A KAIST research team has developed a process that cuts the production time for vanadium redox flow batteries' core material by 67%, overcoming a critical bottleneck to commercialization. This breakthrough could significantly accelerate the development of large-capacity energy storage technology.
Researchers at KAIST have developed a technology converting CO2 dissolved in seawater into calcium carbonate, enabling permanent storage and helping the ocean absorb more carbon dioxide. The system reduced electricity consumption by up to 54% and produced high-purity hydrogen and magnesium hydroxide.
A research team at KAIST has developed RL-SPH, a reinforcement-learning-based method that can independently generate feasible solutions satisfying all constraints. The technique achieved a 100% feasibility rate across five benchmarks, reducing the primal gap by an average of 28.6 times and improving search efficiency.
A KAIST research team has developed an RNA-based therapeutic strategy that blocks a brain signal to prevent muscle loss and extend survival in cancer patients. The treatment showed significant improvements in both muscle loss and metabolic dysfunction, with a notable increase in survival rates among treated mice.
A KAIST research team developed two core technologies to correct AI hallucinations caused by sensory misinterpretation. The first technology uses the Diverse Negative Attributes method to accurately understand special camera sensors, while the second technology Modality-Adaptive Decoding blocks cross-modal hallucinations at the source.
Researchers at KAIST have developed Stable-GFlowNet, a new AI safety verification framework that uncovers seven times more hidden vulnerabilities in AI than existing methods. The technology is expected to serve as a foundation for developing safer and more trustworthy generative AI models.
A KAIST research team found that algal blooms accelerate the early-stage weathering of plastics, leading to microplastic formation. The study suggests a new direction for managing water pollution and plastic waste together.
A KAIST research team developed a next-generation world model that learns executable theories from observation alone. The Neural Theorizer (NEO) model discovers reusable primitives and composes them into executable programs to explain new situations.
A research team at KAIST has uncovered the molecular mechanism by which amino acid signals activate cell growth signaling. The findings suggest a potential basis for next-generation anticancer therapies that target abnormal growth signaling in tumor cells.
Researchers developed a self-aligned, thin-film growth technology to grow tellurium film in a uniform crystal orientation at a low temperature of 150°C. This approach enables the precise fabrication of high-quality semiconductor films for next-generation semiconductors and optoelectronic devices.
Researchers at KAIST have created an antibody that precisely targets intracellular cancer mutations using computational methods. The antibody selectively recognizes only cancer cells carrying the KRAS(G12D) mutation, demonstrating its potential for precision antibody therapeutics.
A KAIST research team has developed a non-contact, non-destructive method to measure minute variations in battery electrode thickness, improving battery safety and quality by identifying invisible defects during manufacturing. The technology combines terahertz waves with an optical frequency comb for ultra-precise measurements.
A joint KAIST research team developed a new framework for analyzing networks of circulating amino acids, reflecting the body's metabolic state. They showed that this approach can predict recurrence or metastasis in patients with colorectal cancer more accurately than current methods.
A KAIST research team has developed a new molecular system that can selectively switch the pathway through which electrons are transferred during oxygen activation. The findings provide a fundamental design principle for next-generation catalysts and energy-conversion technologies.
Researchers at KAIST have developed a groundbreaking oocyte and embryo analysis technology using holotomography to predict developmental potential in IVF. This non-invasive method could revolutionize the selection of embryos for transfer, offering a more objective and quantitative approach.
A KAIST research team developed an XR comics platform, ComiXR, that enables users to read and create comics in immersive environments. The platform demonstrated increased immersion when comic elements were positioned at different depths and incorporated sensory experiences such as facial expression tracking.
Researchers at KAIST create a metal structure that changes shape using light, without any light-absorbing coating. The technology could enable new possibilities for tactile interfaces and wearable devices.
A KAIST research team identified a previously unrecognized immune mechanism through which anti-CTLA-4 promotes B-cell responses in tumor-draining lymph nodes. This response is critical for the antitumor effects of anti-CTLA-4 therapy, opening a new avenue for treating intractable brain tumors like glioblastoma.
KAIST develops robot that can autonomously choose gait strategy for its surroundings, switching between walking, running, jumping, and other locomotion skills. The team generated 15.5 hours of training data using computer simulations alone, enabling the robot to move quickly and stably in real outdoor environments.
Researchers developed Buffer-and-Reinforce framework to preserve AI safety during personalized fine-tuning, maintaining high safety even in extreme settings. The framework achieved strong customized performance and state-of-the-art safety without additional safety data or increased computational cost.
A joint KAIST–University of Tokyo research team found that temperature-related suicide mortality is expected to rise globally due to climate change. Regional differences in future rises are driven by varying temperature-suicide relationships, with East Asia and South America projected to see relatively small increases.
Researchers from KAIST and MIT create a transmissive mid-infrared spatial light modulator that can perform various sensor functions using electrical signals alone. The device has demonstrated stable performance after over 16,700 switching cycles and is expected to enable software-defined sensors with reconfigurable optical hardware.
A KAIST research team analyzed key challenges in commercializing biomanufacturing and proposed an AI-based strategy to address them. The study suggests a phased approach to simplify production processes and expand into high-value markets first.
A KAIST-Sungkyunkwan University joint research team has developed a new two-dimensional semiconductor structure where electricity flows without obstruction. The team demonstrated that current can flow across the boundary between semi-metallic and semiconducting regions without being blocked.
A KAIST-led research team developed an AI framework that analyzes real-life daily activity and environmental data from older adults to identify digital behavioral markers of cerebrovascular disease risk. The study found that irregular daily rhythms, low indoor humidity, and changes in sleep patterns can serve as important clues for det...
A KAIST study found that immigration-related legislation can lead to increased toxic chemical releases from manufacturing facilities in the US. The research team analyzed data from 14,390 facilities and found a significant increase in pollution when political attention shifted to immigration.
Researchers at KAIST developed technology to automatically identify and fabricate two-dimensional semiconductors, revealing the relationship between thickness and performance. The technology enables data-driven research and accelerates the commercialization of AI semiconductors and ultra-low-power semiconductors.
Researchers at KAIST have developed a core technology for stretchable displays that expands uniformly across the entire screen without distorting images. The platform uses auxetic structures to maintain isotropic expansion, allowing fine images on-screen to expand together while maintaining their original shapes.
A KAIST research team developed a foundational technology for 'temperature-based DNA synthesis,' synthesizing desired DNA using only temperature. The team also demonstrated a 'DNA temperature black box' that records temperature changes during shipping without electricity.
A KAIST research team analyzed the computational cost and energy consumption of AI agents, finding they consume up to 136.5 times more energy per query than conventional generative AI. This study highlights the importance of optimizing AI semiconductors, data centers, and power infrastructure for sustainable AI development.
Researchers at KAIST have developed a prodrug that selectively activates in the brain of patients with Alzheimer's disease, reducing reactive oxygen species and preventing amyloid beta aggregation. This approach shows promise for next-generation dementia treatment.
Researchers from KAIST have provided experimental evidence that electrons form a loop-like circulating order (loop-current order) before reaching the superconducting state. This discovery sheds light on the fundamental principles of superconductivity and offers a crucial clue for understanding unconventional superconductivity.
KAIST researchers have discovered a new way cancer 'hijacks' the blueprint for blood vessel development to fuel its growth. By reactivating a pre-existing gene regulatory program, tumors can drive angiogenesis without evolving entirely new mechanisms.
Researchers have developed a polymer membrane that separates crude oil at room temperature, significantly reducing the need for energy-intensive heating in conventional refining. The membrane uses self-assembled separation channels smaller than 2 nanometers to selectively separate lighter fractions from heavier components.
Researchers at KAIST developed DiSPo, a robot AI model that can flexibly improve task precision from coarse demonstrations, enabling robots to perform sophisticated tasks with high accuracy. The technology achieved significant improvements over existing models in simulation and real-world experiments.
A KAIST research team led by Professor Jee-Hwan Ryu has received the IEEE Robotics and Automation Letters (RA-L) Best Paper Award for the second consecutive year. The award-winning paper presents a novel assistive dressing technology that enables garments to autonomously unfold and move along the user's body using soft robotic principles.
Researchers at KAIST developed a next-generation database technology called AkasicDB, which integrates vector, graph, and relational databases into a single system. This technology reduces AI hallucinations and improves accuracy by up to 78%, addressing a key challenge in enterprise AI commercialization.
Researchers at KAIST have developed a highly stretchable piezoelectric fiber sensor that operates stably even under repeated deformation. The sensor can be stretched up to 668%, generating consistent electrical signals under various movements, and is expected to enable long-term monitoring of biosignals in wearable medical devices.
A joint research team from KAIST and international institutions developed 'Upsample Anything,' a universal technology that can enhance the visual performance of AI even with limited GPU memory. This achievement increases GPU memory efficiency by up to 16 times, allowing AI to perceive its surrounding environment more precisely.
Researchers create a highly efficient liquid-cooling system that cools semiconductor chips using room-temperature water. The system achieves a coefficient of performance (COP) of 106,000, approximately ten times higher than the previous world-leading result.
Researchers at KAIST have developed a new nano-printing technology that allows for the transfer of ultra-fine metal circuits onto plant leaves, fruits, curved automotive surfaces, and robot exteriors without causing damage. This technology has vast potential for applications in smart agriculture, wearable healthcare, and bioelectronics.
Researchers have developed a computational design technology that utilizes computer simulations to analyze and predict the scaling limits of transistors. The technology identifies the quantum tunneling limit, which varies depending on the type of metal and contact structure.
A new model developed by KAIST reveals that a shortage of agricultural workforce can limit farmland utilization in most regions, posing a significant risk to future food security. The study's findings suggest that sustainable development models and migration policies are crucial to addressing this issue.
A KAIST research team has synthesized a core raw material for fabricating asymmetric MXene, a so-called 'Janus-faced' nanomaterial with distinct functions on its two sides. This achievement establishes the foundation for implementing asymmetric MXene in various advanced technology fields.
Researchers at KAIST developed Video-Based Optimal Transport (VOTP), a technology that enables robots to understand human intentions and choose actions on their own with minimal data. This breakthrough accelerates the development of physical AI, which is expected to drastically shorten development time and costs.
The KAIST Mind Care & Growth Center consolidates psychological counseling services under one roof, providing systematic care to students. Researchers collaborate with AI experts to develop evidence-based interventions, addressing mental health challenges arising from AI dependency.
A KAIST research team has developed a technology that leverages natural ingredients to increase the strength of seaweed-based hydrogel by more than fivefold, while controlling its adhesiveness and degradation rate. The new material design strategy utilizes tannic acid to enhance mechanical strength and adhesiveness.
Researchers at KAIST have developed a novel 2D conductive Material that maintains single-layer electronic characteristics even when stacked in multiple layers. This breakthrough resolves the long-standing challenge of performance degradation in 2D materials, enabling high electrical conductivity and efficient electron transport.
A KAIST research team has developed a technology that controls the chemical environment around catalysts at the nanometer scale by designing DNA sequences. This allows for improved hydrogen production efficiency and increased yield of desired chemical products. The DNA layer acts like a traffic control center, guiding the movement of i...
A new analysis of 600,000 research papers reveals that dual-use research consistently has greater scientific impact than comparable research. Strengthening security oversight on dual-use research can impose disproportionate costs on domestic science, the study finds.