International collaboration identifies four correlated metals in two-orbital systems, including a Hund's metal that can give rise to superconductivity. The discovery overturns conventional wisdom and opens up new avenues for understanding strongly correlated materials.
A research group at KAIST successfully produced seven natural rainbow colorants, including carotenoids and violacein derivatives, using engineered Escherichia coli strains. The strategies developed can be applied to the efficient production of other industrially important natural products.
A recent KAIST study revealed that the ventral striatum is a neural basis for our habitual seeking behavior, including addiction. The research found that long-term value memories are retained in the ventral striatum and guide automatic evaluations of objects based on positive values.
Decitabine, used to treat blood cancers like MDS and AML, works by activating endogenous retroviruses that induce an immune response. The study found two key gene sequences involved in this process, Staufen1 and TINCR, whose expression levels determine a patient's response to the drug.
A new study using fruit flies has uncovered the mechanism behind a gut hormone's role in inducing cravings for protein-rich foods. The research found that CNMamide, released by enterocytes in response to protein deprivation, conveys nutrient status to the brain, triggering a desire to consume essential amino acids.
KAIST researchers have developed a deep learning approach to accurately determine the 3D surface atomic structure of nanoparticles. The method enhances precision by nearly 70% and improves surface atom identification, enabling the study of catalytic properties at the atomic scale.
Distinguished Professor Sang Yup Lee at KAIST was elected as a foreign member of the Royal Society, one of the world's most prestigious national science academies. He is recognized for his pioneering work in systems metabolic engineering and developing micro-organisms for producing fuels, chemicals, and natural compounds.
A KAIST research team creates T-GPS, enabling the processing of large-scale graphs without storing them in main memory or on disks. This allows for faster computation and reduced costs compared to traditional approaches.
Centrifugal multispinning technique offers safer and cost-effective mass production of high-performance polymer nanofibers. Researchers successfully fabricate face masks with comparable filtration performance to existing KF80 and KF94 masks.
Researchers at KAIST successfully produced carminic acid from glucose in engineered Escherichia coli, overcoming the need for complex purification processes and protein contaminants. The development of a generally applicable C-glucosyltransferase also enables the production of other valuable natural products.
Researchers at KAIST develop M3I3 Initiative to speed up materials development using multiscale/multimodal imaging and machine learning. The team creates a quantitative model using machine learning and presents a future outlook for advancements in materials science.
Researchers at KAIST discovered that plasma jets produce more stable interactions with water surfaces compared to neutral gas jets, reducing bubbling and splashing. The study's findings will help improve our understanding of plasma-liquid interactions and their applications in various industrial fields.
Researchers successfully demonstrated a new methodology for direct near-field optical imaging of acoustic graphene plasmon fields. This strategy will provide a breakthrough for the practical applications of acoustic graphene plasmon platforms in next-generation optoelectronic devices.
The Korea Advanced Institute of Science and Technology (KAIST) has been featured in a special virtual issue of ACS Nano, highlighting its collective intelligence and technological innovation. The issue showcases KAIST's vision of becoming a global value-creative leading university and its progress over the last 50 years.
A new silicone-based patch fabrication technique fabricates thin patches that rapidly wick water away from the skin, reducing skin irritation caused by wearable biosensors. The technique was developed to improve comfort and performance of wearable bioelectronics.
A research team at KAIST has developed a highly deformable ceramic piezoelectric material that can convert mechanical stimuli into electrical signals. The material's elastic strain limit is three times greater than that of bulk zinc oxide, making it suitable for advancing high-performing haptic technology.
Researchers developed a wireless, rechargeable soft brain implant that can be controlled wirelessly by a smartphone, allowing seamless chronic neuromodulation. The device uses micrometer-sized LEDs to manipulate target neurons in the deep brain, enabling real-time brain control and reducing the burden on patients for long-term use.
Researchers discovered that orthogonal organization in retinal mosaics is mirrored onto the primary visual cortex, initiating clustered topography of higher visual areas. This finding provides insights into efficient sensory information processing and developmental strategy of brain circuitry.
Researchers at KAIST develop novel biosynthetic pathways for short-chain primary amines through retrobiosynthesis, expanding the strategy for bio-based production of chemicals. The team successfully produced multiple short-chain primary amines using Escherichia coli strains and renewable resources.
A joint research team developed DeepTFactor, a deep neural network predicting transcription factors from protein sequences. The tool uses three parallel convolutional neural networks and predicted 332 transcription factors of Escherichia coli K-12 MG1655.
In adult brains, astrocytes eliminate excessive and unnecessary synapses to maintain plasticity. This process is crucial for controlling synapse numbers and neural circuit maturation.
Researchers from KAIST and Florida State University developed a model describing PER molecule motion in cells, showing how aging and diseases disrupt circadian rhythms by hindering condensation around the cell nucleus. This leads to irregular sleep-wake cycles and unstable rhythms.
KAIST researchers have synthesized nanoparticles that emit multiple wavelengths of light from a single particle, allowing for the control of these particles' properties and creation of environmentally responsible displays and lighting. The discovery also sheds new light on the mechanisms governing the optical properties of carbon dots.
A comprehensive review of biosynthesis methods for diverse inorganic nanomaterials produced under mild conditions by microorganisms and bacteriophages, highlights strategies for improving producibility and crystallinity.
A KAIST research team used simulations to identify an enzyme that can reverse cellular senescence, a natural process contributing to aging and age-related diseases. By targeting the enzyme PDK1, cells were able to re-enter the cell cycle without proliferating abnormally.
A novel engineered C. glutamicum strain can produce high-level glutaric acid from glucose, breaking the record for the highest titer ever reported. The new strategy employs systems metabolic engineering strategies, including introducing Pseudomonas putida genes and optimizing culture conditions.
Researchers employed a computer algorithm to analyze nearly 15,000 landscape paintings, finding that compositional structures evolved systematically over time. The study suggests a potential bias in art curators' and historians' selections, contradicting the prevailing view of diverse artistic expression.
Researchers have discovered a way to produce nanoribbons of TMDs, which are more abundant and cheaper than platinum, boosting their catalytic efficiency. The new catalyst could make hydrogen production more economical and play a key role in the transition away from fossil fuels.
A team at KAIST developed an E. coli strain that can grow up to 11-fold higher cell density using CO2 and formic acid as sole carbon sources. The engineered strain shows promise for producing chemicals from these carbon sources, a crucial step forward in biorefinery production.
Researchers from KAIST applied deep learning techniques to identify abnormal brain structures associated with autism. These findings suggest AI can aid in more consistent diagnoses than human observations alone. The analysis tool provides a prognosis of how the condition could develop.
Researchers identified key markers that can pinpoint patients at risk of severe COVID-19, associating neutrophil cells and glucocorticoid receptors with disease severity. This finding could lead to personalized treatment approaches for patients with reduced glucocorticoid receptor expression.
A new wearable piezoelectric harvester using hot pressing and tape casting fabrication process has record high interfacial adhesion strength, enabling durable wearable devices. The study uses a surface and interfacial cutting analysis system to measure adhesion strength.
Researchers developed an open-source 'OpenExpress' technology to improve NVMe performance and accessibility. The new tech achieved parallel data input/output processing, increasing bandwidth by 76% and reducing input/output delay by 68%.
Researchers used computational simulations to show that spontaneous retinal waves can generate long-range horizontal connectivity in the visual cortex, resolving a long-standing puzzle. The findings suggest that neural circuits must begin developing earlier than sensory input to prepare the brain for vision.
Researchers developed a novel technology to create a sulfur-containing polymer (SCP) film with excellent environmental stability and chemical resistance, exhibiting a high refractive index of 1.9 while being fully transparent in the entire visible range.
Researchers at KAIST discovered that tweaking roundworm proteins can boost lifespan and activate AMPK, a key player in cellular energy monitoring. This mechanism may be applied to developing longevity-promoting drugs for humans.
The SoundWear device uses sound augmentation to expand children's play experience, triggering imagination and distinct play behaviors. It also helps children gain a sense of achievement and ownership towards sound.
KAIST researchers used AFM to analyze the effects of acidic and sugary drinks on human tooth enamel at the nanoscale level. The study found significant increases in surface roughness and decreases in elastic modulus with immersion time, highlighting the need for thorough studies on early-stage enamel erosion.
A study by KAIST researchers used X-ray scattering to track protein folding, revealing multiple forms of an unfolded protein follow different pathways and timelines. The findings could improve computer simulations, paving the way for better disease studies and drug development.
A new quantum classifier introduces a tailored quantum kernel, outperforming AI technology and enhancing classification tasks with small datasets. The method exploits the quantum advantage in finding non-linear features, leading to significant improvements.
A deep-learning powered single-strained electronic skin sensor captures complex five-finger motions in real-time, creating a virtual 3D hand. The sensor's rapid situation learning system ensures stable operation regardless of its position on the skin.
Researchers at KAIST designed nanoparticles that significantly reduce cholesterol and macrophage foam cells in arteries, two key triggers of atherosclerotic plaque. The combination drug delivery therapy showed great potential for treating and preventing atherosclerosis with reduced side effects.
Researchers have developed a novel electrode material that allows for direct charging of oxygen from the air, improving lithium-oxygen battery performance. The new strategy involves stabilizing atomic-level electrocatalysts within metal-organic frameworks, resulting in reduced overpotential and increased life cycle.
KAIST researchers developed an algorithm for automated 3D brain imaging data analysis, enabling precise and quantitative mapping of complex neural circuits. The new technology allows for accurate comparison of brain data from different animals and improves the accuracy and consistency of analysis results.
The Mole-bot, a biomimetic drilling robot, has been optimized for underground and space exploration. It boasts powerful forelimbs, a stout scapula, and an expandable drilling bit that can excavate three times faster than conventional models with six times higher directional accuracy.
Researchers at KAIST developed a novel approach to modulate local CO2 concentration in gas-diffusion electrode-based flow electrolyzers. This method improves the selectivity, conversion rate, and electrode stability, promoting C-C coupling reactions for multi-carbon molecule production.
A new easy-to-use smart optical film technology has been developed, enabling smart windows to switch between transparent and opaque states. The film demonstrates high speed and performance, allowing for fast switching and uniform tinting while securing durability, stability, and safety.
Researchers at KAIST developed a universal virus detection platform using reactive polymer-grafted double-stranded RNAs, which can detect viruses without prior knowledge of their genomic sequences. This platform provides enhanced sensitivity and can be used to quickly differentiate infected populations from non-infected ones.
A new visualization method using atomic force microscopy is developed to determine the distribution of components in battery electrodes, providing insights into optimal composite electrode conditions. The method has potential to improve performance and safety of all-solid-state lithium-ion batteries.
Researchers at KAIST have developed a graphene-based active spintronic component that efficiently generates, controls, and detects spin currents. By stacking graphene on top of 2H-TaS2, they increased the spin-orbit coupling of graphene, paving the way for its use in spintronic applications.