A joint research team from KAIST and the APEC Climate Center found that the East Asian summer front has migrated north over the past half century, increasing the risk of heavy rain and heat stress in Korea. The study suggests that summer disaster planning should address flood prevention and heat-illness management together.
A KAIST research team developed a technique to predict OLED lifetime by analyzing small changes in brightness caused by a magnetic field. The method is expected to reduce development time and cost by identifying the most likely to last longer, supporting the development of high-efficiency, long-lifetime OLEDs.
KAIST researchers developed a wearable eyedrop patch that delivers eyedrops to the eye without relying on gravity, for use in space. The patch uses pressure generated inside it to deliver the eyedrop, and has been confirmed to release eyedrops consistently even in different gravity directions.
The research team trained the core image-generating model from scratch on Earth observation data to learn the features of diverse terrain and urban areas. The AI can restore cloud-covered images and convert radar images into images that resemble ordinary photographs with high accuracy.
KAIST researchers developed an unmanned synthesis platform combining robots and light to automate the entire process from mixing raw materials to synthesis and analysis. The platform successfully synthesized the N-methyl pyrrole scaffold and demonstrated potential for continuous manufacturing.
A research team led by KAIST proposes a definition of the Anthropocene, using 1952 as a starting point, to better understand human impact on the environment. The proposed framework aims to establish a consistent understanding of the Anthropocene across disciplines.
Researchers at KAIST created a technology that analyzes daily stress by identifying recurring smartphone behaviors, such as messaging and financial transactions. The system achieved an accuracy of over 95% in classifying behaviors across different apps, and its long-term data showed a more stable structure than conventional approaches.
Researchers at KAIST have developed a dual-state programmable oxide transistor that can implement both long-term and short-term memory independently. This technology uses physical changes within the semiconductor to control when information can be read, offering a secure way to protect sensitive data.
A KAIST research team developed a technology to precisely control the location of nucleation in 2D semiconductor crystals, allowing for deterministic growth at desired positions. This approach enables high-quality semiconductors directly at the required positions on a chip, reducing grain boundaries and improving semiconductor quality.
Researchers created a small soft robot called BeetleBot that combines artificial muscles, a camera, and tactile sensors to perform tasks like gripping objects and avoiding obstacles. The robot uses bidirectional feedback to connect user control with sensory information, enabling practical tasks to be carried out.
A Korean research team has identified the process by which azobenzene changes its structure after absorbing light. The molecule changes shape through a coordinated motion of the two nitrogen atoms at its center, while its benzene rings stay nearly in place.
Researchers at KAIST have discovered that VEGF-C brings two VEGFR-3 receptors together, leading to clustering and amplification of lymphangiogenic signaling. This process may provide new strategies for treating related diseases such as lymphedema and cancer metastasis.
KAIST researchers created a single soft material that combines sensing and actuation, holding its deformed shape for over 10 minutes after light is turned off. The material detects charged objects and is actuated by UV light, with potential for reducing components and wiring in soft robots.
Researchers have developed a technology that stacks semiconductor devices with different response speeds to process fast and slow signal changes together. The technology could be applied to small devices that analyze movement and physiological signals, enabling the recognition of changes in motion over time.
A KAIST research team has developed a genetic switch that works in both bacteria and yeast, allowing for controlled production of a green pigment in both microbes. The hybrid promoter system can be used to select the microbe best suited for producing a target compound, reducing the need for redesigning control elements.
A secure sense of attachment within a group enables members to express dissenting opinions more effectively, leading to better decision-making. This approach can help organizations tap into the knowledge and insights of their most critical employees, who often remain silent due to fear of backlash.
A quadruped robot, RAIBO2, completed a 42.195 km marathon without battery swap, capturing 4 hours and 19 minutes of real-world running data. The research team developed design principles for long-distance operation, focusing on system-level efficiency and reliability.
A Korean research team has developed NUDGE, a foundational technology that redirects cell fate in a desired direction through a minimal, temporary intervention. The approach harnesses the gene regulatory dynamics already present within cells, allowing for a single temporary stimulus to guide a cell to a desired state. NUDGE's technolog...
Researchers at KAIST have developed a technology to extend the lifespan of anode-free batteries by applying nanofabrication techniques to create uniform sites for lithium deposition and a robust protective layer. This technology enables smaller and lighter EV batteries with improved energy density.
Researchers at KAIST developed CURE, a technology that enables small AI models on smartphones to work efficiently with large models on servers, reducing server calls by an average of 55.61% while maintaining high accuracy. This approach allows for faster decisions with less server support.
A KAIST research team developed a strategy to balance radical generation and catalyst regeneration, broadening the possibility of synthesizing complex molecules. The team used a ligand to regulate the copper catalyst's redox behavior, enabling efficient radical generation and catalyst regeneration.
Recent advances in high-performance graphene fibers based on graphene oxide liquid crystals have improved strength and thermal conductivity. Researchers at KAIST and worldwide have developed technologies to overcome limitations, leading to applications in consumer products and emerging fields.
Researchers developed a single-material 'universal charge injector' that injects charge into two types of ultrathin semiconductors using tin diselenide (SnSe2). This technology addresses a major obstacle in atomically thin semiconductors, enabling efficient charge injection and paving the way for smaller, more energy-efficient AI chips.
Researchers found that m6A, a small chemical modification on RNA, acts as a molecular delivery tag to transport specific RNAs to distant regions of neurons. The study provides a basis for investigating RNA delivery errors in brain disorders and may inform the development of new therapeutic strategies.
Researchers developed a wearable electroceutical platform with microneedle electrodes that deliver stable electrical stimulation while reducing the influence of sweat or dead skin cells. The device can be remotely controlled via smartphone and automatically detaches when skin overheats for enhanced safety.
Researchers developed Neural Value Alignment (NVA), a brain-computer interface technology that detects cognitive mismatches between humans and AI through brainwaves. The AI system can revise its actions in real time according to human goals, accelerating the shift from explicit command-based AI to inferential intent-based AI.
A KAIST research team found that all-trans retinoic acid (ATRA) preserves T cells' function and enhances the efficacy of immunotherapy for intractable brain tumors. ATRA suppresses 'terminal exhaustion' in cancer-attacking CD8⁺ T cells, allowing them to maintain their ability to kill brain tumor cells.
A KAIST research team has identified the cause of measurement artifacts in nanoscale battery analysis, which can lead to misinterpretation of ion movement. The team developed a method to reduce these artifacts by smoothing battery material surfaces.
Researchers at KAIST discovered that weak hydrogen bonds can block copper's tendency to reshape its bonding structure, making it less stable. This finding opens new avenues for selective metal separation and recognition, as well as catalyst design.
KAIST researchers develop SafeQL, a technology that identifies and selectively corrects errors in AI-generated SQL queries, reducing the need to regenerate entire queries. The technology improves data retrieval accuracy and speed, accelerating the adoption of AI work assistants in enterprise environments.
KAIST researchers have developed a new catalyst that can remove tetrafluoromethane (CF₄), a greenhouse gas 6,000 times more potent than CO₂, with high efficiency. The catalyst, called entropy-stabilized aluminate (ESA), harnesses the power of disorder to stabilize its structure and maintain performance over extended periods.
A KAIST-developed micro-LED mask boosts skin rejuvenation and brightening through close skin contact, while PN injections provide synergistic benefits for skin regeneration and recovery. The mask achieves 340% greater improvement in deep skin elasticity than conventional LED masks.
A KAIST team uses AI to identify optimal material recipe for 3D-printable, highly stretchable material. The material printed reliably on a DLP 3D printer and showed high stretchability, extending to over six times its original length.
KAIST researchers analyzed key challenges in microbial food industry and proposed growth strategies for next-generation protein market. The study emphasizes the importance of manufacturing readiness, market entry strategies, and regulatory compliance in commercializing microbial foods.
Researchers at KAIST have developed a low-cost smartphone-based technology to detect hidden cameras by analyzing reflections from objects. The technology, called SweepLED, uses deep learning-based analysis to distinguish camera lenses from ordinary objects, achieving 94% detection accuracy. The technology has potential to be developed ...
A team of Korean researchers has created a miniaturized wireless brain implant that can deliver drugs and light to precisely modulate targeted neurons remotely. The device overcomes distance and location constraints, enabling long-term studies of brain disorders and therapeutic devices.
Researchers create unique 'artificial fingerprints' using nanoparticles that can be authenticated with smartphone flashlight and laser pointer. The technology has potential applications in anti-counterfeiting and electronic device authentication.
A KAIST research team developed a 3D digital twin of a commercial graphite anode to analyze localized degradation mechanisms during fast charging. They found that binder and pore space distribution significantly impacted battery performance and lifespan.
Researchers created a technology that controls the thickness and structure of a polymer coating, allowing more water droplets to form and detach quickly. This enhances heat transfer performance during condensation, improving energy efficiency in power plants and industrial applications.
A KAIST research team has identified the molecular lock that keeps cells trapped in an altered state, opening a new path toward releasing that lock and reversing a cell's fate. The team developed a fundamental control technology called ROOT that can regulate these circuits and restore biological states to their original condition.
KAIST researchers develop a new 'oxygen tunnel' structure to stabilize oxygen vacancies in oxide semiconductors, achieving world-class current density and data retention time. The technology is expected to improve next-generation compute-in-memory systems and accelerate AI era advancements.
A KAIST research team has developed a new electrode material that sequentially stores zinc ions and protons, enabling high storage capacity and fast charging/discharging performance. The material achieved 368.7 mAh g⁻¹ storage capacity and retained 46.9% of its capacity even at 16-fold increased charging/discharging rates.
A Korean research team developed a patient-specific blood-brain tumor barrier-on-a-chip model to predict individual responses to glioblastoma therapies. The chip recreates a patient's own tumor cells together with the surrounding peritumoral vascular environment, allowing for precise predictions of treatment responses.
Researchers develop a novel semiconductor technology that tunes noise to process different types of signals, enabling selective encoding of time-series signals across different frequency bands. The technology achieved accuracies of 94.8% in human activity recognition and 95.0% in speech recognition.
Researchers at KAIST create microscale chiral pinwheel arrays through self-assembly of achiral liquid-crystal molecules, enabling circularly polarized light with a desired rotation direction. This breakthrough simplifies the production of chiral optical materials, paving the way for next-generation displays and optical communications.
The KAIST research team has successfully developed a new, eco-friendly hydrogen separation membrane that filters hydrogen through a molecular network. The membrane achieved a high bridge connectivity degree of 73% and showed significant improvements in hydrogen permeability and selectivity.
The KAIST research team developed an explainable AI technology that detects patterns of foreign-linked influence operations in online news comments. The model identifies 23,998 accounts exhibiting patterns consistent with public-opinion manipulation, targeting division and confrontation within Korean society.
A KAIST research team has demonstrated for the first time that a porous material can arrange disordered gas molecules into a crystal-like structure. Using xenon as a model system, they identified a specific cobalt-based material that stabilizes xenon in a regular lattice, showcasing a breakthrough in gas crystallization.
Researchers developed a programmable dynamic memtransistor that can process data at different speeds, reducing prediction errors by up to 40-fold. The technology enables accurate information processing even when input speeds vary.
A KAIST research team has developed a technology that reconstructs the shape, optical thickness, and position of a transparent object from a single shot. The technique uses an optical model and AI framework to analyze light intensity and overcome challenges in conventional phase imaging.