Batteries Make 12Minute Charge for 800km Drive a Reality
<Photo 1. (From left in the front row) Dr. Hyeokjin Kwon from Chemical and Biomolecular Engineering, Professor Hee Tak Kim, and Professor Seong Su Kim from Mechanical Engineering>
Korean researchers have ushered in a new era for electric vehicle (EV) battery technology by solving the long-standing dendrite problem in lithium-metal batteries. While conventional lithium-ion batteries are limited to a maximum range of 600 km, the new battery can achieve a range of 800 km on a single charge, a lifespan of over 300,000 km, and a super-fast charging time of just 12 minutes.
KAIST (President Kwang Hyung Lee) announced on the 4th of September that a research team from the Frontier Research Laboratory (FRL), a joint project between Professor Hee Tak Kim from the Department of Chemical and Biomolecular Engineering, and LG Energy Solution, has developed a "cohesion-inhibiting new liquid electrolyte" original technology that can dramatically increase the performance of lithium-metal batteries.
Lithium-metal batteries replace the graphite anode, a key component of lithium-ion batteries, with lithium metal. However, lithium metal has a technical challenge known as dendrite, which makes it difficult to secure the battery's lifespan and stability. Dendrites are tree-like lithium crystals that form on the anode surface during battery charging, negatively affecting battery performance and stability.
This dendrite phenomenon becomes more severe during rapid charging and can cause an internal short-circuit, making it very difficult to implement a lithium-metal battery that can be recharged under fast-charging conditions.
The FRL joint research team has identified that the fundamental cause of dendrite formation during rapid charging of lithium metal is due to non-uniform interfacial cohesion on the surface of the lithium metal. To solve this problem, they developed a "cohesion-inhibiting new liquid electrolyte."
The new liquid electrolyte utilizes an anion structure with a weak binding affinity to lithium ions (Li⁺), minimizing the non-uniformity of the lithium interface. This effectively suppresses dendrite growth even during rapid charging.
This technology overcomes the slow charging speed, which was a major limitation of existing lithium-metal batteries, while maintaining high energy density. It enables a long driving range and stable operation even with fast charging.
Je-Young Kim, CTO of LG Energy Solution, said, "The four years of collaboration between LG Energy Solution and KAIST through FRL are producing meaningful results. We will continue to strengthen our industry-academia collaboration to solve technical challenges and create the best results in the field of next-generation batteries."
<Figure 1. Infographic on the KAIST-LGES FRL Lithium-Metal Battery Technology>
Hee Tak Kim, Professor from Chemical and Biomolecular Engineering at KAIST, commented, "This research has become a key foundation for overcoming the technical challenges of lithium-metal batteries by understanding the interfacial structure. It has overcome the biggest barrier to the introduction of lithium-metal batteries for electric vehicles."
The study, with Dr. Hyeokjin Kwon from the KAIST Department of Chemical and Biomolecular Engineering as the first author, was published in the prestigious journal Nature Energy on September 3.
Nature Energy: According to the Journal Impact Factor announced by Clarivate Analytics in 2024, it ranks first among 182 energy journals and 23rd among more than 21,000 journals overall.
Article Title: Covariance of interphasic properties and fast chargeability of energy-dense lithium metal batteries
DOI: 10.1038/s41560-025-01838-1
The research was conducted through the Frontier Research Laboratory (FRL, Director Professor Hee Tak Kim), which was established in 2021 by KAIST and LG Energy Solution to develop next-generation lithium-metal battery technology.
KAIST to Foster a 'Robot Valley' in Daejeon with $10 Million Initiative
<Group Photo of Kick-off Meeting>
On September 3, KAIST announced the official launch of the "2025 Deep Tech Scale-up Valley Nurturing Project" with a kick-off meeting at the KAIST Department of Mechanical Engineering.
KAIST was selected for this project by the Ministry of Science and ICT and the Research and Development Special District Foundation. With this selection, the university plans to create a "Robot Valley".
Over the next three and a half years, KAIST will receive a total of 13.65 billion won (approximately $10 million) in funding. The university's goal is to intensively nurture globally competitive, innovative robotics companies based on foundational technologies and to develop Daejeon into a global hub for the robotics industry.
The initiative will leverage Daejeon's exceptional research talent and its startup and investment ecosystem to create a model for regional revitalization and to cultivate the robotics industry as a next-generation strategic sector.
KAIST's vision for this project is to develop "Human-Friendly Robots (HFR)" that are more than just automated machines; they are collaborative partners that share space, roles, and emotions with people.
The project will implement a multi-stage strategy that includes promoting the commercialization of robotics technology, supporting the startup ecosystem, securing global technological competitiveness, and developing robot commercialization platforms. This will establish a virtuous cycle of technology development, startup and investment growth, and reinvestment.
Unlike traditional startup support and scale-up programs, this project aims for the simultaneous growth of the entire robotics industry, not just individual companies. A key element is an open innovation model where leading robotics firms like Angel Robotics Inc. and EuRoBotics Inc. (led by Professor Byung-ho Yu and Professor Hyun Myung) will share common core technologies related to actuators, circuits, AI, and standardized data. This will allow startups to focus on developing robot products that directly meet customer needs.
The project team includes key KAIST robotics researchers. The project leader is Professor Jung Kim (President of the Korea Robotics Society) from the Department of Mechanical Engineering. Other participating professors include Geon-Jae Lee from the Department of Materials Science and Engineering (human augmentation sensors), Hyun Myung from the School of Electrical Engineering (winner of the QRC 2023 quadruped robot autonomous walking competition at IEEE ICRA), Kyung-Chul Kong from the Department of Mechanical Engineering (two-time champion of the Cybathlon International Competition and founder of Angel Robotics), and Suk-Hyung Bae from the Department of Industrial Design (winner of the ACM SIGGRAPH robot sketching competition).
In addition, the KAIST Technology Commercialization Office, KAIST Holdings, Global Techno Valley Lab (GTLAB), and the Daejeon Center for Creative Economy and Innovation will manage technology commercialization and valley construction. The Daejeon Technopark will also participate to provide comprehensive commercialization support.
"The strategic cooperation between Daejeon City's robotics industry nurturing plan and KAIST was the driving force behind the selection for this project," said Geon-Jae Lee, Director of the KAIST Technology Commercialization Office. "We will create a robotics innovation ecosystem based in Daejeon and systematically foster global companies to rival the likes of ABB in Switzerland and KUKA in Germany, which are considered among the top three robotics companies in the world."
< Kick-off Meeting Scene>
Project leader Jung Kim stated, "We will spearhead efforts to discover and nurture over 15 future unicorn companies by promoting the commercialization of deep-tech robotics developed at KAIST. The entire KAIST robotics research team will dedicate its full efforts to ensure that our research and development achievements lead to real-world industries and startups."
KAIST President Kwang-Hyung Lee emphasized, "As Korea's leading research-oriented university, KAIST will actively support Daejeon's growth into a global robotics hub. This project is more than just research and development; it will be a turning point for KAIST to stand at the center of the global robotics ecosystem and create a new growth engine for the region and the nation."
In collaboration with Daejeon City, KAIST plans to form an "HFR Valley Innovation Council" to share and review project outcomes, ultimately building a self-sustaining ecosystem. This initiative aims to establish Daejeon as a world-class robotics industry hub.
KAIST Unlocks the Secret of Next-Generation Memory
<(From Left) Professor Sang-Hee Ko Park, Ph.D candidate Sunghwan Park, Ph.D candidate Chaewon Gong, Professor Seungbum Hong>
Resistive Random Access Memory (ReRAM), which is based on oxide materials, is gaining attention as a next-generation memory and neuromorphic computing device. Its fast speeds, data retention ability, and simple structure make it a promising candidate to replace existing memory technologies. KAIST researchers have now clarified the operating principle of this memory, which is expected to provide a key clue for the development of high-performance, high-reliability next-generation memory.
KAIST (President Kwang Hyung Lee) announced on the 2nd of September that a research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with a research team led by Professor Sang-Hee Ko Park from the same department, has for the first time in the world precisely clarified the operating principle of an oxide-based memory device, which is drawing attention as a core technology for next-generation semiconductors.
Using a 'Multi-modal Scanning Probe Microscope (Multi-modal SPM)' that combines several types of microscopes*, the research team succeeded in simultaneously observing the electron flow channels inside the oxide thin film, the movement of oxygen ions, and changes in surface potential (the distribution of charge on the material's surface). Through this, they clarified the correlation between how current changes and how oxygen defects change during the process of writing and erasing information in the memory.
*Several types of microscopes: Conductive atomic force microscopy (C-AFM) for observing current flow, electrochemical strain microscopy (ESM) for observing oxygen ion movement, and Kelvin probe force microscopy (KPFM) for observing potential changes.
With this special equipment, the research team directly implemented the process of writing and erasing information in the memory by applying an electrical signal to a titanium dioxide (TiO2) thin film, confirming at the nano-level that the reason for the current changes was the variation in the distribution of oxygen defects.
In this process, they confirmed that the current flow changes depending on the amount and location of oxygen defects. For example, when there are more oxygen defects, the electron pathway widens, and the current flows well, but conversely, when they scatter, the current is blocked. Through this, they succeeded in precisely visualizing that the distribution of oxygen defects within the oxide determines the on/off state of the memory.
<Overview of the Research Process. By using one of the SPM modes, C-AFM (Conductive Atomic Force Microscopy), resistive switching corresponding to the electroforming and reset processes is induced in a 10 nm-thick TiO₂ thin film, and the resulting local current variations caused by the applied electric field are observed. Subsequently, at the same location, ESM (Electrochemical Strain Microscopy) and KPFM (Kelvin Probe Force Microscopy) signals are comprehensively analyzed to investigate and interpret the spatial correlation of ion-electronic behaviors that influence the resistive switching phenomenon>
This research was not limited to the distribution at a single point but comprehensively analyzed the changes in current flow, the movement of oxygen ions, and the surface potential distribution after applying an electrical signal over a wide area of several square micrometers (µm2). As a result, they clarified that the process of the memory's resistance changing is not solely due to oxygen defects but is also closely intertwined with the movement of electrons (electronic behavior).
In particular, the research team confirmed that when oxygen ions are injected during the 'erasing process (reset process)', the memory can stably maintain its off state (high resistance state) for a long time. This is a core principle for increasing the reliability of memory devices and is expected to provide an important clue for the future development of stable, next-generation non-volatile memory.
Professor Seungbum Hong of KAIST, who led the research, said, "This is an example that proves we can directly observe the spatial correlation of oxygen defects, ions, and electrons through a multi-modal microscope." He added, "It is expected that this analysis technique will open a new chapter in the research and development of various metal oxide-based next-generation semiconductor devices in the future."
<By combining C-AFM and ESM techniques, the correlation between local conductivity and variations in oxygen vacancy concentration after resistive switching is analyzed. After the electroforming process, regions with increased conductivity exhibit an enhancement in the ESM amplitude signal, which can be interpreted as an increase in defect ion concentration. Conversely, after the reset process, regions with reduced conductivity show a corresponding decrease in this signal. Through these observations, it is spatially demonstrated that changes in conductivity and local defect ion concentration after resistive switching exhibit a positive correlation>
This research, in which Ph.D. candidate Chaewon Gong from the KAIST Department of Materials Science and Engineering participated as the first author, was published on July 20 in 'ACS Applied Materials and Interfaces', a prestigious academic journal in the field of new materials and chemical engineering published by the American Chemical Society (ACS).
※ Paper Title: Spatially Correlated Oxygen Vacancies, Electrons and Conducting Paths in TiO2 Thin Films
This research was carried out with the support of the Ministry of Science and ICT and the National Research Foundation of Korea.
KAIST develops world’s most sensitive light-powered photodetector—20 times more sensitive, operating without electricity
<(From left) Ph.D candidate Jaeha Hwang, Ph.D candidate Jungi Song ,Professor Kayoung Lee from Electrical Engineering>
Silicon semiconductors used in existing photodetectors have low light responsivity, and the two-dimensional semiconductor MoS₂ (molybdenum disulfide) is so thin that doping processes to control its electrical properties are difficult, limiting the realization of high-performance photodetectors. The KAIST research team has overcome this technical limitation and developed the world’s highest-performing self-powered photodetector, which operates without electricity in environments with a light source. This paves the way for an era where precise sensing is possible without batteries in wearable devices, biosignal monitoring, IoT devices, autonomous vehicles, and robots, as long as a light source is present.
KAIST (President Kwang Hyung Lee) announced on the 14th of August that Professor Kayoung Lee’s research team from the School of Electrical Engineering has developed a self-powered photodetector that operates without external power supply. This sensor demonstrated a sensitivity up to 20 times higher than existing products, marking the highest performance level among comparable technologies reported to date.
Professor Kayoung Lee’s team fabricated a “PN junction structure” photodetector capable of generating electrical signals on its own in environments with light, even without an electrical energy supply, by introducing a “van der Waals bottom electrode” that makes semiconductors extremely sensitive to electrical signals without doping.
First, a “PN junction” is a structure formed by joining p-type (hole-rich) and n-type (electron-rich) materials in a semiconductor. This structure causes current to flow in one direction when exposed to light, making it a key component in photodetectors and solar cells.
Normally, to create a proper PN junction, a process called “doping” is required, which involves deliberately introducing impurities into the semiconductor to alter its electrical properties. However, two-dimensional semiconductors such as MoS₂ are only a few atoms thick, so doping in the conventional way can damage the structure or reduce performance, making it difficult to create an ideal PN junction.
To overcome these limitations and maximize device performance, the research team designed a new device structure incorporating two key technologies: the “van der Waals electrode” and the “partial gate.”
The “partial gate” structure applies an electrical signal only to part of the two-dimensional semiconductor, controlling one side to behave like p-type and the other like n-type. This allows the device to function electrically like a PN junction without doping.
Furthermore, considering that conventional metal electrodes can chemically bond strongly to the semiconductor and damage its lattice structure, the “van der Waals bottom electrode” was attached gently using van der Waals forces. This preserved the original structure of the two-dimensional semiconductor while ensuring effective electrical signal transfer.
This innovative approach secured both structural stability and electrical performance, enabling the realization of a PN junction in thin two-dimensional semiconductors without damaging their structure.
Thanks to this innovation, the team succeeded in implementing a high-performance PN junction without doping. The device can generate electrical signals with extreme sensitivity as long as there is light, even without an external power source. Its light detection sensitivity (responsivity) exceeds 21 A/W, more than 20 times higher than powered conventional sensors, 10 times higher than silicon-based self-powered sensors, and over twice as high as existing MoS₂ sensors. This level of sensitivity means it can be applied immediately to high-precision sensors capable of detecting biosignals or operating in dark environments.
Professor Kayoung Lee stated that they “have achieved a level of sensitivity unimaginable in silicon sensors, and although two-dimensional semiconductors are too thin for conventional doping processes, [they] succeeded in implementing a PN junction that controls electrical flow without doping.” She added, “This technology can be used not only in sensors but also in key components that control electricity inside smartphones and electronic devices, providing a foundation for miniaturization and self-powered operation of next-generation electronics.”
Jaeha Hwang, Jungi Song, Experimnet in Porgress>
This research, with doctoral students Jaeha Hwang and Jungi Song as co-first authors, was published online on July 26 in Advanced Functional Materials (IF 19), a leading journal in materials science.
※ Paper title: Gated PN Junction in Ambipolar MoS₂ for Superior Self-Powered Photodetection
※ DOI: https://advanced.onlinelibrary.wiley.com/doi/10.1002/adfm.202510113
Meanwhile, this work was supported by the National Research Foundation of Korea, the Korea Basic Science Institute, Samsung Electronics, and the Korea Institute for Advancement of Technology.
KAIST Develops World’s First Wireless OLED Contact Lens for Retinal Diagnostics
<ID-style photograph against a laboratory background featuring an OLED contact lens sample (center), flanked by the principal authors (left: Professor Seunghyup Yoo ; right: Dr. Jee Hoon Sim). Above them (from top to bottom) are: Professor Se Joon Woo, Professor Sei Kwang Hahn, Dr. Su-Bon Kim, and Dr. Hyeonwook Chae>
Electroretinography (ERG) is an ophthalmic diagnostic method used to determine whether the retina is functioning normally. It is widely employed for diagnosing hereditary retinal diseases or assessing retinal function decline.
A team of Korean researchers has developed a next-generation wireless ophthalmic diagnostic technology that replaces the existing stationary, darkroom-based retinal testing method by incorporating an “ultrathin OLED” into a contact lens. This breakthrough is expected to have applications in diverse fields such as myopia treatment, ocular biosignal analysis, augmented-reality (AR) visual information delivery, and light-based neurostimulation.
On the 12th, KAIST (President Kwang Hyung Lee) announced that a research team led by Professor Seunghyup Yoo from the School of Electrical Engineering, in collaboration with Professor Se Joon Woo of Seoul National University Bundang Hospital (Director Jeong-Han Song), Professor Sei Kwang Hahn of POSTECH (President Sung-Keun Kim) and CEO of PHI Biomed Co., and the Electronics and Telecommunications Research Institute (ETRI, President Seungchan Bang) under the National Research Council of Science & Technology (NST, Chairman Youngshik Kim), has developed the world’s first wireless contact lens-based wearable retinal diagnostic platform using organic light-emitting diodes (OLEDs).
<Figure 1. Schematic and photograph of the wireless OLED contact lens>
This technology enables ERG simply by wearing the lens, eliminating the need for large specialized light sources and dramatically simplifying the conventional, complex ophthalmic diagnostic environment.
Traditionally, ERG requires the use of a stationary Ganzfeld device in a dark room, where patients must keep their eyes open and remain still during the test. This setup imposes spatial constraints and can lead to patient fatigue and compliances challenges.
To overcome these limitations, the joint research team integrated an ultrathin flexible OLED —approximately 12.5 μm thick, or 6–8 times thinner than a human hair— into a contact lens electrode for ERG. They also equipped it with a wireless power receiving antenna and a control chip, completing a system capable of independent operation.
For power transmission, the team adopted a wireless power transfer method using a 433 MHz resonant frequency suitable for stable wireless communication. This was also demonstrated in the form of a wireless controller embedded in a sleep mask, which can be linked to a smartphone —further enhancing practical usability.
<Figure 2. Schematic of the electroretinography (ERG) testing system using a wireless OLED contact lens and an example of an actual test in progress>
While most smart contact lens–type light sources developed for ocular illumination have used inorganic LEDs, these rigid devices emit light almost from a single point, which can lead to excessive heat accumulation and thus usable light intensity. In contrast, OLEDs are areal light sources and were shown to induce retinal responses even under low luminance conditions. In this study, under a relatively low luminance* of 126 nits, the OLED contact lens successfully induced stable ERG signals, producing diagnostic results equivalent to those obtained with existing commercial light sources.
*Luminance: A value indicating how brightly a surface or screen emits light; for reference, the luminance of a smartphone screen is about 300–600 nits (can exceed 1000 nits at maximum).
Animal tests confirmed that the surface temperature of a rabbit’s eye wearing the OLED contact lens remained below 27°C, avoiding corneal heat damage, and that the light-emitting performance was maintained even in humid environments—demonstrating its effectiveness and safety as an ERG diagnostic tool in real clinical settings.
Professor Seunghyup Yoo stated that “integrating the flexibility and diffusive light characteristics of ultrathin OLEDs into a contact lens is a world-first attempt,” and that “this research can help expand smart contact lens technology into on-eye optical diagnostic and phototherapeutic platforms, contributing to the advancement of digital healthcare technology.”
< Wireless operation of the OLED contact lens >
Jee Hoon Sim, Hyeonwook Chae, and Su-Bon Kim, PhD researchers at KAIST, played a key role as co-first authors alongside Dr. Sangbaie Shin of PHI Biomed Co.. Corresponding authors are Professor Seunghyup Yoo (School of Electrical Engineering, KAIST), Professor Sei Kwang Hahn (Department of Materials Science and Engineering, POSTECH), and Professor Se Joon Woo (Seoul National University Bundang Hospital). The results were published online in the internationally renowned journal ACS Nano on May 1st.
● Paper title: Wireless Organic Light-Emitting Diode Contact Lenses for On-Eye Wearable Light Sources and Their Application to Personalized Health Monitoring
● DOI: https://doi.org/10.1021/acsnano.4c18563
● Related video clip: http://bit.ly/3UGg6R8
< Close-up of the OLED contact lens sample >
KAIST Develops Bioelectrosynthesis Platform for Switch-Like Precision Control of Cell Signaling
<(From left)Professor Jimin Park, Ph.D candidate Myeongeun Lee, Ph.D cadidate Jaewoong Lee,Professor Jihan Kim>
Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally. A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. This approach could provide a foundation for future medical technologies such as electroceuticals, electrogenetics, and personalized cell therapies.
KAIST (President Kwang Hyung Lee) announced on August 11 that a research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Jihan Kim's group, has developed a 'Bioelectrosynthesis Platform' capable of producing either nitric oxide or ammonia on demand using only an electrical signal. The platform allows control over the timing, spatial range, and duration of cell responses.
Inspired by enzymes involved in nitrite reduction, the researchers implemented an electrochemical strategy that selectively produces nitric oxide or ammonia from a single precursor, nitrite (NO₂⁻). By changing the catalyst, the team generated ammonia or nitric oxide from nitrite using a copper-molybdenum-sulfur catalyst (Cu2MoS4) and an iron-incorporated catalyst (FeCuMS4), respectively.
Through electrochemical measurements and computer simulations, the team revealed that Fe sites in the FeCuMoS4 catalyst bind nitric oxide intermediates more strongly, shifting product selectivity toward nitric oxide. Under the same electrical conditions, the Fe-containing catalyst preferentially produces nitric oxide, whereas the Cu2MoS4 catalyst favors ammonia production.
<Figure 1. Schematic diagram of a bio-electrosynthesis platform that synthesizes a desired signaling substance with an electrical signal (left) and the results of precise cell control using it (right)>
The research team demonstrated biological functionality by using the platform to activate ion channels in human cells. Specifically, electrochemically produced nitric oxide activated TRPV1 channels (responsive to heat and chemical stimuli), while electrochemically produced ammonia induced intracellular alkalinization and activated OTOP1 proton channels. By tuning the applied voltage and electrolysis duration, the team modulated the onset time, spatial extent, and termination of cellular responses, which effectively turned cellular signaling on and off like a switch.
<Figure 2. Experimental results showing the change in the production ratio of nitric oxide and ammonia signaling substances according to the type of catalyst (left) and computational simulation results showing the strong bond between iron and nitric oxide (right)>
Professor Jimin Park said, "This work is significant because it enables precise cellular control by selectively producing signaling molecules with electricity. We believe it has strong potential for applications in electroceutical technologies targeting the nervous system or metabolic disorders."
Myeongeun Lee and Jaewoong Lee, Ph.D. students in the Department of Chemical and Biomolecular Engineering at KAIST, served as the co-first authors. Professor Jihan Kim is a co-author. The paper was published online in 'Angewandte Chemie International Edition' on July 8, 2025 (DOI: 10.1002/ange.202508192).
Reference: https://doi.org/10.1002/ange.202508192
Authors: Myeongeun Lee†, Jaewoong Lee†, Yongha Kim, Changho Lee, Sang Yeon Oh, Prof. Jihan Kim, Prof. Jimin Park*
†These authors contributed equally. *Corresponding author.
'Team Atlanta', in which KAIST Professor Insu Yun research team participated, won the DARPA AI Cyber Challenge in the US, with a prize of 5.5 billion KRW
<Photo1. Group Photo of Team Atlanta>
Team Atlanta, led by Professor Insu Yun of the Department of Electrical and Electronic Engineering at KAIST and Tae-soo Kim, an executive from Samsung Research, along with researchers from POSTECH and Georgia Tech, won the final championship at the AI Cyber Challenge (AIxCC) hosted by the Defense Advanced Research Projects Agency (DARPA). The final was held at the world's largest hacking conference, DEF CON 33, in Las Vegas on August 8 (local time).
With this achievement, the team won a prize of $4 million (approximately 5.5 billion KRW), demonstrating the excellence of their AI-based autonomous cyber defense technology on the global stage.
<Photo2.Championship Commemorative:On the left and right are tournament officials. From the second person, Professor Tae-soo Kim(Samsung Research / Georgia Tech), Researcher Hyeong-seok Han (Samsung Research America), and Professor Insu Yun (KAIST)>
The AI Cyber Challenge is a two-year global competition co-hosted by DARPA and the Advanced Research Projects Agency for Health (ARPA-H). It challenges contestants to automatically analyze, detect, and fix software vulnerabilities using AI-based Cyber Reasoning Systems (CRS). The total prize money for the competition is $29.5 million, with the winning team receiving $4 million.
In the final, Team Atlanta scored a total of 392.76 points, a difference of over 170 points from the second-place team, Trail of Bits, securing a dominant victory. The CRS developed by Team Atlanta successfully and automatically detected various types of vulnerabilities and patched a significant number of them in real time.
Among the 7 finalist teams, an average of 77% of the 70 intentionally injected vulnerabilities were found, and 61% of them were patched. The teams also found 18 additional unknown vulnerabilities in real software, proving the potential of AI security technology.
All CRS technologies, including those of the winning team, will be provided as open-source and are expected to be used to strengthen the security of core infrastructure such as hospitals, water, and power systems.
<Photo3. Final Scoreboard: An overwhelming victory with over 170 points>
Professor Insu Yun of KAIST, a member of Team Atlanta, stated, "I am very happy to have achieved such a great result. This is a remarkable achievement that shows Korea's cyber security research has reached the highest level in the world, and it was meaningful to show the capabilities of Korean researchers on the world stage. I will continue to conduct research to protect the digital safety of the nation and global society through the fusion of AI and security technology."
KAIST President Kwang-hyung Lee stated, "This victory is another example that proves KAIST is a world-leading institution in the field of future cyber security and AI convergence. We will continue to provide full support to our researchers so they can compete and produce results on the world stage."
<Photo4. Results Announcement>
Prof. Seungbum Koo’s Team Receives Clinical Biomechanics Award at the 30th International Society of Biomechanics Conference
<(From Left) Ph.D candidate Jeongseok Oh from KAIST, Dr. Seungwoo Yoon from KAIST, Prof.Joon-Ho Wang from Samsung Medical Center, Prof.Seungbum Koo from KAIST>
Professor Seungbum Koo’s research team received the Clinical Biomechanics Award at the 30th International Society of Biomechanics (ISB) Conference, held in July 2025 in Stockholm, Sweden. The Plenary Lecture was delivered by first author and Ph.D. candidate Jeongseok Oh. This research was conducted in collaboration with Professor Joon-Ho Wang’s team at Samsung Medical Center.
Residual Translational and Rotational Kinematics After Combined ACL and Anterolateral Ligament Reconstruction During Walking
Jeongseok Oh, Seungwoo Yoon, Joon-Ho Wang, Seungbum Koo
The study analyzed gait-related knee joint motion using high-speed biplane X-ray imaging and three-dimensional kinematic reconstruction in 10 healthy individuals and 10 patients who underwent ACL reconstruction with ALL augmentation. The patient group showed excessive anterior translation and internal rotation, suggesting incomplete restoration of normal joint kinematics post-surgery. These findings provide mechanistic insight into the early onset of knee osteoarthritis often reported in this population.'
The ISB conference, held biennially for over 60 years, is the largest international biomechanics meeting. This year, it hosted 1,600 researchers from 46 countries and featured over 1,400 presentations. The Clinical Biomechanics Award is given to one outstanding study selected from five top-rated abstracts invited for full manuscript review. The winning paper is published in Clinical Biomechanics, and the award includes a monetary prize and a Plenary Lecture opportunity.
From 2019 to 2023, Koo and Wang’s teams developed a system with support from the Samsung Future Technology Development Program to track knee motion in real time during treadmill walking, using high-speed biplane X-rays and custom three-dimensional reconstruction software. This system, along with proprietary software that precisely reconstructs the three-dimensional motion of joints, was approved for clinical trials by the Ministry of Food and Drug Safety and installed at Samsung Medical Center. It is being used to quantitatively analyze abnormal joint motion patterns in patients with knee ligament injuries and those who have undergone knee surgery.
Additionally, Jeongseok Oh was named one of five finalists for the David Winter Young Investigator Award, presenting his work during the award session. This award recognizes promising young researchers in biomechanics worldwide.
KAIST Develops ‘Real-Time Programmable Robotic Sheet’ That Can Grasp and Walk on Its Own
<(From left) Prof. Inkyu Park from KAIST, Prof. Yongrok Jeong from Kyungpook National University, Dr. Hyunkyu Park from KAIST and Prof.Jung Kim from KAIST>
Folding structures are widely used in robot design as an intuitive and efficient shape-morphing mechanism, with applications explored in space and aerospace robots, soft robots, and foldable grippers (hands). However, existing folding mechanisms have fixed hinges and folding directions, requiring redesign and reconstruction every time the environment or task changes. A Korean research team has now developed a “field-programmable robotic folding sheet” that can be programmed in real time according to its surroundings, significantly enhancing robots’ shape-morphing capabilities and opening new possibilities in robotics.
KAIST (President Kwang Hyung Lee) announced on the 6th that Professors Jung Kim and Inkyu Park of the Department of Mechanical Engineering have developed the foundational technology for a “field-programmable robotic folding sheet” that enables real-time shape programming.
This technology is a successful application of the “field-programmability” concept to foldable structures. It proposes an integrated material technology and programming methodology that can instantly reflect user commands—such as “where to fold, in which direction, and by how much”—onto the material's shape in real time.
The robotic sheet consists of a thin and flexible polymer substrate embedded with a micro metal resistor network. These metal resistors simultaneously serve as heaters and temperature sensors, allowing the system to sense and control its folding state without any external devices.
Furthermore, using software that combines genetic algorithms and deep neural networks, the user can input desired folding locations, directions, and intensities. The sheet then autonomously repeats heating and cooling cycles to create the precise desired shape.
In particular, closed-loop control of the temperature distribution enhances real-time folding precision and compensates for environmental changes. It also improves the traditionally slow response time of heat-based folding technologies.
The ability to program shapes in real time enables a wide variety of robotic functions to be implemented on the fly, without the need for complex hardware redesign.
In fact, the research team demonstrated an adaptive robotic hand (gripper) that can change its grasping strategy to suit various object shapes using a single material. They also placed the same robotic sheet on the ground to allow it to walk or crawl, showcasing bioinspired locomotion strategies. This presents potential for expanding into environmentally adaptive autonomous robots that can alter their form in response to surroundings.
Professor Jung Kim stated, “This study brings us a step closer to realizing ‘morphological intelligence,’ a concept where shape itself embodies intelligence and enables smart motion. In the future, we plan to evolve this into a next-generation physical AI platform with applications in disaster-response robots, customized medical assistive devices, and space exploration tools—by improving materials and structures for greater load support and faster cooling, and expanding to electrode-free, fully integrated designs of various forms and sizes.”
This research, co-led by Dr. Hyunkyu Park (currently at Samsung Advanced Institute of Technology, Samsung Electronics) and Professor Yongrok Jeong (currently at Kyungpook National University), was published in the August 2025 online edition of the international journal Nature Communications.
※ Paper title: Field-programmable robotic folding sheet ※ DOI: 10.1038/s41467-025-61838-3
This research was supported by the National Research Foundation of Korea (Ministry of Science and ICT). (RS-2021-NR059641, 2021R1A2C3008742)
Video file: https://drive.google.com/file/d/18R0oW7SJVYH-gd1Er_S-9Myar8dm8Fzp/view?usp=sharing
Key Figures in the Establishment of KAIST, Specially Invited to the Presidential Office’s National Appointment Ceremony
KAIST announced on August 6 that Professor Emeritus Jung-Woong Ra from the Department of Electrical Engineering and Won-ki Kwon, former Vice Minister of the Ministry of Science and Technology, who played pivotal roles in the establishment of KAIST, were selected as special guests for the 'National Appointment Ceremony' hosted by the Presidential Office on August 15th.
The Presidential Office selected special invitees across eight categories for the ceremony. These include individuals born in 1945 (referred to as 'Liberation Babies'), those involved in the founding of KAIST in 1971, independence activists and national patriots, overseas workers in Germany and the Middle East, AI industry professionals, residents from regions facing depopulation, leading figures in K-culture, military personnel, firefighters, police officers, families of fallen public servants and victims of social disasters, as well as promising talents in economics, science, culture, and the arts.
Considering the historical significance of its establishment and its symbolic meaning for the development of national science and technology, KAIST Professor Emeritus Jung-Woong Ra, who was a key figure in the establishment of the Department of Electrical Engineering after being appointed as a professor in 1971, and former Vice Minister Kwon Won-ki, who was the first practical leader of the establishment project. Both were officially included on the special invitation list.
Briefing from the Presidential Office regarding the 'National Appointment Ceremony' (2025.07.28) https://www.president.go.kr/newsroom/briefing/grehGMuP
Material Innovation Realized with Robotic Arms and AI, Without Human Researchers
<(From Left) M.S candidate Dongwoo Kim from KAIST, Ph.D candidate Hyun-Gi Lee from KAIST, Intern Yeham Kang from KAIST, M.S candidate Seongjae Bae from KAIST, Professor Dong-Hwa Seo from KAIST, (From top right, from left) Senior Researcher Inchul Park from POSCO Holdings, Senior Researcher Jung Woo Park, senior researcher from POSCO Holdings>
A joint research team from industry and academia in Korea has successfully developed an autonomous lab that uses AI and automation to create new cathode materials for secondary batteries. This system operates without human intervention, drastically reducing researcher labor and cutting the material discovery period by 93%.
* Autonomous Lab: A platform that autonomously designs, conducts, and analyzes experiments to find the optimal material.
KAIST (President Kwang Hyung Lee) announced on the 3rd of August that the research team led by Professor Dong-Hwa Seo of the Department of Materials Science and Engineering, in collaboration with the team of LIB Materials Research Center in Energy Materials R&D Laboratories at POSCO Holdings' POSCO N.EX.T Hub (Director Ki Soo Kim), built the lab to explore cathode materials using AI and automation technology.
Developing secondary battery cathode materials is a labor-intensive and time-consuming process for skilled researchers. It involves extensive exploration of various compositions and experimental variables through weighing, transporting, mixing, sintering*, and analyzing samples.
* Sintering: A process in which powder particles are heated to form a single solid mass through thermal activation.
The research team's autonomous lab combines an automated system with an AI model. The system handles all experimental steps—weighing, mixing, pelletizing, sintering, and analysis—without human interference. The AI model then interprets the data, learns from it, and selects the best candidates for the next experiment.
<Figure 1. Outline of the Anode Material Autonomous Exploration Laboratory>
To increase efficiency, the team designed the automation system with separate modules for each process, which are managed by a central robotic arm. This modular approach reduces the system's reliance on the robotic arm.
The team also significantly improved the synthesis speed by using a new high-speed sintering method, which is 50 times faster than the conventional low-speed method. This allows the autonomous lab to acquire 12 times more material data compared to traditional, researcher-led experiments.
<Figure 2. Synthesis of Cathode Material Using a High-Speed Sintering Device>
The vast amount of data collected is automatically interpreted by the AI model to extract information such as synthesized phases and impurity ratios. This data is systematically stored to create a high-quality database, which then serves as training data for an optimization AI model. This creates a closed-loop experimental system that recommends the next cathode composition and synthesis conditions for the automated system.
* Closed-loop experimental system: A system that independently performs all experimental processes without researcher intervention.
Operating this intelligent automation system 24 hours a day can secure more than 12 times the experimental data and shorten material discovery time by 93%. For a project requiring 500 experiments, the system can complete the work in about 6 days, whereas a traditional researcher-led approach would take 84 days.
During development, POSCO Holdings team managed the overall project planning, reviewed the platform design, and co-developed the partial module design and AI-based experimental model. The KAIST team, led by Professor Dong-hwa Seo, was responsible for the actual system implementation and operation, including platform design, module fabrication, algorithm creation, and system verification and improvement.
Professor Dong-Hwa Seo of KAIST stated that this system is a solution to the decrease in research personnel due to the low birth rate in Korea. He expects it will enhance global competitiveness by accelerating secondary battery material development through the acquisition of high-quality data.
<Figure 3. Exterior View (Side) of the Cathode Material Autonomous Exploration Laboratory>
POSCO N.EX.T Hub plans to apply an upgraded version of this autonomous lab to its own research facilities after 2026 to dramatically speed up next-generation secondary battery material development. They are planning further developments to enhance the system's stability and scalability, and hope this industry-academia collaboration will serve as a model for using innovative technology in real-world R&D.
<Figure 4. Exterior View (Front) of the Cathode Material Autonomous Exploration Laboratory>
The research was spearheaded by Ph.D. student Hyun-Gi Lee, along with master's students Seongjae Bae and Dongwoo Kim from Professor Dong-Hwa Seo’s lab at KAIST. Senior researchers Jung Woo Park and Inchul Park from LIB Materials Research Center of POSCO N.EX.T Hub's Energy Materials R&D Laboratories (Director Jeongjin Hong) also participated.
Is 24-hour health monitoring possible with ambient light energy?
<(From left) Ph.D candidate Youngmin Sim, Ph.D candidate Do Yun Park, Dr. Chanho Park, Professor Kyeongha Kwon>
Miniaturization and weight reduction of medical wearable devices for continuous health monitoring such as heart rate, blood oxygen saturation, and sweat component analysis remain major challenges. In particular, optical sensors consume a significant amount of power for LED operation and wireless transmission, requiring heavy and bulky batteries. To overcome these limitations, KAIST researchers have developed a next-generation wearable platform that enables 24-hour continuous measurement by using ambient light as an energy source and optimizing power management according to the power environment.
KAIST (President Kwang Hyung Lee) announced on the 30th that Professor Kyeongha Kwon's team from the School of Electrical Engineering, in collaboration with Dr. Chanho Park’s team at Northwestern University in the U.S., has developed an adaptive wireless wearable platform that reduces battery load by utilizing ambient light.
To address the battery issue of medical wearable devices, Professor Kyeongha Kwon’s research team developed an innovative platform that utilizes ambient natural light as an energy source. This platform integrates three complementary light energy technologies.
<Figure1.The wireless wearable platform minimizes the energy required for light sources through i) Photometric system that directly utilizes ambient light passing through windows for measurements, ii) Photovoltaic system that receives power from high-efficiency photovoltaic cells and wireless power receiver coils, and iii) Photoluminescent system that stores light using photoluminescent materials and emits light in dark conditions to support the two aforementioned systems. In-sensor computing minimizes power consumption by wirelessly transmitting only essential data. The adaptive power management system efficiently manages power by automatically selecting the optimal mode among 11 different power modes through a power selector based on the power supply level from the photovoltaic system and battery charge status.>
The first core technology, the Photometric Method, is a technique that adaptively adjusts LED brightness depending on the intensity of the ambient light source. By combining ambient natural light with LED light to maintain a constant total illumination level, it automatically dims the LED when natural light is strong and brightens it when natural light is weak.
Whereas conventional sensors had to keep the LED on at a fixed brightness regardless of the environment, this technology optimizes LED power in real time according to the surrounding environment. Experimental results showed that it reduced power consumption by as much as 86.22% under sufficient lighting conditions.
The second is the Photovoltaic Method using high-efficiency multijunction solar cells. This goes beyond simple solar power generation to convert light in both indoor and outdoor environments into electricity. In particular, the adaptive power management system automatically switches among 11 different power configurations based on ambient conditions and battery status to achieve optimal energy efficiency.
The third innovative technology is the Photoluminescent Method. By mixing strontium aluminate microparticles* into the sensor’s silicone encapsulation structure, light from the surroundings is absorbed and stored during the day and slowly released in the dark. As a result, after being exposed to 500W/m² of sunlight for 10 minutes, continuous measurement is possible for 2.5 minutes even in complete darkness.
*Strontium aluminate microparticles: A photoluminescent material used in glow-in-the-dark paint or safety signs, which absorbs light and emits it in the dark for an extended time.
These three technologies work complementarily—during bright conditions, the first and second methods are active, and in dark conditions, the third method provides additional support—enabling 24-hour continuous operation.
The research team applied this platform to various medical sensors to verify its practicality. The photoplethysmography sensor monitors heart rate and blood oxygen saturation in real time, allowing early detection of cardiovascular diseases. The blue light dosimeter accurately measures blue light, which causes skin aging and damage, and provides personalized skin protection guidance. The sweat analysis sensor uses microfluidic technology to simultaneously analyze salt, glucose, and pH in sweat, enabling real-time detection of dehydration and electrolyte imbalances.
Additionally, introducing in-sensor data computing significantly reduced wireless communication power consumption. Previously, all raw data had to be transmitted externally, but now only the necessary results are calculated and transmitted within the sensor, reducing data transmission requirements from 400B/s to 4B/s—a 100-fold decrease.
To validate performance, the research tested the device on healthy adult subjects in four different environments: bright indoor lighting, dim lighting, infrared lighting, and complete darkness. The results showed measurement accuracy equivalent to that of commercial medical devices in all conditions A mouse model experiment confirmed accurate blood oxygen saturation measurement in hypoxic conditions.
<Frigure2.The multimodal device applying the energy harvesting and power management platform consists of i) photoplethysmography (PPG) sensor, ii) blue light dosimeter, iii) photoluminescent microfluidic channel for sweat analysis and biomarker sensors (chloride ion, glucose, and pH), and iv) temperature sensor. This device was implemented with flexible printed circuit board (fPCB) to enable attachment to the skin. A silicon substrate with a window that allows ambient light and measurement light to pass through, along with photoluminescent encapsulation layer, encapsulates the PPG, blue light dosimeter, and temperature sensors, while the photoluminescent microfluidic channel is attached below the photoluminescent encapsulation layer to collect sweat>
Professor Kyeongha Kwon of KAIST, who led the research, stated, “This technology will enable 24-hour continuous health monitoring, shifting the medical paradigm from treatment-centered to prevention-centered shifting the medical paradigm from treatment-centered to prevention-centered,” further stating that “cost savings through early diagnosis as well as strengthened technological competitiveness in the next-generation wearable healthcare market are anticipated.”
This research was published on July 1 in the international journal Nature Communications, with Do Yun Park, a doctoral student in the AI Semiconductor Graduate Program, as co–first author.
※ Paper title: Adaptive Electronics for Photovoltaic, Photoluminescent and Photometric Methods in Power Harvesting for Wireless and Wearable Sensors ※ DOI: https://doi.org/10.1038/s41467-025-60911-1 ※ URL: https://www.nature.com/articles/s41467-025-60911-1
This research was supported by the National Research Foundation of Korea (Outstanding Young Researcher Program and Regional Innovation Leading Research Center Project), the Ministry of Science and ICT and Institute of Information & Communications Technology Planning & Evaluation (IITP) AI Semiconductor Graduate Program, and the BK FOUR Program (Connected AI Education & Research Program for Industry and Society Innovation, KAIST EE).