Researchers at KAIST developed a quadrupedal robot control technology that enables robots to walk robustly on deformable terrain like sandy beaches. The technology uses artificial neural networks to simulate ground characteristics and adapt to changing environments, allowing the robot to maintain balance and perform high-speed walking.
The 30-year history of metabolic engineering has progressed significantly, enabling microorganisms to efficiently produce chemicals and degrade recalcitrant contaminants. Recent breakthroughs in systems metabolic engineering and data science have driven advancements in sustainability and health.
Researchers from KAIST and Chungnam National University have developed a new equation to predict drug interactions, improving accuracy by 80% compared to the existing FDA formula. The new equation takes into account factors such as gut bioavailability and enzyme concentration.
M.A.R.V.E.L.'s magnetic soles made of Electro-Permanent Magnet (EPM) and Magneto-Rheological Elastomer (MRE) enable fast movement on uneven surfaces. The robot can climb at speeds of up to 70 cm/s on walls and 50 cm/s on ceilings, making it the world's fastest walking climbing robot.
A KAIST research team has developed a surface-lighting microLED patch for UV-induced melanogenesis inhibition. The patch demonstrated significant suppression of melanin synthesis and minimized epidermal photo-toxicity, making it a promising treatment option for skin diseases such as spots and freckles.
Researchers established a novel strategy to treat Huntington's disease by converting the disease-causing form of the huntingtin protein into its disease-free form. This process maintains the original function of the protein, offering a new approach to tackle the neurodegenerative disorder.
Researchers have developed a systematic strategy for creating phage-resistant E. coli strains, solving a major problem in industrial fermentation. The approach integrates a defense system and mutations to restrict phage life cycle, maintaining bacterial functionality and productivity.
Researchers have developed an interactive metabolic map of bio-based chemicals, providing a versatile tool for easy assessment and optimization of synthetic pathways. The map enables exploration and analysis of complex networks of biological and/or chemical reactions, facilitating the design and production of desired chemicals.
Researchers at KAIST developed a novel fusion protein drug, αAβ-Gas6, which efficiently eliminates amyloid beta (Aβ) without causing inflammatory side effects. The study showed that αAβ-Gas6 promoted the robust uptake of Aβ without inflammation and neurotoxicity.
Researchers at KAIST have developed a method to produce lutein in E. coli bacteria using glycerol as a cheap carbon source. The production process involves systems metabolic engineering and substrate channeling to overcome bottleneck enzymes that inhibit lutein biosynthesis.
A KAIST research team has discovered a new role for somatostatin, a protein-based neurotransmitter, in reducing the toxicity caused by Alzheimers disease. When somatostatin is met with copper and Aβ proteins, it attenuates the toxicity and agglomeration of metal-Aβ complexes.
A team led by Professor Song Min Kim developed a system that can support concurrent communications for tens of millions of IoT devices using backscattering millimeter-level waves. The system offers internet connectivity on a mass scale to IoT devices at a low installation cost.
Researchers demonstrate a new platform for guiding compressed mid-infrared light waves in ultra-thin van der Waals crystals, enabling strong light-matter interactions and improved detection limits. The use of atomically-smooth gold crystals provides a low-loss environment for the propagation of phonon-polaritons.
Researchers developed a new imaging technique called PICASSO that allows for the use of more than 15 colors to image and parse overlapping proteins. This approach, which employs artificial intelligence, enables accurate information unmixing without reference spectra measurements, making it suitable for complex specimens like the brain.
Scientists at KAIST have discovered a new polymer mesophase structure that forms through a random copolymer sequence. This unique structure is characterized by a bilayer-folded lamellar mesophase, which exhibits properties such as birefringence and viscoelasticity.
A new neuromorphic memory device simulates both neurons and synapses in a single unit cell, enabling the development of brain-like artificial intelligence. This breakthrough achieves synergistic interactions between neurons and synapses, overcoming current limitations in neuromorphic computing.
Scientists at KAIST have proposed a novel 'stashing system' inspired by the human brain's neural activity, which efficiently handles mathematical operations for artificial intelligence. This technology reduces power consumption by 37% while maintaining accuracy, paving the way for next-generation semiconductor chips.
A new methodology has been demonstrated to achieve full 360° active phase modulation for metasurfaces while maintaining uniform levels of optical amplitude. The strategy involves using two optical resonances with specific properties to overcome the trade-offs between dynamic phase and amplitude control.
The KAIST research team has developed LightPC, a lightweight persistence centric system that ensures both data and execution persistence using only non-volatile memory. This technology reduces power consumption and increases performance by minimizing internal volatile memory components and increasing parallelism.
A team of scientists from KAIST has developed a method to directly measure the frequency of floral scent emissions in lilies using optical interferometry. This technology reveals the temporal pattern of scent release and provides new insights into the ecological evolution of plant-pollinator interactions.
Cell-to-cell variability in antibiotic stress response is found to increase as the number of rate-limiting steps in signaling pathways increases. This discovery could lead to more effective chemotherapies for cancer treatment.
A research team at KAIST developed a method for direct measurement of dielectric tensors in 3D anisotropic structures, overcoming previous limitations. This breakthrough enables the exploration of inaccessible nematic structures and interactions in non-equilibrium dynamics.
A team of researchers from KAIST has developed a mind-reading system that can interpret arm movement directions from neural signals in the brain. The new system, based on a machine-learning algorithm and mathematical probability model, successfully classified arm movements in 24 directions in three-dimensional space.
Researchers developed a machine learning technique that can identify different bacteria in arbitrary media with accuracies of up to 98% using surface-enhanced Raman spectroscopy and deep learning. The technique, called DualWKNet, enables rapid detection without the need for bacterial separation steps.
Researchers at KAIST developed an AI-powered microscope that can image live cells in 3D without exogenous labeling agents, achieving high accuracy and speed. The 'AI microscope' uses deep learning to predict fluorescence images from holographic images, confirming its potential for various biological research.
A KAIST research team has developed graphene-inorganic-hybrid micro-supercapacitors made of leaves using femtosecond direct laser writing lithography. The innovation enables mass production of flexible and green graphene-based electronic devices, reducing waste and environmental issues associated with traditional batteries.
A joint research team at KAIST developed a technique for facial expression detection using near-infrared light-field cameras and AI technology. The resulting NIR-based light-field camera (NIR-LFC) acquired high-quality 3D reconstruction images of facial expressions regardless of lighting conditions.
A KAIST research team found that visual selectivity of facial images can arise spontaneously in completely untrained deep neural networks. This discovery reveals the emergence of primitive visual cognitive functions in biological and artificial neural networks, raising questions about the origin of early brain functions.
Researchers from KAIST have developed a new technology to stabilize the electrode-electrolyte interface of lithium metal batteries, leading to improved performance and lifespan. The technology uses fluorine- and nitrogen-donating ionic additives to create a dual-layer solid electrolyte interphase.
Researchers used mathematical models and genetic analysis to identify key gene regulators that can switch aggressive basal-like breast cancer into less dangerous luminal-A. This approach could lead to novel therapeutic targets for treating many other types of cancer.
Researchers create a wireless ecosystem with implantable devices and IoT infrastructure to control animal brain circuits remotely, speeding up neuroscience studies and uncovering basic brain functions.
Researchers at KAIST discovered a single amino acid change in the PTEN protein that improves health status while retaining longevity. The study, published in Nature Communications, highlights the potential for targeting this protein to develop therapies for promoting healthy longevity.
A study analyzing player experiences with The Last of Us Part II found that player-character relationships significantly affected game satisfaction. Researchers discovered three key factors influencing players' emotional responses, including tolerance of forced character switches and flexibility of attachment.
Scientists have developed a technique called crystal capillary origami, where salt crystals form into spherical shells to enclose water-oil emulsions. The process utilizes Laplace pressure to drive the crystallite plates to cover the surface of the liquid.
A research team developed a new material platform by transferring chirality from molecular to microscale through self-assembly. The resulting chiral nanomaterials exhibit broad optical activity in the short-wave infrared region, enabling applications such as infrared neural stimulation and imaging.
Researchers developed a thin polymeric sensor platform on an RFA needle to monitor temperature and pressure in real time, detecting steam pops and accelerating ablation processes. The integrated sensors may provide valuable information for safer surgical procedures and more effective medical treatments.
A new deep neural network-based forward design approach explores material design space beyond the initial training set through active transfer learning and data augmentation. The framework provides an efficient search, mitigating the limitation of weak predictive power on unseen domains.
A novel method allows for the dynamic tracking and identification of tissue-specific secretory proteins in live mice, revealing distinct patterns from cell culture models. This breakthrough technique can be used to discover biomarkers and therapeutic targets with greater accuracy.
A recent research on electric dance music DJs found that those with a distinct genre identity and network positions combining brokerage and cohesion tend to have higher social standing. The study analyzed playlist data from 815 DJs and found that focused musical identity is correlated with social standing among EDM DJs.
A new technique developed by KAIST researchers uses a 'nanoscale focus pinspot' to isolate and enhance the quality of quantum emitters. By reducing unwanted background noise without altering the optical properties, this method enables the production of single, pure photons with improved purity.
Researchers at KAIST used whole-genome sequencing to track human embryonic development from fertilized egg to fully grown adult. The study identified key characteristics of the developmental process, including mutation rates and unequal cell contribution.
A study by KAIST scientists shows that neurons carrying somatic mutations in MTOR can lead to focal cortical dysplasia, the most common cause of uncontrolled seizures. Nearby non-mutated neurons become hyperexcitable due to adenosine kinase overproduction, triggering seizures.
Researchers at KAIST have developed a brain-inspired highly scalable neuromorphic hardware by co-integrating single transistor neurons and synapses. This innovation dramatically reduces hardware cost and accelerates the commercialization of neuromorphic hardware, enabling its application in mobile and IoT devices.
A KAIST study found that specific macrophages play a key role in lung damage during COVID-19. The research provides new insights into dynamic immunological changes and could lead to more precise use of immunosuppressive agents.
Researchers use 3D visualization to analyze bioplastic granule accumulation in bacteria, providing insights into sustainable plastic substitutes. The study found distinctive differences in PHA granule density and localization between microorganisms.
A KAIST research team developed a hydrogel-based flexible brain-machine interface that can detect neural signals for up to six months. The device minimizes foreign body responses by mimicking the properties of surrounding tissues when exposed to body fluids.
A joint research group from KAIST and Institut Pasteur Korea has identified 38 potential repurposed drugs for COVID-19 treatment using a virtual screening strategy. Seven compounds inhibited SARS-CoV-2 replication in human lung cells, showing anti-SARS-CoV-2 activity.
Scientists at KAIST developed a laser system generating highly interactive quantum particles at room temperature, which can recycle lost energy to achieve lower threshold energy levels. The system exploits parity-time reversal symmetry, allowing energy loss to be used as gain for high-efficiency and low-threshold lasers.
Most COVID-19 patients develop and maintain T cell memory for over 10 months, suggesting effective long-term immunity. The study provides new insights into vaccine development by revealing the self-renewal capacity and multipotency of memory T cells.
A recent study found that urban green spaces, including parks and gardens, have a positive correlation with citizen happiness. The study analyzed data from satellite images of 60 countries and found that the area of green space acted as a more important factor affecting happiness in countries with higher GDP per capita.