%44%65%70%61%72%74%6d%65%6e%74%20%6f%66%20%6d%65%63%68%61%6e%69%63%61%6c%20%45%6e%67%69%6e%65%65%72%69%6e%67
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Seeing Black Holes More Clearly with Laser Light
<(From Left) Researcher Junyong Choi, Researcher Woosong Jeong, Professor Jungwon Kim, Researcher Jihoon Baek >
Radio telescopes are instruments that capture faint radio signals from space and convert them into images of celestial bodies. To observe distant black holes clearly, multiple radio telescopes must capture cosmic signals at exactly the same time, acting as a single unit. Research teams at KAIST have developedr a new reference signal technology that uses laser light to precisely synchronize the observation timing and phase of these telescopes.
KAIST announced on January 15th that a research team led by Professor Jungwon Kim from the Department of Mechanical Engineering—in collaboration with the Korea Astronomy and Space Science Institute, the Korea Research Institute of Standards and Science, and the Max Planck Institute for Radio Astronomy (MPIfR) in Germany—has implemented a technology that directly applies optical frequency comb lasers to radio telescope receivers.
While a typical laser emits only one color (frequency), an optical frequency comb laser emits tens of thousands of extremely accurate colors arranged at regular intervals. This appearance resembles the teeth of a comb, hence the name "frequency comb." Since the frequency of each individual "tooth" is known exactly and the intervals can be precision-tuned to the level of an atomic clock, scientists refer to it as an "ultra-precision ruler made of light."
The core of Very Long Baseline Interferometry (VLBI), a technique where multiple radio telescopes observe simultaneously, is aligning the phases of the radio signals received by each telescope as if aligning them to a single precise ruler. However, existing electronic reference signal methods faced limitations; as observation frequencies increased, precise phase calibration is becoming more difficult.
In response, the KAIST research team developed a method to deliver the optical frequency comb laser directly into the radio telescope, based on the idea of "improving the fundamental precision of phase alignment by utilizing light (lasers) from the signal generation stage." Through this, they successfully solved the problems of reference signal generation and phase calibration simultaneously within a single optical system.
If the conventional method was like using a "ruler that makes phase alignment difficult" at higher frequencies, this new technology can be compared to setting a standard with an "ultra-precision ruler that fixes the phase with extremely stable light." As a result, they have laid the foundation for distant radio telescopes to interoperate as elaborately as one giant telescope.
This technology was verified through test observations at the Korea VLBI Network (KVN) Yonsei Radio Telescope. The research team succeeded in detecting stable interference patterns (fringes) between radio telescopes and proved through actual observation that precise phase calibration is possible. Recently, this system was also installed at the KVN SNU Pyeongchang Radio Telescope, leading to expanded experiments using multiple observation sites simultaneously.
The team expects that this will not only allow for clearer imaging of black holes but also drastically reduce phase delay errors between instruments—a long-standing issue in VLBI observations.
The applications of this technology are not limited to astronomical observations. The team anticipates that it can be expanded to various advanced fields requiring precise space-time measurements, such as▲ Intercontinental ultra-precision clock comparison ▲Space geodesy ▲Deep-space probe tracking
< Illustration of the system principle (Image generated by AI) >
Professor Jungwon Kim of KAIST stated, "This research is a case where the limits of existing electronic signal generation technology were overcome by directly applying optical frequency comb lasers to radio telescopes. It will significantly contribute to improving the precision of next-generation black hole observations and advancing the fields of frequency metrology and time standards."
Dr. Minji Hyun (currently at KRISS) and Dr. Changmin Ahn from KAIST participated as co-first authors. The research findings were published on January 4th in the international academic journal Light: Science & Applications.
Paper Title: Optical frequency comb integration in radio telescopes: advancing signal generation and phase calibration
DOI: 10.1038/s41377-025-02056-w
Lead Authors: Dr. Minji Hyun (KAIST, currently KRISS), Dr. Changmin Ahn (KAIST), Jungwon Kim (KAIST)
This research was conducted with support from the National Research Council of Science & Technology (NST) Creative Alliance Project(CAP), the National Research Foundation of Korea (NRF), and the Institute of Information & Communications Technology Planning & Evaluation (IITP).
2026.01.15 View 368 -
KAIST, AI judges manufacturing beyond craftsmanship and language barriers
<(From Left) M.S candidate Inhyo Lee, Ph.D candidate Heekyu Kim, Ph.D candidate joonyoung Kim, Professor Seunghwa Ryu>
Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce identical items. However, even slight changes in conditions can lead to defects, so the process has long relied on the intuition of highly skilled workers. Now, KAIST researchers have proposed an AI-based solution that autonomously optimizes processes and transfers manufacturing knowledge, addressing concerns that expertise could be lost due to the retirement of skilled workers and the increase in foreign labor.
KAIST (President Kwang Hyung Lee) announced on the 22nd of December that a research team led by Professor Seunghwa Ryu from the Department of Mechanical Engineering · InnoCORE PRISM-AI Center has, for the first time in the world, developed generative AI technology that autonomously optimizes injection molding processes, along with an LLM-based knowledge transfer system that makes on-site expertise accessible to anyone. The team also reported that these achievements were published consecutively in an internationally renowned journal.
The first achievement is a generative AI–based process inference technology that automatically infers optimal process conditions based on environmental changes or quality requirements. Previously, whenever temperature, humidity, or desired quality levels changed, skilled workers had to rely on trial and error to readjust conditions.
The research team implemented a diffusion model–based approach that reverse-engineers process conditions satisfying target quality requirements, using environmental data and process parameters collected over several months from an actual injection molding factory.
In addition, the team built a surrogate model that substitutes for actual production, enabling quality prediction without running the real process. As a result, they achieved an error rate of just 1.63%, significantly lower than the 23~44% error rates of representative existing technologies such as GAN* and VAE** models traditionally used for process prediction. Experiments applying the AI-generated conditions to real processes confirmed successful production of acceptable products, demonstrating practical applicability.
*GAN (Generative Adversarial Network): a method in which two AI models compete with each other to generate data
**VAE (Variational Autoencoder): a method that compresses and learns common patterns in data and then reconstructs them
<Figure 1. Generative AI–Based Process Reasoning Technology>
The second achievement is the IM-Chat, an LLM-based knowledge transfer system designed to address skilled worker retirement and multilingual work environments. IM-Chat is a multi-agent AI system that combines large language models (LLMs) with retrieval-augmented generation (RAG), serving as an AI assistant for manufacturing sites by providing appropriate solutions to problems encountered by novice or foreign workers.
When a worker asks a question in natural language, the AI understands it and, if necessary, automatically calls the generative process inference AI, simultaneously providing optimal process condition calculations along with relevant standards and background explanations.
For example, when asked, “What is the appropriate injection pressure when the factory humidity is 43.5%?”, the AI calculates the optimal condition and presents the supporting manual references as well. With support for multilingual interfaces, foreign workers can receive the same level of decision-making support.
This research is regarded as a core manufacturing AI transformation (AX) technology that can be extended beyond injection molding to molds, presses, extrusion, 3D printing, batteries, bio-manufacturing, and other industries.
In particular, the work is significant in that it presents a paradigm for autonomous manufacturing AI, integrating generative AI and LLM agents through a Tool-Calling approach*, enabling AI to make its own judgments and invoke necessary functions.
*Tool-Calling approach: a method in which AI autonomously calls and uses the functions or programs required for a given situation
<Figure 2. Large Language Model–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 3. Example of Operation of the Large Language Model (LLM)–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 4. Illustration of the Application of an LLM-Based Multilingual Knowledge Transfer Multi-Agent IM-Chat (AI-Generated)>
Professor Seunghwa Ryu explained, “This is a case where we addressed fundamental problems in manufacturing in a data-driven way by combining AI that autonomously optimizes processes with LLMs that make on-site knowledge accessible to anyone,” adding, “We will continue expanding this approach to various manufacturing processes to accelerate intelligence and autonomy across the industry.”
This research involved doctoral candidates Junhyeong Lee, Joon-Young Kim, and Heekyu Kim from the Department of Mechanical Engineering as co–first authors, with Professor Seunghwa Ryu as the corresponding author. The results were published consecutively in the April and December issues of Journal of Manufacturing Systems (JCR 1/69, IF 14.2), the world’s top-ranked international journal in engineering and industrial fields.
※ Paper 1: “Development of an Injection Molding Production Condition Inference System Based on Diffusion Model,” DOI: https://doi.org/10.1016/j.jmsy.2025.01.008 ※ Paper 2: “IM-Chat: A multi-agent LLM framework integrating tool-calling and diffusion modeling for knowledge transfer in injection molding industry,” DOI: https://doi.org/10.1016/j.jmsy.2025.11.007
This research was supported by the Ministry of Science and ICT, the Ministry of SMEs and Startups, and the Ministry of Trade, Industry and Energy.
2025.12.22 View 644 -
KAIST, Production Temperature ↓ by 500°C, Power Output ↑ 2x… Next-Generation Ceramic Electrochemical Cell Reborn
<(Top row, from left) Professor Kang Taek Lee, Ph.D candidate Yejin Kang, Dr. Dongyeon Kim, (Bottom row, from left) M.S candidate Mincheol Lee, Ph.D candidate Seeun Oh, Ph.D candidate Seungsoo Jang, Ph.D candidate Hyeonggeun Kim>
As power demand surges in the AI era, the “protonic ceramic electrochemical cell (PCEC),” which can simultaneously produce electricity and hydrogen, is gaining attention as a next-generation energy technology. However, this cell has faced the technical limitation of requiring an ultra-high production temperature of 1,500°C. A KAIST research team has succeeded in establishing a new manufacturing process that lowers this limit by more than 500°C for the first time in the world.
KAIST (President Kwang Hyung Lee) announced on the 4th of December that Professor Kang Taek Lee’s research team in the Department of Mechanical Engineering developed a new process that enables the fabrication of high-performance protonic ceramic electrochemical cells at temperatures more than 500°C lower than before, using “microwave + vapor control technology” that leverages microwave heating principles and the diffusion environment of chemical vapor generated from specific chemical components.
The electrolyte—the key material of protonic ceramic electrochemical cells—contains barium (Ba), and barium easily evaporates at temperatures above 1,500°C, which has been the main cause of performance degradation. Therefore, the ability to harden the ceramic electrolyte at a lower temperature has been the core issue that determines cell performance.
As power demand surges in the AI era, the “protonic ceramic electrochemical cell (PCEC),” which can simultaneously produce electricity and hydrogen, is gaining attention as a next-generation energy technology. However, this cell has faced the technical limitation of requiring an ultra-high production temperature of 1,500°C. A KAIST research team has succeeded in establishing a new manufacturing process that lowers this limit by more than 500°C for the first time in the world.
KAIST (President Kwang Hyung Lee) announced on the 4th of December that Professor Kang Taek Lee’s research team in the Department of Mechanical Engineering developed a new process that enables the fabrication of high-performance protonic ceramic electrochemical cells at temperatures more than 500°C lower than before, using “microwave + vapor control technology” that leverages microwave heating principles and the diffusion environment of chemical vapor generated from specific chemical components.
The electrolyte—the key material of protonic ceramic electrochemical cells—contains barium (Ba), and barium easily evaporates at temperatures above 1,500°C, which has been the main cause of performance degradation. Therefore, the ability to harden the ceramic electrolyte at a lower temperature has been the core issue that determines cell performance.
To solve this, the research team devised a new heat-treatment method called “vapor-phase diffusion.” This technique places a special auxiliary material (a vapor source) next to the cell and irradiates it with microwaves to quickly diffuse vapor. When the temperature reaches approximately 800°C, the vapor released from the auxiliary material moves toward the electrolyte and tightly bonds the ceramic particles. Thanks to this technology, a process that previously required 1,500°C can now be completed at just 980°C. In other words, a world-first ceramic electrochemical cell fabrication technology has been created that produces high-performance electricity at a “low temperature” without damaging the electrolyte.
A cell fabricated with this process produced 2 W of power stably from a 1 cm² cell (roughly the size of a fingernail) at 600°C and generated 205 mL of hydrogen per hour at 600°C (about the volume of a small paper cup, among the highest in the industry). It also maintained stability without performance degradation during 500 hours of continuous operation.
In other words, this technology reduces the production temperature (−500°C), lowers the operating temperature (600°C), doubles performance (2 W/cm²), and extends the lifespan (500-hour stability), achieving world-class performance in ceramic cell technology.
The research team also enhanced the reliability of the technology by using digital twins (virtual simulations) to analyze gas-transport phenomena occurring in the microscopic internal structure of the cell − phenomena that are difficult to observe in actual experiments.
<Figure 1. (a) Schematic of the vapor-diffusion-based process; (b) Surface microstructure of the electrolyte; (c) Internal barium composition ratio of the electrolyte according to processing conditions; (d) Comparison of power-generation performance with previous studies>
< Figure 2. (a) Three-dimensional reconstructed image of the protonic ceramic electrochemical cell fuel electrode according to processing conditions (b) Pore structure (c) Gas-transport simulation results >
Professor Kang Taek Lee emphasized, “This study is the world’s first case of using vapor to lower the heat-treatment temperature by more than 500°C while still producing a high-performance, high-stability cell.” He added, “It is expected to become a key manufacturing technology that addresses the power challenges of the AI era and accelerates the hydrogen society.”
Dongyeon Kim (KAIST PhD) and Yejin Kang (KAIST PhD candidate) participated as co–first authors. The research results were published in Advanced Materials (IF: 26.8), one of the world’s leading journals in energy and materials science, and were selected as the Inside Front Cover article on October 29.
(Paper title: “Sub-1000°C Sintering of Protonic Ceramic Electrochemical Cells via Microwave-Driven Vapor Phase Diffusion,” DOI: https://doi.org/10.1002/adma.202506905)
This research was supported by the MSIT’s Mid-career Researcher Program and the H2 Next Round Program.
2025.12.05 View 1166 -
KAIST Develops Room-Temperature 3D Printing Technology for ‘Electronic Eyes’—Miniaturized Infrared Sensors
<(From Left) Professor Ji Tae Kim of the Department of Mechanical Engineering, Professor Soong Ju Oh of Korea University and Professor Tianshuo Zhao of the University of Hong Kong>
The “electronic eyes” technology that can recognize objects even in darkness has taken a step forward. Infrared sensors, which act as the “seeing” component in devices such as LiDAR for autonomous vehicles, 3D face recognition systems in smartphones, and wearable healthcare devices, are regarded as key components in next-generation electronics. Now, a research team at KAIST and their collaborators have developed the world’s first room-temperature 3D printing technology that can fabricate miniature infrared sensors in any desired shape and size.
KAIST (President Kwang Hyung Lee) announced on the 3rd of November that the research team led by Professor Ji Tae Kim of the Department of Mechanical Engineering, in collaboration with Professor Soong Ju Oh of Korea University and Professor Tianshuo Zhao of the University of Hong Kong, has developed a 3D printing technique capable of fabricating ultra-small infrared sensors—smaller than 10 micrometers (µm)—in customized shapes and sizes at room temperature.
Infrared sensors convert invisible infrared signals into electrical signals and serve as essential components in realizing future electronic technologies such as robotic vision. Accordingly, miniaturization, weight reduction, and flexible form-factor design have become increasingly important.
Conventional semiconductor fabrication processes were well suited for mass production but struggled to adapt flexibly to rapidly changing technological demands. They also required high-temperature processing, which limited material choices and consumed large amounts of energy.
To overcome these challenges, the research team developed an ultra-precise 3D printing process that uses metal, semiconductor, and insulator materials in the form of liquid nanocrystal inks, stacking them layer by layer within a single printing platform.
This method enables direct fabrication of core components of infrared sensors at room temperature, allowing for the realization of customized miniature sensors of various shapes and sizes.
Particularly, the researchers achieved excellent electrical performance without the need for high-temperature annealing by applying a “ligand-exchange” process, where insulating molecules on the surface of nanoparticles are replaced with conductive ones.
As a result, the team successfully fabricated ultra-small infrared sensors measuring less than one-tenth the thickness of a human hair (under 10 µm).
<Figure 1. 3D printing of infrared sensors.a. Room-temperature printing process for the electrodes and photoactive layer that make up the infrared sensor.b. Structure and chemical composition of the printed infrared microsensor. c.Printed infrared sensor micropixel array.>
Professor Ji Tae Kim commented, “The developed 3D printing technology not only advances the miniaturization and lightweight design of infrared sensors but also paves the way for the creation of innovative new form-factor products that were previously unimaginable. Moreover, by reducing the massive energy consumption associated with high-temperature processes, this approach can lower production costs and enable eco-friendly manufacturing—contributing to the sustainable development of the infrared sensor industry.”
The research results were published online in Nature Communications on October 16, 2025, under the title “Ligand-exchange-assisted printing of colloidal nanocrystals to enable all-printed sub-micron optoelectronics” (DOI: https://doi.org/10.1038/s41467-025-64596-4).
This research was supported by the Ministry of Science and ICT of Korea through the Excellent Young Researcher Program (RS−2025−00556379), the National Strategic Technology Material Development Program (RS−2024−00407084), and the International Cooperation Research Program for Original Technology Development (RS−2024−00438059).
2025.11.03 View 2720 -
KAIST Fabricates Green Hydrogen Cells in Just 10 Minutes Like Using a Microwave
<(From Left) Ph.D candidate Hyeongmin Yu, Ph.D candidate Seungsoo Jang, Ph.D candidate Donghun Lee, Ph.D candidate Gayoung Yoon, Professor Kang Taek Lee>
Solid oxide electrolysis cells (SOECs), a key technology for producing green hydrogen without carbon emissions, require a high-temperature “sintering” process to harden ceramic powders. Researchers at KAIST have successfully shortened this process from six hours to just ten minutes, while also reducing the required temperature from 1,400°C to 1,200°C. This innovation dramatically cuts both energy consumption and production time, marking a major step forward for the green hydrogen era.
KAIST (President Kwang Hyung Lee) announced on the 25th of October that a research team led by Professor Kang Taek Lee from the Department of Mechanical Engineering has developed an ultra-fast manufacturing method capable of producing high-performance green hydrogen electrolysis cells in only ten minutes.
The core of this technology lies in sintering—a process in which ceramic powders are baked at high temperatures to form a dense, tightly bonded structure. Proper sintering is critical: it ensures that gases do not leak (as hydrogen and oxygen mixing could cause explosions), oxygen ions move efficiently, and the electrodes adhere firmly to the electrolyte to allow smooth current flow. In short, the precision of the sintering process directly determines the cell’s performance and lifetime.
To address these challenges, the KAIST team applied a “volumetric heating” technique that uses microwaves to heat the material uniformly from the inside out. This approach shortened the sintering process by more than thirtyfold compared to conventional methods. Whereas traditional sintering requires prolonged heating above 1,400°C, the new process uses microwaves to heat the material internally and evenly, achieving stable electrolyte formation at just 1,200°C within 10 minutes.
In conventional fabrication, the essential materials—ceria (CeO₂) and zirconia (ZrO₂)—tend to intermix at excessively high temperatures, degrading material quality. KAIST’s new method allows these two materials to bond firmly at the right temperature without mixing, producing a dense, defect-free bilayer electrolyte.
The total “processing time” includes heating, holding, and cooling. The conventional sintering process required about 36.5 hours, whereas KAIST’s microwave-based technique completes the entire cycle in only 70 minutes—over 30 times faster.
<Figure 1. (a) Schematic illustration of the microwave-based ultrafast sintering process and the conventional sintering process (b) Cross-sectional SEM images of the bilayer ceramic electrolyte according to the sintering process>
The resulting electrochemical cells demonstrated remarkable performance: they produced 23.7 mL of hydrogen per minute at 750°C, maintained stable operation for over 250 hours, and exhibited excellent durability. Using 3D digital twin simulations, the team further revealed that ultra-fast microwave heating improves electrolyte density and suppresses abnormal grain growth of nickel oxide (NiO) particles within the fuel electrode, thereby enhancing hydrogen production efficiency.
<Figure 2. 3D reconstruction, contact area, and electrochemically active site images of the solid oxide electrochemical cell according to the sintering process>
Professor Kang Taek Lee stated, “This research introduces a new manufacturing paradigm that enables the rapid and efficient production of high-performance solid oxide electrolysis cells.” He added, “Compared to conventional processes, our approach drastically reduces both energy consumption and production time, offering strong potential for commercialization.”
This study was co-first-authored by Hyeongmin Yu and Seungsoo Jang, both Ph.D. candidates in Mechanical Engineering at KAIST, with Donghun Lee and Gayoung Youn as collaborators. The research was published online on October 2 in Advanced Materials (Impact Factor: 26.8) and was selected as the Inside Front Cover feature paper for its scientific significance.
※ Paper title: “Ultra-Fast Microwave-Assisted Volumetric Heating Engineered Defect-Free Ceria/Zirconia Bilayer Electrolytes for Solid Oxide Electrochemical Cells”, DOI: 10.1002/adma.202500183)
This work was supported by the Ministry of Science and ICT through the H2 Next Round Program, the Mid-Career Researcher Program, and the Global Research Laboratory (GRL) Program.
2025.10.29 View 1392 -
3D Printing Becomes Stronger and More Economical with Light and AI
<(Front) Ph.D. candidate Jisoo Nam, (Back row, from left) Ph.D. candidate Boxin Chen, Professor Miso Kim>
Photocurable 3D printing, widely used for everything from dental treatments to complex prototype manufacturing, is fast and precise but has the limitation of being fragile and easily broken by impact. A KAIST research team has developed a new technology to overcome this weakness, paving the way for the more robust and economical production of everything from medical implants to precision machine parts.
KAIST (President Kwang Hyung Lee) announced on the 29th that Professor Miso Kim's research team in the Department of Mechanical Engineering has developed a new technology that fundamentally resolves the durability limitations of photocurable 3D printing.
Digital Light Processing (DLP)-based 3D printing is a technique that uses light to solidify liquid resin (polymer) to rapidly manufacture precise structures, used in various fields such as dentistry and precision machinery. While traditional injection molding offers excellent durability, it requires significant time and cost for mold fabrication. In contrast, photocurable 3D printing allows for flexible shape realization but has a durability drawback.
Professor Kim's team solved this problem by combining two key elements:
A new photocurable resin material that absorbs shock and vibration while allowing for a wide range of properties from rubber to plastic.
A machine learning-based design technology that automatically assigns optimal strength to each part of the structure.
<Figure 1. Schematic of a new manufacturing technology for high-durability photocurable 3D printing using light-controlled gradient structures. This approach integrates the development of stiffness-controllable viscoelastic polyurethane acrylate (PUA) materials, machine learning-based property gradient optimization, and grayscale DLP 3D printing. The technology enhances damping performance and alleviates stress concentration, providing an integrated solution for high reliability, durability, and customized manufacturing. It demonstrates potential applications in structural components subjected to repetitive loads such as joints, automotive interior parts, and precision machinery components>
The research team developed a Polyurethane Acrylate (PUA) material incorporating dynamic bonds, which significantly increases shock and vibration absorption capability compared to existing materials. Furthermore, they successfully applied 'grayscale DLP' technology, which controls the light intensity to achieve different strengths from a single resin composition, thereby assigning customized strength to specific areas within the structure. This concept is inspired by the harmonious and different roles played by bone and cartilage in the human body.
A machine learning algorithm automatically proposes the optimal strength distribution by analyzing the structure and load conditions. This organically connects material development and structural design, enabling customized strength distribution.
The economic efficiency is also noteworthy. Previously, expensive 'multi-material printing' technology was required to achieve diverse material properties, but this new technology yields the same effect with a single material and a single process, significantly reducing production costs. It eliminates the need for complex equipment or material management, and the AI-based structural optimization shortens research and development time and product design costs.
Professor Miso Kim explained, "This technology simultaneously expands the degrees of freedom in material properties and structural design. Patient-specific implants will become more durable and comfortable, and precision machine parts can be manufactured more robustly." She added, "The fact that it secures economic viability by realizing various strengths with a single material and single process is highly significant," and "We anticipate its utilization across various industrial fields such as biomedical, aerospace, and robotics."
The research was spearheaded by Professor Miso Kim's team at the KAIST Department of Mechanical Engineering, with Ph.D. candidate Jisoo Nam as the first author. Boxin Chen, a student from Sungkyunkwan University, also contributed to the collaborative research. The findings were published online on July 16 in the world-renowned journal in materials science, Advanced Materials (IF 26.8). Recognizing the research's excellence, it was also selected for the journal's Frontispiece.
Paper Title: Machine Learning-Driven Grayscale Digital Light Processing for Mechanically Robust 3D-Printed Gradient Materials
DOI: 10.1002/adma.202504075
The achievements of this research have brought Professor Miso Kim significant international attention, as she simultaneously received the 'Wiley Rising Star Award' and the 'Wiley Women in Materials Science Award' in July 2025, hosted by the international academic publisher Wiley.
The Wiley Rising Star Award is given to emerging researchers with the potential for academic leadership, and the Wiley Women in Materials Science Award is a prestigious honor established to celebrate outstanding female scientists in the field of materials science.
<Figure 2. Frontispiece image (scheduled for Issue 42). Multi-property structure fabricated using a photocurable 3D printer. By varying the projector light intensity by location, stronger light creates rigid regions while weaker light forms flexible ones. AI designs an optimized pattern for the structural shape to prevent fracture and reinforce the overall strength.>
This research was supported by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (Nos. NRF-2021R1A2C2095767, RS-2023-00254689, and RS-2024-00433654).
2025.09.30 View 1979 -
KAIST to Foster a 'Robot Valley' in Daejeon with $10 Million Initiative
<Group Photo of Kick-off Meeting>
On September 3, KAIST announced the official launch of the "2025 Deep Tech Scale-up Valley Nurturing Project" with a kick-off meeting at the KAIST Department of Mechanical Engineering.
KAIST was selected for this project by the Ministry of Science and ICT and the Research and Development Special District Foundation. With this selection, the university plans to create a "Robot Valley".
Over the next three and a half years, KAIST will receive a total of 13.65 billion won (approximately $10 million) in funding. The university's goal is to intensively nurture globally competitive, innovative robotics companies based on foundational technologies and to develop Daejeon into a global hub for the robotics industry.
The initiative will leverage Daejeon's exceptional research talent and its startup and investment ecosystem to create a model for regional revitalization and to cultivate the robotics industry as a next-generation strategic sector.
KAIST's vision for this project is to develop "Human-Friendly Robots (HFR)" that are more than just automated machines; they are collaborative partners that share space, roles, and emotions with people.
The project will implement a multi-stage strategy that includes promoting the commercialization of robotics technology, supporting the startup ecosystem, securing global technological competitiveness, and developing robot commercialization platforms. This will establish a virtuous cycle of technology development, startup and investment growth, and reinvestment.
Unlike traditional startup support and scale-up programs, this project aims for the simultaneous growth of the entire robotics industry, not just individual companies. A key element is an open innovation model where leading robotics firms like Angel Robotics Inc. and EuRoBotics Inc. (led by Professor Byung-ho Yu and Professor Hyun Myung) will share common core technologies related to actuators, circuits, AI, and standardized data. This will allow startups to focus on developing robot products that directly meet customer needs.
The project team includes key KAIST robotics researchers. The project leader is Professor Jung Kim (President of the Korea Robotics Society) from the Department of Mechanical Engineering. Other participating professors include Geon-Jae Lee from the Department of Materials Science and Engineering (human augmentation sensors), Hyun Myung from the School of Electrical Engineering (winner of the QRC 2023 quadruped robot autonomous walking competition at IEEE ICRA), Kyung-Chul Kong from the Department of Mechanical Engineering (two-time champion of the Cybathlon International Competition and founder of Angel Robotics), and Suk-Hyung Bae from the Department of Industrial Design (winner of the ACM SIGGRAPH robot sketching competition).
In addition, the KAIST Technology Commercialization Office, KAIST Holdings, Global Techno Valley Lab (GTLAB), and the Daejeon Center for Creative Economy and Innovation will manage technology commercialization and valley construction. The Daejeon Technopark will also participate to provide comprehensive commercialization support.
"The strategic cooperation between Daejeon City's robotics industry nurturing plan and KAIST was the driving force behind the selection for this project," said Geon-Jae Lee, Director of the KAIST Technology Commercialization Office. "We will create a robotics innovation ecosystem based in Daejeon and systematically foster global companies to rival the likes of ABB in Switzerland and KUKA in Germany, which are considered among the top three robotics companies in the world."
< Kick-off Meeting Scene>
Project leader Jung Kim stated, "We will spearhead efforts to discover and nurture over 15 future unicorn companies by promoting the commercialization of deep-tech robotics developed at KAIST. The entire KAIST robotics research team will dedicate its full efforts to ensure that our research and development achievements lead to real-world industries and startups."
KAIST President Kwang-Hyung Lee emphasized, "As Korea's leading research-oriented university, KAIST will actively support Daejeon's growth into a global robotics hub. This project is more than just research and development; it will be a turning point for KAIST to stand at the center of the global robotics ecosystem and create a new growth engine for the region and the nation."
In collaboration with Daejeon City, KAIST plans to form an "HFR Valley Innovation Council" to share and review project outcomes, ultimately building a self-sustaining ecosystem. This initiative aims to establish Daejeon as a world-class robotics industry hub.
2025.09.03 View 3075 -
Approaches to Human-Robot Interaction Using Biosignals
<(From left) Dr. Hwa-young Jeong, Professor Kyung-seo Park, Dr. Yoon-tae Jeong, Dr. Ji-hoon Seo, Professor Min-kyu Je, Professor Jung Kim >
A joint research team led by Professor Jung Kim of KAIST Department of Mechanical Engineering and Professor Min-kyu Je of the Department of Electrical and Electronic Engineering recently published a review paper on the latest trends and advancements in intuitive Human-Robot Interaction (HRI) using bio-potential and bio-impedance in the internationally renowned academic journal 'Nature Reviews Electrical Engineering'.
This review paper is the result of a collaborative effort by Dr. Kyung-seo Park (DGIST, co-first author), Dr. Hwa-young Jeong (EPFL, co-first author), Dr. Yoon-tae Jeong (IMEC), and Dr. Ji-hoon Seo (UCSD), all doctoral graduates from the two laboratories. Nature Reviews Electrical Engineering is a review specialized journal in the field of electrical, electronic, and artificial intelligence technology, newly launched by Nature Publishing Group last year. It is known to invite world-renowned scholars in the field through strict selection criteria. Professor Jung Kim's research team's paper, titled "Using bio-potential and bio-impedance for intuitive human-robot interaction," was published on July 18, 2025. (DOI: https://doi.org/10.1038/s44287-025-00191-5)
This review paper explains how biosignals can be used to quickly and accurately detect movement intentions and introduces advancements in movement prediction technology based on neural signals and muscle activity. It also focuses on the crucial role of integrated circuits (ICs) in maximizing low-noise performance and energy efficiency in biosignal sensing, covering thelatest development trends in low-noise, low-power designs for accurately measuring bio-potential and impedance signals.
The review emphasizes the importance of hybrid and multi-modal sensing approaches, presenting the possibility of building robust, intuitive, and scalable HRI systems. The research team stressed that collaboration between sensor and IC design fields is essential for the practical application of biosignal-based HRI systems and stated that interdisciplinary collaboration will play a significant role in the development of next-generation HRI technology. Dr. Hwa-young Jeong, a co-first author of the paper, presented the potential of bio-potential and impedance signals to make human-robot interaction more intuitive and efficient, predicting that it will make significant contributions to the development of HRI technologies such as rehabilitation robots and robotic prostheses using biosignals in the future. This research was supported by several research projects, including the Human Plus Project of the National Research Foundation of Korea.
2025.07.24 View 4063 -
KAIST Develops Customized Tactile Sensor That Can Detect Light Breath, Pressure and Sound
< Photo 1. (From left) Professor Inkyu Park of KAIST Department of Mechanical Engineering (ME), Dr. Jungrak Choi of ETRI, Ph.D. Candidate Donho Lee and M.S. Graduate Chankyu Han of KAIST ME >
When a robot grabs an object or a medical device detects a pulse, the tactile sensor is the technology that senses pressure like a fingertip. Existing sensors had disadvantages, such as slow responses or declining accuracy after repeated use, but Korean researchers have succeeded in developing a sensor that can quickly and accurately detect even light breath, pressure, and sound. This sensor can be used across a broad range — from everyday movements to medical diagnostics.
KAIST (represented by President Kwang Hyung Lee) announced on the 23rd of June that Professor Inkyu Park’s team from the Department of Mechanical Engineering, through a collaborative research project with the Electronics and Telecommunications Research Institute (ETRI, President Seung Chan Bang ) under the National Research Council of Science & Technology (NST, Chairman Young Sik Kim), has developed an innovative technology that overcomes the structural limitations of existing tactile sensors.
The core of this joint research is the implementation of a customized tactile sensor that simultaneously achieves flexibility, precision, and repeatable durability by applying Thermoformed 3D Electronics (T3DE).
< Figure 1. Comparative evaluation of soft elastomer–based 3D structure versus thermoforming-based 3D structure in terms of mechanical properties. >
In particular, soft elastomer-based sensors (rubber, silicone, etc. — materials that stretch and return to their original shape) have structural problems such as slow response times, high hysteresis*, and creep**, but this new platform operates precisely in diverse environments and overcomes these limitations.
*Hysteresis: A phenomenon where the previously applied force or change is retained like a “memory,” so that the same stimulus does not always produce the same result.
**Creep: The phenomenon where a material slowly deforms when a force is continuously applied.
T3DE sensors are manufactured by precisely forming electrodes on a 2D film, then thermoforming them into a 3D structure under heat and pressure. Specifically, the top electrodes and supporting pillar structures of the sensor are designed to allow the fine-tuning of the mechanical properties for different purposes. By adjusting microstructural parameters — such as the thickness, length, and number of support pillars — the sensor’s Young’s modulus* can be tuned across a broad range of 10 Pa to 1 MPa. This matches the stiffness of biological tissues like skin, muscle, and tendons, making them highly suitable as bio-interface sensors.
*Young’s modulus: An index representing a material's stiffness; this research can control this index to match various biological tissues.
The newly developed T3DE sensor uses air as a dielectric material to reduce power consumption and demonstrates outstanding performance in sensitivity, response time, thermal stability, and repeatable accuracy.
Experimental results showed that the sensor achieved △sensitivity of 5,884 kPa⁻¹, △response time of 0.1 ms (less than one-thousandth of a second), △hysteresis of less than 0.5%, and maintained a repeatable precision of 99.9% or higher even after 5,000 repeated measurements.
< Figure 2. Graphic Overview of thermoformed 3D electronics (T3DE) >
The research team also constructed a high-resolution 40×70 array, comprising a total of 2,800 densely packed sensors, to visualize the pressure distribution on the sole of the foot in real time during exercise and confirmed the possibility of using the sensor for wrist pulse measurement to assess vascular health. Furthermore, successful results were also achieved in sound-detection experiments at a level comparable to commercial acoustic sensors. In short, the sensor can precisely and quickly measure foot pressure, pulse, and sound, allowing it to be applied in areas such as sports, health, and sound sensing.
The T3DE technology was also applied to an augmented-reality(AR)-based surgical training system. By adjusting the stiffness of each sensor element to match that of biological tissues, the system provided real-time visual and tactile feedback according to the pressure applied during surgical incisions. It also offered real-time warnings if an incision was too deep or approached a risky area, making it a promising technology for enhancing immersion and accuracy in medical training.
KAIST Professor Inkyu Park stated, “Because this sensor can be precisely tuned from the design stage and operates reliably across diverse environments, it can be used not only in everyday life, but also in a variety of fields such as healthcare, rehabilitation, and virtual reality.”
The research was co-led as first authors by Dr. Jungrak Choi of ETRI, KAIST master’s student Chankyu Han, and Ph.D. candidate Donho Lee, under the overall guidance of Professor Inkyu Park. The research results were published in the May 2025 issue of ‘Science Advances’ and introduced to the global research community through the journal’s official SNS channels (Facebook, Twitter).
※ Thesis Title: Thermoforming 2D films into 3D electronics for high-performance, customizable tactile sensing
※ DOI: 10.1126/sciadv.adv0057
< Figure 3. The introduction of the study on the official SNS posting by Science Advances >
This research was supported by the Ministry of Trade, Industry and Energy, the National Research Foundation of Korea, and the Korea Institute for Advancement of Technology.
2025.06.23 View 6152 -
RAIBO Runs over Walls with Feline Agility... Ready for Effortless Search over Mountaineous and Rough Terrains
< Photo 1. Research Team Photo (Professor Jemin Hwangbo, second from right in the front row) >
KAIST's quadrupedal robot, RAIBO, can now move at high speed across discontinuous and complex terrains such as stairs, gaps, walls, and debris. It has demonstrated its ability to run on vertical walls, leap over 1.3-meter-wide gaps, sprint at approximately 14.4 km/h over stepping stones, and move quickly and nimbly on terrain combining 30° slopes, stairs, and stepping stones. RAIBO is expected to be deployed soon for practical missions such as disaster site exploration and mountain searches.
Professor Jemin Hwangbo's research team in the Department of Mechanical Engineering at our university announced on June 3rd that they have developed a quadrupedal robot navigation framework capable of high-speed locomotion at 14.4 km/h (4m/s) even on discontinuous and complex terrains such as walls, stairs, and stepping stones.
The research team developed a quadrupedal navigation system that enables the robot to reach its target destination quickly and safely in complex and discontinuous terrain.
To achieve this, they approached the problem by breaking it down into two stages: first, developing a planner for planning foothold positions, and second, developing a tracker to accurately follow the planned foothold positions.
First, the planner module quickly searches for physically feasible foothold positions using a sampling-based optimization method with neural network-based heuristics and verifies the optimal path through simulation rollouts.
While existing methods considered various factors such as contact timing and robot posture in addition to foothold positions, this research significantly reduced computational complexity by setting only foothold positions as the search space. Furthermore, inspired by the walking method of cats, the introduction of a structure where the hind feet step on the same spots as the front feet further significantly reduced computational complexity.
< Figure 1. High-speed navigation across various discontinuous terrains >
Second, the tracker module is trained to accurately step on planned positions, and tracking training is conducted through a generative model that competes in environments of appropriate difficulty.
The tracker is trained through reinforcement learning to accurately step on planned plots, and during this process, a generative model called the 'map generator' provides the target distribution.
This generative model is trained simultaneously and adversarially with the tracker to allow the tracker to progressively adapt to more challenging difficulties. Subsequently, a sampling-based planner was designed to generate feasible foothold plans that can reflect the characteristics and performance of the trained tracker.
This hierarchical structure showed superior performance in both planning speed and stability compared to existing techniques, and experiments proved its high-speed locomotion capabilities across various obstacles and discontinuous terrains, as well as its general applicability to unseen terrains.
Professor Jemin Hwangbo stated, "We approached the problem of high-speed navigation in discontinuous terrain, which previously required a significantly large amount of computation, from the simple perspective of how to select the footprint positions. Inspired by the placements of cat's paw, allowing the hind feet to step where the front feet stepped drastically reduced computation. We expect this to significantly expand the range of discontinuous terrain that walking robots can overcome and enable them to traverse it at high speeds, contributing to the robot's ability to perform practical missions such as disaster site exploration and mountain searches."
This research achievement was published in the May 2025 issue of the international journal Science Robotics.
Paper Title: High-speed control and navigation for quadrupedal robots on complex and discrete terrain, (https://www.science.org/doi/10.1126/scirobotics.ads6192)YouTube Link: https://youtu.be/EZbM594T3c4?si=kfxLF2XnVUvYVIyk
2025.06.04 View 9549 -
KAIST, Galaxy Corporation Hold Signboard Ceremony for ‘AI Entertech Research Center’
KAIST (President Kwang-Hyung Lee) announced on the 9th that it will hold a signboard ceremony for the establishment of the ‘AI Entertech Research Center’ with the artificial intelligence entertech company, Galaxy Corporation (CEO Yong-ho Choi) at the main campus of KAIST.
< (Galaxy Corporation, from center to the left) CEO Yongho Choi, Director Hyunjung Kim and related persons / (KAIST, from center to the right) Professor SeungSeob Lee of the Department of Mechanical Engineering, Provost and Executive Vice President Gyun Min Lee, Dean Jung Kim of the Department of Mechanical Engineering and Professor Yong Jin Yoon of the same department >
This collaboration is a part of KAIST’s art convergence research strategy and is an extension of its efforts to lead future K-Culture through the development of creative cultural content based on science and technology. Beyond simple technological development, KAIST has been continuously implementing the convergence model of ‘Tech-Art’ that expands the horizon of the content industry through the fusion of emotional technology and cultural imagination.
Previously, KAIST established the ‘Sumi Jo Performing Arts Research Center’ in collaboration with world-renowned soprano Sumi Jo, a visiting professor, and has been leading the convergence research of art and engineering, such as AI-based interactive performance technology and immersive content. The establishment of the ‘AI Entertech Research Center’ this time is being evaluated as a new challenge for the technological expansion of the K-content industry.
In addition, the role of singer G-Dragon (real name Kwon Ji-yong), an artist affiliated with Galaxy Corporation and a visiting professor in the Department of Mechanical Engineering at KAIST, was also a major factor. Since being appointed to KAIST last year, Professor Kwon has been actively promoting the establishment of a research center and soliciting KAIST research projects through his agency to develop the ‘AI Entertech’ field, which fuses entertainment and cutting-edge technology.
< (Galaxy Corporation, from center to the left) CEO Yongho Choi, Director Hyunjung Kim and related persons / (KAIST, from center to the right) Professor SeungSeob Lee of the Department of Mechanical Engineering, Provost and Executive Vice President Gyun Min Lee, Dean Jung Kim of the Department of Mechanical Engineering and Professor Yong Jin Yoon of the same department >
The AI Entertech Research Center is scheduled to officially launch in the third quarter of this year, and this inauguration ceremony was held in line with Professor Kwon Ji-yong’s schedule to visit KAIST. Galaxy Corporation recently had a private meeting with Microsoft (MS) CEO Nadella as the only entertech company, and is actively promoting the globalization of AI entertech. In addition, since last year, it has established a cooperative relationship with KAIST and plans to actively seek the convergence of entertech and technology that transcends time and space through the establishment of a research center.
Professor Kwon Ji-yong will attend the ‘Innovate Korea 2025’ event co-hosted by KAIST, Herald Media Group, and the National Research Council of Science and Technology, held at the KAIST Lyu Keun-Chul Sports Complex in the afternoon of the same day, and will give a special talk on the topic of ‘The Future of AI Entertech.’ In addition to Professor Kwon, Professor SeungSeob Lee of the Department of Mechanical Engineering at KAIST, Professor Sang-gyun Kim of Kyunghee University, and CEO Yong-ho Choi of Galaxy Corporation will also participate in this talk show.
The two organizations signed an MOU last year to jointly research science and technology for the global spread of K-pop, and the establishment of this research center is the first tangible result of this. Once the research center is fully operational, various projects such as the development of an AI-based entertech platform and joint research on global content technology will be promoted.
< A photo of Professor Kwon Ji-yong (right) from at the talk show with KAIST President Kwang-Hyung Lee (left) from the previous year >
Yong-ho Choi, Galaxy Corporation CHO (Chief Happiness Officer), said, “This collaboration is the starting point for providing a completely new entertainment experience to fans around the world by grafting KAIST AI and cutting-edge technologies onto the fandom platform,” and added, “The convergence of AI and entertech is not just technological advancement; it is a driving force for innovation that enriches human life.”
Kwang-Hyung Lee, KAIST President, said, “I am confident that KAIST’s scientific and technological capabilities, combined with Professor Kwon Ji-yong’s global sensibility, will lead the technological evolution of K-culture,” and added, “I hope that KAIST’s spirit of challenge and research DNA will create a new wave in the entertech market.”
Meanwhile, Galaxy Corporation, the agency of Professor G-Dragon Kwon Ji-yong, is an AI entertainment technology company that presents a new paradigm based on IP, media, tech, and entertainment convergence technology. (End)
2025.04.09 View 9775 -
KAIST Research Team Develops an AI Framework Capable of Overcoming the Strength-Ductility Dilemma in Additive-manufactured Titanium Alloys
<(From Left) Ph.D. Student Jaejung Park and Professor Seungchul Lee of KAIST Department of Mechanical Engineering and , Professor Hyoung Seop Kim of POSTECH, and M.S.–Ph.D. Integrated Program Student Jeong Ah Lee of POSTECH. >
The KAIST research team led by Professor Seungchul Lee from Department of Mechanical Engineering, in collaboration with Professor Hyoung Seop Kim’s team at POSTECH, successfully overcame the strength–ductility dilemma of Ti 6Al 4V alloy using artificial intelligence, enabling the production of high strength, high ductility metal products. The AI developed by the team accurately predicts mechanical properties based on various 3D printing process parameters while also providing uncertainty information, and it uses both to recommend process parameters that hold high promise for 3D printing.
Among various 3D printing technologies, laser powder bed fusion is an innovative method for manufacturing Ti-6Al-4V alloy, renowned for its high strength and bio-compatibility. However, this alloy made via 3D printing has traditionally faced challenges in simultaneously achieving high strength and high ductility. Although there have been attempts to address this issue by adjusting both the printing process parameters and heat treatment conditions, the vast number of possible combinations made it difficult to explore them all through experiments and simulations alone.
The active learning framework developed by the team quickly explores a wide range of 3D printing process parameters and heat treatment conditions to recommend those expected to improve both strength and ductility of the alloy. These recommendations are based on the AI model’s predictions of ultimate tensile strength and total elongation along with associated uncertainty information for each set of process parameters and heat treatment conditions. The recommended conditions are then validated by performing 3D printing and tensile tests to obtain the true mechanical property values. These new data are incorporated into further AI model training, and through iterative exploration, the optimal process parameters and heat treatment conditions for producing high-performance alloys were determined in only five iterations. With these optimized conditions, the 3D printed Ti-6Al-4V alloy achieved an ultimate tensile strength of 1190 MPa and a total elongation of 16.5%, successfully overcoming the strength–ductility dilemma.
Professor Seungchul Lee commented, “In this study, by optimizing the 3D printing process parameters and heat treatment conditions, we were able to develop a high-strength, high-ductility Ti-6Al-4V alloy with minimal experimentation trials. Compared to previous studies, we produced an alloy with a similar ultimate tensile strength but higher total elongation, as well as that with a similar elongation but greater ultimate tensile strength.” He added, “Furthermore, if our approach is applied not only to mechanical properties but also to other properties such as thermal conductivity and thermal expansion, we anticipate that it will enable efficient exploration of 3D printing process parameters and heat treatment conditions.”
This study was published in Nature Communications on January 22 (https://doi.org/10.1038/s41467-025-56267-1), and the research was supported by the National Research Foundation of Korea’s Nano & Material Technology Development Program and the Leading Research Center Program.
2025.02.21 View 11193