Team KAIST placed among top two at MBZIRC Maritime..
Representing Korean Robotics at Sea: KAIST’s 26-month strife rewarded Team KAIST placed among top two at MBZIRC Maritime Grand Challenge - Team KAIST, composed of students from the labs of Professor Jinwhan Kim of the Department of Mechanical Engineering and Professor Hyunchul Shim of the School of Electrical and Engineering, came through the challenge as the first runner-up winning the prize money totaling up to ＄650,000 (KRW 860 million). - Successfully led the autonomous collaboration of unmanned aerial and maritime vehicles using cutting-edge robotics and AI technology through to the final round of the competition held in Abu Dhabi from January 10 to February 6, 2024. KAIST (President Kwang-Hyung Lee), reported on the 8th that Team KAIST, led by students from the labs of Professor Jinwhan Kim of the Department of Mechanical Engineering and Professor Hyunchul Shim of the School of Electrical Engineering, with Pablo Aviation as a partner, won a total prize money of ＄650,000 (KRW 860 million) at the Maritime Grand Challenge by the Mohamed Bin Zayed International Robotics Challenge (MBZIRC), finishing first runner-up. This competition, which is the largest ever robotics competition held over water, is sponsored by the government of the United Arab Emirates and organized by ASPIRE, an organization under the Abu Dhabi Ministry of Science, with a total prize money of ＄3 million. In the competition, which started at the end of 2021, 52 teams from around the world participated and five teams were selected to go on to the finals in February 2023 after going through the first and second stages of screening. The final round was held from January 10 to February 6, 2024, using actual unmanned ships and drones in a secluded sea area of 10 km2 off the coast of Abu Dhabi, the capital of the United Arab Emirates. A total of 18 KAIST students and Professor Jinwhan Kim and Professor Hyunchul Shim took part in this competition at the location at Abu Dhabi. Team KAIST will receive ＄500,000 in prize money for taking second place in the final, and the team’s prize money totals up to ＄650,000 including ＄150,000 that was as special midterm award for finalists. The final mission scenario is to find the target vessel on the run carrying illegal cargoes among many ships moving within the GPS-disabled marine surface, and inspect the deck for two different types of stolen cargo to recover them using the aerial vehicle to bring the small cargo and the robot manipulator topped on an unmanned ship to retrieve the larger one. The true aim of the mission is to complete it through autonomous collaboration of the unmanned ship and the aerial vehicle without human intervention throughout the entire mission process. In particular, since GPS cannot be used in this competition due to regulations, Professor Jinwhan Kim's research team developed autonomous operation techniques for unmanned ships, including searching and navigating methods using maritime radar, and Professor Hyunchul Shim's research team developed video-based navigation and a technology to combine a small autonomous robot with a drone. The final mission is to retrieve cargo on board a ship fleeing at sea through autonomous collaboration between unmanned ships and unmanned aerial vehicles without human intervention. The overall mission consists the first stage of conducting the inspection to find the target ship among several ships moving at sea and the second stage of conducting the intervention mission to retrieve the cargoes on the deck of the ship. Each team was given a total of three opportunities, and the team that completed the highest-level mission in the shortest time during the three attempts received the highest score. In the first attempt, KAIST was the only team to succeed in the first stage search mission, but the competition began in earnest as the Croatian team also completed the first stage mission in the second attempt. As the competition schedule was delayed due to strong winds and high waves that continued for several days, the organizers decided to hold the finals with the three teams, including the Team KAIST and the team from Croatia’s the University of Zagreb, which completed the first stage of the mission, and Team Fly-Eagle, a team of researcher from China and UAE that partially completed the first stage. The three teams were given the chance to proceed to the finals and try for the third attempt, and in the final competition, the Croatian team won, KAIST took the second place, and the combined team of UAE-China combined team took the third place. The final prize to be given for the winning team is set at ＄2 million with ＄500,000 for the runner-up team, and ＄250,000 for the third-place. Professor Jinwhan Kim of the Department of Mechanical Engineering, who served as the advisor for Team KAIST, said, “I would like to express my gratitude and congratulations to the students who put in a huge academic and physical efforts in preparing for the competition over the past two years. I feel rewarded because, regardless of the results, every bit of efforts put into this up to this point will become the base of their confidence and a valuable asset in their growth into a great researcher.” Sol Han, a doctoral student in mechanical engineering who served as the team leader, said, “I am disappointed of how narrowly we missed out on winning at the end, but I am satisfied with the significance of the output we’ve got and I am grateful to the team members who worked hard together for that.” HD Hyundai, Rainbow Robotics, Avikus, and FIMS also participated as sponsors for Team KAIST's campaign.
KAIST develops an artificial muscle device that pr..
- 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
A KAIST Research Team Develops High-Performance St..
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.
KAIST presents strategies for environmentally frie..
- Provides current research trends in bio-based polyamide production - Research on bio-based polyamides production gains importance for achieving a carbon-neutral society Global industries focused on carbon neutrality, under the slogan "Net-Zero," are gaining increasing attention. In particular, research on microbial production of polymers, replacing traditional chemical methods with biological approaches, is actively progressing. Polyamides, represented by nylon, are linear polymers widely used in various industries such as automotive, electronics, textiles, and medical fields. They possess beneficial properties such as high tensile strength, electrical insulation, heat resistance, wear resistance, and biocompatibility. Since the commercialization of nylon in 1938, approximately 7 million tons of polyamides are produced worldwide annually. Considering their broad applications and significance, producing polyamides through bio-based methods holds considerable environmental and industrial importance. KAIST (President Kwang-Hyung Lee) announced that a research team led by Distinguished Professor Sang Yup Lee, including Dr. Jong An Lee and doctoral candidate Ji Yeon Kim from the Department of Chemical and Biomolecular Engineering, published a paper titled "Current Advancements in Bio-Based Production of Polyamides”. The paper was featured on the cover of the monthly issue of "Trends in Chemistry” by Cell Press. As part of climate change response technologies, bio-refineries involve using biotechnological and chemical methods to produce industrially important chemicals and biofuels from renewable biomass without relying on fossil resources. Notably, systems metabolic engineering, pioneered by KAIST's Distinguished Professor Sang Yup Lee, is a research field that effectively manipulates microbial metabolic pathways to produce valuable chemicals, forming the core technology for bio-refineries. The research team has successfully developed high-performance strains producing a variety of compounds, including succinic acid, biodegradable plastics, biofuels, and natural products, using systems metabolic engineering tools and strategies. The research team predicted that if bio-based polyamide production technology, which is widely used in the production of clothing and textiles, becomes widespread, it will attract attention as a future technology that can respond to the climate crisis due to its environment-friendly production technology. In this study, the research team comprehensively reviewed the bio-based polyamide production strategies. They provided insights into the advancements in polyamide monomer production using metabolically engineered microorganisms and highlighted the recent trends in bio-based polyamide advancements utilizing these monomers. Additionally, they reviewed the strategies for synthesizing bio-based polyamides through chemical conversion of natural oils and discussed the biodegradability and recycling of the polyamides. Furthermore, the paper presented the future direction in which metabolic engineering can be applied for the bio-based polyamide production, contributing to environmentally friendly and sustainable society. Ji Yeon Kim, the co-first author of this paper from KAIST, stated "The importance of utilizing systems metabolic engineering tools and strategies for bio-based polyamides production is becoming increasingly prominent in achieving carbon neutrality." Professor Sang Yup Lee emphasized, "Amid growing concerns about climate change, the significance of environmentally friendly and sustainable industrial development is greater than ever. Systems metabolic engineering is expected to have a significant impact not only on the chemical industry but also in various fields." < [Figure 1] A schematic overview of the overall process for polyamides production > This paper by Dr. Jong An Lee, PhD student Ji Yeon Kim, Dr. Jung Ho Ahn, and Master Yeah-Ji Ahn from the Department of Chemical and Biomolecular Engineering at KAIST was published in the December issue of 'Trends in Chemistry', an authoritative review journal in the field of chemistry published by Cell. It was published on December 7 as the cover paper and featured review. ※ Paper title: Current advancements in the bio-based production of polyamides ※ Author information: Jong An Lee, Ji Yeon Kim, Jung Ho Ahn, Yeah-Ji Ahn, and Sang Yup Lee This research was conducted with the support from the development of platform technologies of microbial cell factories for the next-generation biorefineries project and C1 gas refinery program by Korean Ministry of Science and ICT. < [Figure 2] Cover paper of the December issue of Trends in Chemistry >
KAIST introduces eco-friendly technologies for pla..
- A research team under Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering published a paper in Nature Microbiology on the overview and trends of plastic production and degradation technology using microorganisms. - Eco-friendly and sustainable plastic production and degradation technology using microorganisms as a core technology to achieve a plastic circular economy was presented. Plastic is one of the important materials in modern society, with approximately 460 million tons produced annually and with expected production reaching approximately 1.23 billion tons in 2060. However, since 1950, plastic waste totaling more than 6.3 billion tons has been generated, and it is believed that more than 140 million tons of plastic waste has accumulated in the aquatic environment. Recently, the seriousness of microplastic pollution has emerged, not only posing a risk to the marine ecosystem and human health, but also worsening global warming by inhibiting the activity of marine plankton, which play an important role in lowering the Earth's carbon dioxide concentration. KAIST President Kwang-Hyung Lee announced on December 11 that a research team under Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering had published a paper titled 'Sustainable production and degradation of plastics using microbes', which covers the latest technologies for producing plastics and processing waste plastics in an eco-friendly manner using microorganisms. As the international community moves to solve this plastic problem, various efforts are being made, including 175 countries participating to conclude a legally binding agreement with the goal of ending plastic pollution by 2024. Various technologies are being developed for sustainable plastic production and processing, and among them, biotechnology using microorganisms is attracting attention. Microorganisms have the ability to naturally produce or decompose certain compounds, and this ability is maximized through biotechnologies such as metabolic engineering and enzyme engineering to produce plastics from renewable biomass resources instead of fossil raw materials and to decompose waste plastics. Accordingly, the research team comprehensively analyzed the latest microorganism-based technologies for the sustainable production and decomposition of plastics and presented how they actually contribute to solving the plastic problem. Based on this, they presented limitations, prospects, and research directions of the technologies for achieving a circular economy for plastics. Microorganism-based technologies for various plastics range from widely used synthetic plastics such as polyethylene (PE) to promising bioplastics such as natural polymers derived from microorganisms (polyhydroxyalkanoate (PHA)) that are completely biodegradable in the natural environment and do not pose a risk of microplastic generation. Commercialization statuses and latest technologies were also discussed. In addition, the technology to decompose these plastics using microorganisms and their enzymes and the upcycling technology to convert them into other useful compounds after decomposition were introduced, highlighting the competitiveness and potential of technology using microorganisms. First author So Young Choi, a research assistant professor in the Department of Chemical and Biomolecular Engineering at KAIST, said, “In the future, we will be able to easily find eco-friendly plastics made using microorganisms all around us,” and corresponding author Distinguished Professor Sang Yup Lee said, “Plastic can be made more sustainable. It is important to use plastics responsibly to protect the environment and simultaneously achieve economic and social development through the new plastics industry, and we look forward to the improved performance of microbial metabolic engineering technology.” This paper was published on November 30th in the online edition of Nature Microbiology. ※ Paper Title : Sustainable production and degradation of plastics using microbes Authors: So Young Choi, Youngjoon Lee, Hye Eun Yu, In Jin Cho, Minju Kang & Sang Yup Lee < Life cycle of plastics produced using microbial biotechnologies > This research was conducted with the support from the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries Project (2022M3J5A1056117) and the Development of Platform Technology for the Production of Novel Aromatic Bioplastic Using Microbial Cell Factories Project (2022M3J4A1053699) by the Korean Ministry of Science and ICT.
KAIST-UCSD researchers build an enzyme discovering..
- A joint research team led by Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering and Bernhard Palsson of UCSD developed ‘DeepECtransformer’, an artificial intelligence that can predict Enzyme Commission (EC) number of proteins. - The AI is tasked to discover new enzymes that have not been discovered yet, which would allow prediction for a total of 5,360 types of Enzyme Commission (EC) numbers - It is expected to be used in the development of microbial cell factories that produce environmentally friendly chemicals as a core technology for analyzing the metabolic network of a genome. While E. coli is one of the most studied organisms, the function of 30％ of proteins that make up E. coli has not yet been clearly revealed. For this, an artificial intelligence was used to discover 464 types of enzymes from the proteins that were unknown, and the researchers went on to verify the predictions of 3 types of proteins were successfully identified through in vitro enzyme assay. KAIST (President Kwang-Hyung Lee) announced on the 24th that a joint research team comprised of Gi Bae Kim, Ji Yeon Kim, Dr. Jong An Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST, and Dr. Charles J. Norsigian and Professor Bernhard O. Palsson of the Department of Bioengineering at UCSD has developed DeepECtransformer, an artificial intelligence that can predict the enzyme functions from the protein sequence, and has established a prediction system by utilizing the AI to quickly and accurately identify the enzyme function. Enzymes are proteins that catalyze biological reactions, and identifying the function of each enzyme is essential to understanding the various chemical reactions that exist in living organisms and the metabolic characteristics of those organisms. Enzyme Commission (EC) number is an enzyme function classification system designed by the International Union of Biochemistry and Molecular Biology, and in order to understand the metabolic characteristics of various organisms, it is necessary to develop a technology that can quickly analyze enzymes and EC numbers of the enzymes present in the genome. Various methodologies based on deep learning have been developed to analyze the features of biological sequences, including protein function prediction, but most of them have a problem of a black box, where the inference process of AI cannot be interpreted. Various prediction systems that utilize AI for enzyme function prediction have also been reported, but they do not solve this black box problem, or cannot interpret the reasoning process in fine-grained level (e.g., the level of amino acid residues in the enzyme sequence). The joint team developed DeepECtransformer, an AI that utilizes deep learning and a protein homology analysis module to predict the enzyme function of a given protein sequence. To better understand the features of protein sequences, the transformer architecture, which is commonly used in natural language processing, was additionally used to extract important features about enzyme functions in the context of the entire protein sequence, which enabled the team to accurately predict the EC number of the enzyme. The developed DeepECtransformer can predict a total of 5360 EC numbers. The joint team further analyzed the transformer architecture to understand the inference process of DeepECtransformer, and found that in the inference process, the AI utilizes information on catalytic active sites and/or the cofactor binding sites which are important for enzyme function. By analyzing the black box of DeepECtransformer, it was confirmed that the AI was able to identify the features that are important for enzyme function on its own during the learning process. "By utilizing the prediction system we developed, we were able to predict the functions of enzymes that had not yet been identified and verify them experimentally," said Gi Bae Kim, the first author of the paper. "By using DeepECtransformer to identify previously unknown enzymes in living organisms, we will be able to more accurately analyze various facets involved in the metabolic processes of organisms, such as the enzymes needed to biosynthesize various useful compounds or the enzymes needed to biodegrade plastics." he added. "DeepECtransformer, which quickly and accurately predicts enzyme functions, is a key technology in functional genomics, enabling us to analyze the function of entire enzymes at the systems level," said Professor Sang Yup Lee. He added, “We will be able to use it to develop eco-friendly microbial factories based on comprehensive genome-scale metabolic models, potentially minimizing missing information of metabolism.” The joint team’s work on DeepECtransformer is described in the paper titled "Functional annotation of enzyme-encoding genes using deep learning with transformer layers" written by Gi Bae Kim, Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST and their colleagues. The paper was published via peer-review on the 14th of November on “Nature Communications”. This research was conducted with the support by “the Development of next-generation bioreﬁnery platform technologies for leading bio-based chemicals industry project (2022M3J5A1056072)” and by “Development of platform technologies of microbial cell factories for the next-generation bioreﬁneries project (2022M3J5A1056117)” from National Research Foundation supported by the Korean Ministry of Science and ICT (Project Leader: Distinguished Professor Sang Yup Lee, KAIST). < Figure 1. The structure of DeepECtransformer's artificial neural network >
An intravenous needle that irreversibly softens vi..
- A joint research team at KAIST developed an intravenous (IV) needle that softens upon insertion, minimizing risk of damage to blood vessels and tissues. - Once used, it remains soft even at room temperature, preventing accidental needle stick injuries and unethical multiple use of needle. - A thin-film temperature sensor can be embedded with this needle, enabling real-time monitoring of the patient's core body temperature, or detection of unintended fluid leakage, during IV medication. Intravenous (IV) injection is a method commonly used in patient’s treatment worldwide as it induces rapid effects and allows treatment through continuous administration of medication by directly injecting drugs into the blood vessel. However, medical IV needles, made of hard materials such as stainless steel or plastic which do not mechanically match the soft biological tissues of the body, can cause critical problems in healthcare settings, starting from minor tissue damages in the injection sites to serious inflammations. The structure and dexterity of rigid medical IV devices also enable unethical reuse of needles for reduction of injection costs, leading to transmission of deadly blood-borne disease infections such as human immunodeficiency virus (HIV) and hepatitis B/C viruses. Furthermore, unintended needlestick injuries are frequently occurring in medical settings worldwide, that are viable sources of such infections, with IV needles having the greatest susceptibility of being the medium of transmissible diseases. For these reasons, the World Health Organization (WHO) in 2015 launched a policy on safe injection practices to encourage the development and use of “smart” syringes that have features to prevent re-use, after a tremendous increase in the number of deadly infectious disease worldwide due to medical-sharps related issues. KAIST announced on the 13th that Professor Jae-Woong Jeong and his research team of its School of Electrical Engineering succeeded in developing the Phase-Convertible, Adapting and non-REusable (P-CARE) needle with variable stiffness that can improve patient health and ensure the safety of medical staff through convergent joint research with another team led by Professor Won-Il Jeong of the Graduate School of Medical Sciences. The new technology is expected to allow patients to move without worrying about pain at the injection site as it reduces the risk of damage to the wall of the blood vessel as patients receive IV medication. This is possible with the needle’s stiffness-tunable characteristics which will make it soft and flexible upon insertion into the body due to increased temperature, adapting to the movement of thin-walled vein. It is also expected to prevent blood-borne disease infections caused by accidental needlestick injuries or unethical re-using of syringes as the deformed needle remains perpetually soft even after it is retracted from the injection site. The results of this research, in which Karen-Christian Agno, a doctoral researcher of the School of Electrical Engineering at and Dr. Keungmo Yang of the Graduate School of Medical Sciences participated as co-first authors, was published in Nature Biomedical Engineering on October 30. (Paper title: A temperature-responsive intravenous needle that irreversibly softens on insertion) < Figure 1. Disposable variable stiffness intravenous needle. (a) Conceptual illustration of the key features of the P-CARE needle whose mechanical properties can be changed by body temperature, (b) Photograph of commonly used IV access devices and the P-CARE needle, (c) Performance of common IV access devices and the P-CARE needle > “We’ve developed this special needle using advanced materials and micro/nano engineering techniques, and it can solve many global problems related to conventional medical needles used in healthcare worldwide”, said Jae-Woong Jeong, Ph.D., an associate professor of Electrical Engineering at KAIST and a lead senior author of the study. The softening IV needle created by the research team is made up of liquid metal gallium that forms the hollow, mechanical needle frame encapsulated within an ultra-soft silicone material. In its solid state, gallium has sufficient hardness that enables puncturing of soft biological tissues. However, gallium melts when it is exposed to body temperature upon insertion, and changes it into a soft state like the surrounding tissue, enabling stable delivery of the drug without damaging blood vessels. Once used, a needle remains soft even at room temperature due to the supercooling phenomenon of gallium, fundamentally preventing needlestick accidents and reuse problems. Biocompatibility of the softening IV needle was validated through in vivo studies in mice. The studies showed that implanted needles caused significantly less inflammation relative to the standard IV access devices of similar size made of metal needles or plastic catheters. The study also confirmed the new needle was able to deliver medications as reliably as commercial injection needles. < Photo 1. Photo of the P-CARE needle that softens with body temperature. > Researchers also showed possibility of integrating a customized ultra-thin temperature sensor with the softening IV needle to measure the on-site temperature which can further enhance patient’s well-being. The single assembly of sensor-needle device can be used to monitor the core body temperature, or even detect if there is a fluid leakage on-site during indwelling use, eliminating the need for additional medical tools or procedures to provide the patients with better health care services. The researchers believe that this transformative IV needle can open new opportunities for wide range of applications particularly in clinical setups, in terms of redesigning other medical needles and sharp medical tools to reduce muscle tissue injury during indwelling use. The softening IV needle may become even more valuable in the present times as there is an estimated 16 billion medical injections administered annually in a global scale, yet not all needles are disposed of properly, based on a 2018 WHO report. < Figure 2. Biocompatibility test for P-CARE needle: Images of H&E stained histology (the area inside the dashed box on the left is provided in an expanded view in the right), TUNEL staining (green), DAPI staining of nuclei (blue) and co-staining (TUNEL and DAPI) of muscle tissue from different organs. > < Figure 3. Conceptual images of potential utilization for temperature monitoring function of P-CARE needle integrated with a temperature sensor. > (a) Schematic diagram of injecting a drug through intravenous injection into the abdomen of a laboratory mouse (b) Change of body temperature upon injection of drug (c) Conceptual illustration of normal intravenous drug injection (top) and fluid leakage (bottom) (d) Comparison of body temperature during normal drug injection and fluid leakage: when the fluid leak occur due to incorrect insertion, a sudden drop of temperature is detected. This work was supported by grants from the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT.
KAIST Civil Engineering Students named Runner-up a..
A team of five students from the Korea Advanced Institute of Science and Technology (KAIST) were awarded second place in a premier urban design student competition hosted by the Urban Land Institute and Hines, 2023 ULI Hines Student Competition - Asia Pacific. The competition, which was held for the first time in the Asia-Pacific region, is an internationally recognized event which typically attract hundreds of applicants. Jonah Remigio, Sojung Noh, Estefania Rodriguez, Jihyun Kang, and Ayantu Teshome, who joined forces under the name of “Team Hashtag Development”, were supported by faculty advisors Dr. Albert Han and Dr. Youngchul Kim of the Department of Civil and Environmental Engineering to imagine a more sustainable and enriched way of living in the Jurong district of Singapore. Their submission, titled “Proposal: The Nest”, analyzed the big data within Singapore, using the data to determine which real estate business strategies would best enhance the quality of living and economy of the region. Their final design, "The Nest" utilized mixed-use zoning to integrate the site’s scenic waterfront with homes, medical innovation, and sustainable technology, altogether creating a place to innovate, inhabit, and immerse. < The Nest by Team Hashtag Development (Jonah Remigio, Ayantu Teshome Mossisa, Estefania Ayelen Rodriguez del Puerto, Sojung Noh, Jihyun Kang) ©2023 Urban Land Institute > Ultimately, the team was recognized for their hard work and determination, imprinting South Korea’s indelible footprint in the arena of international scholastic achievement as they were named to be one of the Finalists on April 13th. < Members of Team Hashtag Development > Team Hashtag Development gave a virtual presentation to a jury of six ULI members on April 20th along with the "Team The REAL" from the University of Economics Ho Chi Minh City of Vietnam and "Team Omusubi" from the Waseda University of Japan, the team that submitted the proposal "Jurong Urban Health Campus" which was announced to be the winner on the 31st of May, after the virtual briefing by the top three finalists.
A KAIST research team develops a high-performance ..
In recent years, there has been a rise in demand for large amounts of data to train AI models and, thus, data size has become increasingly important over time. Accordingly, solid state drives (SSDs, storage devices that use a semiconductor memory unit), which are core storage devices for data centers and cloud services, have also seen an increase in demand. However, the internal components of higher performing SSDs have become more tightly coupled, and this tightly-coupled structure limits SSD from maximized performance. On June 15, a KAIST research team led by Professor Dongjun Kim (John Kim) from the School of Electrical Engineering (EE) announced the development of the first SSD system semiconductor structure that can increase the reading/writing performance of next generation SSDs and extend their lifespan through high-performance modular SSD systems. Professor Kim’s team identified the limitations of the tightly-coupled structures in existing SSD designs and proposed a de-coupled structure that can maximize SSD performance by configuring an internal on-chip network specialized for flash memory. This technique utilizes on-chip network technology, which can freely send packet-based data within the chip and is often used to design non-memory system semiconductors like CPUs and GPUs. Through this, the team developed a ‘modular SSD’, which shows reduced interdependence between front-end and back-end designs, and allows their independent design and assembly. ＊on-chip network: a packet-based connection structure for the internal components of system semiconductors like CPUs/GPUs. On-chip networks are one of the most critical design components for high-performing system semiconductors, and their importance grows with the size of the semiconductor chip. Professor Kim’s team refers to the components nearer to the CPU as the front-end and the parts closer to the flash memory as back-end. They newly constructed an on-chip network specific to flash memory in order to allow data transmission between the back-end’s flash controller, proposing a de-coupled structure that can minimize performance drop. The SSD can accelerate some functions of the flash translation layer, a critical element to drive the SSD, in order to allow flash memory to actively overcome its limitations. Another advantage of the de-coupled, modular structure is that the flash translation layer is not limited to the characteristics of specific flash memories. Instead, their front-end and back-end designs can be carried out independently. Through this, the team could produce 21-times faster response times compared to existing systems and extend SSD lifespan by 23％ by also applying the DDS defect detection technique. < Figure 1. Schematic diagram of the structure of a high-performance modular SSD system developed by Professor Dong-Jun Kim's team > This research, conducted by first author and Ph.D. candidate Jiho Kim from the KAIST School of EE and co-author Professor Myoungsoo Jung, was presented on the 19th of June at the 50th IEEE/ACM International Symposium on Computer Architecture, the most prestigious academic conference in the field of computer architecture, held in Orlando, Florida. (Paper Title: Decoupled SSD: Rethinking SSD Architecture through Network-based Flash Controllers) < Figure 2. Conceptual diagram of hardware acceleration through high-performance modular SSD system > Professor Dongjun Kim, who led the research, said, “This research is significant in that it identified the structural limitations of existing SSDs, and showed that on-chip network technology based on system memory semiconductors like CPUs can drive the hardware to actively carry out the necessary actions. We expect this to contribute greatly to the next-generation high-performance SSD market.” He added, “The de-coupled architecture is a structure that can actively operate to extend devices’ lifespan. In other words, its significance is not limited to the level of performance and can, therefore, be used for various applications.” KAIST commented that this research is also meaningful in that the results were reaped through a collaborative study between two world-renowned researchers: Professor Myeongsoo Jung, recognized in the field of computer system storage devices, and Professor Dongjun Kim, a leading researcher in computer architecture and interconnection networks. This research was funded by the National Research Foundation of Korea, Samsung Electronics, the IC Design Education Center, and Next Generation Semiconductor Technology and Development granted by the Institute of Information & Communications Technology, Planning & Evaluation.
A KAIST Research Team Identifies a Cancer Reversio..
Despite decades of intensive cancer research by numerous biomedical scientists, cancer still holds its place as the number one cause of death in Korea. The fundamental reason behind the limitations of current cancer treatment methods is the fact that they all aim to completely destroy cancer cells, which eventually allows the cancer cells to acquire immunity. In other words, recurrences and side-effects caused by the destruction of healthy cells are inevitable. To this end, some have suggested anticancer treatment methods based on cancer reversion, which can revert cancer cells back to normal or near-normal cells under certain conditions. However, the practical development of this idea has not yet been attempted. On June 8, a KAIST research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering reported to have successfully identified the fundamental principle of a process that can revert cancer cells back to normal cells without killing the cells. Professor Cho’s team focused on the fact that unlike normal cells, which react according to external stimuli, cancer cells tend to ignore such stimuli and only undergo uncontrolled cell division. Through computer simulation analysis, the team discovered that the input-output (I/O) relationships that were distorted by genetic mutations could be reverted back to normal I/O relationships under certain conditions. The team then demonstrated through molecular cell experiments that such I/O relationship recovery also occurred in real cancer cells. The results of this study, written by Dr. Jae Il Joo and Dr. Hwa-Jeong Park, were published in Wiley’s Advanced Science online on June 2 under the title, "Normalizing input-output relationships of cancer networks for reversion therapy.“ < Image 1. Input-output (I/O) relationships in gene regulatory networks > Professor Kwang-Hyun Cho's research team classified genes into four types by simulation-analyzing the effect of gene mutations on the I/O relationship of gene regulatory networks. (Figure A-J) In addition, by analyzing 18 genes of the cancer-related gene regulatory network, it was confirmed that when mutations occur in more than half of the genes constituting each network, reversibility is possible through appropriate control. (Figure K) Professor Cho’s team uncovered that the reason the distorted I/O relationships of cancer cells could be reverted back to normal ones was the robustness and redundancy of intracellular gene control networks that developed over the course of evolution. In addition, they found that some genes were more promising as targets for cancer reversion than others, and showed through molecular cell experiments that controlling such genes could revert the distorted I/O relationships of cancer cells back to normal ones. < Image 2. Simulation results of restoration of bladder cancer gene regulation network and I/O relationship of bladder cancer cells. > The research team classified the effects of gene mutations on the I/O relationship in the bladder cancer gene regulation network by simulation analysis and classified them into 4 types. (Figure A) Through this, it was found that the distorted input-output relationship between bladder cancer cell lines KU-1919 and HCT-1197 could be restored to normal. (Figure B) < Image 3. Analysis of survival of bladder cancer patients according to reversible gene mutation and I/O recovery experiment of bladder cancer cells. > As predicted through network simulation analysis, Professor Kwang-Hyun Cho's research team confirmed through molecular cell experiments that the response to TGF-b was normally restored when AKT and MAP3K1 were inhibited in the bladder cancer cell line KU-1919. (Figure A-G) In addition, it was confirmed that there is a difference in the survival rate of bladder cancer patients depending on the presence or absence of a reversible gene mutation. (Figure H) The results of this research show that the reversion of real cancer cells does not happen by chance, and that it is possible to systematically explore targets that can induce this phenomenon, thereby creating the potential for the development of innovative anticancer drugs that can control such target genes. < Image 4. Cancer cell reversibility principle > The research team analyzed the reversibility, redundancy, and robustness of various networks and found that there was a positive correlation between them. From this, it was found that reversibility was additionally inherent in the process of evolution in which the gene regulatory network acquired redundancy and consistency. Professor Cho said, “By uncovering the fundamental principles of a new cancer reversion treatment strategy that may overcome the unresolved limitations of existing chemotherapy, we have increased the possibility of developing new and innovative drugs that can improve both the prognosis and quality of life of cancer patients.” < Image 5. Conceptual diagram of research results > The research team identified the fundamental control principle of cancer cell reversibility through systems biology research. When the I/O relationship of the intracellular gene regulatory network is distorted by mutation, the distorted I/O relationship can be restored to a normal state by identifying and adjusting the reversible gene target based on the redundancy of the molecular circuit inherent in the complex network. After Professor Cho’s team first suggested the concept of reversion treatment, they published their results for reverting colorectal cancer in January 2020, and in January 2022 they successfully re-programmed malignant breast cancer cells back into hormone-treatable ones. In January 2023, the team successfully removed the metastasis ability from lung cancer cells and reverted them back to a state that allowed improved drug reactivity. However, these results were case studies of specific types of cancer and did not reveal what common principle allowed cancer reversion across all cancer types, making this the first revelation of the general principle of cancer reversion and its evolutionary origins. This research was funded by the Ministry of Science and ICT of the Republic of Korea and the National Research Foundation of Korea.
Synthetic sRNAs to knockdown genes in medical and ..
Bacteria are intimately involved in our daily lives. These microorganisms have been used in human history for food such as cheese, yogurt, and wine, In more recent years, through metabolic engineering, microorganisms been used extensively as microbial cell factories to manufacture plastics, feed for livestock, dietary supplements, and drugs. However, in addition to these bacteria that are beneficial to human lives, pathogens such as Pneumonia, Salmonella, and Staphylococcus that cause various infectious diseases are also ubiquitously present. It is important to be able to metabolically control these beneficial industrial bacteria for high value-added chemicals production and to manipulate harmful pathogens to suppress its pathogenic traits. KAIST (President Kwang Hyung Lee) announced on the 10th that a research team led by Distinguished Professor Sang Yup Lee of the Department of Biochemical Engineering has developed a new sRNA tool that can effectively inhibit target genes in various bacteria, including both Gram-negative and Gram-positive bacteria. The research results were published online on April 24 in Nature Communications. ※ Thesis title: Targeted and high-throughput gene knockdown in diverse bacteria using synthetic sRNAs ※ Author information : Jae Sung Cho (co-1st), Dongsoo Yang (co-1st), Cindy Pricilia Surya Prabowo (co-author), Mohammad Rifqi Ghiffary (co-author), Taehee Han (co-author), Kyeong Rok Choi (co-author), Cheon Woo Moon (co-author), Hengrui Zhou (co-author), Jae Yong Ryu (co-author), Hyun Uk Kim (co-author) and Sang Yup Lee (corresponding author). sRNA is an effective tool for synthesizing and regulating target genes in E. coli, but it has been difficult to apply to industrially useful Gram-positive bacteria such as Bacillus subtilis and Corynebacterium in addition to Gram-negative bacteria such as E. coli. To address this issue, a research team led by Distinguished Professor Lee Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a new sRNA platform that can effectively suppress target genes in various bacteria, including both Gram-negative and positive bacteria. The research team surveyed thousands of microbial-derived sRNA systems in the microbial database, and eventually designated the sRNA system derived from 'Bacillus subtilis' that showed the highest gene knockdown efficiency, and designated it as “Broad-Host-Range sRNA”, or BHR-sRNA. A similar well-known system is the CRISPR interference (CRISPRi) system, which is a modified CRISPR system that knocks down gene expression by suppressing the gene transcription process. However, the Cas9 protein in the CRISPRi system has a very high molecular weight, and there have been reports growth inhibition in bacteria. The BHR-sRNA system developed in this study did not affect bacterial growth while showing similar gene knockdown efficiencies to CRISPRi. < Figure 1. a) Schematic illustration demonstrating the mechanism of syntetic sRNA b) Phylogenetic tree of the 16 Gram-negative and Gram-positive bacterial species tested for gene knockdown by the BHR-sRNA system. > To validate the versatility of the BHR-sRNA system, 16 different gram-negative and gram-positive bacteria were selected and tested, where the BHR-sRNA system worked successfully in 15 of them. In addition, it was demonstrated that the gene knockdown capability was more effective than that of the existing E. coli-based sRNA system in 10 bacteria. The BHR-sRNA system proved to be a universal tool capable of effectively inhibiting gene expression in various bacteria. In order to address the problem of antibiotic-resistant pathogens that have recently become more serious, the BHR-sRNA was demonstrated to suppress the pathogenicity by suppressing the gene producing the virulence factor. By using BHR-sRNA, biofilm formation, one of the factors resulting in antibiotic resistance, was inhibited by 73％ in Staphylococcus epidermidis a pathogen that can cause hospital-acquired infections. Antibiotic resistance was also weakened by 58％ in the pneumonia causing bacteria Klebsiella pneumoniae. In addition, BHR-sRNA was applied to industrial bacteria to develop microbial cell factories to produce high value-added chemicals with better production performance. Notably, superior industrial strains were constructed with the aid of BHR-sRNA to produce the following chemicals: valerolactam, a raw material for polyamide polymers, methyl-anthranilate, a grape-flavor food additive, and indigoidine, a blue-toned natural dye. The BHR-sRNA developed through this study will help expedite the commercialization of bioprocesses to produce high value-added compounds and materials such as artificial meat, jet fuel, health supplements, pharmaceuticals, and plastics. It is also anticipated that to help eradicating antibiotic-resistant pathogens in preparation for another upcoming pandemic. “In the past, we could only develop new tools for gene knockdown for each bacterium, but now we have developed a tool that works for a variety of bacteria” said Distinguished Professor Sang Yup Lee. This work was supported by 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 from NRF supported by the Korean MSIT.
KAIST debuts “DreamWaQer” - a quadrupedal robot th..
- The team led by Professor Hyun Myung of the School of Electrical Engineering developed “DreamWaQ”, a deep reinforcement learning-based walking robot control technology that can walk in an atypical environment without visual and/or tactile information - Utilization of “DreamWaQ” technology can enable mass production of various types of “DreamWaQers” - Expected to be used in exploration of atypical environment involving unique circumstances such as disasters by fire. A team of Korean engineering researchers has developed a quadrupedal robot technology that can climb up and down the steps and moves without falling over in uneven environments such as tree roots without the help of visual or tactile sensors even in disastrous situations in which visual confirmation is impeded due to darkness or thick smoke from the flames. KAIST (President Kwang Hyung Lee) announced on the 29th of March that Professor Hyun Myung's research team at the Urban Robotics Lab in the School of Electrical Engineering developed a walking robot control technology that enables robust 'blind locomotion' in various atypical environments. < (From left) Prof. Hyun Myung, Doctoral Candidates I Made Aswin Nahrendra, Byeongho Yu, and Minho Oh. In the foreground is the DreamWaQer, a quadrupedal robot equipped with DreamWaQ technology. > The KAIST research team developed "DreamWaQ" technology, which was named so as it enables walking robots to move about even in the dark, just as a person can walk without visual help fresh out of bed and going to the bathroom in the dark. With this technology installed atop any legged robots, it will be possible to create various types of "DreamWaQers". Existing walking robot controllers are based on kinematics and/or dynamics models. This is expressed as a model-based control method. In particular, on atypical environments like the open, uneven fields, it is necessary to obtain the feature information of the terrain more quickly in order to maintain stability as it walks. However, it has been shown to depend heavily on the cognitive ability to survey the surrounding environment. In contrast, the controller developed by Professor Hyun Myung's research team based on deep reinforcement learning (RL) methods can quickly calculate appropriate control commands for each motor of the walking robot through data of various environments obtained from the simulator. Whereas the existing controllers that learned from simulations required a separate re-orchestration to make it work with an actual robot, this controller developed by the research team is expected to be easily applied to various walking robots because it does not require an additional tuning process. DreamWaQ, the controller developed by the research team, is largely composed of a context estimation network that estimates the ground and robot information and a policy network that computes control commands. The context-aided estimator network estimates the ground information implicitly and the robot’s status explicitly through inertial information and joint information. This information is fed into the policy network to be used to generate optimal control commands. Both networks are learned together in the simulation. While the context-aided estimator network is learned through supervised learning, the policy network is learned through an actor-critic architecture, a deep RL methodology. The actor network can only implicitly infer surrounding terrain information. In the simulation, the surrounding terrain information is known, and the critic, or the value network, that has the exact terrain information evaluates the policy of the actor network. This whole learning process takes only about an hour in a GPU-enabled PC, and the actual robot is equipped with only the network of learned actors. Without looking at the surrounding terrain, it goes through the process of imagining which environment is similar to one of the various environments learned in the simulation using only the inertial sensor (IMU) inside the robot and the measurement of joint angles. If it suddenly encounters an offset, such as a staircase, it will not know until its foot touches the step, but it will quickly draw up terrain information the moment its foot touches the surface. Then the control command suitable for the estimated terrain information is transmitted to each motor, enabling rapidly adapted walking. The DreamWaQer robot walked not only in the laboratory environment, but also in on outdoor environment around the campus with many curbs and speed bumps, and over a field with many tree roots and gravel, demonstrating its abilities by overcoming a staircase with a difference of a height that is two-thirds of its body. In addition, regardless of the environment, the research team confirmed that it was capable of stable walking ranging from a slow speed of 0.3 m/s to a rather fast speed of 1.0 m/s. The results of this study were produced by a student in doctorate course, I Made Aswin Nahrendra, as the first author, and his colleague Byeongho Yu as a co-author. It has been accepted to be presented at the upcoming IEEE International Conference on Robotics and Automation (ICRA) scheduled to be held in London at the end of May. (Paper title: DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning) The videos of the walking robot DreamWaQer equipped with the developed DreamWaQ can be found at the address below. Main Introduction: https://youtu.be/JC1_bnTxPiQ Experiment Sketches: https://youtu.be/mhUUZVbeDA0 Meanwhile, this research was carried out with the support from the Robot Industry Core Technology Development Program of the Ministry of Trade, Industry and Energy (MOTIE). (Task title: Development of Mobile Intelligence SW for Autonomous Navigation of Legged Robots in Dynamic and Atypical Environments for Real Application) < Figure 1. Overview of DreamWaQ, a controller developed by this research team. This network consists of an estimator network that learns implicit and explicit estimates together, a policy network that acts as a controller, and a value network that provides guides to the policies during training. When implemented in a real robot, only the estimator and policy network are used. Both networks run in less than 1 ms on the robot's on-board computer. > < Figure 2. Since the estimator can implicitly estimate the ground information as the foot touches the surface, it is possible to adapt quickly to rapidly changing ground conditions. > < Figure 3. Results showing that even a small walking robot was able to overcome steps with height differences of about 20cm. >