new strategies for utilizing AFM to precisely control electrical properties at the nanoscale and presented a direction for next-generation materials research.
Ferroelectric materials possess electric polarization similar to magnetism, and this property enables the realization of memory devices that retain information even without power, as well as highly sensitive sensors. As semiconductor devices continue to shrink, nanoscale physical phenomena increasingly determine overall device performance, making technologies capable of precisely analyzing and controlling these phenomena more important than ever.
The team presented an integrated analytical framework that uses AFM to both observe and directly manipulate materials at the nanoscale. AFM is a device that scans surfaces using an extremely fine probe to obtain atomic-level information, effectively serving as both the “eye” and “hand” of the nanoscale world.
Based on AFM, which measures physical and electrical properties at the atomic scale by scanning surfaces with a fine probe, the researchers established a system that integrates various techniques—including piezoresponse force microscopy (PFM) for measuring electrical responses, Kelvin probe force microscopy (KPFM) for analyzing surface potential, and conductive atomic force microscopy (C-AFM) for measuring current flow—into a unified framework. This allows for a three-dimensional understanding of material structures and charge distributions.
This approach goes beyond simple observation and represents the evolution of AFM into a research platform capable of directly designing and manipulating data domains at the nanoscale by applying electrical stimuli through the probe.
Furthermore, AFM can apply electrical stimulation or mechanical pressure directly to extremely small nanoscale regions, enabling changes and control of material properties. In other words, it has evolved from a tool that merely observes to one that enables design and experimentation at the nanoscale. In particular, this study demonstrates applications in evaluating and improving the performance of next-generation semiconductor materials such as two-dimensional transition metal dichalcogenides like molybdenum disulfide (MoS₂) and ultrathin hafnium–zirconium oxide (HfZrO₂)-based materials.
The research team also proposed future directions involving the integration of high-speed AFM with artificial intelligence (AI), enabling rapid interpretation of complex nanoscale structures that are difficult for humans to analyze manually, as well as more efficient design of advanced materials.
< Research Image (AI-Generated Image) >
Professor Seungbum Hong stated, “This review shows that atomic force microscopy has evolved beyond a simple observation tool into a key process technology for designing and precisely controlling advanced materials,” adding, “Analytical techniques combined with artificial intelligence will play a critical role in securing technological competitiveness in next-generation semiconductor and energy materials.”
This review was led by Yeongyu Kim (Doctoral student) and Kunwoo Park (integrated MS–PhD program student), both from the Department of Materials Science and Engineering at KAIST, as co-first authors. The research was recognized for its excellence and published as a front cover article in the international journal Journal of Materials Chemistry C, published by the Royal Society of Chemistry, on February 26.
※ Paper title: “Atomic Force Microscopy for Ferroelectric Materials Research”
DOI: https://pubs.rsc.org/en/content/articlehtml/2026/tc/d5tc03998c
< Front Cover Selection Image for Journal of Materials Chemistry C (JMCC) >
This work was supported by the Ministry of Science and ICT and the National Research Foundation of Korea through the project on developing an AI platform for multi-scale data-integrated lithium secondary battery design, and has been recognized as establishing a new milestone in the field of nanomaterials.
2026.04.08 View 237 -
Era of Ultra-Slim, Wide Field-of-View and , High-Resolution Cameras Opens with Natural Vision Principles
<(From left) Young-Gil Cha, Hyun-Kyung Kim, Jae-Myeong Kwon, Professor Ki-Hun Jeong, (Top right) Professor Min H. Kim>
A breakthrough technology has emerged to fundamentally solve the "camera protrusion/thickness issue," which has been a persistent limitation as smart devices become thinner. KAIST research team has developed an ultra-thin camera that achieves a wide 140-degree field of view (FOV) without any lens protrusion. This technology is expected to be applied across various fields, including medical endoscopes, wearable devices, and micro-robots.
On the 7th, a joint research team led by Professor Ki-Hun Jeong from the Department of Bio and Brain Engineering and Professor Min H. Kim from the School of Computing announced the development of a "wide-angle biomimetic camera." Inspired by insect vision, the camera is exceptionally thin yet boasts a vast field of view. The team successfully secured a diagonal FOV of 140 degrees—surpassing human peripheral vision—within an ultra-thin structure of less than 1 mm, roughly the thickness of a coin.
High-performance wide-angle cameras typically require multiple stacked lenses, inevitably leading to increased thickness. To overcome this, the research team focused on the visual structure of the parasitic insect Xenos peckii.
<Conceptual diagram of the camera structure mimicking insect compound eye principles and photos of the manufactured ultra-thin camera>
While typical insect compound eyes offer a wide FOV, they suffer from low resolution. Conversely, single-lens cameras provide high resolution but limited FOV. Xenos peckii, however, possesses a unique visual system where multiple eyes capture partial segments of a scene, which the brain then integrates into a single high-resolution image. By introducing this "split-capture and integration" principle into the camera architecture, the team simultaneously achieved both thinness and high image quality. This overcomes the low-resolution issues of conventional compound eye cameras and the narrow FOV limits of single-lens systems.
<Result of reconstructing a single scene by combining partial images captured via a microlens array>
The team implemented a method where several micro-lenses with ellipsoidal shape capture different directions simultaneously, merging them into one sharp image without optical aberration. Notably, by precisely adjusting the lens shape and light entry points, they prevented blurring at the edges of the frame. As a result, uniform clarity is maintained from the center to the periphery, enabling stable imaging even at very close ranges.
With a thickness of only 0.94 mm, this ultra-thin camera is expected to bring innovation to space-constrained fields. It can significantly enhance image acquisition efficiency for medical endoscopes requiring precise observation of narrow areas, as well as for micro-robots and wearable healthcare equipment. This technology shifts the design paradigm from increasing device size for better performance to enabling high-performance imaging in ultra-small form factors.
<Results of photographing actual subjects at close range: microfluidic channels (20 mm distance), oral models (30 mm), and human faces (50 mm)>
Furthermore, the research team has completed a technology transfer to MicroPix Co., Ltd., a specialist in optical imaging, with the goal of full-scale commercialization by next year.
"Conventional wide-angle cameras faced a trade-off where reducing size lowered resolution, and increasing resolution enlarged the device," explained Professor Ki-Hun Jeong. "By applying visual principles from nature, we have secured both a wide FOV and stable image quality in an ultra-compact structure. This is a new image acquisition method usable even in extreme space-constrained environments."
Jae-Myeong Kwon, Ph.D candidate at KAIST, participated as the lead author. The study was published on March 23 in the world-renowned academic journal Nature Communications.
Paper Title: Biologically inspired microlens array camera for high-resolution wide field-of-view imaging
DOI: https://doi.org/10.1038/s41467-026-70967-2
Authors: Jae-Myeong Kwon, Yejoon Kwon, Young-Gil Cha, Dong Hyun Han, Hyun-Kyung Kim, Je-Kyun Park, Min H. Kim & Ki-Hun Jeong
This research was conducted with support from the Mid-Career Researcher Program of the National Research Foundation of Korea (Ministry of Science and ICT), the Korean ARPA-H Project (Ministry of Health and Welfare), and the Materials and Components Technology Development Program (Ministry of Trade, Industry and Energy).
2026.04.07 View 385 -
KAIST Develops Electrode Technology Achieving 86% Efficiency for Converting CO₂ into Plastic Precursors
<(From Left) Dr. Jonghyeok Park, Ph.D candidate Yunkyoung Han, Professor Hyunjoon Song, Dr. Sungjoo Kim>
KAIST Develops Electrode Technology Achieving 86% Efficiency for Converting CO₂ into Plastic Precursors
In the process of converting carbon dioxide into useful chemicals such as ethylene—a key precursor for plastics—a major challenge has been the flooding of electrodes, where electrolyte penetrates the electrode structure and reduces performance. KAIST researchers have developed a new electrode design that blocks water while maintaining efficient electrical conduction and catalytic reactions, thereby improving both efficiency and stability.
KAIST (President Kwang Hyung Lee) announced on the 6th of April that a research team led by Professor Hyunjoon Song from the Department of Chemistry has developed a novel electrode structure utilizing silver nanowire networks—ultrafine silver wires arranged like a spiderweb—to significantly enhance the efficiency of electrochemical CO₂ conversion to useful chemical products.
In electrochemical CO₂ conversion processes, a long-standing issue has been flooding, where the electrode becomes saturated with electrolyte, reducing the space available for CO₂ to react. While hydrophobic materials can prevent water intrusion, they typically suffer from low electrical conductivity, requiring additional components and complicating the system.
To overcome this, the research team designed a three-layer electrode architecture that simultaneously repels water and enables efficient charge transport. The structure consists of a hydrophobic substrate, a catalyst layer, and an overlaid silver nanowire (Ag NW) network, which acts as an efficient current collector while preventing electrolyte flooding.
< Schematic diagram of a porous polymer–copper oxide catalyst silver nanowire network electrode structure >
A key finding of this study is that the silver nanowires do more than just conduct electricity—they actively participate in the chemical reaction. During CO₂ reduction, the silver nanowires generate carbon monoxide (CO), which is then transferred to adjacent copper-based catalysts, where further reactions occur. This creates a tandem catalytic system, in which two catalysts cooperate sequentially, significantly enhancing the production of multi-carbon compounds such as ethylene.
The electrode demonstrated outstanding performance. It achieved 79% selectivity toward C₂₊ products in alkaline electrolytes and 86% selectivity in neutral electrolytes, representing a world-leading level. It also maintained stable operation for more than 50 hours without performance degradation. These results indicate that most of the converted products are the desired chemicals, while also overcoming the durability limitations of conventional systems.
< Conceptual diagram of a CO₂ electrolysis electrode utilizing a stacked silver nanowire structure (AI-generated image) >
Professor Hyunjoon Song stated, “This study is significant in showing that silver nanowires not only serve as electrical conductors but also directly participate in chemical reactions,” adding, “This approach provides a new design strategy that can be extended to converting CO₂ into a wide range of valuable products such as ethanol and fuels.”
This research, led by Jonghyeok Park (KAIST, first author), was published on March 24, 2026, in the international journal Advanced Science.
※ Paper title: “Overlaid Conductive Silver Nanowire Networks on Gas Diffusion Electrodes for High-Performance Electrochemical CO₂-to-C₂₊ Conversion,” DOI: https://doi.org/10.1002/advs.75003
2026.04.07 View 360 -
KAIST Achieves 3-fold Increase in Hydrogen Production Using “High-Entropy” Design—More Mixing, More Strength
<(From Left) Professor Kang Taek Lee, Ph.D candidate Seeun Oh, Researcher Incheol Jeong, Dr. Dongyeon Kim, Ph.D candidate Hyeonggeun Kim>
While mixing materials typically leads to instability, there exists a phenomenon known as “high entropy,” where increasing compositional complexity can actually enhance stability. KAIST researchers leveraged this principle to enable faster proton transport and more efficient reactions within electrochemical cells, developing a technology that significantly improves hydrogen production efficiency. This breakthrough is expected to reduce hydrogen costs and accelerate the transition to clean energy.
KAIST (President Kwang Hyung Lee) announced on the 5th of April that a research team led by Professor Kang Taek Lee from the Department of Mechanical Engineering has developed a novel oxygen electrode material that dramatically improves reaction kinetics and power performance through entropy-maximized design. The oxygen electrode is a key component in electrochemical cells where oxygen evolution occurs during hydrogen production.
Green hydrogen—produced from water without carbon emissions—is considered a cornerstone of future clean energy systems. In particular, protonic ceramic electrochemical cells (PCECs), which generate hydrogen by splitting water using electrical energy while protons migrate through the cell, have attracted attention for their high efficiency. However, their performance has been limited by slow reaction kinetics at the oxygen electrode.
To address this issue, the research team adopted a high-entropy strategy, introducing multiple metal elements simultaneously to increase configurational disorder. Although mixing many elements typically destabilizes structures, under certain compositions, maximizing entropy can instead stabilize a single-phase structure.
<Structural and chemical characterization of PBSCF and PLNNCBSCF. XRD patterns of a) the synthesized PBSCF and PLNNCBSCF and b) enlarged view of the XRD patterns from 31.5 to 33.5°. c) Rietveld refinement results of the XRD profile for PLNNCBSCF, with the inset showing the idealized structure. d) HR-TEM image of PLNNCBSCF with the inset showing lattice fringes. e) Corresponding EDS mappings of the PLNNCBSCF elements. XPS of F) survey peak, G) Pr 3d, and H) O 1s spectra for PBSCF and PLNNCBSCF>
Based on this concept, the researchers designed a high-entropy double perovskite oxygen electrode by incorporating seven different metal elements (Pr, La, Na, Nd, Ca, Ba, Sr) into the A-site of the electrode structure. This material combines a perovskite crystal framework with a double perovskite structure, further enhanced by high-entropy design.
The presence of multiple mixed metal elements improves charge transport and oxygen-related reactions within the electrode, resulting in significantly faster electrochemical reactions for both electricity generation and hydrogen production.
Notably, density functional theory (DFT) calculations revealed that the energy required to form oxygen vacancies—active sites where reactions occur—was reduced by more than 60% compared to conventional materials. This indicates that reactive sites can form more easily and in greater abundance.
Additionally, time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis showed that proton transport speed increased by more than sevenfold, demonstrating that hydrogen generation processes proceed much more efficiently within the electrode.
The performance improvements were substantial. Cells incorporating the new electrode achieved a power density of 1.77 W cm⁻² at 650°C, approximately 2.6 times higher than conventional systems. Hydrogen production performance also improved by approximately threefold (4.42 A cm⁻²) under the same conditions.
Moreover, in long-term testing under steam conditions for 500 hours, performance degradation was only 0.76%, confirming excellent durability and stability over extended operation.
Professor Kang Taek Lee stated, “This study demonstrates that the thermodynamic concept of entropy can be used to control electrode reactivity,” adding, “It has the potential to significantly enhance green hydrogen production efficiency and accelerate the commercialization of the hydrogen economy.”
This study was co-led by Seeun Oh of the Department of Mechanical Engineering at KAIST and Incheol Jeong of the Korea Institute of Geoscience and Mineral Resources. The findings were published on December 16, 2025, in the international journal Advanced Energy Materials (IF: 26.0) and were selected as a front cover article, highlighting their scientific impact.
※ Paper title: “Unveiling Entropy-Driven Performance Enhancement in Double Perovskite Oxygen Electrodes for Protonic Ceramic Electrochemical Cells,” DOI: https://doi.org/10.1002/aenm.202503176※ Authors: Seeun Oh (KAIST, first author), Incheol Jeong (Korea Institute of Geoscience and Mineral Resources, first author), Dongyeon Kim (second author), Hyeonggeun Kim (second author), Kang Taek Lee (corresponding author)
This research was supported by the Mid-Career Researcher Program and the Global Basic Research Laboratory Program funded by the Ministry of Science and ICT (MSIT), Korea.
2026.04.06 View 229