KAIST Identifies a Route to Faster-Charging, Longer-Lasting EV Batteries
Can electric vehicles charge quickly without sacrificing battery longevity? A KAIST research team has identified a potential solution using a three-dimensional digital twin—a virtual model that recreates the internal microstructure of a real battery electrode. The team found that fast-charging performance and degradation behavior are influenced not only by the amounts of materials and pore space within the electrode, but also by how they are distributed.
KAIST (President Choongsik Bae) announced on August 24 that a research team led by Professor Kang Taek Lee from the Department of Mechanical Engineering, in collaboration with Professor EunAe Cho of the Department of Materials Science and Engineering, constructed a 3D digital twin informed by the microstructure and specifications of a commercial graphite anode. Using the model, the researchers quantitatively analyzed localized degradation mechanisms that arise during fast charging.
A lithium-ion battery anode consists of graphite, which stores lithium; a binder that holds the graphite particles together; and electrolyte-filled pore space where lithium ions travel. When a battery is charged, lithium ions move into the graphite particles in the anode where they are intercalated and stored. But if charging happens too quickly, some lithium ions cannot enter the graphite in time and instead build up as metallic lithium on the surface—a phenomenon called Li plating. It is similar to cars piling up at the entrance of a parking lot when too many arrive at once and cannot get inside fast enough. If this continues, it can degrade both battery performance and lifespan.
During charging, a thin protective film also forms on the graphite surface called the solid electrolyte interphase (SEI) layer. A properly formed SEI layer is necessary, but if it becomes too thick or uneven, it can degrade battery performance. In addition, as lithium enters the graphite particles during charging, the particles expand and push against the surrounding material, creating mechanical stress inside the electrode.
These processes occur simultaneously at the microscale, making their individual effects difficult to distinguish experimentally. Existing computational models have also relied mainly on the electrode's average properties, making it hard to capture the complex internal structure and location-dependent behavior within the electrode.
To address this, the research team built a "3D digital twin" of the battery electrode based on the structure of an actual commercial graphite anode. The team reconstructed the graphite particles, the binder that holds them together, and the electrolyte-filled pores through which lithium ions travel—all in three dimensions.
Using this virtual electrode, the researchers varied the electrode thickness, porosity, and the distribution of the binder, then simulated fast charging to analyze how lithium ions moved. They also examined where Li plating occured, how the protective film formed, and which parts of the anode experienced concentrated stress.
The results showed that even when the overall charge capacities were similar, the internal degradation behavior of the anodes could differ significantly depending on how the binder and pore space were arranged inside the electrode.
In 50-micrometer (μm) anodes, the difference in charge capacities due to binder distribution was within 4%—meaning there was little apparent difference in charging performance. Inside the electrode, however, the locations where lithium was intercalated and where performance-degrading reactions occurred differed clearly.
In particular, when the binder was concentrated near the separator, the available pore space for lithium-ion transport decreased, making it more difficult for lithium ions to move through the anode. It is much like how a narrower road causes traffic congestion. In this case, Li plating near the current collector increased by more than 10% compared to the anode with an evenly distributed binder.
Conversely, when the binder was spread relatively evenly throughout the electrode, lithium-ion transport became more uniform, and the protective film also formed more uniformly.
This difference grew larger as the electrode became thicker. In 83 μm-thick anodes, the charge capacity difference between the two binder distributions widened to about 18%. This suggests that making thicker electrodes to store more energy requires carefully designing not just how much material is used, but exactly how it is arranged inside.
The location of pore space also affected the stress the electrode experienced. Where there was enough pore space, the surrounding area could accommodate the graphite particles as they expanded during charging. Where pore space was insufficient, the graphite particles had no room to expand, concentrating stress in specific areas.
Through this study, the research team proposed a new design direction for fast-charging lithium-ion batteries: rather than simply looking at how much binder and pore space an electrode contains, researchers should also consider where and how they are distributed.
Using a 3D digital twin makes it possible to examine potential problems inside a battery in virtual space before building and testing multiple electrode designs by hand. The approach is expected to help identify optimal electrode structure, contributing to the development of batteries that can charge faster while maintaining longer service life.
"This research is significant in that it used a 3D digital twin to uncover internal battery problems that were difficult to detect from overall charging performance alone," said Professor Lee. He added that properly arranging the binder and pore space inside the electrode could help design batteries that store more energy while charge faster, and last longer.
The study, with KAIST PhD candidate Yejin Kang from the Department of Mechanical Engineering as first author, was published in the international journal InfoMat (Impact Factor 19.6) and was for the journal’s back cover on July 7.
Paper title: Digital twin quantifies spatial-heterogeneity-driven failure in fast-charging lithium-ion battery anodes,
DOI: https://doi.org/10.1002/inf2.70141
This research was supported by the Ministry of Science and ICT's Mid-Career Researcher Support Program, its Convergence Technology Development Program, and the InnoCORE Research Center.
KAIST and Samsung Heavy Industries Launch Advanced Maritime Research Center, Marking 32 Years of Industry–Academia Collaboration
KAIST (President Choongsik Bae) announced that it held an opening ceremony for the SHI–KAIST Advanced Maritime Research Center (AMRC) with Samsung Heavy Industries (Vice Chairman and CEO Sung-an Choi) on August 13 at the John Hannah Hall in KAIST Academic Cultural Complex on its main campus in Daejeon.
The new center marks a major milestone in the 32-year industry–academia partnership between the two institutions, which dates back to 1995. Building on more than three decades of joint research and mutual trust, KAIST and Samsung Heavy Industries are expanding their partnership through a joint research hub dedicated to developing key technologies for the future of the shipbuilding and offshore industries.
Through the center, the two institutions will jointly develop technologies that address industry needs in areas including AI, robotics, and green technologies. They will also work to bring research outcomes into industrial applications and develop highly skilled professionals.
“Physical AI that drives innovation in real-world industrial settings will be a determining factor in manufacturing competitiveness,” said KAIST President Choongsik Bae. “The shipbuilding and offshore industry is a prime field for creating new value through the convergence of mechanical engineering, AI, and robotics. I hope the center will grow into a research hub that addresses challenges facing industry and sets new benchmarks for future technologies.”
“It is especially meaningful to see our 32 years of collaboration with KAIST culminate in the establishment of the Advanced Maritime Research Center,” said Sung-an Choi, Vice Chairman and CEO of Samsung Heavy Industries. “We will further accelerate our efforts to secure technological competitiveness and foster talent for the future shipbuilding and offshore industry in areas including autonomous navigation, eco-friendly vessels, and smart manufacturing.”
To secure key technologies for the future shipbuilding and offshore industry, the center will conduct joint research in four areas. AI technologies for autonomous operation and intelligent navigation; propulsion systems using zero- and low-carbon fuels; manufacturing innovation for smart shipyards and digital twins; and robotics specialized for shipbuilding and offshore applications.
In autonomous navigation, researchers will develop AI algorithms for advanced autonomous navigation systems, including technologies for situational awareness, optimal route planning, and collision avoidance. The center will also conduct research on zero- and low-carbon fuels in response to international efforts toward carbon neutrality and the green transition of the shipping and shipbuilding industries. This work will focus on key vessel components and fuel-supply technologies for clean fuels such as ammonia and hydrogen.
In the area of smart shipyards, the center will use AI and digital twin technologies to optimize complex shipbuilding processes, including block erection and production management. This research aims to improve productivity and quality while reducing costs and energy consumption. In specialized maritime robotics, researchers will develop technologies to automate demanding on-site tasks such as welding, painting, and inspection. These technologies will help address the decline in the working-age population while improving worker safety and production efficiency.
Beyond technology development, the center will serve as a hub for training specialists who will lead the future maritime industry. The two institutions will use industry–academia cooperation funding and other resources to support student research and scholarship programs. They will also expand personnel exchange programs connecting industrial sites and research laboratories, thereby continuously fostering research talent with the practical, industry-relevant capabilities needed in the field.
The center was established on the foundation of more than three decades of cooperation between the two institutions. Their partnership began in 1995, when Samsung Heavy Industries’ Ship & Offshore Research Institute and KAIST’s Department of Mechanical Engineering established the SHI–KAIST Industry–Academia Cooperation Council. Since then, they have conducted joint research spanning the shipbuilding and offshore engineering fields—including structures, fluid dynamics, cryogenics, green technologies, smart ships, and autonomous navigation—and accumulated a broad base of foundational technologies.
The institutions have continued to strengthen the connection between research and industry through initiatives such as the Advisory Board program, industry-tailored courses, and joint SEED research projects. The number of collaborative projects and technical consulting cases conducted through the Advisory Board program has exceeded 1,000. The two institutions have also maintained active personnel exchanges through short-term researcher training and cooperative education programs.
Approximately 50 people attended the opening ceremony to celebrate the launch of the center, including KAIST President Choongsik Bae, faculty members and professors emeriti from the Department of Mechanical Engineering, Samsung Heavy Industries Vice Chairman and CEO Sung-an Choi, and other executives and officials.
KAIST brings ‘giant batteries’ closer to commercialization in the AI data center era
The explosive growth of AI data centers has brought the commercialization of "giant batteries" one step closer. A KAIST research team has developed a process that cuts the production time for a core material used in large-capacity batteries by 67%, resolving the largest production bottleneck standing in the way of commercialization.
KAIST (President Choongsik Bae) announced on August 5 that a research team led by Professor Hee-Tak Kim from the Department of Chemical and Biomolecular Engineering has developed a process for producing the core electrolyte of vanadium redox flow batteries (VRFBs)—a leading candidate for large-capacity energy storage systems (ESS)—faster and more stably.
As AI data centers operate around the clock in growing numbers, large-capacity ESS that can store electricity generated from solar and wind power and supply it reliably when needed have become increasingly important.
Because VRFBs use nonflammable, water-based electrolytes, they have a lower fire risk than many conventional battery systems. And their energy-storage capacity can be scaled by increasing the amount of electrolyte stored in external tanks. This has drawn attention to VRFBs as ultra-large batteries suited to AI data centers and renewable energy storage. However, producing the vanadium electrolyte with an average oxidation state of 3.5+—the standard starting composition for VRFB operation— has been slow and costly, making it a critical obstacle to commercialization.
The conventional process first produces the electrolyte through chemical reduction—a reaction in which a chemical reducing agent causes vanadium ions to gain electrons—and then refines it through electrochemical reduction, which applies electric current to adjust the vanadium ions' electron state to the desired level. This final electrochemical step, however, relies on a costly VRFB stack and significant electrical energy, increasing both operational complexity and capital costs.Beyond the limitations of the electrochemical reduction process, the research team found, for the first time, that the alternative chemical reduction process also suffers from a distinct kinetic bottleneck. The reaction rate slows sharply at a specific point, much like highway traffic suddenly backing up at a bottleneck. This bottleneck occurs when the average vanadium oxidation state reaches approximately +4.1, an intermediate stage in the production of V3.5+ electrolyte.
In previous research, the team had replaced the conventional electrochemical adjustment step with a Pt/C-catalyzed reduction process, preventing the waste of leftover electrolyte. In the present study, it further extended the catalytic process into the bottleneck region of oxalic-acid-based chemical reduction. By switching from chemical to catalytic reduction at an average oxidation state of approximately +4.1, the team was able to bypass the slowest stage of the production process.
As a result, production time for V3.5+ electrolyte was cut by 67% compared to the conventional process. The switch also eliminated residual oxalic acid, an impurity that can degrade battery performance. The same catalyst was reused more than 2,500 times without a notable drop in performance, demonstrating the process's viability for industrial-scale production.
"This study combined reaction engineering principles with thermodynamic predictions to identify the rate-determining step in the chemical reduction and redesigned the electrolyte production process to overcome this major bottleneck to the commercialization of large-scale batteries," said Hee-Tak Kim, professor in the Department of Chemical and Biomolecular Engineering. He added, "By scientifically identifying the conditions under which the catalyst operates stably without degrading in the electrolyte environment, we resolved a production bottleneck relevant to industry, and we expect this to significantly accelerate the commercialization of large-capacity energy storage technology."
Kyunghwa Seok, a PhD candidate in the Department of Chemical and Biomolecular Engineering, led the research as first author. The findings were published online in Advanced Energy Materials—a leading international journal in the energy field—on May 7. In particular, in recognition of its academic significance, the study was selected as the cover article for Issue 34, which is scheduled to be published online in early September.
Paper title: Streamlined V3.5+ Electrolyte Production by Leveraging Chemical and Catalytic Reductions
DOI: https://doi.org/10.1002/aenm.71029
Authors: Kyunghwa Seok (KAIST, first author), Minseong Kang (KAIST, second author), and Hee-Tak Kim (KAIST, corresponding author).
This research was supported by Lotte Chemical.
KAIST Gives Antibodies “Eyes” to Detect Cancer, Targeting Cancer Mutations Inside Cells
Antibodies are like “guided missiles” that find and attack cancer cells, but cancer-causing mutations inside cells have remained a “blind spot” for treatment because antibodies cannot reach them. KAIST researchers have now succeeded in precisely targeting even intracellular cancer mutations using a newly designed antibody created through computational methods. This achievement is expected to open a new path toward next-generation precision therapies for difficult-to-treat cancers, going beyond the limitations of conventional antibody treatments.
KAIST (President Choongsik Bae) announced on the 24th of July that a research team led by Professor Byung-Ha Oh from the Department of Biological Sciences, together with researchers from Therazyne, a KAIST faculty startup specializing in protein design and headed by Professor Oh, has developed an antibody that selectively recognizes only cancer cells carrying KRAS(G12D), a representative cancer-driving mutation. By combining computational antibody design with experimental validation, the team designed a new antibody that would have been difficult to develop through conventional approaches and is now verifying its efficacy in animal disease models.
KRAS(G12D) is a mutated form of the KRAS protein, which regulates cell growth and proliferation. It is one of the most common cancer-driving mutations found in pancreatic, colorectal, and lung cancers. However, because the KRAS protein exists inside cells, it has long been considered an “undruggable target” that is difficult to directly target with conventional antibody therapeutics.
The research team focused on the natural process by which cells break down aged or damaged proteins into small fragments. The KRAS(G12D) protein inside cells is also processed in this way into small protein fragments, known as neoantigens, which serve as clues that allow immune cells to distinguish cancer cells. Some of these fragments are then transported to the cell surface and presented to immune cells. By combining computational protein design with experimental screening, the team developed a TCR-like antibody that precisely recognizes only this cancer-mutation-derived fragment.
TCR, or T cell receptor, acts as a “sensor” that allows T cells, the body’s immune cells, to read protein fragments displayed on the surface of cells and identify cancer cells or virus-infected cells. The TCR-like antibody developed in this study works on a similar principle, effectively giving an antibody the “eyes” of a T cell. It was designed to selectively recognize traces of intracellular cancer mutations that conventional antibodies cannot easily access.
Experimental results confirmed that the antibody developed by the team selectively recognizes only cancer cells carrying the KRAS(G12D) mutation, while showing little to no reaction with normal cells or other proteins. When applied to immunotherapy, it was also shown to effectively eliminate only cancer cells carrying the mutation. This finding suggests the possibility of expanding antibody therapy to intracellular cancer-driving proteins that conventional antibody treatments have been unable to target. It is also expected to serve as a platform technology for developing next-generation precision antibody therapies targeting not only KRAS but also a wide range of cancer mutations.
Professor Byung-Ha Oh said, “The antibody developed in this study can selectively identify only cancer cells carrying the KRAS(G12D) mutation, demonstrating the potential for precision antibody therapeutics that minimize damage to normal cells.” He added, “The computational antibody design technology developed in this research is expected to be widely applicable to the development of next-generation antibody therapeutics targeting KRAS as well as various other cancer mutations.”
Both the first author and corresponding authors of this study are KAIST-affiliated researchers. SangPhil Ahn, a researcher at Therazyne, participated as the first author, while Professor Byung-Ha Oh and Bo-Seong Jeong, Head of Research at Therazyne, jointly led the study as co-corresponding authors. The research was published online on June 3 in Molecular Therapy, a leading international journal in the field of gene and cell therapy.
Paper title: Discovery of TCR-like antibodies to the KRAS G12D neoantigen via in silico-in vitro workflow DOI: https://doi.org/10.1016/j.ymthe.2026.05.032
This research was conducted in collaboration with Therazyne and the New Drug Development Center of the Osong Biomedical Innovation Foundation, and was supported by the Ministry of Science and ICT’s Industry-Academia-Research Linked New Drug Development Program and the National Research Foundation of Korea’s Bio & Medical Technology Development Program.
KAIST Brings the Era of Microbial Cell Factories One Step Closer
The era of "biomanufacturing", in which microbes, not petroleum, produce chemical products, is one step closer. A KAIST research team has analyzed the key challenges limiting the commercialization of biomanufacturing and proposed an AI-driven strategy for industrialization.
KAIST (President Choongsik Bae) announced on the 14th of July that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering has comprehensively analyzed the key bottlenecks to commercializing biomanufacturing and proposed an industrialization strategy and a roadmap for future growth to address them.
Most chemical products today — including plastics, textiles, and pharmaceutical raw materials — are produced from petroleum. But as concerns over carbon emissions and environmental pollution grow, biomanufacturing, which uses microbes to produce chemicals, is drawing attention as a next-generation manufacturing technology. Still, scaling up lab-developed technologies into economically viable mass production at actual factories remains a major challenge.
Systems metabolic engineering, a core technology in biomanufacturing, designs and optimizes microbial metabolic pathways to build "microbial cell factories" that produce desired chemicals. But technologies that show high productivity in the lab often perform worse once moved to industrial settings — productivity drops, production costs rise, and many fail to achieve price competitiveness, ultimately failing to commercialize.
The research team analyzed succinic acid, a bio-based chemical feedstock, and polyhydroxyalkanoate (PHA), a biodegradable plastic, as representative cases illustrating this "gap between the lab and industry," often called the "valley of death."
Succinic acid is a key raw material for producing eco-friendly plastics and various chemical materials. The team explained that for succinic acid to compete with existing petrochemical products, competitiveness depends not just on production volume, but also on raw material and separation/purification costs, the fermentation process, and market size — all of which must be weighed together. The team also suggested that a phased strategy — entering high-value markets such as pharmaceuticals, cosmetics, and food ingredients first — could be a realistic solution.
PHA is a biodegradable plastic that microbes accumulate inside their cells, an eco-friendly material that breaks down naturally in the environment after use. But PHA is currently less price-competitive than conventional plastics due to high production and recovery costs, and its intrinsic material properties pose a separate barrier: the archetypal polymer P(3HB) is highly crystalline, becomes brittle with age, and has a narrow window between its melting and decomposition temperatures, meaning PHAs are generally not suitable as direct "drop-in" replacements.The team found that a phased approach is needed — simplifying the production process and first applying it to high-value fields such as medical applications and food packaging before expanding into general-purpose markets.
The team predicted that artificial intelligence will become a key to industrializing biomanufacturing going forward. AI can optimize the entire biomanufacturing process — from enzyme and microbial design to digital twins that virtually simulate production processes, and technologies that simultaneously analyze economic feasibility and environmental impact. The team explained that this can shorten development timelines, reduce production costs, and increase the likelihood of successful commercialization.
The team also proposed that techno-economic analysis (TEA) and life cycle assessment (LCA) should be applied as design criteria from the earliest stages of research, rather than as evaluations conducted only after research is complete. The team further emphasized that supply chain resilience — accounting for raw material availability and shifts in the international landscape — should be considered a new design standard for biomanufacturing.
This study is significant not for developing a new production technology, but for comprehensively analyzing the conditions for successful biomanufacturing industrialization and presenting an industrialization roadmap spanning the entire cycle — from securing raw materials to microbial design, fermentation, separation and purification, and market entry. The team expects the study to accelerate the commercialization of the bio-based chemical industry and, over the long term, contribute to shifting the petroleum-centered chemical industry toward an eco-friendly bioeconomy.
The paper, with Ji Yeon Kim and Hye Eun Yu as co-first authors, both Ph.D. candidates in KAIST's Department of Chemical and Biomolecular Engineering, was published online on May 30 in the international journal Nature Communications.
※ Paper title: Beyond petrochemicals: challenges and opportunities in industrial-scale biomanufacturing
※ DOI: 10.1038/s41467-026-73835-1
※ Authors: Ji Yeon Kim (KAIST, co-first author), Hye Eun Yu (KAIST, co-first author), Min Ho Kim (KAIST), Sang Yup Lee (KAIST, corresponding author)
This research was supported by the National Research Foundation of Korea, funded by the Ministry of Science and ICT, through the “Development of Platform Technologies of Microbial Cell Factories for Next-Generation Biorefineries” project (Project No. 2022M3J5A1056117) and the “Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry” project (Project No. RS-2024-00399424).
KAIST: Dementia-Causing Substance Turns On a Therapeutic “Switch”
A substance that worsens dementia has become a “switch” that initiates treatment. KAIST researchers have developed a new therapeutic approach that uses hydrogen peroxide (H₂O₂), a reactive oxygen species that damages cells and increases in the brains of patients with Alzheimer’s disease, to activate a drug selectively in diseased brain tissue. The team also confirmed improvements in cognitive function through animal experiments, presenting a new possibility for next-generation dementia treatment.
KAIST announced on the 2nd that a research team led by Professor Mi Hee Lim of the Department of Chemistry, in collaboration with Professor Mingeun Kim of Chonnam National University, Dr. Chul-Ho Lee and Dr. Kyoung-Shim Kim of the Korea Research Institute of Bioscience and Biotechnology, and Dr. Young-Ho Lee of the Korea Basic Science Institute, has developed a prodrug that is activated selectively in the diseased brain in Alzheimer’s disease and confirmed its therapeutic effects through animal experiments.
A prodrug is a drug that initially has minimal therapeutic effect but is converted into an active therapeutic agent only under specific conditions inside the body. In this study, the prodrug was designed to be activated only when it encounters hydrogen peroxide, which increases in the brains of patients with Alzheimer’s disease, allowing it to function as a “smart therapeutic agent” that selectively acts in diseased brain tissue.
In the brains of Alzheimer’s disease patients, hydrogen peroxide, which damages cells, is elevated above normal levels. Until now, it has generally been regarded only as a harmful substance that should be removed. However, the research team devised a method to use it instead as a signal that activates a drug.
The prodrugs developed by the research team, BE-1 and BE-2, are designed to remain minimally reactive in a healthy brain. However, when they encounter hydrogen peroxide in a brain affected by dementia, they are converted into active therapeutic compounds, AP-1 and AP-2. Through this process, they reduce reactive oxygen species, including hydrogen peroxide, while also preventing amyloid beta (Aβ) peptides — peptides known as a major cause of dementia that accumulate in the brain and damage nerve cells — from aggregating into highly toxic clumps.
Using advanced analytical techniques, the research team confirmed that the activated drug alters the morphology of amyloid beta aggregates and suppresses their growth into large aggregates.
These effects were also confirmed in Alzheimer’s disease mouse models. The drug crossed the blood-brain barrier (BBB), a protective barrier that controls whether substances in the blood can enter the brain, and was converted into the therapeutic compound inside the diseased brain. In mice that received long-term drug administration, oxidative stress in the hippocampus, which is responsible for memory, was reduced, and amyloid beta accumulation in the brain also decreased. In behavioral experiments assessing the ability to recognize new objects and navigate mazes, cognitive function was also found to improve.
This study is significant in that the drug was designed to operate only where needed by using the environment of the diseased brain itself. This approach presents a new strategy for dementia treatment that can enhance therapeutic efficacy while reducing side effects, and it is expected to be applicable to the treatment of other neurodegenerative diseases, such as Parkinson’s disease.
Professor Mi Hee Lim of KAIST’s Department of Chemistry said, “This study is meaningful in that hydrogen peroxide, which had previously been regarded only as something to be eliminated, was used as a signal to activate a drug. We expect this strategy, which activates drugs in diseased tissue, to become a new platform for treating complex diseases such as Alzheimer’s disease more safely and effectively.”
This study was co-first-authored by Jimin Lee and Eunseo Hong, Ph.D. candidates in KAIST’s Department of Chemistry, and was published online on May 31, 2026, in the international journal Small (Impact Factor: 12.1, top 10% in the field of chemistry).
※ Paper title: A Prodrug Approach for Activity-Based Chemical Modulation toward Multiple Pathological Targets in Alzheimer’s Disease
DOI: 10.1002/smll.74013
This research was supported by the National Research Foundation of Korea’s Leader Researcher Program, Global Leading Research Center Program, Sejong Science Fellowship, Graduate Student Research Encouragement Program, and institutional programs of KRIBB and KBSI.
KAIST Teams Win Both International Challenges at ICRA 2026 and CVPR 2026
Two research teams from KAIST have claimed first place in international challenge competitions held at the world’s premier robotics and computer vision conferences.
KAIST (President Kwang-Hyung Lee) announced that the ACDC-K Team and the Curaytor Team, both from the laboratory of Prof. Hyun Myung in the School of Electrical Engineering, won first place in international challenge competitions held in conjunction with the IEEE International Conference on Robotics and Automation (ICRA 2026) and the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026), respectively.
The achievement highlights the global competitiveness of KAIST’s robotic perception and spatial intelligence technologies, with two teams from the same laboratory securing victories in leading international competitions across distinct research fields.
The ACDC-K Team won first place among more than 60 participating teams in the SLAM (Simultaneous Localization And Mapping) category of the Hilti×Trimble SLAM Challenge 2026, held during the Open Challenges in Robotics for Asset Inspection (OCRAIM) Workshop at ICRA 2026 in Vienna, Austria, from June 1 to 5.
Jointly organized by Hilti, Trimble, and the University of Oxford, the challenge evaluates robotic localization and mapping performance using sensor data collected from real construction sites. Participants were required to address practical challenges frequently encountered in construction environments, including non-overlapping front and rear fisheye camera configurations, low-texture indoor scenes, and rapid camera motion.
To tackle these challenges, the ACDC-K Team developed a robust visual-inertial SLAM system that fuses front and rear fisheye camera data with inertial measurements. By integrating feature-point and feature-line observations with adaptive constraints and correction mechanisms, the team achieved highly reliable localization and mapping performance in complex construction environments.
Meanwhile, the Curaytor Team won first place among eight participating teams in the Nothing Stands Still (NSS) Challenge 2026, held during the Computer Vision for the Built World (CV4AEC) Workshop at CVPR 2026 in Denver, Colorado, from June 3 to 7.
Jointly organized by Stanford University, ETH Zurich, and Oregon State University, the NSS Challenge evaluates 3D point cloud registration technologies for construction and industrial environments that evolve over time.
The Curaytor Team developed a novel multi-registration framework capable of aligning multiple LiDAR scans collected across different times and locations. The framework integrates feature extraction, correspondence estimation, robust global registration, registration confidence assessment, and change-aware refinement techniques. As a result, the team achieved highly accurate registration performance even in environments containing structural changes and dynamic objects.
“This achievement demonstrates the robustness of our visual-inertial SLAM and 3D LiDAR registration technologies in complex and constantly changing real-world environments,” said Prof. Hyun Myung. “It is particularly meaningful that our students secured first-place finishes in highly competitive international challenges hosted at two of the world’s most prestigious conferences in robotics and computer vision.”
Prof. Hyun Myung’s laboratory has consistently demonstrated excellence in spatial intelligence research. The laboratory previously won first place in the LiDAR track and ranked first among academic teams in the vision track of the Hilti SLAM Challenge in 2023. In addition, the Curaytor Team successfully defended its title in the NSS Challenge, securing back-to-back championships in 2025 and 2026.
AI Developed to Locate Slums Worldwide... Wins Best Paper Award at AAAI 2026
<(From Left) Sumin Lee, Sungwon Park, Prof. Jihee Kim, Prof. Meeyoung Cha, Prof. Jeasurk Yang>
"Cities don't even know where their slums (impoverished areas) are located."
In many developing nations, the most vulnerable citizens are invisible to the state simply because their homes don't appear on any official map. Today, a breakthrough using Artificial Intelligence (AI) is changing that.
A joint research team from KAIST and Chonnam National University in South Korea and MPI-SP in Germany has developed an AI technology that autonomously identifies slum areas using nothing but satellite imagery. This technology is expected to fundamentally transform urban policy-making and public resource allocation in developing countries where data is scarce and has won the Best Paper Award in the ‘AI for Social Impact’ category at the AAAI 2026 (Association for the Advancement of Artificial Intelligence), the world's premiermost prestigious AI academic conference.
Why it Matters
While previous studies struggle to recognize slums across countries due to varying architectural styles, the team introduced a "Mixture-of-Experts (MoE)" structure. In this system, multiple AI models learn different regional characteristics; when a new city is inputted, the system automatically selects the most appropriate model.
<Figure1. Overview of the Mixture-of-Experts(MoE) structure to identify slum areas>
The core of this research is "Test-Time Adaptation (TTA)" technology. Even if humans do not pre-mark slum locations in a new city, the AI reduces its own errors by comparing and verifying the prediction results of multiple models, trusting only the areas where they commonly agree. This ensures stable performance even in regions with insufficient data.
The research team applied this technology to major cities such as Kampala (Uganda) and Maputo (Mozambique) and confirmed that it distinguishes slum areas more precisely than existing state-of-the-art technologies.
This technology is expected to be utilized in various policy fields, including:
Establishing urban infrastructure expansion plans for developing countries.
Identifying areas vulnerable to disasters and infectious diseases in advance.
Selecting targets for housing environment improvement projects.
Monitoring the implementation of UN Sustainable Development Goals (SDGs).
<Figure2. Slum segmentation results in Kampala in 2015 (yellow) and 2023 (red). Over the eight-year period, the slum ratio in the city increased from 8.4% to 8.6%>
Meeyoung Cha, an AI researcher and author, stated, "This research proves that AI is no longer just a tool for analysis. It is a tool for action. Our technology can bridge the data gap to solve the world’s most pressing social challenges." Jihee Kim, an economist and author, added, "It will complement costly field surveys and help effectively allocate limited resources to the areas that need them most."
The research results were presented at AAAI 2026 in Singapore on January 25th.
Paper Title: Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts
Paper Link: https://aaai.org/about-aaai/aaai-awards/aaai-conference-paper-awards-and-recognition/
This research was supported by the National Research Foundation of Korea (NRF) through the Mid-career Researcher Support Program and the Data Science Convergence Human Resources Training Program.
KAIST Solves Key Commercialization Challenges of Next-Generation Anode-Free Lithium Batteries
<(From Left) Ph.D candidate Juhyun Lee, Postdoctoral Researcher Jinuk Kim, (Upper Right) Professor Jinwoo Lee>
Anode-free lithium metal batteries, which have attracted attention as candidates for electric vehicles, drones, and next-generation high-performance batteries, offer much higher energy density than conventional lithium-ion batteries. However, their short lifespan has made commercialization difficult. KAIST researchers have now moved beyond conventional approaches that required repeatedly changing electrolytes and have succeeded in dramatically extending battery life through electrode surface design alone.
KAIST (President Kwang Hyung Lee) announced on the 4th of January that a research team led by Professors Jinwoo Lee and Sung Gap Im of the Department of Chemical and Biomolecular Engineering fundamentally resolved the issue of interfacial instability—the greatest weakness of anode-free lithium metal batteries—by introducing an ultrathin artificial polymer layer with a thickness of 15 nanometers (nm) on the electrode surface.
Anode-free lithium metal batteries have a simple structure that uses only a copper current collector instead of graphite or lithium metal at the anode. This design offers advantages such as 30–50% higher energy density compared to conventional lithium-ion batteries, lower manufacturing costs, and simplified processes. However, during the initial charging process, lithium deposits directly onto the copper surface, rapidly consuming the electrolyte and forming an unstable solid electrolyte interphase (SEI), which leads to a sharp reduction in battery lifespan.
Rather than changing the electrolyte composition, the research team chose a strategy of redesigning the electrode surface where the problem originates. By forming a uniform ultrathin polymer layer on the copper current collector using an iCVD (initiated chemical vapor deposition) process, they found that this layer regulates interactions with the electrolyte, precisely controlling lithium-ion transport and electrolyte decomposition pathways.
<Figure 1. Schematic of an ultrathin artificial polymer layer (15 nm thick) introduced onto the electrode surface>
In conventional batteries, electrolyte solvents decompose to form soft and unstable organic SEI layers, causing non-uniform lithium deposition and promoting the growth of sharp, needle-like dendrites. In contrast, the polymer layer developed in this study does not readily mix with the electrolyte solvent, inducing the decomposition of salt components rather than solvents. As a result, a rigid and stable inorganic SEI is formed, simultaneously suppressing electrolyte consumption and excessive SEI growth.
Using operando Raman spectroscopy and molecular dynamics (MD) simulations, the researchers identified the mechanism by which an anion-rich environment forms at the electrode surface during battery operation, leading to the formation of a stable inorganic SEI.
This technology requires only the addition of a thin surface layer without altering electrolyte composition, offering high compatibility with existing manufacturing processes and minimal cost burden. In particular, the iCVD process enables large-area, continuous roll-to-roll production, making it suitable for industrial-scale mass production beyond the laboratory.
<Figure 2. Design rationale of the current collector-modifying artificial polymer layer and the SEI formation mechanism>
Professor Jinwoo Lee stated, “Beyond developing new materials, this study is significant in that it presents a design principle showing how electrolyte reactions and interfacial stability can be controlled through electrode surface engineering,” adding, “This technology can accelerate the commercialization of anode-free lithium metal batteries in next-generation high-energy battery markets such as electric vehicles and energy storage systems (ESS).”
This research was conducted with Ph.D candidate Juhyun Lee, and postdoctoral Jinuk Kim, a postdoctoral researcher from the Department of Chemical and Biomolecular Engineering at KAIST, serving as co–first authors. The results were published on December 10, 2025, in Joule, one of the most prestigious journals in the field of energy.
※ Paper title: “A Strategic Tuning of Interfacial Li⁺ Solvation with Ultrathin Polymer Layers for Anode-Free Lithium Metal Batteries,” Authors: Juhyun Lee (KAIST, co–first author), Jinuk Kim (KAIST, co–first author), Jinwoo Lee (KAIST, corresponding author), Sung Gap Im (KAIST, corresponding author), among a total of 18 authors, DOI: 10.1016/j.joule.2025.102226
This research was conducted at the Frontier Research Laboratory, jointly established by KAIST and LG Energy Solution, and was supported by the National Research Foundation of Korea (NRF) Mid-Career Research Program, the Korea Forest Service (Korea Forestry Promotion Institute) Advanced Technology Development Program for High Value-Added Wood Resources, and the KAIST Jang Young Sil Fellowship Program.
A World Led by Scientists and Engineers: The Joy of a Lecture Series
On the September 9th, KAIST announced a lecture series titled "The Joy of a World Led by Scientists and Engineers," where leading professors will share the joy, achievements, and social value they've found in their research. The series will run for a total of nine sessions until October 20th. This series was created to deliver a message of challenge and hope, especially to KAIST students and young people who have chosen, or are dreaming of choosing, a STEM field.
<Professor Dae-sik Kim giving a lecture on the joy of creating thinking machines>
The first lecture was held on the 8th. Professor Dae-Shik Kim of the Department of Electrical and Electronic Engineering spoke on the topic of "The Joy of Creating Thinking Machines" in the auditorium of the Digital Humanities and Social Sciences Building (N4).
September 10th: Professor Ha-woong Jeong from the Department of Physics will show how seemingly difficult physics applies to real life through various examples. Professor Jeong plans to introduce fascinating research cases in complex systems physics, including election prediction using Google search, epidemic prevention and new drug development through network analysis, fusion industry trend prediction based on patent data, and even analyzing the flocking of birds and hidden patterns in artworks with AI. He will emphasize that "complex systems, which are called 21st-century science, make physics approachable and enjoyable."
September 15th: Professor Hyun Myung of the Department of Electrical and Electronic Engineering will give a lecture on "The Joy of Making Robots Move." Professor Myung will share the story of his lifelong dream of robotics and the journey that led him to serious research. He will also share his experiences developing a cleaning robot at the Samsung Advanced Institute of Technology and creating robots that solve social problems, such as jellyfish-eradication and algae-removal robots, after joining KAIST. He will also tell the story of his recent successful startup, which developed "Dreamwalk," a controller for autonomous bipedal robots.
September 24th: Professor Jaeseung Jeong of the Department of Brain and Cognitive Sciences will present "The Joy of Brain Science: Reflecting on Happiness by Looking into the Brain." He will scientifically explore the essence of happiness, introducing recent research that shows happiness is not just a simple emotion but is deeply connected to brain neural circuits, chemical regulation, social relationships, and life attitudes. He plans to share insights from a brain science perspective on the conditions for happiness, which money and success alone can't provide.
The final lecture in the series will feature Professor Hyun-jeong Seok of the Department of Industrial Design. She will share the successful story of the KAIST mascot "Neopjuk-i" and how this once-ignored content grew into a beloved national character. This lecture aims to not only present scientific achievements but also to vividly share the joy and challenges felt by researchers, broadly publicizing the various ways science and engineering can make the world a more joyful place.
<Poster of A World Led by Scientists and Engineers: The Joy of a Lecture Series>
Young-chul Kim, Director of Student Policy, who planned the event, said, "This lecture series was organized to share the joy and value of science through the research journeys of our professors and to provide new inspiration to students and the public."
KAIST President Kwang-hyung Lee stated, "Students will feel a sense of pride in their decision to choose KAIST after directly listening to lectures from our leading professors. I hope this lecture series will be a meaningful opportunity to inspire students currently in or aspiring to a STEM field, and to show the achievements and successes that naturally result from professors enjoying their research."
Except for lectures where the entire or a portion of the content cannot be made public due to the nature of the research, a highlight video of the key contents will be produced and made available for public viewing on KAIST's official YouTube channel.
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 Wins Bid for ‘Physical AI Core Technology Demonstration’ Pilot Project
KAIST (President Kwang Hyung Lee) announced on the 28th of August that, together with Jeonbuk State, Jeonbuk National University, and Sungkyunkwan University, it has jointly won the Ministry of Science and ICT’s pilot project for the “Physical AI Core Technology Proof of Concept (PoC)”, with KAIST serving as the overall research lead. The consortium also plans to participate in a full-scale demonstration project that is expected to reach a total scale of 1 trillion KRW in the future.
In this project, KAIST led the research planning under the theme of “Collaborative Intelligence Physical AI.” Based on this, Jeonbuk National University and Jeonbuk State will carry out joint research and establish a collaborative intelligence physical AI industrial ecosystem within the province. The pilot project will begin on September 1 this year and will run until the end of the year over the next five years. Through this effort, Jeonbuk State aims to be built into a global hub for physical AI.
KAIST will take charge of developing original research technologies, creating a research environment through the establishment of a testbed, and promoting industrial diffusion. Professor Young Jae Jang of the Department of Industrial and Systems Engineering at KAIST, who is the overall project director, has been leading research on collaborative intelligence physical AI since 2016. His “Collaborative Intelligence-Based Smart Manufacturing Innovation Technology” was selected as one of KAIST’s “Top 10 Research Achievements” in 2019.
“Physical AI” refers to cutting-edge artificial intelligence technology that enables physical devices such as robots, autonomous vehicles, and factory automation equipment to perform tasks without human instruction by understanding spatiotemporal concepts.
In particular, collaborative intelligence physical AI is a technology in which numerous robots and automated devices in a factory environment work together to achieve goals. It is attracting attention as a key foundation for realizing “dark factories” in industries such as semiconductors, secondary batteries, and automobile manufacturing.
Unlike existing manufacturing AI, this technology does not necessarily require massive amounts of historical data. Through real-time, simulation-based learning, it can quickly adapt even to manufacturing environments with frequent changes and has been deemed a next-generation technology that overcomes the limitations of data dependency.
Currently, the global AI industry is led by LLMs that simulate linguistic intelligence. However, physical AI must go beyond linguistic intelligence to include spatial intelligence and virtual environment learning, requiring the organic integration of hardware such as robots, sensors, and motors with software. As a manufacturing powerhouse, Korea is well-positioned to build such an ecosystem and seize the opportunity to lead global competition.
In fact, in April 2025, KAIST won first place at INFORMS (Institute for Operations Research and the Management Sciences), the world’s largest industrial engineering society, with its case study on collaborative intelligence physical AI, beating MIT and Amazon. This achievement is recognized as proof of Korea’s global competitiveness in the physical AI technology realm.
Professor Young Jae Jang, KAIST’s overall project director, said, “Winning this large-scale national project is the result of KAIST’s collaborative intelligence physical AI research capabilities accumulated over the past decade being recognized both domestically and internationally. This will be a turning point for establishing Korea’s manufacturing industry as a global leading ‘Physical AI Manufacturing Innovation Model.’”
KAIST President Kwang Hyung Lee emphasized that “KAIST is taking on the role of leading not only academic research but also the practical industrialization of national strategic technologies. Building on this achievement, we will collaborate with Jeonbuk National University and Jeonbuk State to develop Korea into a world-class hub for physical AI innovation.”
Through this project, KAIST, Jeonbuk National University, and Jeonbuk State plan to develop Korea into a global industrial hub for physical AI.