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KAIST Researchers Suggest an Extraordinary Alternative to Petroleum-based PET - Bacteria!
< (From left) Dr. Cindy Pricilia, Ph.D. Candidate Cheon Woo Moon, Distinguished Professor Sang Yup Lee > Currently, the world is suffering from environmental problems caused by plastic waste. The KAIST research team has succeeded in producing a microbial-based plastic that is biodegradable and can replace existing PET bottles, making it a hot topic. Our university announced on the 7th of November that the research team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering has succeeded in developing a microbial strain that efficiently produces pseudoaromatic polyester monomer to replace polyethylene terephthalate (PET) using systems metabolic engineering. Pseudoaromatic dicarboxylic acids have better physical properties and higher biodegradability than aromatic polyester (PET) when synthesized as polymers, and are attracting attention as an eco-friendly monomer* that can be synthesized into polymers. The production of pseudoaromatic dicarboxylic acids through chemical methods has the problems of low yield and selectivity, complex reaction conditions, and the generation of hazardous waste. *Monomer: A material for making polymers, which is used to synthesize polymers by polymerizing monomers together < Figure. Overview of pseudoaromatic dicarboxylic acid production using metabolically engineered C. glutamicum. > To solve this problem, Professor Sang Yup Lee's research team used metabolic engineering to develop a microbial strain that efficiently produces five types of pseudoaromatic dicarboxylic acids, including 2-pyrone-4,6-dicarboxylic acid and four types of pyridine dicarboxylic acids (2,3-, 2,4-, 2,5-, 2,6-pyridine dicarboxylic acids), in Corynebacterium, a bacterium mainly used for amino acid production. The research team used metabolic engineering techniques to build a platform microbial strain that enhances the metabolic flow of protocatechuic acid, which is used as a precursor for several pseudoaromatic dicarboxylic acids, and prevents the loss of precursors. Based on this, the genetic manipulation target was discovered through transcriptome analysis, producing 76.17 g/L of 2-pyrone-4,6-dicarboxylic acid, and by newly discovering and constructing three types of pyridine dicarboxylic acid production metabolic pathways, successfully producing 2.79 g/L of 2,3-pyridine dicarboxylic acid, 0.49 g/L of 2,4-pyridine dicarboxylic acid, and 1.42 g/L of 2,5-pyridine dicarboxylic acid. In addition, the research team confirmed the production of 15.01 g/L through the construction and reinforcement of the 2,6-pyridine dicarboxylic acid biosynthesis pathway, successfully producing a total of five similar aromatic dicarboxylic acids with high efficiency. In conclusion, the team succeeded in producing 2,4-, 2,5-, and 2,6-pyridine dicarboxylic acids at the world's highest concentration. In particular, 2,4-, 2,5-pyridine dicarboxylic acid achieved production on the scale of g/L, which was previously produced in extremely small amounts (mg/L). Based on this study, it is expected that it will be applied to various polyester production industrial processes, and it is also expected that it will be actively utilized in research on the production of similar aromatic polyesters. Professor Sang Yup Lee, the corresponding author, said, “The significance lies in the fact that we have developed an eco-friendly technology that efficiently produces similar aromatic polyester monomers based on microorganisms,” and “This study will help the microorganism-based bio-monomer industry replace the petrochemical-based chemical industry in the future.” The results of this study were published in the international academic journal, the Proceedings of the National Academy of Sciences of United States of America (PNAS) on October 30th. ※ Paper title: Metabolic engineering of Corynebacterium glutamicum for the production of pyrone and pyridine dicarboxylic acids ※ Author information: Jae Sung Cho (co-first author), Zi Wei Luo (co-first author), Cheon Woo Moon (co-first author), Cindy Prabowo (co-author), Sang Yup Lee (corresponding author) - a total of 5 people This study was conducted with the support of the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project leader: Professor Sang Yup Lee) from the National Research Foundation supported by the Ministry of Science and Technology and ICT of Korea.
2024.11.08
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A KAIST Team Develops Face-Conforming LED Mask Showing 340% Improved Efficacy in Deep Skin Elasticity
- A KAIST research team led by Professor Keon Jae Lee has developed a deep skin-stimulating LED mask which has been verified in clinical trials to improve dermis elasticity by 340%. < Figure 1. Overall concept of face-fit surface-lighting micro-LEDs (FSLED) mask. a. Optical image of the FSLED mask showing uniform surface-lighting. schematic illustration of the FSLED mask. The 2D to 3D transformation procedure b. Difference in cosmetic effect on deep skin elasticity, wrinkles, and sagging between FSLED mask and CLED mask. (improvement percentage in eight weeks) > Conventional LED masks, with their rigid design, fail to conform closely to the skin's contours. This limitation causes substantial light reflection, with up to 90% reflected over a distance of 2 cm, reducing light penetration and limiting stimulation of the deep skin layers essential for effective skin rejuvenation. To address these challenges, Professor Lee's team developed a face-conforming surface lighting micro-LED (FSLED) mask, which can provide uniform photostimulation to the dermis. The key technology lies in the mask's ability to deliver uniform light to deep skin tissues while maintaining a conformal skin attachment. This is achieved through a 3D origami structure, integrated with 3,770 micro-LEDs and flexible surface light-diffusion layer, minimizing the gaps between the light source and the skin. In clinical trials involving 33 participants, the FSLED mask demonstrated a 340% improvement in deep skin elasticity compared to conventional LED masks, proving its efficacy in significantly reducing skin wrinkles, sagging and aging. Professor Keon Jae Lee said, “The FSLED mask provides cosmetic benefits to the entire facial dermis without the side effects of low-temperature burns, making home-care anti-aging treatment that enhances the quality of human life possible. The product is being manufactured by Fronics, KAIST startup company, and will be distributed globally through Amorepacific's network, with sales starting in November.” This result titled “Clinical Validation of Face-fit Surface-lighting Micro Light-emitting Diode Mask for Skin Anti-aging Treatment”, in which Min Seo Kim, a student of the Master-Doctorate integrated program, and Jaehun An, a Ph.D. candidate, in the Department of Materials Science and Engineering of KAIST, took part as co-first authors, was published in Advanced Materials on October 22nd, 2024 (DOI: 10.1002/adma.202411651). Introductory Video: Face-conforming surface LED mask for skin anti-aging ( https://www.youtube.com/watch?v=kSccLwx8N_w )
2024.10.29
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KAIST Proposes a New Way to Circumvent a Long-time Frustration in Neural Computing
The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables much faster and more accurate learning when exposed to actual data by pre-learning random information in a brain-mimicking artificial neural network, and is expected to be a breakthrough in the development of brain-based artificial intelligence and neuromorphic computing technology in the future. KAIST (President Kwang-Hyung Lee) announced on the 23rd of October that Professor Se-Bum Paik 's research team in the Department of Brain Cognitive Sciences solved the weight transport problem*, a long-standing challenge in neural network learning, and through this, explained the principles that enable resource-efficient learning in biological brain neural networks. *Weight transport problem: This is the biggest obstacle to the development of artificial intelligence that mimics the biological brain. It is the fundamental reason why large-scale memory and computational work are required in the learning of general artificial neural networks, unlike biological brains. Over the past several decades, the development of artificial intelligence has been based on error backpropagation learning proposed by Geoffery Hinton, who won the Nobel Prize in Physics this year. However, error backpropagation learning was thought to be impossible in biological brains because it requires the unrealistic assumption that individual neurons must know all the connected information across multiple layers in order to calculate the error signal for learning. < Figure 1. Illustration depicting the method of random noise training and its effects > This difficult problem, called the weight transport problem, was raised by Francis Crick, who won the Nobel Prize in Physiology or Medicine for the discovery of the structure of DNA, after the error backpropagation learning was proposed by Hinton in 1986. Since then, it has been considered the reason why the operating principles of natural neural networks and artificial neural networks will forever be fundamentally different. At the borderline of artificial intelligence and neuroscience, researchers including Hinton have continued to attempt to create biologically plausible models that can implement the learning principles of the brain by solving the weight transport problem. In 2016, a joint research team from Oxford University and DeepMind in the UK first proposed the concept of error backpropagation learning being possible without weight transport, drawing attention from the academic world. However, biologically plausible error backpropagation learning without weight transport was inefficient, with slow learning speeds and low accuracy, making it difficult to apply in reality. KAIST research team noted that the biological brain begins learning through internal spontaneous random neural activity even before experiencing external sensory experiences. To mimic this, the research team pre-trained a biologically plausible neural network without weight transport with meaningless random information (random noise). As a result, they showed that the symmetry of the forward and backward neural cell connections of the neural network, which is an essential condition for error backpropagation learning, can be created. In other words, learning without weight transport is possible through random pre-training. < Figure 2. Illustration depicting the meta-learning effect of random noise training > The research team revealed that learning random information before learning actual data has the property of meta-learning, which is ‘learning how to learn.’ It was shown that neural networks that pre-learned random noise perform much faster and more accurate learning when exposed to actual data, and can achieve high learning efficiency without weight transport. < Figure 3. Illustration depicting research on understanding the brain's operating principles through artificial neural networks > Professor Se-Bum Paik said, “It breaks the conventional understanding of existing machine learning that only data learning is important, and provides a new perspective that focuses on the neuroscience principles of creating appropriate conditions before learning,” and added, “It is significant in that it solves important problems in artificial neural network learning through clues from developmental neuroscience, and at the same time provides insight into the brain’s learning principles through artificial neural network models.” This study, in which Jeonghwan Cheon, a Master’s candidate of KAIST Department of Brain and Cognitive Sciences participated as the first author and Professor Sang Wan Lee of the same department as a co-author, will be presented at the 38th Neural Information Processing Systems (NeurIPS), the world's top artificial intelligence conference, to be held in Vancouver, Canada from December 10 to 15, 2024. (Paper title: Pretraining with random noise for fast and robust learning without weight transport) This study was conducted with the support of the National Research Foundation of Korea's Basic Research Program in Science and Engineering, the Information and Communications Technology Planning and Evaluation Institute's Talent Development Program, and the KAIST Singularity Professor Program.
2024.10.23
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Professor Jimin Park and Dr. Inho Kim join the ranks of the 2024 "35 Innovators Under 35" by the MIT Technology Review
< (From left) Professor Jimin Park of the Department of Chemical and Biomolecular Engineering and Dr. Inho Kim, a graduate of the Department of Materials Science and Engineering > KAIST (represented by President Kwang-Hyung Lee) announced on the 13th of September that Professor Jimin Park from KAIST’s Department of Chemical and Biomolecular Engineering and Dr. Inho Kim, a graduate from the Department of Materials Science and Engineering (currently a postdoctoral researcher at Caltech), were selected by the MIT Technology Review as the 2024 "35 Innovators Under 35”. The MIT Technology Review, first published in 1899 by the Massachusetts Institute of Technology, is the world’s oldest and most influential magazine on science and technology, offering in-depth analysis across various technology fields, expanding knowledge and providing insights into cutting-edge technology trends. Since 1999, the magazine has annually named 35 innovators under the age of 35, recognizing young talents making groundbreaking contributions in modern technology fields. The recognition is globally considered a prestigious honor and a dream for young researchers in the science and technology community. < Image 1. Introduction for Professor Jimin Park at the Meet 35 Innovators Under 35 Summit 2024 > Professor Jimin Park is developing next-generation bio-interfaces that link artificial materials with living organisms, and is engaged in advanced research in areas such as digital healthcare and carbon-neutral compound manufacturing technologies. In 2014, Professor Park was also recognized as one of the ‘Asia Pacific Innovators Under 35’ by the MIT Technology Review, which highlights young scientists in the Asia-Pacific region. Professor Park responded, “It’s a great honor to be named as one of the young innovators by the MIT Technology Review, a symbol of innovation with a long history. I will continue to pursue challenging, interdisciplinary research to develop next-generation interfaces that seamlessly connect artificial materials and living organisms, from atomic to system levels.” < Image 2. Introduction for Dr. Inho Kim as the 2024 Innovator of Materials Science for 35 Innovators Under 35 > Dr. Inho Kim, who earned his PhD from KAIST in 2020 under the supervision of Professor Sang Ouk Kim from the Department of Materials Science and Engineering, recently succeeded in developing a new artificial muscle using composite fibers. This new material is considered the most human-like muscle ever reported in scientific literature, while also being 17 times stronger than natural human muscle. Dr. Kim is researching the application of artificial muscle fibers in next-generation wearable assistive devices that move more naturally, like humans or animals, noting that the fibers are lightweight, flexible, and exhibit conductivity during contraction, enabling real-time feedback. Recognized for this potential, Dr. Inho Kim was named one of the '35 Innovators Under 35' this year, making him the first researcher to win the honor with the research conducted at KAIST and a PhD earned from Korea. Dr. Kim stated, “I aim to develop robots using these new materials that can replace today’s expensive and heavy exoskeleton suits by eliminating motors and rigid frames. This will significantly reduce costs and allow for better customization, making cutting-edge technology more accessible to those who need it most, like children with cerebral palsy.”
2024.09.13
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The World’s First Hacking-preventing Cryptographic Semiconductor Chip
With the dramatic increase in the amount of information exchanged between components or devices in the 5G/6G era, such as for the Internet of Things (IoT) and autonomous driving, hacking attacks are becoming more sophisticated. Consequently, enhancing security functions is essential for safely transmitting data between and among devices. On February 29th, a KAIST research team led by Professors Yang-gyu Choi and Seung-tak Ryu from the School of Electrical Engineering announced the successful development of the world's first security cryptographic semiconductor. The team has developed the Cryptoristor, a cryptographic transistor based on FinFET technology, produced through a 100% silicon-compatible process, for the first time in the world. Cryptoristor is a random number generator (RNG) with unparalleled characteristics, featuring a unique structure comprising a single transistor and a distinctive mechanism. In all security environments, including artificial intelligence, the most crucial element is the RNG. In the most commonly used security chip, the Advanced Encryption Standard (AES), the RNG is a core component, occupying approximately 75% of the total chip area and more than 85% of its energy consumption. Hence, there is an urgent need for the development of low-power/ultra-small RNGs suitable for mobile or IoT devices. Existing RNGs come with limitations as they lack compatibility with silicon CMOS processes and circuit-based RNGs occupy a large surface area. In contrast, the team’s newly developed Cryptoristor, a cryptographic semiconductor based on a single-component structure, consumes and occupies less than .001 of the power and area compared to the current chips being used. Utilizing the inherent randomness of FinFETs, fabricated on a Silicon-on-Insulator (SOI) substrate with an insulating layer formed beneath the silicon, the team developed an RNG that unpredictably produces zeroes and ones. < Figure 1. Conceptual diagram of the security cryptographic transistor device. > Generally speaking, preventing hackers from predicting the encrypted algorithms during data exchanges through mobile devices is pivotal. Therefore, this method ensures unpredictability by generating random sequences of zeroes and ones that change every time. Moreover, while the Cryptoristor-based RNG research is the world's first of its kind without any international implementation cases, it shares the same transistor structure as existing logic or memory components. This enables 100% production through rapid mass production processes using existing semiconductor facilities at a low cost. Seung-il Kim, a PhD student who led the research, explained the significance of the study, stating, "As a cryptographic semiconductor, the ultra-small/low-power random number generator enhances security through its distinctive unpredictability, supporting safe hyperconnectivity with secure transmissions between chips or devices. Particularly, compared to previous research, it offers excellent advantages in terms of energy consumption, integration density, and cost, making it suitable for IoT device environments." This research, with master’s student Hyung-jin Yoo as the co-author, was officially published in the online edition of Science Advances, a sister journal of Science, in February 2024 (research paper title: Cryptographic transistor for true random number generator with low power consumption). This research received support from the Next-Generation Intelligent Semiconductor Technology Development Project and the Core Technology Development Project for the National Semiconductor Research Laboratory.
2024.03.07
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A KAIST Research Team Develops a Novel “Bone Bandage” Material for Cracked Bones
Bone regeneration is a complex process, and existing methods to aid regeneration including transplants and growth factor transmissions face limitations such as the high cost. But recently, a piezoelectric material that can promote the growth of bone tissue has been developed. A KAIST research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering (DMSE) announced on January 25 the development of a biomimetic scaffold that generates electrical signals upon the application of pressure by utilizing the unique osteogenic ability of hydroxyapatite (HAp). This research was conducted in collaboration with a team led by Professor Jangho Kim from the Department of Convergence Biosystems Engineering at Chonnam National University. HAp is a basic calcium phosphate material found in bones and teeth. This biocompatible mineral substance is also known to prevent tooth decay and is often used in toothpaste. Previous studies on piezoelectric scaffolds confirmed the effects of piezoelectricity on promoting bone regeneration and improving bone fusion in various polymer-based materials, but were limited in simulating the complex cellular environment required for optimal bone tissue regeneration. However, this research suggests a new method for utilizing the unique osteogenic abilities of HAp to develop a material that mimics the environment for bone tissue in a living body. < Figure 1. Design and characterization of piezoelectrically and topographically originated biomimetic scaffolds. (a) Schematic representation of the enhanced bone regeneration mechanism through electrical and topographical cues provided by HAp-incorporated P(VDF-TrFE) scaffolds. (b) Schematic diagram of the fabrication process. > The research team developed a manufacturing process that fuses HAp with a polymer film. The flexible and free-standing scaffold developed through this process demonstrated its remarkable potential for promoting bone regeneration through in-vitro and in-vivo experiments in rats. The team also identified the principles of bone regeneration that their scaffold is based on. Using atomic force microscopy (AFM), they analysed the electrical properties of the scaffold and evaluated the detailed surface properties related to cell shape and cell skeletal protein formation. They also investigated the effects of piezoelectricity and surface properties on the expression of growth factors. Professor Hong from KAIST’s DMSE said, “We have developed a HAp-based piezoelectric composite material that can act like a ‘bone bandage’ through its ability to accelerate bone regeneration.” He added, “This research not only suggests a new direction for designing biomaterials, but is also significant in having explored the effects of piezoelectricity and surface properties on bone regeneration.” This research, conducted by co-first authors Soyun Joo and Soyeon Kim from Professor Hong’s group, was published on ACS Applied Materials & Interfaces on January 4 under the title “Piezoelectrically and Topographically Engineered Scaffolds for Accelerating Bone Regeneration”. From Professor Kim’s group, Ph.D. candidate Yonghyun Gwon also participated as co-first author, and Professor Kim himself as a corresponding author. < Figure 2. Analysis of piezoelectric and surface properties of the biomimetic scaffolds using atomic force microscopy. (a) PFM amplitude and phase images of box-poled composite scaffolds. The white bar represents 2 μm. (b) 3D representations of composite scaffolds paired with typical 2D line sections. (c) In vivo bone regeneration micro-CT analysis, (d) schematic representation of filler-derived electrical origins in bone regeneration. > This research was supported by the KAIST Research and Development Team, the KUSTAR-KAIST Joint Research Center, the KAIST Global Singularity Project, and the government-funded Basic Research Project by the National Research Foundation of Korea.
2024.02.01
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KAIST Research Team Develops Sweat-Resistant Wearable Robot Sensor
New electromyography (EMG) sensor technology that allows the long-term stable control of wearable robots and is not affected by the wearer’s sweat and dead skin has gained attention recently. Wearable robots are devices used across a variety of rehabilitation treatments for the elderly and patients recovering from stroke or trauma. A joint research team led by Professor Jae-Woong Jung from the KAIST School of Electrical Engineering (EE) and Professor Jung Kim from the KAIST Department of Mechanical Engineering (ME) announced on January 23rd that they have successfully developed a stretchable and adhesive microneedle sensor that can electrically sense physiological signals at a high level without being affected by the state of the user’s skin. For wearable robots to recognize the intentions behind human movement for their use in rehabilitation treatment, they require a wearable electrophysiological sensor that gives precise EMG measurements. However, existing sensors often show deteriorating signal quality over time and are greatly affected by the user’s skin conditions. Furthermore, the sensor’s higher mechanical hardness causes noise since the contact surface is unable to keep up with the deformation of the skin. These shortcomings limit the reliable, long-term control of wearable robots. < Figure 1. Design and working concept of the Stretchable microNeedle Adhesive Patch (SNAP). (A) Schematic illustration showing the overall system configuration and application of SNAP. (B) Exploded view schematic diagram of a SNAP, consisting of stretchable serpentine interconnects, Au-coated Si microneedle, and ECA made of Ag flakes–silicone composite. (C) Optical images showing high mechanical compliance of SNAP. > However, the recently developed technology is expected to allow long-term and high-quality EMG measurements as it uses a stretchable and adhesive conducting substrate integrated with microneedle arrays that can easily penetrate the stratum corneum without causing discomfort. Through its excellent performance, the sensor is anticipated to be able to stably control wearable robots over a long period of time regardless of the wearer’s changing skin conditions and without the need for a preparation step that removes sweat and dead cells from the surface of their skin. The research team created a stretchable and adhesive microneedle sensor by integrating microneedles into a soft silicon polymer substrate. The hard microneedles penetrate through the stratum corneum, which has high electrical resistance. As a result, the sensor can effectively lower contact resistance with the skin and obtain high-quality electrophysiological signals regardless of contamination. At the same time, the soft and adhesive conducting substrate can adapt to the skin’s surface that stretches with the wearer’s movement, providing a comfortable fit and minimizing noise caused by movement. < Figure 2. Demonstration of the wireless Stretchable microNeedle Adhesive Patch (SNAP) system as an Human-machine interfaces (HMI) for closed-loop control of an exoskeleton robot. (A) Illustration depicting the system architecture and control strategy of an exoskeleton robot. (B) The hardware configuration of the pneumatic back support exoskeleton system. (C) Comparison of root mean square (RMS) of electromyography (EMG) with and without robotic assistance of pretreated skin and non-pretreated skin. > To verify the usability of the new patch, the research team conducted a motion assistance experiment using a wearable robot. They attached the microneedle patch on a user’s leg, where it could sense the electrical signals generated by the muscle. The sensor then sent the detected intention to a wearable robot, allowing the robot to help the wearer lift a heavy object more easily. Professor Jae-Woong Jung, who led the research, said, “The developed stretchable and adhesive microneedle sensor can stability detect EMG signals without being affected by the state of a user’s skin. Through this, we will be able to control wearable robots with higher precision and stability, which will help the rehabilitation of patients who use robots.” The results of this research, written by co-first authors Heesoo Kim and Juhyun Lee, who are both Ph.D. candidates in the KAIST School of EE, were published in Science Advances on January 17th under the title “Skin-preparation-free, stretchable microneedle adhesive patches for reliable electrophysiological sensing and exoskeleton robot control”. This research was supported by the Bio-signal Sensor Integrated Technology Development Project by the National Research Foundation of Korea, the Electronic Medicinal Technology Development Project, and the Step 4 BK21 Project.
2024.01.30
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KAIST develops an artificial muscle device that produces force 34 times its weight
- Professor IlKwon Oh’s research team in KAIST’s Department of Mechanical Engineering developed a soft fluidic switch using an ionic polymer artificial muscle that runs with ultra-low power to lift objects 34 times greater than its weight. - Its light weight and small size make it applicable to various industrial fields such as soft electronics, smart textiles, and biomedical devices by controlling fluid flow with high precision, even in narrow spaces. Soft robots, medical devices, and wearable devices have permeated our daily lives. KAIST researchers have developed a fluid switch using ionic polymer artificial muscles that operates at ultra-low power and produces a force 34 times greater than its weight. Fluid switches control fluid flow, causing the fluid to flow in a specific direction to invoke various movements. KAIST (President Kwang-Hyung Lee) announced on the 4th of January that a research team under Professor IlKwon Oh from the Department of Mechanical Engineering has developed a soft fluidic switch that operates at ultra-low voltage and can be used in narrow spaces. Artificial muscles imitate human muscles and provide flexible and natural movements compared to traditional motors, making them one of the basic elements used in soft robots, medical devices, and wearable devices. These artificial muscles create movements in response to external stimuli such as electricity, air pressure, and temperature changes, and in order to utilize artificial muscles, it is important to control these movements precisely. Switches based on existing motors were difficult to use within limited spaces due to their rigidity and large size. In order to address these issues, the research team developed an electro-ionic soft actuator that can control fluid flow while producing large amounts of force, even in a narrow pipe, and used it as a soft fluidic switch. < Figure 1. The separation of fluid droplets using a soft fluid switch at ultra-low voltage. > The ionic polymer artificial muscle developed by the research team is composed of metal electrodes and ionic polymers, and it generates force and movement in response to electricity. A polysulfonated covalent organic framework (pS-COF) made by combining organic molecules on the surface of the artificial muscle electrode was used to generate an impressive amount of force relative to its weight with ultra-low power (~0.01V). As a result, the artificial muscle, which was manufactured to be as thin as a hair with a thickness of 180 µm, produced a force more than 34 times greater than its light weight of 10 mg to initiate smooth movement. Through this, the research team was able to precisely control the direction of fluid flow with low power. < Figure 2. The synthesis and use of pS-COF as a common electrode-electrolyte host for electroactive soft fluid switches. A) The synthesis schematic of pS-COF. B) The schematic diagram of the operating principle of the electrochemical soft switch. C) The schematic diagram of using a pS-COF-based electrochemical soft switch to control fluid flow in dynamic operation. > Professor IlKwon Oh, who led this research, said, “The electrochemical soft fluidic switch that operate at ultra-low power can open up many possibilities in the fields of soft robots, soft electronics, and microfluidics based on fluid control.” He added, “From smart fibers to biomedical devices, this technology has the potential to be immediately put to use in a variety of industrial settings as it can be easily applied to ultra-small electronic systems in our daily lives.” The results of this study, in which Dr. Manmatha Mahato, a research professor in the Department of Mechanical Engineering at KAIST, participated as the first author, were published in the international academic journal Science Advances on December 13, 2023. (Paper title: Polysulfonated Covalent Organic Framework as Active Electrode Host for Mobile Cation Guests in Electrochemical Soft Actuator) This research was conducted with support from the National Research Foundation of Korea's Leader Scientist Support Project (Creative Research Group) and Future Convergence Pioneer Project. * Paper DOI: https://www.science.org/doi/abs/10.1126/sciadv.adk9752
2024.01.11
View 6423
KAIST Demonstrates AI and sustainable technologies at CES 2024
On January 2, KAIST announced it will be participating in the Consumer Electronics Show (CES) 2024, held between January 9 and 12. CES 2024 is one of the world’s largest tech conferences to take place in Las Vegas. Under the slogan “KAIST, the Global Value Creator” for its exhibition, KAIST has submitted technologies falling under one of following themes: “Expansion of Human Intelligence, Mobility, and Reality”, and “Pursuit of Human Security and Sustainable Development”. 24 startups and pre-startups whose technologies stand out in various fields including artificial intelligence (AI), mobility, virtual reality, healthcare and human security, and sustainable development, will welcome their visitors at an exclusive booth of 232 m2 prepared for KAIST at Eureka Park in Las Vegas. 12 businesses will participate in the first category, “Expansion of Human Intelligence, Mobility, and Reality”, including MicroPix, Panmnesia, DeepAuto, MGL, Reports, Narnia Labs, EL FACTORY, Korea Position Technology, AudAi, Planby Technologies, Movin, and Studio Lab. In the “Pursuit of Human Security and Sustainable Development” category, 12 businesses including Aldaver, ADNC, Solve, Iris, Blue Device, Barreleye, TR, A2US, Greeners, Iron Boys, Shard Partners and Kingbot, will be introduced. In particular, Aldaver is a startup that received the Korean Business Award 2023 as well as the presidential award at the Challenge K-Startup with its biomimetic material and printing technology. It has attracted 4.5 billion KRW of investment thus far. Narnia Labs, with its AI design solution for manufacturing, won the grand prize for K-tech Startups 2022, and has so far attracted 3.5 billion KRW of investments. Panmnesia is a startup that won the 2024 CES Innovation Award, recognized for their fab-less AI semiconductor technology. They attracted 16 billion KRW of investment through seed round alone. Meanwhile, student startups will also be presented during the exhibition. Studio Lab received a CES 2024 Best of Innovation Award in the AI category. The team developed the software Seller Canvas, which automatically generates a page for product details when a user uploads an image of a product. The central stage at the KAIST exhibition booth will be used to interview members of the participating startups between Jan 9 to 11, as well as a networking site for businesses and invited investors during KAIST NIGHT on the evening of 10th, between 5 and 7 PM. Director Sung-Yool Choi of the KAIST Institute of Technology Value Creation said, “Through CES 2024, KAIST will overcome the limits of human intelligence, mobility, and space with the deep-tech based technologies developed by its startups, and will demonstrate its achievements for realizing its vision as a global value-creating university through the solutions for human security and sustainable development.”
2024.01.05
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A KAIST Research Team Develops High-Performance Stretchable Solar Cells
With the market for wearable electric devices growing rapidly, stretchable solar cells that can function under strain have received considerable attention as an energy source. To build such solar cells, it is necessary that their photoactive layer, which converts light into electricity, shows high electrical performance while possessing mechanical elasticity. However, satisfying both of these two requirements is challenging, making stretchable solar cells difficult to develop. On December 26, a KAIST research team from the Department of Chemical and Biomolecular Engineering (CBE) led by Professor Bumjoon Kim announced the development of a new conductive polymer material that achieved both high electrical performance and elasticity while introducing the world’s highest-performing stretchable organic solar cell. Organic solar cells are devices whose photoactive layer, which is responsible for the conversion of light into electricity, is composed of organic materials. Compared to existing non-organic material-based solar cells, they are lighter and flexible, making them highly applicable for wearable electrical devices. Solar cells as an energy source are particularly important for building electrical devices, but high-efficiency solar cells often lack flexibility, and their application in wearable devices have therefore been limited to this point. The team led by Professor Kim conjugated a highly stretchable polymer to an electrically conductive polymer with excellent electrical properties through chemical bonding, and developed a new conductive polymer with both electrical conductivity and mechanical stretchability. This polymer meets the highest reported level of photovoltaic conversion efficiency (19%) using organic solar cells, while also showing 10 times the stretchability of existing devices. The team thereby built the world’s highest performing stretchable solar cell that can be stretched up to 40% during operation, and demonstrated its applicability for wearable devices. < Figure 1. Chemical structure of the newly developed conductive polymer and performance of stretchable organic solar cells using the material. > Professor Kim said, “Through this research, we not only developed the world’s best performing stretchable organic solar cell, but it is also significant that we developed a new polymer that can be applicable as a base material for various electronic devices that needs to be malleable and/or elastic.” < Figure 2. Photovoltaic efficiency and mechanical stretchability of newly developed polymers compared to existing polymers. > This research, conducted by KAIST researchers Jin-Woo Lee and Heung-Goo Lee as first co-authors in cooperation with teams led by Professor Taek-Soo Kim from the Department of Mechanical Engineering and Professor Sheng Li from the Department of CBE, was published in Joule on December 1 (Paper Title: Rigid and Soft Block-Copolymerized Conjugated Polymers Enable High-Performance Intrinsically-Stretchable Organic Solar Cells). This research was supported by the National Research Foundation of Korea.
2024.01.04
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2023 Global Entrepreneurship Summer School in Silicon Valley Successfully Concluded
< 2023 Silicon Valley Global Entrepreneurship Summer School Participants > The 2023 KAIST Global Entrepreneurship Summer School (GESS) was successfully held. Co-hosted by the Center for Global Strategies and Planning (GSP) (Director Man-Sung Yim) and the Startup KAIST (Director Hyeonmin Bae), the 2023 KAIST GESS was the second one of the summer programs, repeating the Silicon Valley global entrepreneurship bootcamp of 2022 (2022 GESC), based on industry-academia collaboration. This program was designed to provide students with the opportunity to visit Silicon Valley, the global hub of entrepreneurship, and personally experience the Silicon Valley culture while developing human networks that would serve as a foundation for their overseas startup development. A total of 20 participants were selected earlier this year, including potential KAISTian entrepreneurs and early-stage entrepreneurs from KAIST within one year of incorporation. In particular, a number of foreign students of various nationalities such as Vietnam, Azerbaijan, Honduras, Indonesia, Philippines, and Kazakhstan, increased significantly, demonstrating the enthusiasm for entrepreneurship across national boundaries along with the program's growing international status. This year's event was also open to 20 Impact MBA and Social Entrepreneur (SE) students from KAIST's College of Business for the Silicon Valley program. For the past two months, the participants have trained on business model development and pitching at KAIST's main campus in Daejeon. From June 21st to the 30th, they visited the campuses of leading universities, such as, Stanford University, UC Santa Cruz, and UC Berkeley, as well as KOTRA Silicon Valley Trade Center (Manager Hyoung il Kim), and local alumni companies and Apple company to experience the global technology startups. The start-ups by KAIST alums including B Garage (CEO Aiden Kim), ImpriMed (CEO Sungwon Lim), Medic Life Sciences (CEO Kyuho Han), and VESSL AI (CEO Jaeman Ahn) participated in the program and gave lectures and company tours to inspire the participants to have passion to take on the entrepreneurial endeavors and challenges. On the last day, the participants gave presentations on their team’s business items in front of local venture capitalists in Silicon Valley. After receiving continuous coaching from Silicon Valley's professional accelerators through remote video conferencing and face-to-face mentoring for the last two months, the participants developed their business models and presented their creative and innovative ideas, revealing their potential as future global entrepreneurs. At the final competition, Team Sparky that developed “Snoove” won the first prize. Snoove is a scientifically-proven mattress accessory that applies mild vibration to the mattress to aid users in achieving better sleep, a method previously used to soothe infants. < GESS Pitching Day Presentation > Kevin Choi from the Team Sparky said, "Seeing and experiencing the realities of entrepreneurship in Silicon Valley, a global startup scene, made me think about the importance of unlearning, challenging, and failing to be a global entrepreneur who contributes to our society." Man-Sung Yim, the Associate Vice President of the International Office, who organized the event added, "Through this experience, we expect KAIST students to grow to become global leaders who would create global values and enhance the international reputation of our university." Meanwhile, the GSP and Startup KAIST commented that they will to continue to develop the KAIST GESS program to foster prospective entrepreneurs who can compete in the global market based on the success of this program.
2023.07.05
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Prof. Austin Givens of KAIST Language Center receives Ministerial Commendation
< Professor Austin Givens posing with the Letter of Commendation by the Miniser Hwang-Keun Chung of the Ministry of Agriculture, Food and Rural Affairs at the Language Center > Professor Austin Givens of our Language Center received a Ministerial Commendation from the Korean Ministry of Agriculture, Food and Rural Affairs dated December 21st, 2022 for his contribution for the development of the Korean Foodservices Industry through his active and prominent media presence. Professor Austin Givens has been working with the KAIST Language Center since 2017, and has shown his passion for Korean food through his YouTube channel "Austin! Eating What is Given", introducing not only the food but also the culture of Korea and KAIST to his international viewers through the videos he shares of his candid reviews of the food and restaurants around town on the popular video streaming platform. < Thumbnail introductions of Professor Givens' videos on his YouTube channel, "Austin! Eating What is Given" > - KAIST Language Center
2023.02.09
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