Kaist

Turning a Toxic Gas into a Therapeutic Tool Using ..

<(From Left) Professor Jimin Park, Dr. Jaewoong Lee, M.S candidate Lian Lim, Ph.D candidate Changho Lee> KAIST Research Team Develops a 'Bioelectronic Platform' for Precision Hydrogen Sulfide Delivery, Opening New Doors for Digital Healthcare and Precision Medicine A toxic gas known for its "rotten egg smell" has been transformed into a therapeutic tool. A research team at KAIST has developed a technology to precisely control hydrogen sulfide (H2S) using electrical signals, bringing us one step closer to precision medicine that targets only the desired areas while minimizing side effects. KAIST announced on March 23 that a research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering has developed a "bioelectronic H2S delivery platform." This platform can precisely regulate the generation and delivery of H2S at specific times and locations. < Schematic Diagram of a Hydrogen Sulfide–Generating Bioelectronic Platform (AI-Generated Image) > While H2S has long been recognized as a hazardous substance due to its odor and toxicity, it has recently gained attention as a "biological signaling molecule" that maintains cellular health and regulates protein functions. In particular, H2S acts as a "chemical switch" that can modulate protein functions by subtly altering their conformations. However, its use in clinical therapy has been limited because it is difficult to control its concentration and deliver it precisely to specific sites. The research team solved these issues by implementing a technology that controls H2S delivery precisely like an electrical switch. Inspired by the metabolic cycles of bacteria in nature, the team designed a system that generates H2S by applying electricity to thiosulfate ions (S2O32-), a precursor harmless to the human body. This method offers higher safety and precision compared to conventional chemical administration methods. < Hydrogen Sulfide Regulation Capability Depending on Electrode Materials and Input Parameters > Furthermore, through a comparative analysis of various metal electrodes, the team identified the "silver (Ag) electrode" as the most efficient material for H2S electrosynthesis. The Ag electrode selectively generates H2S with high electron transfer efficiency, allowing precise control over its production. Using this platform, both the amount and release kinetics of H2S can be finely tuned by adjusting the voltage and electrolysis time, enabling delivery at the optimal time based on the patient’s condition or the treatment site. When applied to human-derived cells (HEK293T), the research team successfully regulated ion channels (TRPA1), which act as an internal cellular "switch" for sensing pain and irritation. Notably, when applied to cells under oxidative stress (such as those with increased reactive oxygen species), the delivered H2S restored cellular redox balance and demonstrated protective effects. Minimal cytotoxicity was observed, confirming its safety for potential human applications. < Spatiotemporal Regulation of TRPA1 Activation by a Hydrogen Sulfide–Delivering Bioelectronic Platform > < Spatiotemporal Recovery of Oxidative Stress Using a Hydrogen Sulfide–Delivering Bioelectronic Platform > Professor Jimin Park explained, "This study is significant in that it transforms H2S, once regarded solely as a toxic substance, into a new tool for regulating biological systems through precise electrical control." He added, "This technology holds great potential for expansion into precision medical devices for treating neurological and cardiovascular diseases, as well as digital healthcare for real-time health management." This research involved Lian Lim, Changho Lee, and Jaewoong Lee as co-first authors. The study also included contributions from Myeongeun Lee, Yongha Kim, Tae Kyoung Lee, Gwangbin Lee, Jinsoo Kim, and Sang Yeon Oh, with Professor Jihan Kim as a co-author and Professor Jimin Park as the corresponding author. The findings were published on March 19 in the internationally renowned academic journal Science Advances. Paper Title: Bioelectronic Synthesis of Hydrogen Sulfide Enables Spatiotemporal Regulation of Protein Modification and Cellular Redox DOI: https://doi.org/10.1126/sciadv.aeb3401 This research was supported by the National Research Foundation of Korea (NRF) through the Young Researcher Program and the Global Matching Program. < Research Illustration (AI-Generated Image) >

KAIST Develops Motor-less Robotic Hand Actuation T..

< (From left) KAIST Ph.D. students Sangyoon Bae and Professor Seong Su Kim, Ph.D. student Dajeong Kang, and Dr. Wonvin Kim > While space structures and robotic arms require lightweight actuation devices capable of repetitive movement, conventional motor-based systems face limitations due to their heavy weight and complex structures. A KAIST research team has developed a smart material-based actuation technology that operates rapidly in less than a second without a motor, suggesting new possibilities for next-generation robotics and space deployable structures. KAIST announced on the 22nd that a research team led by Professor Seong Su Kim from the Department of Mechanical Engineering has developed a "two-way shape memory material-based hybrid smart actuator" capable of "reversible self-shape change." This technology allows the material to change its shape in response to external stimuli, such as heat, and return to its original state without the need for additional complex mechanical devices. The research team designed a hybrid composite actuator that combines Shape Memory Alloys (SMA) and Shape Memory Polymers (SMP) to leverage the advantages of both materials. SMAs are metallic materials that return to their original shape when heated, while SMPs are polymer materials that change shape in response to heat or other external stimuli. Conventional shape memory materials had limitations; they either could not return to their original state once deformed (one-way) or had extremely slow recovery speeds. Furthermore, because metal alloys and polymer materials have different levels of stiffness, they often failed to restore their shape accurately during repetitive use. To solve these issues, the research team improved both the material and its structure. First, they adjusted the chemical composition of the SMP and reinforced it with carbon fibers to make the material more rigid. Additionally, they applied a "tape spring" structure—similar to a retractable measuring tape—to the actuator. This structure creates a "snap-through" phenomenon, where energy is stored during deformation and released instantaneously, significantly increasing both the speed and accuracy of the movement. As a result, the developed actuator achieved full two-way actuation, bending when heated and flattening again as the temperature drops. The technology also demonstrated a significantly increased range of deformation and a nearly 100％ recovery rate to the initial shape. The recovery speed was also greatly improved, confirming that the actuator can operate repeatedly without the need for complex control systems. < Development process of the SMA-SMP hybrid two-way actuator > The shape memory actuator developed in this study is highly significant as it simultaneously achieves two-way deformation, sub-second actuation speed, and high deployment accuracy. This achievement is evaluated as a major step forward in the practical application of shape memory material-based actuation technology. Professor Seong Su Kim stated, "This research overcomes the physical limitations of materials through original structural design, elevating the performance of shape memory actuators to the next level. We expect this technology to be applied in various fields, such as robotic grippers requiring repetitive motions or deployable structures for space applications." Dajeong Kang, a Ph.D. student, participated as the lead author of this study. The paper was published online on January 19, 2026, in Advanced Functional Materials, an international journal published by Wiley. In recognition of its excellence, the study was featured as the Front Cover of the March 2026 issue of Advanced Functional Materials. Paper Title: Two-Way Shape Memory Alloy and Polymer Composite Hybrid Smart Actuator With High Speed, Accuracy, and Reversible Deformation DOI: https://doi.org/10.1002/adfm.202528863 Author Information: Dajeong Kang (KAIST, First Author), Seong Yeon Park (KAIST, Co-author), Yitro Samuel Aditya (KAIST, Co-author), Ha Eun Lee (KAIST, Co-author), Wonvin Kim (KAIST, Co-author), Sangyoon Bae (KAIST, Co-author), and Seong Su Kim (KAIST, Corresponding Author) < Image of the Front Cover of Advanced Functional Materials > This research was conducted with the support of the Nano and Materials Technology Development Program (Project No. RS-2024-00450477) and the National Semiconductor Research Laboratory Core Technology Development Program (Project No. RS-2023-00260461) funded by the Ministry of Science and ICT and the National Research Foundation of Korea.

KAIST Expands Storage Capacity with Smart Gate Sem..

<(From Left) Ph. D candidate Dae Hyun Kang, Professor Byung Jin Cho> From smartphones to large-scale AI servers, most digital information in modern society is stored in NAND flash memory＊. KAIST researchers have developed an innovative technology that can overcome the limitations of next-generation semiconductors, where more data must be stored in smaller spaces. This advancement is expected to serve as a key enabling technology for realizing ultra-high-capacity memory. ＊NAND flash memory: a non-volatile semiconductor memory used in storage devices such as smartphones and SSDs, where data such as photos, videos, and apps are retained even when power is turned off. KAIST (President Kwang Hyung Lee) announced on the 20th of March that a research team led by Professor Byung Jin Cho of the School of Electrical Engineering has overcome the scaling limitations of 3D V-NAND memory＊ by implementing a “smart gate” structure that selectively controls electron movement depending on conditions, using a new material applied to an ultra-thin semiconductor layer thinner than a human hair. ＊3D V-NAND: a memory technology that stacks memory cells vertically, unlike conventional planar (2D) arrangements, enabling higher data storage density. This research is particularly significant in that it addresses the longstanding issues of speed degradation and reliability during data write and erase operations by utilizing a novel material called boron oxynitride (BON). In semiconductor memory, the tunneling layer—a thin insulating layer that acts as a pathway for electrons to move in and out of the memory cell—has historically faced a trade-off between performance and reliability. With conventional materials, it has been difficult to achieve both simultaneously. For example, the widely used silicon oxynitride (SiON) increases data leakage when the tunneling path is widened to improve erase speed, while narrowing the path to prevent leakage significantly slows down data erasure. This trade-off has been a major obstacle to implementing next-generation penta-level cell (PLC) technology. PLC technology stores 5 bits of data per memory cell by distinguishing 32 different voltage states, allowing much higher data density within the same physical size. To overcome this limitation, the research team introduced BON, a completely new material beyond conventional silicon-based systems, into the tunneling layer. This material exhibits a unique physical property in which the energy barrier height differs depending on the type of charge carrier. Leveraging this property, the team designed an asymmetric energy barrier structure that allows holes (positive charge carriers)—needed for data erase—to pass through easily, while blocking electrons, which represent stored data, from leaking out. An asymmetric energy barrier refers to a structure in which the energy required for charge carriers to move varies depending on the type of charge. This enables efficient charge transport during erase operations while effectively preventing data loss. The concept is analogous to a “smart gate” that opens easily for entry but firmly blocks exit, implemented at the semiconductor level. Experimental results showed that devices using the BON tunneling layer achieved up to a 23-fold improvement in erase speed compared to conventional technologies and demonstrated excellent durability with minimal performance degradation even after tens of thousands of operation cycles. Notably, even under the highly demanding PLC operation—where 32 distinct voltage levels must be precisely controlled—the researchers achieved more than threefold improvement in controlling data distribution across devices. < Schematic diagram of the asymmetric energy barrier structure and operating principle of the BON tunneling layer > This achievement is considered by both academia and industry to be beyond a purely experimental result, reaching a level immediately applicable to real semiconductor manufacturing processes. Professor Byung Jin Cho stated, “This research presents a novel technology that can be directly applied to the production of next-generation ultra-high-capacity memory,” adding, “It will significantly contribute to maintaining Korea’s technological leadership in the semiconductor industry.” This study was implemented by Dae Hyun Kang, an integrated master’s–PhD student in Electrical Engineering, as the first author. The research was presented at the IEEE International Electron Devices Meeting (IEDM) on December 9, one of the most prestigious conferences in the semiconductor field, attracting global attention. The work also received the Grand Prize (first place overall in the university category) at the 32nd Samsung Human Tech Paper Awards, marking a notable achievement as a traditional semiconductor device study in a competition typically dominated by AI-related research. ※ Paper title: “Bandgap-Engineered Boron Oxynitride Tunneling Layer for Reliable PLC Operation of 3D V-NAND Flash Memory Devices,” DOI: https://doi.org/10.1109/IEDM50572.2025.11353681 This research was supported by the National Semiconductor Research Lab Core Technology Development Program funded by the Ministry of Science and ICT.

KAIST Develops Liquid Powder That Enables Electron..

<(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).

Professor Jihyeon Yeom Selected as Early Career Ad..

< Professor Jihyeon Yeom > KAIST announced on the 13th that Professor Jihyeon Yeom from the Department of Materials Science and Engineering has been selected as a member of the Early Career Advisory Board (ECAB) for Chemical Reviews, widely considered the world's most prestigious academic journal in the field of chemistry. Published by the American Chemical Society (ACS), Chemical Reviews is a flagship review journal that comprehensively organizes and surveys the most influential research achievements across all areas of chemistry and materials science. It is evaluated as a top-tier international journal in the field. The journal boasts an Impact Factor (IF) of 56, ranking it among the highest of all scientific journals worldwide. Its authority is particularly significant because it is a review journal that analyzes global research trends to suggest future academic directions, rather than simply publishing individual experimental data. The ECAB, which began its term in January 2026, consists of 10 researchers selected from among rising global science leaders. Candidates are evaluated based on academic originality, research impact, and contributions to the scientific community. Members provide advisory roles for the journal's academic direction and strategic planning, contributing to the discovery of next-generation research trends and the expansion of global research networks. This selection highlights that Professor Yeom’s research achievements are receiving high international acclaim. Professor Yeom is conducting research on applying "chirality"—a property where objects, like DNA or proteins, are mirror images of each other but cannot be perfectly superimposed—to nanomaterials. Her core work involves precisely controlling atomic arrangements to realize artificial materials that can interact naturally with biological signals. In particular, she is gaining attention for developing next-generation smart healthcare technology that combines light-responsive chiral materials with Artificial Intelligence (AI) to detect and analyze minute changes in the human body in real time. Professor Yeom explained that these chiral characteristics offer new possibilities for expanding information transmission and processing capabilities beyond simple structural properties. Building on this foundation, she plans to expand her research into various fields, including precision medical diagnostic technology, next-generation optoelectronic devices utilizing circularly polarized light, and AI-based platforms. Professor Yeom has established herself as a global leader in chiral materials research, recently publishing results in world-renowned journals such as Nature Communications, Advanced Materials, ACS Nano, and Accounts of Chemical Research. "Chirality is not just a structural characteristic, but a new degree of freedom that expands the functional and information-processing capabilities of matter," said Professor Yeom. "I plan to expand my research into chiral-based electronic and optical devices, bio-diagnostic technologies, and AI-based spectroscopic platforms in the future." This ECAB selection once again demonstrates the research competitiveness and international standing of the KAIST Department of Materials Science and Engineering. It is expected to further strengthen KAIST's role as a global research hub in the field of next-generation materials research.

KAIST Solves the 500-Year-Old ‘Pain’ Behind Michel..

<(From Left) Ph.D candidate Minwoo Choi, Ph.D candidate Hyejoon Jun, Professor Hyoungsoo Kim> More than 500 years ago, Michelangelo spent four years painting The Creation of Adam on the ceiling of the Sistine Chapel, struggling with paint dripping onto his face. He described the process as “closer to torture than painting.” Now, researchers at KAIST have developed a technology that can effectively “hold up falling paint.” Beyond ceiling paintings, this principle could help solve the problem of liquid films collapsing on inclined surfaces, with potential applications in precision coating, electronic circuit printing, 3D printing, and fluid control in space environments. KAIST (President Kwang Hyung Lee) announced on the 12th of March that a research team led by Professor Hyungsoo Kim of the Department of Mechanical Engineering has reinterpreted the fundamental cause of downward flow under gravity—known as gravitational instability—from the perspective of interfacial fluid mechanics＊ and proposed a method to control it by mixing a small amount of volatile liquid into a suspended liquid film. ＊Interfacial fluid mechanics: the study of the balance of microscopic forces acting at the surface of liquids. Why was it so difficult for Michelangelo to paint on the ceiling? When paint is applied to a ceiling, a thin liquid film forms. However, this film gradually becomes unstable due to gravity and eventually drips down. This phenomenon is common in everyday life. For example, when steam condenses on a bathroom ceiling, it first forms a thin layer of water that eventually gathers into droplets and falls. Similarly, droplets that appear on the ceiling of a refrigerator initially form a thin layer but gradually grow and begin to drip downward. This type of instability, where liquid accumulated on an upper surface collapses under gravity, is known as Rayleigh–Taylor instability. Until now, it has generally been considered unavoidable in the presence of gravity. The research team proposed mixing a small amount of volatile liquid into the suspended liquid film. As the volatile component evaporates, it changes the concentration distribution along the liquid surface, creating differences in surface tension. Surface tension is the force that pulls a liquid surface inward, which is why water droplets maintain a rounded shape. When differences in surface tension arise, the region with stronger tension pulls liquid toward itself from regions with weaker tension. This creates a surface flow known as the Marangoni effect. Through experiments and theoretical analysis, the researchers demonstrated that this surface flow can effectively hold the liquid in place and suppress the gravitational instability that would otherwise cause it to fall. A familiar example can illustrate this effect. If pepper powder is sprinkled evenly on the surface of water, it remains floating. However, if a drop of detergent is placed in the center, the pepper suddenly moves outward toward the edges. This happens because the detergent reduces the surface tension where it touches the water, allowing the surrounding regions with stronger surface tension to pull the liquid outward. As the surface flow develops, the pepper particles move along with it. In this study, evaporation of the volatile liquid created a similar surface tension difference. But instead of pushing particles outward like in the pepper example, the flow pulled the liquid upward, counteracting the force that would otherwise cause it to drip downward. As a result, under certain conditions the liquid film remained intact despite gravity. In some cases, the researchers even observed a new behavior in which droplets did not fall but the liquid film oscillated periodically. This demonstrates that gravitational instability can be actively controlled using only natural processes—such as liquid composition and evaporation—without any external energy input. This principle could enable thinner and more uniform liquid films in precision coating, printing, and layer-by-layer manufacturing processes, allowing stable coating even on tilted surfaces. It may also extend to technologies such as 3D printing and fluid control in specialized environments like space. In essence, the physical limitation that Michelangelo struggled with 500 years ago may now inspire future industrial technologies. <A fictional staged scene of Michelangelo painting The Creation of Adam (AI-generated image)> Professor Hyungsoo Kim stated, “Rayleigh–Taylor instability has long been considered unavoidable as long as gravity exists. This research is meaningful because it shows that gravitational instability can be actively controlled without external energy by utilizing natural processes such as liquid composition and evaporation.” He added, “This principle could extend beyond coating, printing, and layering processes to fluid control technologies in space environments.” This study was led by Minwoo Choi, an integrated master’s–PhD student in Mechanical Engineering, as the first author. The discovery, recognized as a new finding in the control of hydrodynamic instability, was published online on January 29 in the international journal Advanced Science (Wiley) and was selected as a Frontispiece article. ※ Paper title: “Evaporation-Driven Solutal Marangoni Control of Rayleigh–Taylor Instability in Inverted Films,” Authors: First author Minwoo Choi (KAIST), co-author Hyejoon Jun (KAIST), corresponding author Hyungsoo Kim (KAIST), DOI: https://doi.org/10.1002/advs.202520343 This research was supported by the Mid-Career Researcher Program of the National Research Foundation of Korea (MSIT: 2021R1A2C2007835)

KAIST Develops mRNA Platform That Remains Effectiv..

<(From Left) Dr. Subin Yoon, Ph.D candidate Hyeonggon Cho, Prof. Jae-Hwan Nam, Prof. Young-suk Lee> Since the COVID-19 pandemic, mRNA vaccines have gained attention as a next-generation pharmaceutical technology. mRNA therapeutics work by delivering genetic instructions that enable cells to produce specific proteins for therapeutic effects. However, their efficacy has been reported to decline in elderly individuals or patients with obesity. To address this limitation, Korean researchers have newly designed a key regulatory region of mRNA that improves therapeutic protein production efficiency, developing a next-generation mRNA platform that maintains effectiveness even in aging and obesity conditions. KAIST (President Kwang Hyung Lee) announced on the 10th of March that a joint research team led by Professor Young-suk Lee of the Department of Bio and Brain Engineering and Professor Jae-Hwan Nam of The Catholic University of Korea (President Jun-Gyu Choi) has developed a new mRNA platform by precisely designing the sequence of the 5′ untranslated region (5′UTR)＊, a key regulatory region of mRNA. ＊5′ untranslated region (5′UTR): A region of mRNA that initiates and regulates protein production. The design of this region influences both the amount and speed of protein synthesis. The research team analyzed large-scale bioinformatics datasets to identify 5′UTR sequences that enable proteins to be produced more efficiently across diverse cellular environments. When applied, the designed sequences significantly enhanced protein production and immune responses even in preclinical models of aging and obesity. mRNA is a long single-stranded RNA molecule that serves as the blueprint for producing proteins required by the body. It consists of several components: the 5′UTR, which initiates and regulates the rate of protein production; the coding sequence (CDS), which contains the genetic information for a specific protein; the 3′ untranslated region (3′UTR), which helps maintain mRNA stability within cells; and the poly(A) tail, which further enhances stability and supports protein synthesis. Among these components, the 5′UTR and 3′UTR do not determine the type of protein produced, but they play a critical role in regulating how efficiently the protein is synthesized. For this reason, these regions are receiving increasing attention as key bioengineering platforms for improving the performance of various mRNA therapeutics, including vaccines and treatments. <Schematic Diagram of mRNA Therapeutic Design and Validation Using Bioinformatics> To identify highly efficient 5′UTR sequences capable of promoting protein production across multiple tissues and cellular environments, the team conducted an integrated analysis of large-scale biological datasets. This included multiple analytical approaches such as RNA sequencing (RNA-seq) for analyzing gene activity across tissues, single-cell RNA sequencing (scRNA-seq) for examining gene expression at the individual cell level, and ribosome profiling (Ribo-seq) for measuring actual protein translation efficiency. The researchers also focused on the fact that in aging or obesity conditions, cells often experience high levels of stress—particularly oxidative stress—which can reduce their ability to synthesize proteins. When the newly designed mRNA therapeutics were applied to preclinical models of aging and obesity, the results showed significantly improved protein production and immune responses compared with existing approaches. This research is expected to be applicable not only to mRNA vaccines but also to a wide range of biopharmaceutical technologies, including gene therapies and immunotherapies. <Multimodal Bio–Big Data Analysis–Based mRNA Therapeutic Design (AI-Generated Image)> Professor Young-suk Lee of KAIST Department of Bio and Brain Engineering stated, “This study identified a design strategy that enables mRNA to produce proteins more efficiently by analyzing large-scale biological data,” adding, “This technology will provide an important foundation for ensuring that mRNA vaccines and therapeutics remain effective even in environments where drug efficacy may decline, such as in elderly or obese patients.” In this study, Dr. Subin Yoon from The Catholic University of Korea and doctoral candidate Hyeonggon Cho from KAIST participated as co-first authors. The research findings were published online on January 2 in the internationally renowned journal Molecular Therapy (IF = 12.0), a leading journal in gene and cell therapy. (Paper title: ”Designing 5′UTR sequences improves the capacity of mRNA therapeutics in preclinical models of aging and obesity” DOI: https://doi.org/10.1016/j.ymthe.2025.12.060) This research was supported by the Excellent Young Researcher Program and the Bio-Medical Technology Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT, the Infectious Disease Response Innovative Technology Support Program of the Ministry of Food and Drug Safety, and the Infectious Disease Prevention and Therapeutics Technology Development Program of the Korea Health Industry Development Institute.

KAIST Surpasses the Limits of AlphaFold… AI Now Pr..

<(From Left) Ph.D candidate Hyojin Son, Professor Gwan-su Yi> Proteins in our body function like switches. When a drug binds to a protein, the structure at the binding site changes, and this structural change propagates throughout the protein, turning its function on or off. Google DeepMind’s AlphaFold3 successfully predicted whether drugs bind to proteins and the three-dimensional structure of binding sites. However, it could not predict how signals propagate inside the protein after drug binding, how the entire structure changes, or whether the protein’s function is ultimately activated or inhibited. KAIST researchers have developed an AI that predicts not only whether a drug binds but whether it actually works. KAIST (President Kwang Hyung Lee) announced on the 4th of March that a research team led by Professor Gwan-Su Yi of the Department of Bio and Brain Engineering has developed an artificial intelligence model called “GPCRact” that predicts whether candidate molecules not only bind to G-protein-coupled receptors (GPCRs)—a major drug target—but also actually activate the protein. GPCRs act as “signal receivers” on the surface of cells. When hormones, neurotransmitters, or drugs send signals from outside the cell, GPCRs function as gates that receive these signals and transmit them into the cell. There are about 800 types of GPCRs in the human body, and roughly 30–40％ of currently marketed drugs target them. They are key proteins involved in numerous physiological functions, including heart rate regulation, blood pressure control, pain sensing, immune responses, and emotional regulation. However, a drug binding to a GPCR does not always trigger the desired biological function. Structural changes inside the protein and subsequent signal transmission determine whether the drug actually produces an effect. This process is known as allosteric signal propagation. The research team designed the AI to learn the drug action process in two stages: ① the drug–target binding stage, and ② the intracellular signal propagation stage within the protein. The three-dimensional protein structure was represented as an atom-level graph, and an attention mechanism was applied to enable the model to learn important signaling pathways. Through this approach, the AI analyzes not only the drug binding signal but also the internal signaling pathways of the protein to predict whether the protein becomes activated. As a result, the model significantly improved the prediction performance of drug activity even in proteins with complex structures that existing models struggled to analyze. Importantly, the model does not simply output “active” or “inactive.” It also presents the key internal signaling pathways that form the basis of its predictions, overcoming the limitations of so-called “black-box AI.” <Schematic diagram of drug activity prediction and mechanism interpretation using the GPCRact artificial intelligence model> This represents an important advance, as it allows researchers to interpret and verify predictions while simultaneously improving the reliability and efficiency of drug discovery. In the future, the model is expected to serve as a precision drug discovery AI platform capable of predicting not only whether drugs bind to GPCRs but also whether they truly activate them in various diseases targeting GPCRs. <AI-generated image to help illustrate the research> Professor Gwan-Su Yi explained, “Allosteric structural change refers to a phenomenon in which a drug binds to one part of a protein and its influence propagates internally, altering the function of other regions,” adding, “The key contribution of this research is incorporating this operational principle into deep learning.” He further noted, “We plan to expand the model to various proteins and ultimately develop technologies capable of predicting cellular and whole-body responses.” Ph.D candidate Hyojin Son participated as the first author in this study. The paper was published on January 15 in the international journal Briefings in Bioinformatics, one of the leading journals in the field of bioinformatics. ※ Paper title: “GPCRact: a hierarchical framework for predicting ligand-induced GPCR activity via allosteric communication modeling” DOI: https://doi.org/10.1093/bib/bbaf719 ※ Author information: Hyojin Son (KAIST, first author), Gwan-Su Yi (KAIST, corresponding author) This research was supported by the Basic Research Program for Individual Research funded by the Ministry of Science and ICT and the National Research Foundation of Korea (RS-2025-24533057).

KAIST Team Led by Dong-won Lee Wins Grand Prize at..

< (From Left) M.S candidate Dongwon Lee from School of Electrical Engineering, Ph.D candidate Jaehun Han from Graduate School of Quantum Science and Technology > "Team Yangja-jorim," consisting of Dongwon Lee, Gyungjun Kim and Jaehun Han , has been honored with the Grand Prize at the '2026 2nd Global Quantum AI Competition.' The event was hosted and organized by NORMA, a specialized quantum computing company. This global competition was designed to expand hands-on experience with quantum cloud services and to discover next-generation talent in the field of quantum artificial intelligence. The event spanned approximately 70 days, beginning with the preliminary opening ceremony held at Korea University’s Hana Square on December 17 last year. The final winners were announced during an awards ceremony held at NORMA's headquarters on the 27th of last month. The competition attracted significant interest from quantum technology talent worldwide, including university students, developers, and researchers. A total of 137 teams participated in the preliminaries, with the top 10 teams advancing to the finals—a competitive ratio of approximately 13.7 to 1. < An acquaintance attended the awards ceremony of the 2nd Global Quantum AI Competition to accept the prize on behalf of the team. > In the final round, participants were presented with four generative problems utilizing the Quantum Circuit Born Machine (QCBM) model. To overcome the current limitations of quantum machine learning, the contestants were tasked with designing and validating Quantum-Classical Hybrid Generative AI models that integrate classical techniques. Notably, the final problem provided an opportunity to verify the proposed methods using a real Quantum Processing Unit (QPU) from Rigetti Computing, a leading global quantum computing firm. The judging process employed a double-blind system, where the identities of both evaluators and participants remained undisclosed to ensure maximum fairness and credibility. "Through this competition, we were able to explore the research potential of the quantum AI field more deeply," said KAIST's Team Yangja-jorim in their acceptance speech. "We hope to continue contributing to the advancement of quantum technology through consistent research and new challenges."

Professor Kuk-Jin Yoon’s Research Team at the Depa..

<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)>

Earth’s Safety Limit Already Exceeded… Carbon Emis..

<(From Left) Professor Haewon McJeon, Dr. Paul Wolfram> Earth is not infinite. Pollution beyond certain levels threatens the climate and ecosystems. To prevent this, scientists have proposed “Planetary Boundaries,” defining the safe operating limits of the Earth system. A KAIST research team recalculated climate change and nitrogen pollution using the same standard and found that current carbon emissions already exceed the planet’s sustainable limit by more than double. KAIST (President Kwang Hyung Lee) announced on the 6th of March that Professor Haewon McJeon of the Graduate School of Green Growth and Sustainability, in collaboration with Dr. Paul Wolfram’s team at the Pacific Northwest National Laboratory (PNNL) of the U.S. Department of Energy, recalculated the carbon dioxide emission boundary using an annual emissions (flow) framework rather than the traditional cumulative carbon stock framework. Until now, climate change has been evaluated based on how much CO₂ accumulates in the atmosphere (stock). In contrast, nitrogen and phosphorus pollution have been assessed based on how much is emitted each year (flow). Because these problems were measured using different metrics, it was difficult to fairly compare their relative severity. The research team therefore recalculated carbon emissions using the same annual emissions framework used for nitrogen pollution. Based on the condition of limiting the rise in global average temperature to within 1.5°C, the analysis showed that the Earth’s safe limit for annual CO₂ emissions is approximately 4–17 gigatons (Gt CO₂ per year). However, humanity’s current annual emissions amount to about 37 gigatons (Gt CO₂ per year). This level exceeds the Earth’s safe operating space by more than twofold. Professor Haewon McJeon stated, “When carbon emissions are compared using the same framework as nitrogen pollution, the severity of climate change becomes much clearer,” adding, “This study helps place different environmental problems on the same analytical basis, which can contribute to setting clearer policy priorities.” <Comparative Measurement of Planetary Boundaries and Proposal for Flow-Based Carbon Emission Limits> <Scope and Sensitivity of Flow-Based Carbon Emission Limits> He further emphasized, “The need for integrated strategies that simultaneously consider carbon, nitrogen, and phosphorus pollution is growing,” adding that global efforts toward decarbonization must accelerate further. The study was jointly led by Professor Haewon McJeon and Dr. Paul Wolfram as co-corresponding authors, with Hassan Niazi, Page Kyle, and other researchers from PNNL participating as collaborators. The research results were published on February 16 in the international journal Nature Sustainability. ※ Paper title: “Ensuring consistency between biogeochemical planetary boundaries” DOI: https://doi.org/10.1038/s41893-026-01770-6 This research was supported by the project “Development of an AI-Based Next-Generation Integrated Assessment Model for Climate–Human Interactions” funded by the Ministry of Science and ICT and the National Research Foundation of Korea. In a Science commentary published on March 5 titled “Thirty-six solutions to stabilize Earth’s climate,” Professor McJeon revisited the progress of climate technologies over the past 20 years. He pointed out that although humanity has possessed many of the necessary technologies, they have not been implemented quickly enough, allowing the climate crisis to intensify. He also emphasized that the pace of decarbonization must accelerate to achieve carbon neutrality. ※ Commentary: “Thirty-six solutions to stabilize Earth’s climate” Link: https://doi.org/10.1126/science.aed5212

Designing the Heart of Hydrogen Cars with AI... De..

<(From left) KAIST Ph.D. Candidate HyunWoo Chang, Professor EunAe Cho. (Top, from left) Seoul National University Professor Won Bo Lee, Dr. Jae Hyun Ryu.> In the era of climate crisis, hydrogen vehicles are emerging as an alternative for eco-friendly mobility. However, the fuel cell, known as the ‘heart of the hydrogen car,’ still faces limitations of high cost and short lifespan. The core cause is the platinum catalyst. While it is a decisive material for generating electricity, the reaction is slow, performance degrades over time, and manufacturing costs are high. Korean researchers have presented a clue to solving this difficult problem. KAIST announced on February 26th that the research team led by Professor EunAe Cho of the Department of Materials Science and Engineering, together with the team of Professor Won Bo Lee of the School of Chemical and Biological Engineering at Seoul National University, has developed a technology that predicts the ‘atomic arrangement’ tendency of catalysts using artificial intelligence (AI). This technology is akin to calculating beforehand which combination is advantageous for completing a puzzle before putting it together. By having AI calculate the arrangement speed of metal atoms first, it has become possible to efficiently design catalysts with better performance. The core of this research is that ‘AI revealed the fact that zinc plays a decisive role in the platinum-cobalt atomic arrangement.’ <Schematic diagram of AI-based atomic alignment prediction> Despite the high performance of existing platinum-cobalt (Pt-Co) alloy catalysts, very high-temperature heat treatment was required to create the ‘intermetallic (L1₀)’ structure, where atoms are regularly arranged. In this process, particles would clump together, or the structure would become unstable, posing limitations for actual fuel cell application. To solve this problem, the research team introduced machine learning-based quantum chemistry simulations. Through AI, they precisely predicted how atoms move and arrange themselves inside the catalyst. As a result, they discovered that zinc (Zn) acts as a mediating element that promotes atomic arrangement. The principle is that when zinc is introduced, atoms find their places more easily, forming a more sophisticated and stable structure. In other words, AI has found the ‘optimal path for atomic arrangement creation’ in advance. < Synthesis process of Zinc-introduced Platinum-Cobalt catalyst> The zinc-platinum-cobalt catalyst, synthesized based on AI predictions, secured both higher activity and superior long-term durability compared to commercial platinum catalysts. This is a case proving that the ‘virtual blueprint’ calculated by artificial intelligence can be implemented as a high-performance catalyst in an actual laboratory. In particular, this technology is expected to contribute to extending catalyst lifespan and reducing manufacturing costs across core carbon-neutral industries, such as hydrogen passenger cars, hydrogen trucks requiring long-distance operation, hydrogen ships, and energy storage systems (ESS). < Conceptual diagram of AI-based catalyst development (AI-generated image) > Professor EunAe Cho stated, “This research is a case of utilizing machine learning to predict the atomic arrangement tendency of catalysts in advance and implementing this through actual synthesis,” and added, “AI-based material design will become a new paradigm for the development of next-generation fuel cell catalysts.” Ph.D. Candidate HyunWoo Chang from KAIST’s Department of Materials Science and Engineering and Dr. Jae Hyun Ryu from Seoul National University’s School of Chemical and Biological Engineering participated as co-first authors in this research. The research results were published on January 15, 2026, in ‘Advanced Energy Materials,’ a world-renowned academic journal in the energy materials field. ※ Paper Title: Machine Learning-Guided Design of L1₀-PtCo Intermetallic Catalysts: Zn-Mediated Atomic Ordering, DOI: https://doi.org/10.1002/aenm.202505211 This research was conducted with the support of the National Research Foundation of Korea’s Nano & Material Technology Development Program and the Korea Institute of Energy Technology Evaluation and Planning’s Energy Innovation Research Center for Fuel Cell Technology.