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KAIST Develops Liquid Powder That Enables Electronics to Work Just by Drawing a Line
<(From left) Dr. Osman Gul, Distinguished Professor Inkyu Park, Dr. Hye Jin Kim>
What if electronic circuits could be created simply by drawing lines with a pencil on paper or leaves—and then immediately applied to soft robots or skin-attached health monitoring devices? Korean researchers have developed an electronic materials technology that forms electrically conductive liquid metal in a fine powder form, allowing circuits to be drawn directly on a wide variety of surfaces. This technology presents new possibilities for next-generation flexible electronics, including applications on paper and plastic as well as in soft robotic systems and wearable devices.
KAIST (President Kwang Hyung Lee) announced on the 15th of March that a research team led by Distinguished Professor Inkyu Park from the Department of Mechanical Engineering, in collaboration with Dr. Hye Jin Kim’s team at the Electronics and Telecommunications Research Institute (ETRI, President Seungchan Bang), has developed a liquid metal powder–based electronic material technology that allows electronic circuits to be directly drawn on desired surfaces.
The material the researchers focused on is liquid metal, which flows like a liquid yet conducts electricity like a metal. However, conventional liquid metals have very high surface tension and poor wettability on most surfaces, making it difficult to create precise circuits at desired locations. They tend to spread or clump easily, requiring additional surface treatments or processing steps that limit practical applications.
To overcome these limitations, the research team developed a new approach that converts liquid metal into fine powder particles. Each particle consists of liquid metal encapsulated by a thin oxide shell. Under normal conditions, the powder does not conduct electricity. The oxide layer forms naturally when the metal reacts with oxygen in the air, creating a very thin protective film. However, when light mechanical stimulation—such as brushing with a paintbrush or pressing with a finger—is applied, the oxide shell breaks and the metal particles connect with one another, enabling electrical conductivity.
<Demonstration Video>
In other words, the powder can be applied to a surface and only the required areas can be pressed to “activate” the electronic circuit, overcoming the spreading and patterning difficulties associated with conventional liquid metal circuits.
One of the most notable features of this technology is its versatility across locations and materials. Without requiring any thermal processing, circuits can be created instantly on surfaces such as paper, glass, plastic, textiles, and even living plant leaves. The method significantly reduces issues such as spreading, sedimentation, and pattern distortion that were common in conventional liquid metal circuits, enabling stable circuit fabrication on diverse surfaces.
Using this technology, the research team demonstrated practical applications including skin-mounted wireless health monitoring devices and flexible circuits for soft robots that can freely change shape. Because precise circuits can be fabricated on many surfaces without complex equipment, the technology is expected to find applications in next-generation electronic systems such as wearable healthcare devices, soft robotics, and flexible electronics.
The technology also offers advantages in terms of environmental sustainability. After use, the circuits can be dissolved in water and chemically treated (for example with sodium hydroxide, NaOH) to recover the liquid metal. The recovered metal can then be converted back into powder form and reused. This capability makes the technology an environmentally friendly approach that can help reduce electronic waste.
The powder also demonstrates stable performance. According to the research team, the developed powder maintains its functionality even after being stored at room temperature for more than a year and remains electrically intact after tens of thousands of bending or twisting cycles. These characteristics make it suitable for temporary electronic circuits that disappear after use as well as for customizable electronic devices.
<Research Image(AI-generated image)>
Distinguished Professor Inkyu Park stated, “This research enables electronic circuits to be fabricated as intuitively as drawing a picture, while also allowing recycling of the materials,” adding, “We expect it to be applied across various fields, including wearable computers and adaptive IoT systems that can change shape.”
This research was led by Osman Gul, a postdoctoral researcher in the Department of Mechanical Engineering at KAIST, as the first author. The study was published online on December 9, 2025, in the international journal Advanced Functional Materials. The work was also selected as the Back Cover article of the journal in recognition of its significance.
※ Paper title: “Mechanochemically Activatable Liquid Metal Powders for Sustainable, Reconfigurable, and Versatile Electronics”, DOI: https://doi.org/10.1002/adfm.202527396
This research was supported by the Mid-Career Researcher Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT, as well as by a project supported by the Korea Evaluation Institute of Industrial Technology (KEIT).
2026.03.16 View 804 -
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 2398 -
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 2326 -
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 2246 -
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 2612 -
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 4984 -
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 2650 -
Ultra High Speed Optical Measurement Technology Developed
< (From left) Tae Jin Ha, CEO of VIRNECT, Kwang Hyung Lee, President of KAIST >
An open platform for industry-academia-research collaboration, which has accumulated K-Metaverse technology capabilities that break down the boundaries between reality and virtuality and share experiences beyond the limits of time and space, is expected to be built on our university campus.
Our university announced on the 13th that it’s signing an agreement for the establishment and operation of a 'Virtual Convergence Research Center' with the Graduate School of Metaverse and VIRNECT Co., Ltd. (CEO Tae Jin Ha), a domestic augmented/virtual reality (XR) specialized company and a startup founded by a KAIST alumnus.
The Virtual Convergence Research Center, which will be newly constructed on our university campus, plans to prepare for the future participation of related government-funded research institutes, and is expected to function as a national strategic hub that creates future growth engines for the Republic of Korea, going beyond simple industry-academia cooperation. VIRNECT Co., Ltd. plans to create the research center as an open research collaboration platform in which domestic and international industry, academia, and research institutes jointly participate with KAIST.
This research center is expected to experiment with the convergence of reality and virtuality and establish itself as a global hub for the 'K-Metaverse Innovation Ecosystem' where technology development, talent cultivation, and industrial diffusion are in a virtuous cycle.
VIRNECT Co., Ltd. was founded by KAIST alumnus Tae Jin Ha, listed on KOSDAQ in 2023, and won the CES Innovation Award for developing the industrial AI smart goggles 'VisionX'. It has grown into a representative domestic spatial computing company based on various industrial innovation technologies such as AI/XR solutions and digital twin. Synergistic co-prosperity with KAIST is anticipated through this collaboration.
Spatial computing and XR technology are areas where global big techs like Apple, Meta, Google, Microsoft, and Samsung are engaged in fierce competition for dominance, paying attention to them as the next-generation AI platforms. With major countries such as the US and China investing enormous capital and capabilities, the launch of the KAIST Virtual Convergence Research Center is evaluated as a strategic response for South Korea not to fall behind in the competition of the post-metaverse era.
The research center plans to lead both industrial productivity and social innovation as an R&BD (Research & Business Development) hub that integrates core technologies such as digital twin, metaverse, spatial/physical intelligence, and wearable XR. Furthermore, it will quickly verify the applicability to industrial sites and support the creation of new industries through a full-cycle system covering education, research, demonstration, commercialization, and diffusion.
Moreover, the research center will create national synergy by being closely linked with government policies. Strengthening the link between education and research, fostering a sustainable metaverse ecosystem, and expanding global leadership through an open industry-academia-research platform align with the government's strategy for advancing the virtual convergence industry.
< Executives from both organizations attending the signing ceremony >
VIRNECT CEO Tae Jin Ha said, "The long-term cooperation with KAIST is a stepping stone for us to leap forward as a game-changer in the global XR industry," adding, "We will strengthen virtual convergence technology competitiveness through research and education infrastructure and accelerate commercialization through demonstration."
Professor Woontack Woo, Dean of the Graduate School of Metaverse, emphasized, "The Virtual Convergence Research Center will serve as an open platform where industry, academia, and research institutes jointly experiment with K-Metaverse innovation, and a 'Meta Power Plant' that cultivates future core personnel and disseminates research results to the industry."
KAIST President Kwang Hyung Lee said, "This agreement is a strategic investment to secure global leadership by breaking down the boundaries between research and industry, going beyond simply creating a new research center," and "KAIST will spare no support for the research center."
With the future designation of the KAIST Virtual Convergence Research Center as a government-specialized graduate school/research center for the virtual convergence industry and increased industry cooperation, it will establish itself as a national innovation platform that concentrates South Korea's metaverse capabilities. This is expected to lead to the creation of new value for the future society and the strengthening of national competitiveness, going beyond simple technology development.
2025.10.13 View 2323 -
Physics Informed AI Excels at Large Scale Discovery of New Materials!
<(From left) Ph.D candidates Songho Lee, Donggeun Park, and Hyeonbin Moon, and Professor Seunghwa Ryu from the Department of Mechanical Engineering; (top) Professor Jae Hyuk Lim from Kyung Hee University and Dr. Wabi Demeke from KAIST>
One of the key steps in developing new materials is “property identification,” which has long relied on massive amounts of experimental data and expensive equipment, limiting research efficiency. A KAIST research team has introduced a new technique that combines “physical laws,” which govern deformation and interaction of materials and energy, with artificial intelligence. This approach allows for rapid exploration of new materials even under data-scarce conditions and provides a foundation for accelerating design and verification across multiple engineering fields, including materials, mechanics, energy, and electronics.
KAIST (President Kwang Hyung Lee) announced on the 2nd of October that Professor Seunghwa Ryu’s research group in the Department of Mechanical Engineering, in collaboration with Professor Jae Hyuk Lim’s group at Kyung Hee University (President Jinsang Kim) and Dr. Byungki Ryu at the Korea Electrotechnology Research Institute (President Namkyun Kim), proposed a new method that can accurately determine material properties with only limited data. The method uses Physics-Informed Machine Learning (PIML), which directly incorporates physical laws into the AI learning process.
<Schematic Diagram of a Physics-Based Machine Learning Methodology for Understanding Material Properties>
In the first study, the researchers focused on hyperelastic materials, such as rubber. They presented a Physics-Informed Neural Network (PINN) method that can identify both the deformation behavior and the properties of materials using only a small amount of data obtained from a single experiment. Whereas previous approaches required large, complex datasets, this research demonstrated that material characteristics can be reliably reproduced even when data is scarce, limited, or noisy.
In the second study, the team turned to thermoelectric materials—new materials that convert heat into electricity and electricity into heat. They proposed a PINN-based inverse inference technique that can estimate key indicators, such as thermal conductivity (how well heat is transferred) and the Seebeck coefficient (how efficiently electricity is generated), from just a few measurements.
Going further, the researchers introduced a Physics-Informed Neural Operator (PINO), an AI model that understands the physical laws of nature, and showed that it can generalize to previously unseen materials without requiring retraining.
In fact, after training the system on 20 materials, they tested it on 60 entirely new materials, and in all cases it predicted their properties with high accuracy. This breakthrough points to a future where large-scale, high-speed screening of countless candidate materials becomes possible.
This achievement goes beyond simply reducing the need for experiments. By intricately combining physical laws with AI, the researchers provided the first example of improving experimental efficiency while preserving reliability.
Professor Seunghwa Ryu, who led both studies, stated, “This is the first case of applying AI that understands physical laws to real material research. It enables reliable identification of material properties even when data availability is limited, and it is expected to expand into various engineering fields.”
The first paper, co-first-authored by KAIST Mechanical Engineering PhD candidates Hyeonbin Moon and Donggeun Park, was published on August 13 in Computer Methods in Applied Mechanics and Engineering.
※ Paper title: “Physics-informed neural network-based discovery of hyperelastic constitutive models from extremely scarce data”
※ DOI: https://doi.org/10.1016/j.cma.2025.118258
The second paper, co-first-authored by KAIST Mechanical Engineering PhD candidates Hyeonbin Moon and Songho Lee, and Dr. Wabi Demeke, was published on August 22 in npj Computational Materials.
※ Paper title: “Physics-informed neural operators for generalizable and label-free inference of temperature-dependent thermoelectric properties” ※ DOI: https://doi.org/10.1038/s41524-025-01769-1
Meanwhile, the first study was supported by the Korea Research Foundation and the Ministry of Science and ICT’s INNOCore Program, as well as by a research project from the Ministry of Food and Drug Safety. The second study was carried out with support from the Korea Research Foundation and the Ministry of Science and ICT’s INNOCore Program.
2025.10.10 View 2892 -
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 3516 -
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 4837 -
Professor Sung Yong Kim Publishes English Book, 'A Cup of Coffee and the Ocean'
<Professor Sung Yong Kim from Department of Mechanical Engineering>
Professor Sung Yong Kim of the Department of Mechanical Engineering announced the publication of his English book, ‘A Cup of Coffee and the Ocean: Basics of Ocean Dynamics for Everyone’, by the world-renowned academic publisher Springer Nature on August 22nd. The book was designed to easily explain the basics of the ocean, various physical phenomena, and safety common sense to high school students, university students, and the general public, using the familiar subject of coffee.
Professor Kim previously published 'Coffee and the Ocean,' Volume 34 of the 'Scholars Talk about Science and Technology' series, with support from the Korean Academy of Science and Technology in 2019. The new English edition is a rewrite based on that content, targeting an international readership.
The book explains the characteristics of fluids found in everyday coffee, expanding this to illustrate fluid phenomena in the ocean, and also includes various ocean-related safety tips. The goal is to help readers understand the principles of fluids and raise awareness of marine safety. Furthermore, it emphasizes that understanding the ocean is directly connected to national competence and includes a plea from the perspective of an oceanographer.
Professor Kim commented, "The ocean is a global shared space that is not limited by the boundaries of specific regions. This English book was published to broaden the understanding of the ocean not just domestically but among readers worldwide. Through this, I hope to see more oceanographers with a sense of mission who can see the bigger picture."
Book Cover Image
< Book Cover Image >
Related Book Links:
(Link for KAIST Insiders)
https://link-springer-com.libra.kaist.ac.kr/book/10.1007/978-981-96-6835-9
(Link for the General Public)
https://link.springer.com/book/10.1007/978-981-96-6835-9
< QR Code Linking to the Site >
This book was introduced on the UN Ocean Decade official website, and its significance is further amplified by its subject matter being closely aligned with the UN Sustainable Development Goals (SDGs).Furthermore, Professor Nadia Pinardi, who specializes in Physical Oceanography at the University of Bologna (Università di Bologna) in Italy, has communicated that the university plans to translate the book into Italian and utilize it as a textbook for marine education across Italy starting in 2027.The search results include a video featuring Professor Nadia Pinardi discussing sea level rise and coastal adaptation.
https://oceandecade.org/publications/a-cup-of-coffee-and-the-ocean-the-basics-of-ocean-dynamics/
2025.08.27 View 918