Researchers have developed a xenogeneic-free culture platform that significantly enhances the migration and regenerative capacity of intestinal stem cells. The technology, called PLUS, maintains identical performance even after storage at room temperature for three years, securing industrial scalability.
Researchers at KAIST have developed generative AI technology that autonomously optimizes injection molding processes, achieving an error rate of just 1.63%. Additionally, they built an LLM-based knowledge transfer system, IM-Chat, to make on-site expertise accessible to anyone, regardless of language or cultural background.
The KAIST-UEL team has developed a transformative wheel capable of traversing the Moon's extreme terrains, including steep lunar pits and lava tubes. The 'origami' airless wheel expands from a compact size to overcome obstacles, while utilizing flexible materials and specialized design elements to withstand harsh lunar conditions.
Researchers developed a nasal antiviral platform using AI to stabilize interferon-lambda protein, ensuring effective diffusion and long-term retention in the nasal mucosa. The platform showed a massive improvement in stability, surviving for two weeks at 50℃ and inhibiting influenza virus levels by over 85% in animal models.
Researchers develop shape-morphing device to overcome pancreatic tumor microenvironment barriers, achieving remarkable therapeutic efficacy in mouse models. The device delivers low-intensity photostimulation that precisely targets cancer cells while preserving normal tissue.
A KAIST research team created a water-based air purification device that removes ultrafine dust with high efficiency, long-term stability, and low power consumption. The device operates without filters, ozone, or noise, making it an eco-friendly next-generation air purification platform.
High-nickel batteries suffer from rapid performance degradation due to an electrolyte additive called succinonitrile. Researchers found that this additive attaches strongly to nickel ions, destroying the protective electrical double layer and accelerating damage.
Researchers at KAIST have developed a technology to directly observe nano-sized water droplets using an Atomic Force Microscope, enabling precise analysis of wettability. This breakthrough is expected to improve hydrogen production, fuel cells, batteries, and semiconductor processes.
Researchers at KAIST have developed a new strategy to control the initiation timing and rate of mRNA protein production, enabling safer treatment. By using this method, proteins can be produced sequentially in a desired order, reducing the risk of side effects.
Researchers at KAIST have confirmed that red OLED light reduces amyloid-β plaques and improves long-term memory in an Alzheimer's disease model. The study shows that even short periods of light stimulation can lead to significant pathological improvements and cognitive enhancements.
Researchers at KAIST have found that depression is linked to an imbalance in the body's immune response, affecting brain function. The study identified novel biomarkers and a potential new approach for treating depression by integrating blood analysis, single-cell analysis, and patient-derived brain organoids.
The research team created a flexible hydrogel-based 'Latent-Radiative Thermostat' that autonomously switches between cooling and heating modes. The LRT can maintain temperatures up to 3.7 °C lower in summer and 3.5 °C higher in winter, reducing energy consumption by up to 153 MJ/m² compared to existing roof coatings.
A KAIST team has developed a modular co-culture platform to produce multicolored bacterial cellulose, overcoming the limitations of environmental challenges and complex processing requirements. The platform enables one-pot production of colored living materials without additional chemical processing.
A KAIST research team has developed a highly efficient technique to characterize complex multimode quantum operations, which is essential for scalable optical quantum computing and quantum communication technologies. The new 'Multimode Quantum Process Tomography' technique can analyze large-scale operations with less data, representing...
KAIST's research team presents a new direction for future software security research with their automatic C-to-Rust translation technology. The technology proves the mathematical correctness of the conversion, solving existing AI limitations and C language security issues.
A research team at KAIST has elucidated the principle by which cells decide their direction of movement without external stimuli. The study reveals that proteins interact within living cells to control cell movement, with specific combinations governing straight or changed direction.
Researchers at KAIST have developed a new technology called SHARE that can reconstruct high-quality 3D scenes using only ordinary images without precise camera pose information. This breakthrough enables rapid and precise reconstruction in real-world environments without additional training or complex calibration processes.
Researchers at KAIST have identified the molecular basis of nonspecific activation in killer T cells and proposed a new therapeutic strategy to control it. The study reveals that interleukin-15 can abnormally excite killer T cells, causing them to attack uninfected host cells.
Researchers at KAIST have created a new manufacturing method for high-performance green hydrogen electrolysis cells, reducing production time from six hours to just ten minutes. The technique uses microwaves to heat ceramic powders uniformly, achieving stable electrolyte formation at lower temperatures.
A comprehensive review paper analyzes the impact of AI on materials science and engineering, highlighting its role in Discovery, Development, and Optimization stages. The AI-based catalyst search platform demonstrates the potential for robots to autonomously design, execute, and optimize experiments.
A research team at KAIST developed a novel platform technology using a 0.02-second flash of light to generate an ultrahigh temperature of 3,000 °C. This process enables the highly efficient synthesis of catalysts and boosts hydrogen production efficiency by up to six times.
A KAIST research team found that in-home IoT data can accurately track mental health status using environmental data and smartphone-wearable data combined. Regular routines are essential for maintaining mental health, while variability in daily patterns is a key indicator of worsening mental health.
A joint research team found that countries with stricter environmental regulations see increased sales of green products like electric vehicles. This challenges the traditional 'pollution haven' hypothesis and suggests a link between strong regulations and eco-friendly product competitiveness.
Researchers at KAIST have developed a core AI semiconductor technology called PIMBA, which combines the Transformer's intelligence with the Mamba's efficiency. This technology results in a four-fold increase in inference speed and a 2.2-fold reduction in power consumption for Large Language Models.
Researchers at KAIST have developed a generative AI-based technology capable of identifying drugs and genetic targets that can guide cells toward a desired state. The model can predict the reactions of previously untested cell-drug combinations and reveal how drugs function inside cells.
A chemobiological platform converts glucose and glycerol into oxygenated precursors, which are then deoxygenated to produce benzene, toluene, ethylbenzene, and p-xylene. The integrated system uses a novel solvent system to streamline the conversion process.
Researchers developed a new technique combining physical laws with artificial intelligence to identify material properties even under data-scarce conditions. The approach enables rapid exploration of new materials and improves experimental efficiency while preserving reliability.
A research team at KAIST has discovered that the huntingtin protein organizes cytoskeletal microfilaments into bundles, playing a crucial role in neural connectivity. This finding is expected to contribute to understanding Huntington's disease and other neurodegenerative disorders.
A KAIST research team has developed a Frequency Switching Neuristor that autonomously adjusts its response characteristics, like the brain's intrinsic plasticity. The device achieves 27.7% less energy consumption than conventional neural networks and can compensate for partial circuit failures to resume normal operation.
Research at KAIST found that nuclear hypertrophy in cancer cells can actually suppress metastasis, rather than being a sign of worsening disease. The study identified DNA replication stress as the cause of nuclear enlargement, which can impose constraints on cancer cell potential for spread.
Researchers developed a technology combining AI analysis with optogenetics to diagnose Parkinson's disease in mice. The AI-predicted Parkinson's disease score exhibited significant differences from controls, proving sensitive in assessing severity.
A KAIST-led team has identified a gene, NR3C1, that regulates the developmental switch in astrocytes, shaping immune system reactions in adulthood. Early-life epigenetic 'memory' can predispose adult brains to excessive inflammation and disease vulnerability.
A KAIST team discovered how gallium doping improves platinum-nickel catalysts' performance and durability, retaining octahedral shape and highly active facets. This breakthrough could lead to more durable fuel cells for hydrogen-powered vehicles and clean energy technologies.
A KAIST research team has developed a wearable sensor that can analyze multiple metabolites in sweat, enabling precise monitoring of internal metabolic changes over time. The patch uses nanophotonics and microfluidics technologies to collect and analyze sweat components without labeling.
Researchers at KAIST have developed a new liquid electrolyte that significantly improves lithium-metal battery performance, enabling fast charging times of just 12 minutes and an 800km driving range. The breakthrough overcomes the long-standing dendrite problem, a major barrier to widespread adoption of lithium-metal batteries.
Researchers at KAIST have precisely clarified the operating principle of an oxide-based memory device using a multi-modal scanning probe microscope. The study reveals that oxygen defects determine the on/off state of the memory and confirms that electronic behavior also plays a role in its resistance changes.
A KAIST research team has developed a universal technology that identifies gene control targets in altered cellular gene networks and restores them. By applying an algebraic approach, they can quickly and accurately calculate how the overall cellular response would change if a specific gene were controlled.
Researchers at KAIST have developed a new time-series domain adaptation technology that allows existing AI models to detect defects accurately even when manufacturing processes or equipment change. The technology achieved up to 9.42% improvement in accuracy compared to existing methods.
Researchers identify PELOTA protein as central regulator of aging, extending lifespan through ribosome-associated quality control. Deficiency in PELOTA accelerates aging by disrupting mTOR and autophagy pathways.
A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. The platform can produce either nitric oxide or ammonia on demand using only an electrical signal.
Researchers at KAIST have developed an AI model named BInD, which can design and optimize drug candidate molecules tailored to a protein's structure alone. The model predicts the binding mechanism between the drug and the target protein, enabling comprehensive design in one step.
Researchers have developed a next-generation wireless ophthalmic diagnostic technology incorporating an ultrathin OLED into a contact lens. This breakthrough simplifies the conventional ophthalmic diagnostic environment, allowing patients to undergo retinal function tests while wearing the lens.
Koo's team received the award for analyzing gait-related knee joint motion in healthy individuals and patients after ACL reconstruction with ALL augmentation. The study found excessive anterior translation and internal rotation, suggesting incomplete restoration of normal joint kinematics post-surgery.
The KAIST research team, led by Professor Insu Yun, won the DARPA AI Cyber Challenge with their AI-based autonomous cyber defense technology. The team scored a dominant victory, detecting and patching over 70 intentionally injected vulnerabilities in real-time.
Researchers at KAIST have developed a 'field-programmable robotic folding sheet' that can be programmed in real time according to its surroundings. The technology enables real-time shape programming and opens new possibilities in robotics.
Researchers found that adding ethane to methanotrophs' core metabolism boosts polyhydroxybutyrate (PHB) synthesis and reduces methane consumption. The study sheds new light on methanotrophic metabolism in mixed-gas environments, offering possibilities for sustainable biopolymer production.
A KAIST research team found that placental inflammation during pregnancy affects the fetus's immune system, leading to stronger allergic reactions after birth. This study presents a new possibility for early prediction and prevention of allergic diseases like pediatric asthma.
Researchers developed AI technology 'MARIOH' that can accurately reconstruct higher-order interactions from low-order interaction data, achieving up to 74% greater accuracy compared to existing methods. The model has potential applications in social network analysis, life sciences, and neuroscience.
KAIST researchers have developed a method to chemically synthesize herpotrichone, a natural substance with excellent anti-neuroinflammatory effects. The team successfully synthesized the substances using a biosynthetically inspired strategy, including the Diels-Alder reaction and hydrogen bonding.
A new sleep algorithm developed by KAIST researchers helps users build healthy sleep habits by recommending the best bedtime based on their body's circadian rhythm. The algorithm is available on Samsung Galaxy smartwatches and aims to improve sleep quality and overall well-being.