Researchers at KAIST discovered that a DNA repair enzyme uses a one-dimensional diffusion strategy to search for damaged sites. The team found that an intrinsically disordered region plays a key role in the DNA search process and stabilizes binding between APE1 and DNA with magnesium ions.
Researchers at KAIST have developed a new catalyst design technology that can improve the efficiency of key reactions in batteries and fuel cells. By adjusting the electrical environment around the catalyst, they were able to increase the desired reaction by 52%, leading to improved performance, lifespan, and stability.
Researchers developed a innovative technology that rapidly discharges bubbles and boosts hydrogen production efficiency by clearing pathway blockages in the catalyst layer. The new structure allows water and gas to pass through, improving stability and performance.
Researchers at KAIST have developed PAVAS, an AI technology that generates realistic sound effects in videos based on the physical properties of objects. The technology analyzes movement and collision characteristics to produce more immersive audio experiences.
Researchers at KAIST have developed an AI system that supports the initial psychiatric interview process, helping patients organize their symptoms and condition in advance. The system effectively obtained key clinical information within 30 minutes of conversation.
Researchers fabricated alloy catalysts made by mixing gold, silver, and palladium to analyze what substances these catalysts convert CO₂ into. Existing catalyst theories predicted that if the electronic reactivity of a catalyst is similar to that of copper, then it should produce multi-carbon compounds like ethylene and ethanol.
Researchers at KAIST have developed a new catalyst structure that improves the performance and durability of ammonia-based protonic ceramic fuel cells. The technology achieved world-class performance, recording a maximum power density of 2.04 W/cm², and demonstrated stable operation for over 255 hours.
Researchers at KAIST-Hanwha Solutions have established a new 'eco-friendly bio-platform' that can mass-produce sustainable raw materials for plastics and textiles using waste resources. The platform uses glycerol as a raw material to convert into 1,3-propanediol, a key material for plastics and cosmetics.
KAIST researchers have identified a neural circuit that switches between past and recent memories, allowing the brain to select necessary information. The study suggests that specific brain rhythms and states are crucial for effective memory retrieval, with longer online states leading to better recall of recent memories.
A real-time diagnostic smart dressing patch has been developed by KAIST to monitor diabetic foot wounds. The patch combines an optoelectronic sensor with a functional dressing to analyze glucose concentration, acidity, and temperature changes in real-time, enabling patients to check their condition using a smartphone.
Researchers at KAIST have developed a next-generation polarization sensor that can read the direction of light and change its own response, enabling high-accuracy object recognition in dark environments. This technology has the potential to improve autonomous driving and medical diagnostics with low energy consumption.
Scientists have identified the fundamental cause of performance decline in lithium metal batteries, which can lead to improved driving range and longer battery lifespan. The research team discovered that 'dead lithium' - electrically disconnected lithium - forms when irregular lithium deposition or stripping occurs, posing safety risks.
Researchers at KAIST demonstrated a chip-scale photonic approach for generating ultralow-noise and highly stable microwave and millimeter-wave signals based on optical frequency combs. The study enabled direct transfer of optical-reference stability to the microcomb, achieving record-breaking performance in low-offset frequencies.
Researchers at KAIST and Stanford University discovered that complex compositions of multimetallic nanoparticles lead to their growth into more uniform structures, contrary to conventional expectations. This phenomenon enables the creation of high-performance catalysts and eco-friendly energy materials.
A KAIST research team developed a new approach to solving combinatorial optimization problems, which can be implemented entirely using existing silicon processes. This enables faster and more accurate decision-making across various industries, including logistics, finance, and semiconductor design.
A new approach has been proposed to address the problem of overconfidence in AI, enabling it to recognize situations involving unfamiliar or unseen knowledge. By incorporating key principles of brain development, AI can develop the ability to distinguish 'what it knows' from 'what it does not know', a crucial step towards meta-cognition.
Researchers at KAIST have developed a novel diagnostic technology that can distinguish multiple viruses and variants by controlling the speed of CRISPR gene scissors. This method, called kinetic barcoding, interprets differences in reaction speeds as signal patterns to identify different viruses.
Researchers at KAIST developed an AI algorithm to correct image aberrations in microscopes, allowing for high-resolution imaging of deep biological tissues. The technology uses Neural Fields to track distortion and compensate for optical aberrations, overcoming the need for costly hardware.
A team of researchers from KAIST has developed a DNA-based molecular computer that can operate at a much smaller scale than conventional semiconductor devices. The system enables both computation and memory within the same device, opening up new possibilities for future computing technologies in bio and medical applications.
Researchers at KAIST developed a new technology using spin waves to process signals, reducing heat generation and power consumption. This breakthrough enables instantaneous frequency switching and is expected to pave the way for smart devices with less heat and longer battery life.
Researchers at KAIST InnoCORE successfully designed artificial proteins using AI to recognize specific compounds. The team developed an AI model that reflects protein-ligand interactions and designed binding proteins for six types of compounds, including metabolites and small-molecule drugs.
Researchers at KAIST have developed a new electrode design that blocks water while maintaining efficient electrical conduction and catalytic reactions. The technology achieves 86% efficiency in converting CO₂ into plastic precursors, outperforming previous systems.
A research team analyzed data from the Annals of the Joseon Dynasty and Mungwa Bangmok to characterize career patterns of over 14,600 Joseon officials. They found that functional recruitment systems led to stability, but concentrated power resulted in inequality and stratification, ultimately leading to a national decline.
A KAIST research team identified the mechanism by which Graphene Oxide exhibits powerful antibacterial effects against bacteria while remaining harmless to human cells. The technology has been applied to consumer products, including a graphene antibacterial toothbrush that has sold over 10 million units.
Professor Lee's doctoral thesis Empty Garden reinterprets uiwon through contemporary data and media language, exploring human sensation and existence in an AI-dominated environment. The work has been acquired by the Ashmolean Museum for its permanent collection, marking a rare distinction even within Oxford's 900-year history.
Researchers at KAIST discovered that skyrmions can spontaneously emerge from magnetism and lattice deformation in most magnetic materials. This finding could lead to the development of next-generation spintronics technology with higher data storage densities and lower power consumption.
Researchers at KAIST have developed a self-regenerating catalyst that restores its activity during operation, overcoming a major challenge in CO₂ conversion technology. The catalyst design strategy allows for continuous maintenance of active sites, enabling stable production of high-value chemicals.
A joint international research team has identified the core principle by which specific inhibitory neurons in the prefrontal cortex regulate cocaine-seeking behavior. The study revealed that addiction relapse is not due to a decline in brain function, but rather an imbalance in specific neural circuits.
Researchers have developed a groundbreaking technology that simultaneously analyzes gene expression, epigenome, and 3D genome structure within a single cell. This innovation enables precise identification of disease genes and their dynamics, laying the foundation for developing treatment strategies for complex diseases.
Researchers at KAIST have developed a technology that predicts atomic arrangement tendency of catalysts using artificial intelligence, leading to more efficient design of fuel cell catalysts. The zinc-platinum-cobalt catalyst secured both higher activity and superior long-term durability compared to commercial platinum catalysts.
A Korean research team developed a technology that resolves the most critical challenge of lithium-metal batteries, interfacial instability, by creating an intelligent protective layer. This allows lithium ions to move stably along the electrode surface, suppressing dendrite growth and extending battery lifespan.
Researchers at KAIST have developed a new image sensor technology that can accurately represent colors regardless of the angle at which light enters. The team achieved this by utilizing a 'metamaterial' that designs the movement of light through structures too small to be seen with the naked eye.
Researchers at KAIST create a new technique to process semiconductor surfaces uniformly down to the atomic level using carbon nanotubes as abrasive materials. This technology demonstrates potential to significantly improve surface quality and precision in advanced semiconductor processes like high-bandwidth memory.
Researchers at KAIST have developed an AI model that understands chemical principles to predict molecular structures, achieving up to 20 times higher accuracy than existing models. This technology can speed up research and development in various fields, including new drug development and material creation.
Researchers at KAIST have identified a new principle for catalyst design that allows ceria to selectively use different oxygen sources depending on the reaction environment. By adjusting the size of the catalyst, it can choose whether to use oxygen from the air or store it internally.
KAIST researchers propose a new approach to treating Alzheimer's disease by repositioning molecules without changing their chemical composition. The study demonstrates that subtle differences in molecular arrangement can regulate multiple disease-inducing factors, leading to significant improvements in memory deficits and cognitive imp...
Researchers at KAIST developed a new catalyst architecture that reduces precious-metal usage while enhancing hydrogen production and fuel-cell performance. The ultrathin nanosheet design increased the active surface area participating in reactions, enabling higher hydrogen production with less iridium.
Scientists directly observe charge density wave formation, fragmentation and persistence across a phase transition. Localized order is linked to strain, and isolated pockets persist above the transition temperature.
Researchers at KAIST have developed a new reference signal technology using laser light to precisely synchronize radio telescope observation timing and phase. This allows for clearer imaging of distant black holes and reduces phase delay errors between instruments.
Researchers at KAIST have developed a new surface-control technology to control, at the atomic level, the surface of indium phosphide magic-sized clusters, overcoming the limitation of luminescence efficiency below 1%. The breakthrough results in an 18-fold increase in brightness, opening up applications in next-generation displays and...
A KAIST research team developed a new analysis method to detect electronic traps in semiconductors with high sensitivity. The technique enables precise identification of defect sources, improving semiconductor performance and lifetime while reducing costs. The results demonstrate a 1,000x higher sensitivity than existing techniques.
Researchers at KAIST developed a new near-planar light outcoupling structure and OLED design method to significantly reduce light loss in OLED devices. This enables brighter displays with the same power consumption, extending battery life and reducing heat generation in mobile devices.
Researchers at KAIST have developed a new OLED technology that more than doubles screen brightness while maintaining the flat structure of OLED displays. The new technology uses a thin, near-planar light outcoupling structure and an OLED design method to significantly reduce light loss inside OLED devices.
A research team at KAIST has proposed an AI-driven approach to solve the long-standing mystery of gene function. The team suggests combining computational biology with experimental biology to discover gene functions, leveraging tools like AlphaFold and generative AI.
Researchers at KAIST and Yonsei University have identified Glial Progenitor Cells as the origin of IDH-mutant gliomas. The study reveals that these cells acquire the initial mutation long before a visible tumor mass forms, opening new paths for early diagnosis and treatment.
A Korean research team has developed a design method for core materials in all-solid-state batteries, improving performance while reducing costs. By introducing divalent anions like oxygen and sulfur, they enabled faster lithium-ion transport within solid electrolytes, lowering energy barriers.
Researchers have developed a new 3D printing method to create vertically stacked perovskite nanostructures, which can be used to make high-efficiency nanolasers. The technology achieves single-crystalline alignment and minimizes light loss, enabling commercialization in optical computing and quantum security applications.
KAIST researchers have developed a biomicrofluidic system that can recreate the process by which drug-induced muscle damage leads to kidney injury. The system allows for precise reproduction of inter-organ reactions, enabling the early prediction of drug side effects and identification of causes of acute kidney injury.
Researchers at KAIST have developed a new therapeutic approach that converts dormant immune cells inside tumors into potent anticancer agents. By reprogramming tumor-associated macrophages, they created CAR-macrophages that recognize and kill cancer cells while activating surrounding immune responses.
Researchers at KAIST developed 'SpecEdge,' a system that utilizes affordable, consumer-grade GPUs to provide AI services at lower costs. This technology significantly lowers LLM infrastructure costs and improves server throughput by up to 2.22 times.