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KAIST Solves the 500-Year-Old ‘Pain’ Behind Michelangelo’s painting of The Creation of Adam
<(From Left) Ph.D candidate Minwoo Choi, Ph.D candidate Hyejoon Jun, Professor Hyoungsoo Kim>
More than 500 years ago, Michelangelo spent four years painting The Creation of Adam on the ceiling of the Sistine Chapel, struggling with paint dripping onto his face. He described the process as “closer to torture than painting.” Now, researchers at KAIST have developed a technology that can effectively “hold up falling paint.” Beyond ceiling paintings, this principle could help solve the problem of liquid films collapsing on inclined surfaces, with potential applications in precision coating, electronic circuit printing, 3D printing, and fluid control in space environments.
KAIST (President Kwang Hyung Lee) announced on the 12th of March that a research team led by Professor Hyungsoo Kim of the Department of Mechanical Engineering has reinterpreted the fundamental cause of downward flow under gravity—known as gravitational instability—from the perspective of interfacial fluid mechanics* and proposed a method to control it by mixing a small amount of volatile liquid into a suspended liquid film.*Interfacial fluid mechanics: the study of the balance of microscopic forces acting at the surface of liquids.
Why was it so difficult for Michelangelo to paint on the ceiling? When paint is applied to a ceiling, a thin liquid film forms. However, this film gradually becomes unstable due to gravity and eventually drips down. This phenomenon is common in everyday life.
For example, when steam condenses on a bathroom ceiling, it first forms a thin layer of water that eventually gathers into droplets and falls. Similarly, droplets that appear on the ceiling of a refrigerator initially form a thin layer but gradually grow and begin to drip downward. This type of instability, where liquid accumulated on an upper surface collapses under gravity, is known as Rayleigh–Taylor instability. Until now, it has generally been considered unavoidable in the presence of gravity.
The research team proposed mixing a small amount of volatile liquid into the suspended liquid film. As the volatile component evaporates, it changes the concentration distribution along the liquid surface, creating differences in surface tension. Surface tension is the force that pulls a liquid surface inward, which is why water droplets maintain a rounded shape.
When differences in surface tension arise, the region with stronger tension pulls liquid toward itself from regions with weaker tension. This creates a surface flow known as the Marangoni effect. Through experiments and theoretical analysis, the researchers demonstrated that this surface flow can effectively hold the liquid in place and suppress the gravitational instability that would otherwise cause it to fall.
A familiar example can illustrate this effect. If pepper powder is sprinkled evenly on the surface of water, it remains floating. However, if a drop of detergent is placed in the center, the pepper suddenly moves outward toward the edges. This happens because the detergent reduces the surface tension where it touches the water, allowing the surrounding regions with stronger surface tension to pull the liquid outward. As the surface flow develops, the pepper particles move along with it.
In this study, evaporation of the volatile liquid created a similar surface tension difference. But instead of pushing particles outward like in the pepper example, the flow pulled the liquid upward, counteracting the force that would otherwise cause it to drip downward.
As a result, under certain conditions the liquid film remained intact despite gravity. In some cases, the researchers even observed a new behavior in which droplets did not fall but the liquid film oscillated periodically. This demonstrates that gravitational instability can be actively controlled using only natural processes—such as liquid composition and evaporation—without any external energy input.
This principle could enable thinner and more uniform liquid films in precision coating, printing, and layer-by-layer manufacturing processes, allowing stable coating even on tilted surfaces. It may also extend to technologies such as 3D printing and fluid control in specialized environments like space. In essence, the physical limitation that Michelangelo struggled with 500 years ago may now inspire future industrial technologies.
<A fictional staged scene of Michelangelo painting The Creation of Adam (AI-generated image)>
Professor Hyungsoo Kim stated, “Rayleigh–Taylor instability has long been considered unavoidable as long as gravity exists. This research is meaningful because it shows that gravitational instability can be actively controlled without external energy by utilizing natural processes such as liquid composition and evaporation.” He added, “This principle could extend beyond coating, printing, and layering processes to fluid control technologies in space environments.”
This study was led by Minwoo Choi, an integrated master’s–PhD student in Mechanical Engineering, as the first author. The discovery, recognized as a new finding in the control of hydrodynamic instability, was published online on January 29 in the international journal Advanced Science (Wiley) and was selected as a Frontispiece article.
※ Paper title: “Evaporation-Driven Solutal Marangoni Control of Rayleigh–Taylor Instability in Inverted Films,” Authors: First author Minwoo Choi (KAIST), co-author Hyejoon Jun (KAIST), corresponding author Hyungsoo Kim (KAIST), DOI: https://doi.org/10.1002/advs.202520343
This research was supported by the Mid-Career Researcher Program of the National Research Foundation of Korea (MSIT: 2021R1A2C2007835)
2026.03.12 View 99 -
KAIST Develops Self-Regenerating Catalyst That Restores Its Own Performance, Opening a Breakthrough for CO₂ Conversion Technology
<(From Left) Professor Dong Young Chung, Ph.D Candidate Hongmin An, Hanjoo Kim>
Technologies that convert carbon dioxide (CO₂) emitted from factories and power plants into useful chemical feedstocks are considered key to achieving carbon neutrality. However, rapid degradation of catalyst performance has long hindered commercialization. KAIST researchers have now developed a “self-regenerating” catalyst that restores its activity during operation, offering a potential solution to this challenge.
KAIST (President Kwang Hyung Lee) announced on the 11th of March that a research team led by Professor Dong Young Chung from the Department of Chemical and Biomolecular Engineering has identified the fundamental cause of catalyst degradation in electrochemical reactions that convert CO₂ into useful materials and has developed a new design strategy that allows catalysts to maintain their active state during the reaction.
<Schematic Illustration of Copper Catalyst Reconstruction>
The research team focused particularly on copper (Cu) catalysts, which are widely used in CO₂ conversion reactions. Copper catalysts are known not to simply degrade during reactions but instead undergo a process called surface reconstruction, in which their surface structure continuously changes. The study revealed that the performance and lifetime of the catalyst vary significantly depending on how this reconstruction occurs.
The researchers discovered that copper catalyst reconstruction occurs mainly through two different mechanisms. The first involves formation and reduction of oxide layers on the catalyst surface. While this temporarily increases catalytic activity, it ultimately leads to long-term degradation of catalyst performance.
The second mechanism involves partial dissolution of the catalyst metal into the electrolyte followed by redeposition onto the catalyst surface. During this process, new reactive sites—known as active sites—are continuously created on the catalyst surface.
Based on this mechanism, the team proposed a method that allows the catalyst to maintain its active state during the reaction. By introducing a trace amount of copper ions into the electrolyte, dissolution and redeposition of copper occur in a balanced cycle on the catalyst surface. This continuous cycle generates new active sites, enabling the catalyst to maintain stable performance over extended periods.
Importantly, this technology can be implemented without complex additional processes or high-voltage conditions, significantly reducing energy consumption while enabling stable production of high-value C₂ compounds such as ethylene and ethanol. C₂ compounds are molecules containing two carbon atoms and are industrially important chemicals used as feedstocks for plastics, fuels, and other materials.
This research is significant because it proposes a new design concept in which catalysts are not merely optimized at the initial stage but are engineered to maintain their optimal state throughout the reaction process. The concept is expected to be applicable not only to CO₂ conversion technologies but also to a wide range of electrochemical energy conversion systems.
Professor Dong Young Chung stated, “This research approached catalyst degradation not as an inevitable phenomenon but as a controllable process,” adding, “We proposed a new strategy that allows catalysts to continuously maintain optimal activity during the reaction.”
The study was led by Hanjoo Kim, a doctoral student at KAIST, and Hongmin An, a combined master’s-doctoral student, as co-first authors. The research was published online on February 5 in the Journal of the American Chemical Society (JACS), one of the world’s most prestigious journals in chemistry.
※ Paper title: “Dynamic Interface Engineering via Mechanistic Understanding of Copper Reconstruction in Electrochemical CO₂ Reduction Reaction” DOI: 10.1021/jacs.5c16244
This research was supported by the Global Young Connect Program for Materials and the National Strategic Materials Technology Development Program funded through the National Research Foundation of Korea.
2026.03.11 View 168 -
KAIST Team Led by Dong-won Lee Wins Grand Prize at the 2nd Global Quantum AI Competition
< (From Left) M.S candidate Dongwon Lee from School of Electrical Engineering, Ph.D candidate Jaehun Han from Graduate School of Quantum Science and Technology >
"Team Yangja-jorim," consisting of Dongwon Lee, Gyungjun Kim and Jaehun Han , has been honored with the Grand Prize at the '2026 2nd Global Quantum AI Competition.' The event was hosted and organized by NORMA, a specialized quantum computing company.
This global competition was designed to expand hands-on experience with quantum cloud services and to discover next-generation talent in the field of quantum artificial intelligence. The event spanned approximately 70 days, beginning with the preliminary opening ceremony held at Korea University’s Hana Square on December 17 last year. The final winners were announced during an awards ceremony held at NORMA's headquarters on the 27th of last month.
The competition attracted significant interest from quantum technology talent worldwide, including university students, developers, and researchers. A total of 137 teams participated in the preliminaries, with the top 10 teams advancing to the finals—a competitive ratio of approximately 13.7 to 1.
< An acquaintance attended the awards ceremony of the 2nd Global Quantum AI Competition to accept the prize on behalf of the team. >
In the final round, participants were presented with four generative problems utilizing the Quantum Circuit Born Machine (QCBM) model. To overcome the current limitations of quantum machine learning, the contestants were tasked with designing and validating Quantum-Classical Hybrid Generative AI models that integrate classical techniques. Notably, the final problem provided an opportunity to verify the proposed methods using a real Quantum Processing Unit (QPU) from Rigetti Computing, a leading global quantum computing firm.
The judging process employed a double-blind system, where the identities of both evaluators and participants remained undisclosed to ensure maximum fairness and credibility.
"Through this competition, we were able to explore the research potential of the quantum AI field more deeply," said KAIST's Team Yangja-jorim in their acceptance speech. "We hope to continue contributing to the advancement of quantum technology through consistent research and new challenges."
2026.03.10 View 118 -
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.
2026.03.08 View 156 -
Professor Kuk-Jin Yoon’s Research Team at the Department of Mechanical Engineering Achieves Landmark Success with 10 Papers Accepted at CVPR 2026
<Professor Kuk-Jin Joon from Department of Mechanical Engineering>
Professor Kuk-Jin Yoon’s research team from our university’s Department of Mechanical Engineering has once again demonstrated its overwhelming academic prowess by having a total of 10 papers accepted as lead authors at the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026).
CVPR is the most influential international conference in the fields of artificial intelligence and visual intelligence. Since its inception in 1983, it has selected outstanding research through a rigorous peer-review process every year. For CVPR 2026, a total of 16,092 papers were submitted worldwide, with 4,090 accepted, resulting in a competitive acceptance rate of approximately 25.42%. Achieving 10 accepted papers as lead or corresponding authors from a single laboratory is regarded as an exceptionally rare and world-class feat.
Professor Kuk-Jin Yoon’s team conducts extensive research with the ultimate goal of achieving human-level visual intelligence. The papers accepted this year cover cutting-edge topics in computer vision, including:
Event camera-based technologies
Perception technologies for autonomous driving
AI optimization and adaptation techniques
This achievement follows the team's remarkable success at ICCV 2025 last year, where they published 12 papers as lead/corresponding authors. The results at CVPR 2026 further solidify the laboratory's position as a global hub for pioneering computer vision research. The research team plans to continue contributing to the advancement of future AI technologies by tackling challenging research that transcends the limitations of existing methods.
Meanwhile, CVPR 2026 is scheduled to be held in Denver, Colorado, USA, from June 3 to June 7.
<CVPR 2026 (Denver, USA)>
2026.03.06 View 484 -
KAIST Develops Brain-Like AI… Thinks One More Time Even When Predictions Are Wrong
<(From left) Professor Sang Wan Lee, Myoung Hoon Ha, and Dr. Yoondo Sung>
Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.
KAIST (President Kwang Hyung Lee) announced on the 29th that a research team led by Distinguished Professor Sang Wan Lee of the Department of Brain and Cognitive Sciences has developed a new technology that applies the learning principles of the human brain to deep learning, enabling stable training even in deep artificial intelligence models.
Our brain does not passively receive the world. Instead of merely perceiving what is happening in the present, it first predicts what will happen next and, when reality differs from that prediction, adjusts itself to reduce the difference (i.e., prediction error). This is similar to anticipating an opponent’s next move in Go and changing strategy if the prediction turns out to be wrong. This mode of information processing is known as “Predictive Coding.”
< Predictive Coding (PC) Module >
Scientists have attempted to apply this principle to AI, but encountered difficulties. As neural networks become deeper, errors tend to concentrate in specific layers or vanish altogether, repeatedly leading to performance degradation.
The research team mathematically identified the cause of this problem and proposed a new solution. The key idea is simple: instead of predicting only the final outcome, the AI is designed to also predict how its prediction errors will change in the future. The team refers to this as “Meta Prediction.” In simple terms, it is an AI that “thinks once more about its mistakes.” When this method was applied, learning proceeded stably in deep neural networks without halting.
<Analysis of Instability in Predictive Coding Model Errors>
The experimental results were also impressive. In 29 out of 30 experiments, the proposed method achieved higher accuracy than the current standard AI training method, backpropagation. Backpropagation is the representative learning method in which AI “goes backward by the amount of error and corrects it.”
Conventional AI training methods (backpropagation) require tightly interconnected layers, meaning the entire network must be computed and updated simultaneously. In contrast, this new approach demonstrates that, like the brain, large AI models can be effectively trained even when learning occurs in a distributed and partially independent manner.
<Performance Comparison of Predictive Coding Models>
This technology is expected to expand into various fields where power efficiency is critical, including neuromorphic computing, robot AI that must adapt to changing environments, and edge AI operating within devices.
Distinguished Professor Sang Wan Lee stated, “The key to this research is not simply imitating the structure of the brain, but enabling AI to follow the brain’s learning principles themselves,” adding, “We have opened the possibility of artificial intelligence that learns efficiently like the brain.”
This study was conducted with Dr. Myoung Hoon Ha as the first author and Professor Sang Wan Lee as the corresponding author. The paper was accepted to the International Conference on Learning Representations (ICLR 2026) and was published online on January 26.
※ Paper title: “Stable and Scalable Deep Predictive Coding Networks with Meta Prediction Errors”Original paper: https://openreview.net/forum?id=kE5jJUHl9i¬eId=e6T5T9cYqO
This research was supported by the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP) through the Digital Global Research Support Program (joint research with Microsoft Research), the Samsung Electronics SAIT NPRC Program, and the SW Star Lab Program.
2026.03.06 View 448 -
2026 KAIST Commencement: Shining Their Own Light on Their Respective Stages
KAIST (President Kwang Hyung Lee) announced that it held its 2026 Commencement Ceremony at 2 p.m. on February 20th at the Sports Complex on its Main Campus in Daejeon.
At this year’s ceremony, a total of 3,334 graduates received degrees, including 817 doctoral, 1,792 master’s, and 725 bachelor’s degrees. Since its founding in 1971, KAIST has now produced a total of 84,490 highly qualified science and technology professionals, including 18,130 Ph.D. recipients, 43,358 master’s graduates, and 23,002 bachelor’s graduates.
KAIST selected three representative graduates who embody the university’s vision of talent. They are Seunghyun Ryu (Department of Bio and Brain Engineering), the doctoral representative known as the “pianist neuroscientist” for his interdisciplinary research bridging brain science and piano performance; Jeanne Choi (School of Computing), the master’s representative who has pursued warm and inclusive technologies for socially vulnerable groups under the themes of accessibility and inclusion; and Mert Yakup Baykan (Department of Aerospace Engineering), the bachelor’s representative from Cyprus holding Turkish nationality, who became the first international recipient of the KAIST Presidential Scholarship.
Seunghyun Ryu, selected as both the doctoral representative and one of the notable graduates, spent 14 years at KAIST completing his undergraduate through doctoral studies while balancing research and music. He organized and managed performances through the campus piano club “PIAST,” expanding artistic activities within the campus community. His research explored the inverse relationship between Alzheimer’s disease and cancer, revealing how disease-related proteins and anticancer drugs act in neurons and offering new perspectives on inter-disease connections.
Jeanne Choi, the master’s representative and another notable graduate, presented research at AAATE 2023 in Paris, analyzing the experiences of visually impaired users engaging with the metaverse and artificial intelligence. Accompanying a visually impaired professor during the conference, Choi gained firsthand insight into mobility and safety challenges, which further expanded the scope of her research. Choi has since continued field-based research, including serving as a teaching assistant at AI and coding camps for visually impaired youth, and plans to pursue a doctoral degree while continuing research for socially vulnerable communities.
Bachelor’s representative Mert Yakup Baykan actively participated in research during his undergraduate studies, publishing four SCI-indexed papers and delivering five conference presentations. He was also selected as a visiting student researcher at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, gaining international collaborative research experience. As the first international KAIST Presidential Scholar, he plans to pursue a Ph.D. at Stanford University and grow into a leading researcher in space propulsion and combustion.
Awards for outstanding graduates were also presented. Seohyeon Kang (B.S., Brain and Cognitive Sciences) received the Minister of Science and ICT Award (Deputy Prime Minister’s Award). The Chairman of the Board Award was presented to Thai international student Punn Lertjaturaphat (B.S., Industrial Design). The President’s Award went to Kyeongmin Yeo (B.S., School of Computing), while the Alumni Association President’s Award and the KAIST Development Foundation Chairman’s Award were presented to Wonwoo Yoo (B.S., Aerospace Engineering) and Sungbeen Park (B.S., Nuclear and Quantum Engineering), respectively. Hyuk-chae Koo, 1st Vice Minister of Science and ICT, presented the awards on behalf of the Deputy Prime Minister and Minister of Science and ICT.
Seohyeon Kang developed a technology to measure key proteins related to Parkinson’s disease without surgery or tissue damage, opening new possibilities in brain disease research, and was recognized as a model graduate who combined academic excellence with community service. Punn Lertjaturaphat gained recognition at prestigious international conferences such as ACM CHI and co-founded a startup addressing rural elderly care issues, demonstrating creativity in solving social problems through technology and design.
Kyeongmin Yeo published six research papers at leading AI conferences including NeurIPS, ICLR, and CVPR, proposing new theoretical approaches to image generation and demonstrating outstanding academic achievement as a young researcher.
Wonwoo Yoo led the overseas volunteer corps and served as student representative, combining leadership with academic excellence, including winning a grand prize in a rocket launch competition. Sungbeen Park proposed a next-generation beta battery concept, linking it to patents and entrepreneurship, while contributing to public communication and outreach in nuclear technology as student council president and university ambassador.
Commencement addresses were delivered by Dongjae Kang (B.S., Industrial and Systems Engineering) and Gul Osman (Ph.D., Mechanical Engineering), an international student from Türkiye. Kang reflected on how he learned science not merely as an avenue for problem-solving but as a process for exploring the deeper meaning behind phenomena, pledging to remain attentive to unseen challenges faced by others. Osman shared his journey of nurturing his passion for science while working in a factory under difficult economic circumstances, emphasizing that opportunities open to those who persist without giving up. He began his academic journey in Korea through the Korean Government Scholarship Program.
This year, KAIST also spotlighted three notable graduates who forged their own paths encompassing research, the arts, and social value: Seunghyun Ryu, Jeanne Choi, and Daehui Kim (B.S., Civil and Environmental Engineering). Kim led campus environmental organizations and community-based environmental campaigns, earning an Environmental Contribution Award. He plans to pursue a master’s degree focusing on carbon dioxide geological storage research. He also performs as the vocalist of the KAIST metal band “INFINITE,” continuing to balance music and research.
During the ceremony, an Honorary Doctorate in Business Administration was conferred upon uey-Yu Wang, Executive Management Committee Member of Formosa Group and Chairman of Formosa Biomedical Technology Corporation.
President Kwang Hyung Lee encouraged the graduates, saying, “Cherish your dreams, seize opportunities, do not fear failure, and continue to challenge yourselves. I hope you will shine in your own way on your own stage and contribute to society as proud members of the KAIST community.”
2026.02.21 View 1371 -
KAIST Overcomes Limitations of Existing Image Sensors… Clear Colors Even Under Oblique Light
<(From Left) Ph.D candidate Chanhyung Park from Electrical Engineering, Jaehyun Jeon from Department of Physics, Professor Min Seok Jang from Electrical Engineering>
Smartphone cameras are becoming smaller, yet photos are becoming sharper. Korean researchers have elevated the limits of next-generation smartphone cameras by developing a new image sensor technology that can accurately represent colors regardless of the angle at which light enters. The team achieved this by utilizing a “metamaterial” that designs the movement of light through structures too small to be seen with the naked eye.
KAIST (President Kwang Hyung Lee) announced on the 12th of February that a research team led by Professor Min Seok Jang of the School of Electrical Engineering, in collaboration with Professor Haejun Chung’s team at Hanyang, has developed a metamaterial-based technology for image sensors that can stably separate colors even when the angle of light incidence varies.
Conventional smartphone cameras capture images by concentrating light into a small lens. However, as camera pixels become extremely small, lenses alone struggle to gather sufficient light. To address this, the Nanophotonic Color Router was introduced. Instead of concentrating light through a lens, this technology uses microscopic structures invisible to the eye to precisely separate incoming light by color. By designing the pathways through which light travels, this metamaterial-based structure accurately divides light into red (R), green (G), and blue (B).
Samsung Electronics has already demonstrated the commercialization potential of this technology by applying it to actual image sensors under the name “Nano Prism.” Theoretically, stacking multiple layers of extremely fine nanostructures enables greater light collection and more accurate color separation.
<Nanophotonic color router technology that works reliably even under oblique incidence conditions (AI-generated image)>
However, existing Nanophotonic Color Routers had limitations. While they functioned well when light entered vertically, their performance deteriorated significantly—or colors mixed—when light entered at an angle, as is common in smartphone cameras. This issue, known as the “oblique incidence problem,” has been considered a critical challenge that must be resolved for real-world product applications.
The research team first investigated the root cause of this issue. They found that previous designs were overly optimized for vertically incident light, causing performance to drop sharply even with slight changes in the angle of incidence. Since smartphone cameras receive light from various angles, maintaining performance under angular variation is essential.
Instead of manually designing the structure, the team adopted an “inverse design” approach, which allows the computer to autonomously determine the optimal structure. Through this method, they derived a color router design capable of stable color separation even when the angle of incoming light changes.
As a result, whereas previous structures nearly failed when light was tilted by about 12 degrees, the newly designed structure maintained approximately 78% optical efficiency within a ±12-degree range, demonstrating stable color separation performance. In other words, the technology reaches a level suitable for practical smartphone usage environments.
<Nanophotonic color router robust to oblique incidence>
The team further analyzed performance variations by considering factors such as the number of metamaterial layers, design conditions, and potential fabrication errors. They also systematically defined the limits of robustness against changes in the angle of incidence. This study is particularly meaningful in that it presents design criteria for color routers that reflect realistic image sensor environments.
Professor Min Seok Jang of KAIST stated, “This research is significant in that it systematically analyzes the oblique incidence problem, which has hindered the commercialization of color router technology, and proposes a clear solution direction,” adding, “The proposed design methodology can be extended beyond color routers to a wide range of metamaterial-based nanophotonic devices.”
In this study, KAIST undergraduate student Jaehyun Jeon and doctoral candidate Chanhyung Park participated as co-first authors. The research findings were published on January 27 in the international journal Advanced Optical Materials.
※ Paper title: “Inverse Design of Nanophotonic Color Router Robust to Oblique Incidence”
DOI: https://doi.org/10.1002/adom.202501697※ Authors: Jaehyun Jeon (KAIST, first author), Chanhyung Park (KAIST, first author), Doyoung Heo (KAIST), Haejun Chung (Hanyang University), Min Seok Jang (KAIST, corresponding author)
This research was supported by the Ministry of Trade, Industry & Energy (Korea Institute for Advancement of Technology, Korea Semiconductor Research Consortium) under the project “Design Technology of Meta-Optical Structures for Next-Generation Sensors,” by the Ministry of Science and ICT (National Research Foundation of Korea) under the projects “Development of Full-Color Micro LED Devices and Panels Based on Beam-Steerable High-Color-Purity Meta Color Conversion Layers” and “Development of a Real-Time Zero-Energy Argos-Eye Metasurface Network Computing with All Properties of Light,” and by the Ministry of Culture, Sports and Tourism (Korea Creative Content Agency) under the project “International Joint Research for Next-Generation Copyright Protection and Secure Content Distribution Technologies.”
2026.02.19 View 730 -
KAIST Uses Sandpaper to Polish Semiconductors… Opening a New Path for AI Semiconductor Processing
<(From Left) Dr. Sukkyung Kang, Professor Sanha Kim from Department of Mechanical Engineering>
The performance and stability of smartphones and artificial intelligence (AI) services depend on how uniformly and precisely semiconductor surfaces are processed. KAIST researchers have expanded the concept of everyday “sandpaper” into the realm of nanotechnology, developing a new technique capable of processing semiconductor surfaces uniformly down to the atomic level. This technology demonstrates the potential to significantly improve surface quality and processing precision in advanced semiconductor processes such as high-bandwidth memory (HBM).
KAIST (President Kwang Hyung Lee) announced on the 11th of February that a research team led by Professor Sanha Kim of the Department of Mechanical Engineering has developed a “nano sandpaper” that utilizes carbon nanotubes—tens of thousands of times thinner than a human hair—as abrasive materials. This technology enables more precise surface processing than existing semiconductor manufacturing processes, while also reducing environmental burdens generated during fabrication, presenting a new planarization technique.
< Nano Sandpaper AI-Generated Image >
Although sandpaper is a familiar tool used to smooth surfaces by rubbing, it has been difficult to apply it to fields such as semiconductors, where extremely precise surface processing is required. This limitation arises because conventional sandpaper is manufactured by attaching abrasive particles with adhesives, making it difficult to uniformly secure extremely fine particles.
To overcome such limitations, the semiconductor industry has adopted a planarization process known as chemical mechanical polishing (CMP), which uses a chemical slurry in which abrasive particles are dispersed in liquid. However, this method requires additional cleaning steps and generates large amounts of waste, making the process complex and environmentally burdensome.
To address these issues, the research team extended the concept of sandpaper to the nanoscale. By vertically aligning carbon nanotubes, fixing them inside polyurethane, and partially exposing them on the surface, they implemented a “nano sandpaper.” This structure structurally suppresses abrasive detachment, eliminating concerns about surface damage and maintaining stable performance even after repeated use.
The nano sandpaper developed in this study achieves an abrasive density approximately 500,000 times higher than that of the finest commercially available sandpaper. The precision of sandpaper is expressed in terms of “abrasive density (grit number),” which indicates how densely abrasive particles are arranged on the surface. While everyday sandpaper typically ranges from 40 to 3000 grit, the nano sandpaper exceeds 1,000,000,000 grit. Through this extremely dense structure, surfaces could be processed with precision down to several nanometers—equivalent to the thickness of only a few atoms.
The effectiveness of the nano sandpaper was confirmed through experiments. Rough copper surfaces were polished to a smoothness at the nanometer level, and in semiconductor pattern planarization experiments, the technique reduced dishing defects by up to 67% compared with conventional CMP processes. Dishing defects refer to the phenomenon in which the center of interconnect lines becomes recessed, a major defect affecting the performance and reliability of advanced semiconductors such as HBM.
In particular, because the abrasive materials are fixed on the sandpaper surface, the technology does not require continuous supply of slurry solutions as in conventional processes. This reduces cleaning steps and eliminates waste slurry, presenting the possibility of transitioning semiconductor manufacturing toward more environmentally friendly processes.
< Nano Sandpaper Schematic Diagram >
< Detailed Image of Nano Sandpaper >
The research team expects that this technology can be applied to advanced semiconductor planarization processes such as HBM used in AI servers, as well as to hybrid bonding processes, which are gaining attention as next-generation semiconductor interconnection technologies. The study is also significant in that it expands the everyday concept of sandpaper into nano-precision processing technology, suggesting the possibility of securing core technologies required for semiconductor manufacturing.
Professor Sanha Kim stated, “This is an original study demonstrating that the everyday concept of sandpaper can be extended to the nanoscale and applied to ultra-fine semiconductor manufacturing,” adding, “We hope this technology will lead not only to improved semiconductor performance but also to environmentally friendly manufacturing processes.”
In this study, Dr. Sukkyung Kang of the Department of Mechanical Engineering participated as the first author. The research was recognized for its excellence by receiving the Gold Prize (1st place) in the Mechanical Engineering Division at the 31st Samsung Human Tech Paper Award, hosted by Samsung Electronics. The findings were published online on January 8, 2026, in the international journal Advanced Composites and Hybrid Materials (IF 21.8).
※ Paper title: “Carbon nanotube sandpaper for atomic-precision surface finishing”
DOI: https://doi.org/10.1007/s42114-025-01608-3
This research was supported by the National Research Foundation of Korea (Mid-Career Researcher Program; Ministry of Science and ICT, NRF, RS-2025-00560856), the Glocal Lab Program (Ministry of Education, NRF, RS-2025-25406725), the InnoCORE Program (Ministry of Science and ICT, NRF, N10250154), and the KAIST Up Program.
2026.02.11 View 935 -
KAIST Extends Its Deepest Condolences on the Passing of the Late Chairman Chang Sun Jung, Founder of Jungheung Group
KAIST extends its deepest condolences on the passing of the late Chairman Chang Sun Jung, founder of Jungheung Group.
Chairman Jung made significant contributions to the development of Korea’s construction industry and regional economy, and was a visionary leader who deeply recognized and actively supported the importance of nurturing science and technology talent. In particular, through his generous contribution to the KAIST Development Fund, he left a meaningful legacy in fostering future scientific talent and advancing research environments that will shape the nation’s future.
KAIST honors Chairman Jung’s noble spirit of giving and dedication, and will continue to strive to ensure that his vision lives on through the advancement of science and technology in Korea.
We extend our sincere condolences to the bereaved family and to the executives and employees of Jungheung Group, and pray for the eternal rest of the deceased.
2026.02.03 View 500 -
KAIST Proposes a New Dementia Treatment Strategy by Repositioning Molecules without Changing Their Chemical Composition
<(Back row, from left) Professor Mi Hee Lim, Professor Mingeun Kim, Student Jimin Lee, Student Chanju Na, (Upper Right) Dr. Chul-Ho Lee, Dr Kyoung-Shim Kim>
Conventional treatments of Alzheimer’s disease, one of the most common forms of dementia, have been largely focused on targeting individual pathological features. However, Alzheimer’s disease is a multifactorial disorder driven by multiple, tightly interconnected processes, rendering single-target therapeutic approaches inherently limited. Addressing this challenge, KAIST researchers propose a new strategy that enables the simultaneous regulation of multiple disease-inducing factors simply by rearranging the structural positions of drug candidate molecules without altering their chemical substituents.
KAIST (President Kwang Hyung Lee) announced on January 22 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 of the Korea Research Institute of Bioscience and Biotechnology (KRIBB), and Dr. Kyoung-Shim Kim of the Laboratory Animal Resource Center, has elucidated at the molecular level how subtle differences in molecular arrangement, specifically positional isomerism, give rise to distinct modes of action against Alzheimer’s disease.
Using an Alzheimer’s disease mouse model (APP/PS1) harboring human dementia-associated genes, the research team demonstrated that these compounds also exert distinct therapeutic effects in vivo.
Alzheimer’s disease does not arise from a single cause. Rather, multiple pathological factors, including amyloid-b, metal ions, and reactive oxygen species, interact synergistically to exacerbate disease progression. In particular, metal ions bind to amyloid-b, modulating its aggregation and toxicity while promoting the generation of reactive oxygen species, which in turn accelerates neuronal damage. Effective control of Alzheimer’s disease therefore requires therapeutic strategies capable of simultaneously targeting multiple interrelated pathological processes.
< Alzheimer’s Disease – Chemical Approach Illustration (AI-generated image) >
The researchers focused on positional isomers, molecules composed of the same chemical elements but differing only in the positions at which those elements are connected. Remarkably, simple changes in molecular positioning resulted in pronounced differences in reactivity towards reactive oxygen species, as well as in interactions with amyloid-b and metal-bound amyloid-b.
To investigate these effects, the team compared the reactivities of three structurally similar molecules differing only in the positions of their functional groups. Their analyses revealed that even minimal structural rearrangements led to significant differences in antioxidant capacity and produced distinct modes of modulation of amyloid-b and metal-bound amyloid-b through different mechanisms, inducing peptide chemical modifications.
In other words, the study demonstrated that Alzheimer’s disease-related pathological factors can be regulated through mechanistically distinct pathways simply by altering molecular arrangement, without changing molecular composition.
Notably, a specific positional isomer capable of simultaneously modulating reactive oxygen species, amyloid-b, and metal-bound amyloid-b complexes also demonstrated therapeutic efficacy in an Alzheimer’s disease mouse model. In these experiments, the compound reduced oxidative stress in the hippocampus, the brain region critical for memory, and decreased amyloid plaque accumulation, resulting in significant improvements in memory deficits and cognitive impairment.
< In Vivo Efficacy Evaluation and Biological Outcomes According to Positional Isomers of Small-Molecule Compounds >
Professor Mi Hee Lim of KAIST stated, “This study demonstrates that multiple pathological factors associated with Alzheimer’s disease can be targeted simultaneously simply by adjusting molecular positioning, without altering the molecule’s core chemical framework.” She added, “These findings point to a new therapeutic strategy that may enable more precise control of complex, multifactorial diseases such as Alzheimer’s disease.”
This research was conducted with Chanju Na and Jimin Lee, integrated master’s-doctoral students in the Department of Chemistry at KAIST, who served as co-first authors. The results were published in the Journal of the American Chemical Society (Impact Factor: 15.7, top 5.0% in Chemistry) in Issue 1 dated January 14, 2026.
※ Paper title: “Positional Isomerism Tunes Molecular Reactivities and Mechanisms toward Pathological Targets in Dementia”
※ DOI: 10.1021/jacs.5c14323
This study was supported by the National Research Foundation (NRF) of Korea through the Basic Research Program (Creative Research Initiative and Global Science Research Center), the NRF Sejong Science Fellowship, the NRF Ph.D. Followship, and KRIBB Institutional Funding.
2026.01.26 View 819 -
KAIST Directly Visualizes the Hidden Spatial Order of Electrons in a Quantum Material
<(Back row, from left) Yeongkwan Kim, SungBin Lee, Heejun Yang, Yongsoo Yang_(Front row, from left) Jemin Park, Seokjo Hong, Jaewhan Oh>
· Cryogenic 4D-STEM reveals how charge density waves form, fragment, and persist across a phase transition
· First direct measurement of electronic amplitude correlations uncovers strain-driven inhomogeneity and localized order above the transition temperature
Electronic order in quantum materials often emerges not uniformly, but through subtle and complex patterns that vary from place to place. One prominent example is the charge density wave (CDW), an ordered state in which electrons arrange themselves into periodic patterns at low temperatures. Although CDWs have been studied for decades, how their strength and spatial coherence evolve across a phase transition has remained largely inaccessible experimentally.
Now, a team led by Professor Yongsoo Yang of the Department of Physics at KAIST (Korea Advanced Institute of Science and Technology), together with Professors SungBin Lee, Heejun Yang, and Yeongkwan Kim, and in collaboration with Stanford University, has for the first time directly visualized the spatial evolution of charge density wave amplitude order inside a quantum material.
A New Way to See Electronic Order at the Nanoscale
Using a liquid-helium-cooled electron microscope setup combined with four-dimensional scanning transmission electron microscopy (4D-STEM), the researchers mapped how CDW order develops, weakens, and fragments as temperature changes. This approach allowed them to reconstruct nanoscale maps of the CDW amplitude, revealing not just whether the order exists, but how strong it is and how it is spatially connected.
This study is similar to filming the growth of ice crystals as water freezes using an ultra-high-magnification camera. In this case, however, the researchers observed electrons arranging themselves at cryogenic temperatures of around –253°C, and used an electron microscope capable of resolving features one hundred-thousandth the width of a human hair instead of a conventional camera. The results showed that the electronic patterns do not appear uniformly across the material. In some regions, clear patterns are visible, while in neighboring areas they are entirely absent, much like a lake that does not freeze all at once, with patches of ice interspersed with liquid water.
How Electronic Order Breaks Apart in Real Space
The team further demonstrated that this spatial inhomogeneity is closely linked to local strain inside the crystal. Even extremely small distortions that are far below optical resolution strongly suppress the CDW amplitude. This clear anticorrelation between strain and electronic order provides direct evidence that local lattice distortions play a decisive role in shaping CDW patterns.
Unexpectedly, the researchers also observed that localized regions of CDW order can persist even above the transition temperature, where long-range order is generally thought to disappear. These isolated pockets of electronic order suggest that the CDW transition is not a simple, uniform melting process, but instead involves gradual loss of spatial coherence.
A key advance of this work is the world’s first direct measurement of CDW amplitude correlations. By quantifying how the strength of electronic order at one location is related to that at another, the study reveals how CDW coherence collapses across the transition, while local amplitude remains finite. Such information could not be obtained with conventional diffraction or scanning probe techniques.
Toward a New Framework for Studying Electronic Order
Charge density waves are a central feature of many quantum materials and often coexist or compete with other electronic states. By directly accessing their spatial structure and correlations, this study provides a new experimental framework for understanding how collective electronic order forms and evolves in real materials.
Dr. Yongsoo Yang, who led the research, explained the significance of the results: “Until now, the spatial coherence of charge density waves was largely inferred indirectly. Our approach allows us to directly visualize how electronic order varies across space and temperature, and to identify the factors that locally stabilize or suppress it.”
[Figure 1] Schematic illustration of an experiment employing 4D-STEM to probe the spatial variations of charge density waves in the prototypical quantum material NbSe2 under a liquid-helium cryogenic environment (AI-generated image).
This research, with Seokjo Hong, Jaewhan Oh and Jemin Park of KAIST as co-first authors, was published online in Physical Review Letters on January 6th (Title: Spatial correlations of charge density wave order across the transition in 2H-NbSe2).
The study was mainly supported by the National Research Foundation of Korea (NRF) Grants (Individual Basic Research Program, Basic Research Laboratory Program, Nanomaterial Technology Development Program) funded by the Korean Government (MSIT).
2026.01.20 View 888