Kaist

KAIST demonstrates ultralow-noise microwave and mi..

<(From Left) Prof. Jungwon Kim, Dr. Changmin Ahn> Researchers at KAIST have demonstrated a chip-scale photonic approach for generating ultralow-noise and highly stable microwave and millimeter-wave signals based on optical frequency combs (microcombs), offering a potential pathway toward compact, high-performance frequency sources for next-generation technologies. High-frequency signals in the tens to hundreds of gigahertz range are essential for emerging applications such as 6G communications, radar, and precision sensing. However, achieving both low noise and high stability at these frequencies remains a fundamental challenge for conventional electronic signal sources. In the first study, the researchers addressed the long-standing challenge of transferring the stability of an optical reference to a microcomb. Direct stabilization is difficult due to the lack of carrier-envelope offset detection in high-repetition-rate microcombs. To overcome this, they used a mode-locked laser as a transfer oscillator and synchronized it to the microcomb using electro-optic sampling. This approach enabled direct and robust transfer of optical-reference stability to the microcomb repetition rate, achieving fractional frequency stability at the 10-18 level and a phase noise of -125 dBc/Hz at 100 Hz offset from a 22 GHz carrier, representing state-of-the-art performance and more than 80 dB improvement over the free-running microcomb in the low-offset-frequency regime. In the second study, the team addressed the degradation of noise performance typically observed when scaling microcombs to higher repetition rates. While microcombs with lower repetition rates (large resonators) exhibit better noise characteristics, increasing the repetition rate generally leads to performance degradation. The researchers showed that this limitation can be overcome using perfect soliton crystal (PSC) states, which enable repetition-rate multiplication while preserving the low-noise characteristics of the original comb. As a result, they generated millimeter-wave signals at 44 GHz and 66 GHz with timing jitter on the order of 3 femtoseconds, demonstrating that the low-noise performance of a microwave-rate microcomb can be preserved during scaling to millimeter-wave frequencies. <Ultra-compact optical resonator chip with noise suppression based on an optical reference signal and increased frequency via fully solitonic waves (AI-generated image)> Together, these results establish two key capabilities: (1) high-fidelity transfer of optical-reference stability to chip-scale microcombs, and (2) preservation of low-noise performance during frequency scaling to millimeter-wave regimes. This combined capability provides a practical route toward compact photonic signal sources that integrate optical-level stability with high-frequency operation. The research was led by Dr. Changmin Ahn and Prof. Jungwon Kim at KAIST, in collaboration with Prof. Hansuek Lee. The results were published in Laser & Photonics Reviews and Optica. · Optical-to-microcomb stability transfer for ultrastable timing and microwave/millimeter-wave generation (DOI: 10.1002/lpor.71135) · Preserving ultralow timing jitter in microcombs with repetition-rate multiplication via perfect soliton crystal formation (DOI: 10.1364/OPTICA.581054)

First Observation of the Moment Lithium Batteries ..

< (From left) Professor Seungbum Hong, Ph.D candidate Seonghyun Kim, Dr. Youngwoo Choi, and Dr. Yoonhan Cho > A crucial clue to simultaneously increasing electric vehicle (EV) driving range and battery lifespan has been discovered. A research team at our university has observed the exact moment of degradation in lithium metal batteries at the nanoscale (approximately 1/100,000th the thickness of a human hair) and identified the fundamental cause of performance decline. This is evaluated as a significant turning point in accelerating the commercialization of next-generation batteries. KAIST announced on May 10th that a research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering has identified the degradation mechanism of the lithium metal anode, a core component of next-generation batteries. Lithium metal is dubbed a "dream battery material" due to its significantly higher energy density compared to conventional batteries. However, the rapid decline in performance after repeated charge and discharge cycles has been the biggest obstacle to commercialization. In particular, when lithium is deposited or stripped irregularly, it can form "dead lithium"—lithium that is electrically disconnected—which leads to performance degradation and poses safety risks. The research team utilized in situ electrochemical atomic force microscopy (EC-AFM), which allows for real-time observation of the battery interior, to track the entire process of lithium deposition (plating) and removal (stripping). As a result, they confirmed that the lithium reaction does not occur uniformly across the entire surface but occurs selectively at specific locations. <Overview of the EC-AFM Measurement Process> Specifically, in porous regions with rough surfaces, voids were easily formed when lithium was stripped away, leading to the creation of "dead lithium" that becomes electrically isolated. This phenomenon acts as a direct cause of the sudden decline in battery performance. The significance of this study lies in experimentally identifying where and how lithium metal batteries are damaged. Furthermore, it proved that the "initial morphology," where lithium is first formed, is a key variable that determines the long-term lifespan of the battery. <Height Maps and Surface Slope Maps During the 1st–3rd Plating/Stripping Processes> Accordingly, it is expected that if the surface where lithium forms is controlled uniformly and precisely in the future, battery life and stability can be dramatically improved. This suggests a design direction that can simultaneously achieve increased EV driving range and the development of long-life batteries. Professor Seungbum Hong stated, "This research is highly significant as it directly confirmed the cause of battery performance degradation at the nanoscale. It will serve as an important foundation for developing safer and longer-lasting next-generation batteries." Seonghyun Kim, a PhD student in the Department of Materials Science and Engineering, participated as the lead author. The study was published on February 24, 2026, in ACS Energy Letters, a prestigious international academic journal in the fields of materials science, chemistry, and chemical engineering, and was selected as a cover article. ※ Paper Title: Spatially Selective Lithium Plating and Stripping in Lithium Metal Anodes, DOI: https://doi.org/10.1021/acsenergylett.6c00122 < Photo of Selection as ACS Energy Letters Cover Paper > Meanwhile, this research was conducted with support from LG Energy Solution and the Future Pioneering Convergence Science and Technology Development Program (RS-2023-00247245) of the National Research Foundation of Korea, funded by the Ministry of Science and ICT.

KAIST Unveils Complexity Paradox： Nanoparticles Gr..

<(From Left) Ph.D candidate Jeesoo Yoon, Dr. Jinwon Oh, Professor Hee-Tae Jung, Professor Matteo Cargnello> A KAIST and Stanford University joint research team revealed research results that overturn long-standing beliefs in the field of nanomaterials. Contrary to the conventional perception that mixing more metals complicates the system, this study revealed for the first time that complex compositions actually create more uniform nanoparticles, signaling a new turning point for next-generation energy and catalysis technology. KAIST (President Kwang Hyung Lee) announced that a joint research team led by distinguished professor Hee-Tae Jung from the Department of Chemical and Biomolecular Engineering and Professor Matteo Cargnello from Stanford University has identified a paradoxical phenomenon where mixing more metals leads to the formation of more uniform nanoparticles. Nanoparticles are core materials in various industries such as semiconductors, eco-friendly energy, and biotechnology. However, as the number of constituent elements increases, the different reaction rates of each element cause variations in particle size and shape, which has been considered a major challenge for precision control. The research team focused on composition-focusing, a phenomenon where the particle components converge in one direction and become more uniform as the number of metal elements increases. <Figure 1. (Top) Increasing number of possible product metal combinations (Bottom) Composition-focusing behavior>

KAIST Solves Computer Problems That Would Take Tho..

<(From Left) Professor Yang-Kyu Choi, Ph.D. candidate Seong-Yun Yun, (Upper Right) Professor Sanghyeon Kim, Dr. Joon Pyo Kim> In the era of big data and artificial intelligence, a new approach has emerged for solving combinatorial optimization problems, which involve finding the most efficient solution among many possible options and can otherwise take thousands of years to compute. A KAIST research team has developed computational hardware that can be implemented entirely using existing silicon processes, enabling deployment on existing fabrication lines without additional facilities. This is expected to enable faster and more accurate decision-making across various industries, including logistics, finance, and semiconductor design. KAIST (President Kwang-Hyung Lee) announced on the 6th of May that a joint research team led by Professor Yang-Kyu Choi and Professor Sanghyeon Kim from the School of Electrical Engineering has implemented an oscillatory Ising machine (a specialized-purpose computer in which multiple oscillating elements interact to find optimal solutions)—a next-generation specialized optimization hardware—using only conventional silicon semiconductor processes. The research team focused on oscillators that repeat electrical signals periodically. As multiple oscillators exchange signals and synchronize their rhythms, the system naturally reaches the most stable state, and in this process, it finds the optimal solution. Conventional oscillatory Ising machines have limitations in solving complex problems because it is difficult to precisely control slight frequency differences among oscillators, and the connectivity between elements is limited. <An aging machine using a silicon oscillator and coupler> To overcome this, the research team introduced a new approach in which both the oscillators and the couplers are implemented using single silicon transistors, which are the fundamental switching elements of semiconductors. Through this approach, they reduced frequency deviations among oscillators, enabling stable synchronization, and by using couplers, they implemented multi-level coupling, allowing more precise reflection of problem weights. As a result, both the ability to represent complex optimization problems and the performance of solution search were significantly improved. Using this technology, the research team successfully solved the representative combinatorial optimization problem known as the Max-Cut problem, which involves dividing a network into two groups to maximize connections. This problem can be directly applied to various industrial fields such as logistics route optimization, financial portfolio construction, and semiconductor circuit placement. A key advantage of this approach is that it uses the CMOS＊ process currently employed in the semiconductor industry without requiring special materials or non-standard processes. Therefore, the technology suitable for mass production and commercialization on existing semiconductor production lines without additional facility investment. ＊CMOS (Complementary Metal-Oxide-Semiconductor): the most standard process technology in modern semiconductor manufacturing, characterized by very low power consumption and low heat generation, and used to produce chips that serve as the “brains” of almost all digital devices, including smartphones and computer CPUs <(AI-generated image) Concept diagram of an AI-based silicon aging machine> Professor Yang-Kyu Choi stated, “This research presents an oscillatory Ising machine hardware that secures both scalability and precision by implementing both oscillators and couplers with silicon devices,” adding, “It is expected to be applied to various industrial fields requiring large-scale combinatorial optimization, such as semiconductor design automation, communication network optimization, and resource allocation.” He further noted that, as transistor miniaturization approaches its physical limits and increasingly requires atomic-level control, our group has spent the past decade exploring whether the future of transistors should extend beyond scaling toward the discovery of new functions. Futurist Alvin Toffler famously divided the development of society into three stages, describing the modern transition into a knowledge-based society as the “Third Wave.” In a similar way, the history of transistor technology, which now spans more than 80 years, may also be viewed in three waves. In 1935, Oskar Heil proposed the concept of controlling semiconductor current with an electric field in a British patent. In 1946, William Shockley developed the first solid-state transistor, an achievement that later led to the Nobel Prize. In 1961, Dawon Kahng invented the modern metal–oxide–semiconductor field-effect transistor, or MOSFET, which remains the foundation of today’s mass-produced semiconductor devices. From this perspective, the first wave of transistor technology can be defined as the “switch,” and the second wave as the “amplifier.” Our laboratory proposes a newly identified third wave: the transistor as an “oscillator.” For decades, semiconductor progress has largely been driven by improving the switching and amplification performance of transistors through miniaturization. However, as device fabrication now demands atomic-scale precision, the physical limits of scaling are becoming increasingly apparent. Future transistors therefore require a fundamental paradigm shift—from further miniaturization toward the realization of new functions. The greatest technological significance of this work lies in demonstrating the oscillator as a third fundamental function of the transistor. As a proof of this concept, we experimentally realized a physical Ising machine operating at room temperature. This research was led by KAIST Ph.D. candidate Seong-Yun Yun and Dr. Joon Pyo Kim as co-first authors, and was published in Science Advances, one of the world’s most prestigious scientific journals, on March 27. ※ Paper title: “Scalable Ising machine composed entirely of Si transistors,” DOI: 10.1126/sciadv.adz2384 This research was supported by the National Research Foundation of Korea through the Next-Generation Intelligent Semiconductor Technology Development Program, the National Semiconductor Research Laboratory Core Technology Development Program, and the PIM Artificial Intelligence Semiconductor Core Technology Development Program.

KAIST Develops New Concept Hologram Technology Whe..

<(From Left)Dr. Joonkyo Jung. Professor Jonghwa Shin> A new type of hologram technology has been developed that uses the motion of light as a “key,” revealing information only under specific conditions. This is gaining attention as a novel approach that can simultaneously overcome the limitations of existing optical communication and security technologies. KAIST (President Kwang Hyung Lee) announced on the 4th of May that a research team led by Professor Jonghwa Shin from the Department of Materials Science and Engineering has developed a next-generation vectorial hologram metasurface that uses the “total angular momentum (TAM)＊” of light as a key for information selection, enabling the realization of different vectorial images depending on the state of the incident light. ＊Total Angular Momentum (TAM): a physical quantity that represents both the vibration direction (polarization) and rotational (twisting) properties of light, enabling the creation of precise vectorial images whose intensity and polarization distribution vary depending on the state of light Previously, research utilizing either the vibration direction of light, known as “polarization,” or the property of light twisting in a helical form, known as “orbital angular momentum (OAM),” had been actively pursued. However, independently controlling these two properties within a single device had long been considered an unsolved challenge in the field of optics. To address this, the research team precisely designed nanoscale structures much smaller than the thickness of a human hair and implemented a “bi-layer metasurface” by stacking them in two layers. A metasurface is an optical device based on ultra-fine artificial structures designed to freely control the direction and properties of light. This device uses the “total angular momentum (TAM),” which combines the polarization and degree of twist of light, like a complex encryption key. In other words, the device responds and reconstructs hidden information only when light with a specific vibration pattern and a specific number of twists is incident. With this technology, even if light appears identical externally, the information cannot be read without the designated “light key,” ensuring high security. <Conceptual Diagram of the Study> In addition, the twisting state of light (OAM) can theoretically take on a very wide range of values, significantly increasing the amount of information that can be carried by a single light beam. This also enables expansion into ultra-high-capacity optical communication technologies capable of transmitting far more data simultaneously than before. In particular, this study is meaningful in that it goes beyond simple intensity-only image implementation and achieves a “vectorial hologram” that precisely controls the vibration direction (polarization) of light at each point in the image. A vectorial hologram is a high-dimensional holographic technology that represents not only the intensity of light but also its vibration direction information. <Vector hologram that generates independent intensity and polarization images depending on the conditions of the incident light> This achievement is the first demonstration that two key properties of light—polarization and twist—which had been difficult to separate physically, can be independently controlled within a single device. This is expected to enable applications not only in next-generation display technologies such as immersive holograms, smart glasses, augmented reality (AR), and virtual reality (VR) devices, but also in various fields including anti-counterfeiting security labels and ultra-high-speed optical communication. Professor Jonghwa Shin stated, “This study demonstrates that polarization and twist, which are fundamental properties of light, can be combined into a single independent information key and freely utilized,” adding, “It will evolve into a key platform for security systems that are difficult to replicate and for ultra-high-speed, ultra-high-capacity optical communication technologies.” This study, with Dr. Joonkyo Jung as the first author, was published online on March 12 in the international journal Advanced Materials. ※ Paper title: “Arbitrary Total Angular Momentum Vectorial Holography Using Bi-Layer Metasurfaces,” DOI: 10.1002/adma.202519106 This research was supported by the Ministry of Science and ICT through the “Nano Materials Technology Development Program” and the “Group Research Support Program,” as well as by the Ministry of Trade.

Abandoned Fallen Leaves Transformed into ‘Biodegra..

<(From left) (Top to bottom) Professor Jaewook Myung of the Department of Civil and Environmental Engineering, Dr. Shinhyeong Choe, Ph.D candidate Yongjun Cho, M.S candidate Hoseong Moon, (Center) Ph,D candidate Pham Thanh Trung Ninh> Fallen leaves, which were discarded every year, have been transformed into a resource that can replace waste plastics, a major nuisance in rural areas. A research team at our university has developed biodegradable agricultural vinyl made from fallen leaves, presenting a new way to solve the problem of conventional plastic vinyl, which has been pointed out as a cause of soil pollution. KAIST announced on April 30th that a research team led by Professor Jaewook Myung of the Department of Civil and Environmental Engineering developed an eco-friendly agricultural mulch film (an agricultural vinyl that covers the soil to suppress weeds and maintain moisture) that decomposes in the ground using fallen leaves collected from the campus and near the Gapcheon River in Daejeon. This research is significant in that it converted fallen leaves, which are non-edible biomass (plant resources not used for food) that were discarded as useless, into high-value functional materials. Mulch films, widely used in agricultural fields, are essential materials for suppressing weed growth and maintaining soil moisture. However, most films currently used are made of polyethylene (PE, a representative petroleum-based plastic), making them difficult to collect after use. Residuals left in the soil turn into microplastics (plastic particles so small they are invisible to the naked eye), causing environmental pollution. To extract key components from fallen leaves, the research team utilized a Hydrated Deep Eutectic Solvent (DES, a special eco-friendly solvent with low toxicity) that mixes citric acid and choline chloride. Through this, they extracted nanocellulose (plant-derived nanofibers with high strength and eco-friendliness) obtainable from plant cell walls and combined it with polyvinyl alcohol (PVA, a water-soluble and naturally degradable polymer material) to produce a composite film. In particular, the eco-friendliness was further enhanced by performing all manufacturing processes based on water instead of harmful organic solvents. The "fallen leaf film" developed in this way showed sufficient performance even in actual agricultural environments. As a result of the experiment, it effectively blocked ultraviolet rays (UVA and UVB) and exhibited moisturizing performance that suppressed soil moisture loss to a level of about 5％ for 14 days. In addition, ryegrass grown using this film showed better growth status than cases where no film was used. <Figure 1. An eco-friendly strategy that upcycles low-utilization fallen leaves into biodegradable mulching film for natural soil, along with the concept of applying sustainable plasticulture.> <Figure 2. A schematic diagram of the fabrication process and self-assembly mechanism by which a mulching film is formed through complex hydrogen-bonding interactions> Biodegradation performance was also confirmed. As a result of testing under soil conditions, the developed film decomposed by 34.4％ in about 115 days, showing a faster decomposition rate than conventional biodegradable films. Furthermore, it was confirmed that plant toxicity (harmful effects on plant germination or growth) did not occur during the decomposition process, thus not affecting the germination and early growth of ryegrass and bok choy. Professor Jaewook Myung said, “This research is meaningful in that it went beyond simply processing fallen leaves and converted them into functional materials that can protect the agricultural environment. Through the use of fallen leaves that do not compete with food resources and water-based processes, it can be utilized as a sustainable alternative technology for agricultural plastics.” This research was participated in by Pham Thanh Trung Ninh, a PhD student in the Department of Civil and Environmental Engineering, as the first author. The research results were published on February 6, 2026, in ‘Green Chemistry,’ an international academic journal in the fields of chemistry and environment, and were selected as the journal’s inside front cover. ※ Paper Title: All-water-based fabrication of biodegradable mulch films from dead leaves via complex hydrogen-bonded networks, DOI: 10.1039/d5gc06616f (Author Information: Pham Thanh Trung Ninh (KAIST, First Author), Shinhyeong Choe (KAIST), Yongjun Cho (KAIST), Hoseong Moon (KAIST), Jaewook Myung (KAIST, Corresponding Author) total of 5 persons) <Figure 3. The inside front cover page of the latest issue of the Green Chemistry journal> Meanwhile, this research was conducted with the support of the Excellent Young Researcher Program of the National Research Foundation of Korea under the Ministry of Science and ICT and the KAIST Grand Challenge 30 project funds.

KAIST Identifies Multiple Viruses and Variants Sim..

<Professor Sungmin Son, (From Upper Left) Professor Dan Fletcher, Professor Melaine Ott> As the spread of infectious diseases accelerates, technologies that can accurately distinguish multiple viruses in a single test are becoming increasingly important. KAIST and an international research team have developed a new diagnostic technology that simultaneously identifies various viruses and variants by controlling the “speed” of gene scissors. This technology is expected to transform responses to emerging infectious diseases, as it can detect multiple infections at once while reducing the complexity of testing procedures. KAIST (President Kwang Hyung Lee) announced on the 26th of April that a research team led by Professor Sungmin Son from the Department of Bio and Brain Engineering, in collaboration with researchers from the University of California, Berkeley (UC Berkeley) and the Gladstone Institutes, has developed a new ribonucleic acid (RNA) diagnostic technology that can distinguish multiple viruses and variants simultaneously by utilizing the reaction speed of gene scissors. The tool used by the research team is a CRISPR-based protein called Cas13. Gene scissors are proteins that locate and cut specific genetic material, becoming activated when they recognize their target. Cas13 specifically targets RNA. When it finds its target, it becomes activated and cuts surrounding RNA, generating a fluorescent signal. Existing technologies require the use of different gene scissors or various fluorescent colors to detect multiple viruses simultaneously, making the system complex and difficult to apply in real-world settings. The research team took a different approach. They focused on the fact that when gene scissors bind to their target, the speed of “cutting” varies depending on the type of virus. By observing at the single-molecule level within tiny droplets, they confirmed that unique reaction speed patterns emerge depending on the combination of guide RNA and target RNA. Guide RNA is an RNA molecule that provides “positional information,” guiding the gene scissors to their target. < Conceptual diagram of kinetic barcoding using the reaction rate of the CRISPR Cas13 enzyme. The dashed area on the right represents the guide RNA region modified to control the reaction rate. > Based on this, the research team developed a “kinetic barcoding” technology that uses differences in reaction speed like a barcode. This method interprets reaction speeds as signal patterns to distinguish different viruses. Through this technology, it became possible to simultaneously identify multiple viruses and variants using only a single type of gene scissors. < Multiplex virus detection using microdroplet-based kinetic barcoding > In addition, by adjusting the design of guide RNA, the cutting speed of gene scissors can be tuned, enabling scalable and simultaneous detection of a wide range of viruses. The testing process has also been greatly simplified. In conventional methods, detecting RNA viruses requires a “reverse transcription” process that converts RNA into DNA, but this technology enables direct detection of RNA as it is. Reverse transcription is a step that increases testing time and complicates procedures. When tested on actual clinical samples, the technology successfully distinguished various respiratory viruses and SARS-CoV-2 variants in a single reaction. Professor Sungmin Son stated, “This study goes beyond simply determining whether a virus is present, and is the first case to use the reaction speed of gene scissors as a new form of diagnostic information,” adding, “It will become a next-generation platform capable of diagnosing various infectious diseases at once in the field.” This study was led by Professor Sungmin Son of KAIST as the first author and co-corresponding author, and was published on March 31, 2026, in the world-renowned journal in bioengineering, Nature Biomedical Engineering. ※ Paper title: “Programmable kinetic barcoding for multiplexed RNA detection with Cas13a,” DOI: 10.1038/s41551-026-01642-6 This research was supported by KAIST’s New Faculty Settlement Research Fund and by the U.S. National Institutes of Health (NIH/NIAID).

AI Computation Enables Clearer Views of the Deep B..

< Professor Iksung Kang, KAIST > Observing the depths of a living brain with clarity has traditionally required expensive, high-end equipment. However, a KAIST research team has advanced neuroscience research by developing a physics-based AI computational algorithm that restores blurred images into sharp ones without the need for additional optical measurement hardware. KAIST (President Kwang Hyung Lee) announced on April 21st that Professor Iksung Kang (School of Electrical Engineering), in collaboration with Professor Na Ji's research team at UC Berkeley, has developed a technology that accurately corrects image aberrations in microscopes used for live biological imaging. Notably, the experimental design and algorithm development – the core components of this technology – were led by Professor Kang during his postdoctoral fellowship in Professor Na Ji’s group. This breakthrough was achieved using Neural Fields — a neural network-based technology that continuously represents 3D spatial structures to simultaneously reconstruct clear images and volumetric forms. The research team utilized Two-Photon Fluorescence Microscopy, a core technology for observing deep within living biological tissues by using two low-energy photons simultaneously to selectively illuminate specific points. However, as light passes through thick tissue, it bends and scatters, causing the image to become blurred — much like how objects appear distorted underwater. This phenomenon is known as optical aberration. Previously, correcting these distortions required adding complex and costly hardware, such as wavefront sensors, which measure exactly how much the light path has deviated. < Framework for Integrated Distortion Correction in Two-Photon Fluorescence Microscopy > In contrast, the research team developed an algorithm that inversely calculates how light was distorted using only the captured image data and corrects it. In other words, it is a method of restoring image clarity by analyzing blurred photos, without relying on any additional equipment. The core of this technology is a machine learning algorithm based on the Neural Fields model. This algorithm tracks the distortion process that occurs as light travels, implementing an integrated technology that compensates not only for optical aberrations caused by biological tissue but also for microscopic movements of the living specimen and alignment errors of the microscope itself. As a result, the team successfully and reliably obtained high-resolution, high-contrast images from deep within biological tissues, without any separate aberration measurement or correction devices. This research is particularly significant because it overcomes the conventional limitation that “better images require more expensive equipment” by solving the problem through a software-based approach. This is expected to lower the burden of research equipment costs and allow more researchers to perform precise brain observations. < Comparison of images using a framework that integrates correction for optical aberrations, sample motion, and microscope errors (AI-generated image) > Professor Iksung Kang stated, “This research opens the way to see more accurately inside living organisms by combining optics and artificial intelligence technology. Moving forward, we plan to develop this into an intelligent optical imaging system where the microscope itself finds the optimal image.” This study was published on April 13th in Nature Methods, a leading methodology journal in the field of life sciences. Paper Title: Adaptive optical correction for in vivo two-photon fluorescence microscopy with neural fields DOI: 10.1038/s41592-026-03053-6 Authors: Iksung Kang (KAIST, Co-corresponding & First Author), Hyeonggeon Kim, Ryan Natan, Qinrong Zhang, Stella X. Yu, & Na Ji (UC Berkeley, Co-corresponding Author)

Zero-Crease Foldable Technology to Shift the Parad..

< Professor Phil-Seung Lee (center), Master’s graduate Jun-han Bae (top left) > The "crease," long considered the biggest weakness of foldable smartphones, has been pointed out as a major obstacle to market expansion, causing screen distortion and reduced durability over repeated use. A research team at KAIST has presented a solution to this problem, marking a turning point for foldables to leap forward as the standard for next-generation smartphones. Furthermore, the technology is expected to establish itself as a core component of the future mobile industry, expanding into various devices such as laptops. KAIST announced on April 20th that a research team led by Professor Phil-Seung Lee of the Department of Mechanical Engineering has developed an original technology capable of fundamentally solving the crease issue that occurs at the folding area of foldable smartphone displays and has registered a patent for it. The team has secured global technological competitiveness by filing patent applications in the United States, China, and the European Union (EU), in addition to South Korea. While global smartphone companies have attempted to solve this issue through massive R&D investments for years, they have yet to achieve the complete removal of the crease. Consequently, the industry has identified the crease problem as the single greatest barrier to the widespread adoption of the foldable smartphone market. The research team began their study to resolve the inconveniences they personally experienced while using mobile foldable phones. After disassembling dozens of used foldable phones and repeating various experiments, they derived a solution by innovatively redesigning the "adhesive area" between the display and the supporting plate. The core of the design is ensuring that deformation is not concentrated in a specific folding area but is instead distributed to the surrounding sections. Through this, they perfectly demonstrated the feasibility of a "crease-free foldable" while maintaining normal smartphone functionality. To verify performance, the team shone a straight-line LED light onto the screen. Unlike commercial products where the light refracts and the straight line appears curved at the fold, the prototype maintained a sharp, straight reflection without any distortion. Notably, no visual distortion appeared even under conditions sensitive enough to detect minute curves with a crease depth of less than 0.1mm. < Display surface reflecting a straight-line LED lamp > This technology presents a new design paradigm that surpasses the limitations faced by the current industry. It not only fundamentally suppresses the formation of creases but also ensures superior durability by minimizing deformation even after tens of thousands of folding cycles. Furthermore, because the structure is intuitive and simple, it can be easily integrated into existing manufacturing processes. It is expected to have high industrial utility, as it can be expanded beyond smartphones to various foldable display devices, including tablets and laptops. < Core idea of the invention: (a) Adhesive and non-adhesive areas of a conventional foldable smartphone, (b) Adhesive and non-adhesive areas in this invention, (c) Stress distribution in a conventional foldable smartphone display, (d) Stress distribution in a foldable smartphone display applying this technology > Industry experts anticipate that the commercialization of this technology will encourage global companies—which have been hesitant to enter the market due to crease issues—to participate. This is projected to significantly improve consumer satisfaction and accelerate the growth of the stagnating foldable market. Professor Phil-Seung Lee stated, "We have solved a challenge that global giants could not resolve, using a relatively simple and clear method. We expect this technology to spread across next-generation displays, including laptops and tablets, further strengthening Korea's technological competitiveness." Meanwhile, this research was conducted with support from the "2022 Daedeok Innopolis Campus Project," and the patent for the related original technology was registered on September 9, 2025.

Development of Dream Battery Material： Air-Stable ..

<(Bottom row, from left) Dr. Jae-Seung Kim (Seoul National University), Prof. Dong-Hwa Seo (KAIST), Researcher Heeju Park (KAIST), Researcher Jiwon Seo, Researcher Jinyeong Choe. (Top row, from left) Researcher Hae-Yong Kim (Dongguk University), Prof. Eunryeol Lee (Chungbuk National University), Prof. Kyung-Wan Nam (Dongguk University), Prof. Yoon Seok Jung (Yonsei University)> Expectations are rising for all-solid-state batteries—the "dream battery" with low fire risk—not only for electric vehicles but also for various fields such as robotics and Urban Air Mobility (UAM). A research team at our university has presented a new design principle that simultaneously overcomes the limitations of solid electrolytes, which were previously vulnerable to air exposure and suffered from low performance. This technology is gaining significant attention as it can enhance both battery safety and charging speeds, demonstrating the feasibility of commercializing next-generation all-solid-state batteries. KAIST announced on April 16th that a research team led by Professor Dong-Hwa Seo from the Department of Materials Science and Engineering, through joint research with teams from Dongguk University (President Jae-Woong Yoon), Yonsei University (President Dong-Sup Yoon), and Chungbuk National University (Acting President Yu-Sik Park), has developed a design technology for solid electrolytes used in all-solid-state batteries. This technology maintains structural stability even when exposed to air while dramatically increasing ionic conductivity. Unlike conventional lithium-ion batteries that use liquid electrolytes, all-solid-state batteries are spotlighted as next-generation batteries due to their low fire risk. Among these, halide-based solid electrolytes—which contain halogen elements such as chlorine (Cl) and bromine (Br)—are advantageous in terms of performance due to their high ionic conductivity. However, they are known to be difficult materials to manufacture and handle because they are highly vulnerable to moisture in the air, which easily degrades their performance. To solve this problem, the research team introduced a new structure called "Oxygen Anchoring." This method involves stably bonding oxygen inside the electrolyte to strengthen its structural intergrity, a process in which the element Tungsten plays a key role. < Research image on tungsten-based oxygen fixation strategy > As a result, it was confirmed that the electrolyte maintains a stable structure without collapsing, even in air-exposed environments. Furthermore, the research team improved battery performance in addition to stability. The changes in the internal structure of the electrolyte widened the pathways for lithium ions, allowing them to move more smoothly and increasing the ion migration speed. It was confirmed that the oxygen-incorporated material exhibited an ionic conductivity approximately 2.7 times higher than that of conventional zirconium (Zr)-based halide solid electrolytes. Another feature of this technology is that it is not limited to a specific material. The research team applied the same strategy to various halide solid electrolytes, including those based on zirconium (Zr), indium (In), yttrium (Y), and erbium (Er), and confirmed similar effects. This demonstrates that it is a "universal design principle" applicable to a wide range of battery materials. < Research image (AI-generated image) > The research team expects this technology to contribute to the development of solid electrolytes that possess both air stability and high performance. Professor Dong-Hwa Seo stated, "This study presents a new material design principle that optimizes multiple performances through a structural design strategy that simultaneously improves air stability and ionic conductivity. It will serve as a key indicator for future all-solid-state battery research and process development." This study involved Jae-Seung Kim (formerly KAIST, now SNU), Heeju Park, and Hae-Yong Kim as joint first authors. The research included contributions from Eunryeol Lee, Heewon Kim, Soeul Lee, Jinyeong Choe, Jiwon Seo, Hyeon-Jong Lee, Hojoon Kim, Jemin Yeon, and Yoon Seok Jung. The findings were published on March 6, 2026, in the international academic journal Advanced Energy Materials. Paper Title: Universal Oxychlorination Strategy in Halide Solid Electrolytes for All-Solid-State Batteries DOI: https://doi.org/10.1002/aenm.202506744 This research was conducted with support from the Samsung Electronics Future Technology Promotion Center and the Nano and Materials Technology Development Program of the National Research Foundation of Korea. Computational studies were performed using the resources of the National Supercomputing Center.

Breakthrough in Data Processing via Light Control...

< (From left) Undergraduate researcher Taewon Kim and Professor Sangsik Kim > A new technology has been developed that allows light to be "designed" into desired forms, potentially making Artificial Intelligence (AI) and communication technologies faster and more accurate. A KAIST research team has developed an "integrated photonic resonator"—a core component of next-generation optical integrated circuits that process data using light. The research is particularly significant as it was led by an undergraduate student. This technology is expected to serve as a key foundation for next-generation security technologies such as high-speed data processing and quantum communication. KAIST announced on the 15th that a research team led by Professor Sangsik Kim from the School of Electrical Engineering, in collaboration with Professor Jae Woong Yoon’s team from the Department of Physics at Hanyang University (President Kigeong Lee), has developed a new integrated photonic resonator structure capable of freely controlling optical signals by utilizing light interference (the phenomenon where two light waves meet and influence each other). Photonic Integrated Circuits (PICs) process data at ultra-high speeds and with low power consumption using light. They are garnering significant attention as a fundamental platform technology for next-generation fields such as AI, data centers, and quantum information processing. The core of this technology lies in the precision with which light can be controlled. Specifically, the ability to freely adjust the spectrum (color or wavelength distribution) and phase response (timing or wave position) of optical signals is essential for implementing high-performance optical communication and computing. However, conventional methods have faced fundamental limitations. The integrated photonic resonator (optical resonator) focused on by the research team is a key optical device that traps light in a specific space to amplify it or select specific colors (wavelengths), similar to how the body of a musical instrument amplifies sound. However, existing single-bus resonators have had limitations in precisely adjusting the phase and spectrum of optical signals. To overcome these challenges, the research team introduced a "dual-bus" structure. This design allows light that has passed through the resonator to recombine with light that has not, enabling precise control over interference. This allows for the free design of optical signals into desired forms, making it possible to control various types of light signals that were previously difficult to implement. By applying this technology, the research team secured new characteristics for more precise control of wavelength properties and presented new possibilities for non-linear frequency conversion research (changing the color of light). Utilizing this technology enables faster and more accurate data processing, which is expected to provide the groundwork for performance enhancements in future high-speed data centers, AI accelerators, and quantum communication systems. This research is especially meaningful as it was led by an undergraduate student. Taewon Kim, an undergraduate student who conducted the study through the KAIST Undergraduate Research Program (URP), stated, "I was able to develop the resonator principles I learned in the Introduction to Integrated Optics class into actual device designs and a published paper." < Research Image of the Dual-bus Resonator > Professor Sangsik Kim remarked, "This study goes beyond proposing a new device; it demonstrates that by precisely analyzing previously overlooked optical characteristics, physical limitations can be overcome. We expect this to contribute broadly to the development of optics-based AI accelerators and optical communication technologies." KAIST undergraduate student Taewon Kim participated as the lead author of this study, and the results were published on March 6th in the international optics journal, Laser & Photonics Reviews. Paper Title: Dual-bus resonator for multi-port spectral engineering DOI: 10.1002/lpor.202502935 Authors: Taewon Kim, Mehedi Hasan, Yu Sung Choi, Jae Woong Yoon, and Sangsik Kim This research was supported by the KAIST URP Program, the Institute of Information & Communications Technology Planning & Evaluation (IITP), the U.S. Asian Office of Aerospace Research and Development (AOARD), and the National Research Foundation of Korea (NRF).

AI Fixed ＇Temporal Errors＇... Enhancing Reliabilit..

<Ph.D candidate Soyeon Kim, (From Left)Jindong Wang (Microsoft; currently at the College of William & Mary), Xing Xie (Microsoft), and Steven Euijong Whang (Professor at KAIST)> What if ChatGPT answered with the name of a minister from a year ago when asked, "Who was the minister inaugurated last month?" This is a prime example of the limitations of AI that fails to properly reflect the latest information. Our university’s research team has developed a new evaluation technology that automatically reflects changing real-world information while catching "temporal errors" that may appear correct on the surface. This is expected to drastically improve AI reliability. KAIST announced on April14th that a research team led by Professor Steven Euijong Whang from the School of Electrical Engineering, in joint research with Microsoft Research, has developed a system that automatically evaluates and diagnoses the temporal reasoning capabilities of Large Language Models (LLMs) using temporal database technology. For AI to earn user trust, the ability to accurately understand real-world information that changes moment by moment is essential. However, existing evaluation methods only checked whether the answer matched or failed to sufficiently reflect complex temporal relationships, making it difficult to properly evaluate various question scenarios occurring in actual environments. To solve this, the research team introduced "Temporal Database" design theory—which has been verified over the past 40 years—into AI evaluation for the first time. By utilizing the temporal flow and relational structure of data, the core of this technology is the automatic generation of 13 types of complex time-based problems from the database itself, without the need for humans to manually write evaluation questions. <Schematic Diagram of the Evaluation Framework Proposed in This Study> In particular, this technology is evaluated as a major innovation because it shifts from the traditional method where humans manually created problems to a method where evaluation questions are automatically generated based on data. Furthermore, by automating the entire process from problem generation to answer derivation and verification based on the database, the burden of maintenance can be drastically reduced without the need to manually modify questions as was previously required. When real-world information changes, the evaluation questions, answers, and verification criteria are automatically updated simply by updating the corresponding content in the database. While the input of the latest information itself is handled by external data or administrators, this technology is structured to perform the overall evaluation automatically after such data is updated. Additionally, moving beyond the existing method of simply judging whether the final answer is correct or incorrect, the research team introduced a new metric that verifies the logical validity of dates or periods presented during the answering process. Through this, they achieved a performance improvement in detecting "Temporal Hallucination" phenomena—where an answer appears correct but has the wrong temporal basis—by an average of 21.7％ more accurately than before. Applying this technology can significantly reduce evaluation maintenance costs since only the database needs to be updated when information changes, and it showed an effect of reducing the amount of input data by an average of 51％ compared to previous methods. <Future AI Evaluation System (AI-Generated Image)> Professor Steven Euijong Whang stated, "This research is an example showing that classical database design theory can play a crucial role in solving the reliability issues of the latest AI. By converting vast amounts of professional data into evaluation resources, we expect this to become a practical foundation for verifying AI performance in various fields such as medicine and law in the future." Soyeon Kim, a PhD student at KAIST, participated as the lead author of this study, and Jindong Wang (Microsoft Research, currently at William & Mary) and Xing Xie (Microsoft Research) participated as co-authors. The research results will be presented this April at ICLR 2026, the most prestigious academic conference in the field of artificial intelligence. Paper Title: Harnessing Temporal Databases for Systematic Evaluation of Factual Time-Sensitive Question-Answering in Large Language Models Paper Link: https://arxiv.org/abs/2508.02045 Meanwhile, this research was conducted with support from Microsoft Research, the National Research Foundation of Korea, and the Institute for Information & Communications Technology Planning & Evaluation (IITP) Global AI Frontier Lab projects (RS-2024-00469482, RS-2024-00509258).