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KAIST debuts “DreamWaQer” - a quadrupedal robot that can walk in the dark
- 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 an 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. >
Synthetic sRNAs to knockdown genes in medical and industrial bacteria
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 gearing up to train physician-scientists and BT Professionals joining hands with Boston-based organizations
KAIST (President Kwang Hyung Lee) announced on the 29th that it has signed MOUs with Massachusetts General Hospital, a founding member of the Mass General Brigham health care system and a world-class research-oriented hospital, and Moderna, a biotechnology company that developed a COVID-19 vaccine at the Langham Hotel in Boston, MA, USA on the morning of April 28th (local time). The signing ceremony was attended by officials from each institution joined by others headed by Minister LEE Young of the Korean Ministry of SMEs and Startups (MSS), and Commissioner LEE Insil of the Korean Intellectual Property Office. < Photo 1. Photo from the Signing of MOU between KAIST-Harvard University Massachusetts General Hospital and KAIST-Moderna > Mass General is the first and largest teaching hospital of Harvard Medical School in Boston, USA, and it is one of the most innovative hospitals in the world being the alma mater of more than 13 Nobel Prize winners and the home of the Mass General Research Institute, the world’s largest hospital-based research program that utilizes an annual research budget of more than $1.3 billion. KAIST signed a general agreement to explore research and academic exchange with Mass General in September of last year and this MOU is a part of its follow-ups. Mass General works with Harvard and the Massachusetts Institute of Technology (MIT), as well as local hospitals, to support students learn the theories of medicine and engineering, and gain rich clinical research experience. Through this MOU, KAIST will explore cooperation with an innovative ecosystem created through the convergence of medicine and engineering. In particular, KAIST’s goal is to develop a Korean-style training program and implement a differentiated educational program when establishing the science and technology-oriented medical school in the future by further strengthening the science and engineering part of the training including a curriculum on artificial intelligence (AI) and the likes there of. Also, in order to foster innovative physician-scientists, KAIST plans to pursue cooperation to develop programs for exchange of academic and human resources including programs for student and research exchanges and a program for students of the science and technology-oriented medical school at KAIST to have a chance to take part in practical training at Mass General. David F.M. Brown, MD, Mass General President, said, “The collaboration with KAIST has a wide range of potentials, including advice on training of physician-scientists, academic and human resource exchanges, and vitalization of joint research by faculty from both institutions. Through this agreement, we will be able to actively contribute to global cooperation and achieve mutual goals.” Meanwhile, an MOU between KAIST and Moderna was also held on the same day. Its main focus is to foster medical experts in cooperation with KAIST Graduate School of Medical Science and Engineering (GSMSE), and plans to cooperate in various ways in the future, including collaborating for development of vaccine and new drugs, virus research, joint mRNA research, and facilitation of technology commercialization. In over 10 years since its inception, Moderna has transformed from a research-stage company advancing programs in the field of messenger RNA (mRNA) to an enterprise with a diverse clinical portfolio of vaccines and therapeutics across seven modalities. The Company has 48 programs in development across 45 development candidates, of which 38 are currently in active clinical trials. “We are grateful to have laid a foundation for collaboration to foster industry experts with the Korea Advanced Institute of Science and Technology, a leader of science and technology innovation in Korea,” said Arpa Garay, Chief Commercial Officer, Moderna. “Based on our leadership and expertise in developing innovative mRNA vaccines and therapeutics, we hope to contribute to educating and collaborating with professionals in the bio-health field of Korea.“ President Kwang Hyung Lee of KAIST, said, “We deem this occasion to be of grave significance to be able to work closely with Massachusetts General Hospital, one of the world's best research-oriented hospitals, and Moderna, one of the most influential biomedical companies.” President Lee continued, "On the basis of the collaboration with the two institutions, we will be able to bring up qualified physician-scientists and global leaders of the biomedical business who will solve problems of human health and their progress will in turn, accelerate the national R&D efforts in general and diversify the industry."
Seanie Lee of KAIST Kim Jaechul Graduate School of AI, named the 2023 Apple Scholars in AI Machine Learning
Seanie Lee, a Ph.D. candidate at the Kim Jaechul Graduate School of AI, has been selected as one of the Apple Scholars in AI/ML PhD fellowship program recipients for 2023. Lee, advised by Sung Ju Hwang and Juho Lee, is a rising star in AI. < Seanie Lee of KAIST Kim Jaechul Graduate School of AI > The Apple Scholars in AI/ML PhD fellowship program, launched in 2020, aims to discover and support young researchers with a promising future in computer science. Each year, a handful of graduate students in related fields worldwide are selected for the program. For the following two years, the selected students are provided with financial support for research, international conference attendance, internship opportunities, and mentorship by an Apple engineer. This year, 22 PhD students were selected from leading universities worldwide, including Johns Hopkins University, MIT, Stanford University, Imperial College London, Edinburgh University, Tsinghua University, HKUST, and Technion. Seanie Lee is the first Korean student to be selected for the program. Lee’s research focuses on transfer learning, a subfield of AI that reuses pre-trained AI models on large datasets such as images or text corpora to train them for new purposes. (*text corpus: a collection of text resources in computer-readable forms) His work aims to improve the performance of transfer learning by developing new data augmentation methods that allow for more effective training using few training data samples and new regularization techniques that prevent the overfitting of large AI models to training data. He has published 11 papers, all of which were accepted to top-tier conferences such as the Annual Meeting of the Association for Computational Linguistics (ACL), International Conference on Learning Representations (ICLR), and Annual Conference on Neural Information Processing Systems (NeurIPS). “Being selected as one of the Apple Scholars in AI/ML PhD fellowship program is a great motivation for me,” said Lee. “So far, AI research has been largely focused on computer vision and natural language processing, but I want to push the boundaries now and use modern tools of AI to solve problems in natural science, like physics.”
KAIST Team Develops Highly-Sensitive Wearable Piezoelectric Blood Pressure Sensor for Continuous Health Monitoring
- A collaborative research team led by KAIST Professor Keon Jae Lee verifies the accuracy of the highly-sensitive sensor through clinical trials - Commercialization of the watch and patch-type sensor is in progress A KAIST research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering and the College of Medicine of the Catholic University of Korea has developed a highly sensitive, wearable piezoelectric blood pressure sensor. Blood pressure is a critical indicator for assessing general health and predicting stroke or heart failure. In particular, cardiovascular disease is the leading cause of global death, therefore, periodic measurement of blood pressure is crucial for personal healthcare. Recently, there has been a growing interest in healthcare devices for continuous blood pressure monitoring. Although smart watches using LED-based photoplethysmography (PPG) technology have been on market, these devices have been limited by the accuracy constraints of optical sensors, making it hard to meet the international standards of automatic sphygmomanometers. Professor Lee’s team has developed the wearable piezoelectric blood pressure sensor by transferring a highly sensitive, inorganic piezoelectric membrane from bulk sapphire substrates to flexible substrates. Ultrathin piezoelectric sensors with a thickness of several micrometers (one hundredth of the human hair) exhibit conformal contact with the skin to successfully collect accurate blood pressure from the subtle pulsation of the blood vessels. Clinical trial at the St. Mary’s Hospital of the Catholic University validated the accuracy of blood pressure sensor at par with international standard with errors within ±5 mmHg and a standard deviation under 8 mmHg for both systolic and diastolic blood pressure. In addition, the research team successfully embedded the sensor on a watch-type product to enable continuous monitoring of blood pressure. Prof. Keon Jae Lee said, “Major target of our healthcare devices is hypertensive patients for their daily medical check-up. We plan to develop a comfortable patch-type sensor to monitor blood pressure during sleep and have a start-up company commercialize these watch and patch-type products soon.” This result titled “Clinical validation of wearable piezoelectric blood pressure sensor for health monitoring” was published in the online issue of Advanced Materials on March 24th, 2023. (DOI: 10.1002/adma.202301627) Figure 1. Schematic illustration of the overall concept for a wearable piezoelectric blood pressure sensor (WPBPS). Figure 2. Wearable piezoelectric blood pressure sensor (WPBPS) mounted on a watch (a) Schematic design of the WPBPS-embedded wristwatch. (b) Block diagram of the wireless communication circuit, which filters, amplifies, and transmits wireless data to portable devices. (c) Pulse waveforms transmitted from the wristwatch to the portable device by the wireless communication circuit. The inset shows a photograph of monitoring a user’s beat-to-beat pulses and their corresponding BP values in real time using the developed WPBPS-mounted wristwatch.
KAIST researchers find the key to overcome the limits in X-ray microscopy
X-ray microscopes have the advantage of penetrating most substances, so internal organs and skeletons can be observed non-invasively through chest X-rays or CT scans. Recently, studies to increase the resolution of X-ray imaging technology are being actively conducted in order to precisely observe the internal structure of semiconductors and batteries at the nanoscale. KAIST (President Kwang Hyung Lee) announced on April 12th that a joint research team led by Professor YongKeun Park of the Department of Physics and Dr. Jun Lim of the Pohang Accelerator Laboratory has succeeded in developing a core technology that can overcome the resolution limitations of existing X-ray microscopes. d This study, in which Dr. KyeoReh Lee participated as the first author, was published on 6th of April in “Light: Science and Application”, a world-renowned academic journal in optics and photonics. (Paper title: Direct high-resolution X-ray imaging exploiting pseudorandomness). X-ray nanomicroscopes do not have refractive lenses. In an X-ray microscope, a circular grating called a concentric zone plate is used instead of a lens. The resolution of an image obtained using the zone plate is determined by the quality of the nanostructure that comprises the plate. There are several difficulties in fabricating and maintaining these nanostructures, which set the limit to the level of resolution for X-ray microscopy. The research team developed a new X-ray nanomicroscopy technology to overcome this problem. The X-ray lens proposed by the research team is in the form of numerous holes punched in a thin tungsten film, and generates random diffraction patterns by diffracting incident X-rays. The research team mathematically identified that, paradoxically, the high-resolution information of the sample was fully contained in these random diffraction patterns, and actually succeeded in extracting the information and imaging the internal states of the samples. The imaging method using the mathematical properties of random diffraction was proposed and implemented in the visible light band for the first time by Dr. KyeoReh Lee and Professor YongKeun Park in 2016*. This study uses the results of previous studies to solve the difficult, lingering problem in the field of the X-ray imaging. ※ "Exploiting the speckle-correlation scattering matrix for a compact reference-free holographic image sensor." Nature communications 7.1 (2016): 13359. The resolution of the image of the constructed sample has no direct correlation with the size of the pattern etched on the random lens used. Based on this idea, the research team succeeded in acquiring images with 14 nm resolution (approximately 1/7 the size of the coronavirus) by using random lenses made in a circular pattern with a diameter of 300 nm. The imaging technology developed by this research team is a key fundamental technology that can enhance the resolution of X-ray nanomicroscopy, which has been blocked by limitations of the production of existing zone plates. The first author and one of the co-corresponding author, Dr. KyeoReh Lee of KAIST Department of Physics, said, “In this study, the resolution was limited to 14 nm, but if the next-generation X-ray light source and high-performance X-ray detector are used, the resolution would exceed that of the conventional X-ray nano-imaging and approach the resolution of an electron microscope.” and added, “Unlike an electron microscope, X-rays can observe the internal structure without damaging the sample, so it will be able to present a new standard for non-invasive nanostructure observation processes such as quality inspections for semiconductors.”. The co-corresponding author, Dr. Jun Lim of the Pohang Accelerator Laboratory, said, “In the same context, the developed image technology is expected to greatly increase the performance in the 4th generation multipurpose radiation accelerator which is set to be established in Ochang of the Northern Chungcheong Province.” This research was conducted with the support through the Research Leader Program and the Sejong Science Fellowship of the National Research Foundation of Korea. Fig. 1. Designed diffuser as X-ray imaging lens. a, Schematic of full-field transmission X-ray microscopy. The attenuation (amplitude) map of a sample is measured. The image resolution (dx) is limited by the outermost zone width of the zone plate (D). b, Schematic of the proposed method. A designed diffuser is used instead of a zone plate. The image resolution is finer than the hole size of the diffuser (dx << D). Fig. 2. The left panel is a surface electron microscopy (SEM) image of the X-ray diffuser used in the experiment. The middle panel shows the design of the X-ray diffuser, and there is an inset in the middle of the panel that shows a corresponding part of the SEM image. The right panel shows an experimental random X-ray diffraction pattern, also known as a speckle pattern, obtained from the X-ray diffuser. Fig. 3. Images taken from the proposed randomness-based X-ray imaging (bottom) and the corresponding surface electron microscope (SEM) images (top).
KAIST research team develops a cheap and safe redox flow battery
Redox flow batteries, one of the potential replacements for the widely used lithium-ion secondary batteries, can be utilized as new and renewable energy as well as for energy storage systems (ESS) thanks to their low cost, low flammability, and long lifetime of over 20 years. Since the price of vanadium, the most widely used active material for redox flow batteries, has been rising in recent years, scientists have been actively searching for redox materials to replace it. On March 23, a joint research team led by Professors Hye Ryung Byon and Mu-Hyun Baik from the KAIST Department of Chemistry, and Professor Jongcheol Seo from the POSTECH Department of Chemistry announced that they had developed a highly soluble and stable organic redox-active molecule for use in aqueous redox flow batteries. The research team focused on developing aqueous redox flow batteries by redesigning an organic molecule. It is possible to control the solubility and electrochemical redox potential of organic molecules by engineering their design, which makes them a promising active material candidate with possibly higher energy storage capabilities than vanadium. Most organic redox-active molecules have low solubilities or have slow chemical stability during redox reactions. Low solubility means low energy storage capacity and low chemical stability leads to reduced cycle performance. For this research, the team chose naphthalene diimide (NDI) as their active molecule. Until now, there was little research done on NDI despite its high chemical stability, as it shows low solubility in aqueous electrolyte solutions. Although NDI molecules are almost insoluble in water, the research team tethered four ammonium functionalities and achieved a solubility as high as 1.5M* in water. In addition, they confirmed that when a 1M solution of NDI was used in neutral redox flow batteries for 500 cycles, 98% of its capacity was maintained. This means 0.004% capacity decay per cycle, and only 2% of its capacity would be lost if the battery were to be operated for 45 days. Furthermore, the developed NDI molecule can save two electrons per molecule, and the team proved that 2M of electrons could be stored in every 1M of NDI solution used. For reference, vanadium used in vanadium redox flow batteries, which require a highly concentrated sulfuric acid solution, has a solubility of about 1.6M and can only hold one electron per molecule, meaning it can store a total of 1.6M of electrons. Therefore, the newly developed NDI active molecule shows a higher storage capacity compared to existing vanadium devices. *1M (mol/L): 6.022 x 1023 active molecules are present in 1L of solution This paper, written by co-first authors Research Professor Vikram Singh, and Ph.D. candidates Seongyeon Kwon and Yunseop Choi, was published in the online version of Advanced Materials on February 7 under the title, Controlling π-π interactions of highly soluble naphthalene diimide derivatives for neutral pH aqueous redox flow batteries. Ph.D. Candidate Yelim Yi and Professor Mi Hee Lee’s team from the KAIST Department of Chemistry also contributed to the study by conducting electron paramagnetic resonance analyses. Professor Hye Ryung Byon said, “We have demonstrated the principles of molecular design by modifying an existing organic active molecule with low solubility and utilizing it as an active molecule for redox flow batteries. We have also shown that during a redox reaction, we can use molecular interactions to suppress the chemical reactivity of radically formed molecules.” She added, “Should this be used later for aqueous redox flow batteries, along with its high energy density and high solubility, it would also have the advantage of being available for use in neutral pH electrolytes. Vanadium redox flow batteries currently use acidic solutions, which cause corrosion, and we expect our molecule to solve this issue. Since existing lithium ion-based ESS are flammable, we must develop safer and cheaper next-generation ESS, and our research has shown great promise in addressing this.” This research was funded by Samsung Research Funding & Incubation Center, the Institute for Basic Science, and the National Research Foundation. Figure 1. (a) Structures of various NDI molecules. (b) Solubility of NDI molecules in water (black bars) and aqueous electrolytes including KCl electrolyte (blue bars). (c–d) Structural changes of the molecules as the developed NDI molecule stores two electrons. (c) Illustration of cluster combination and separation of NDI molecules developed during redox reaction and (d) Snapshot of the MD simulation. NDI molecules prepared from the left, formation of bimolecular sieve and tetramolecular sieve clusters after the first reductive reaction, and a single molecule with a three-dimensional structure after the second reduction. Figure 2. Performance results of an aqueous redox flow battery using 1M of the developed NDI molecule as the cathode electrolyte and 3.1M of ammonium iodine as the anode electrolyte. Using 1.5 M KCl solution. (a) A schematic diagram of a redox flow battery. (b) Voltage-capacity graph according to cycle in a redox flow battery. (c) Graphs of capacity and coulombs, voltage, and energy efficiency maintained at 500 cycles.
A biohybrid system to extract 20 times more bioplastic from CO2 developed by KAIST researchers
As the issues surrounding global climate change intensify, more attention and determined efforts are required to re-grasp the issue as a state of “crisis” and respond to it properly. Among the various methods of recycling CO2, the electrochemical CO2 conversion technology is a technology that can convert CO2 into useful chemical substances using electrical energy. Since it is easy to operate facilities and can use the electricity from renewable sources like the solar cells or the wind power, it has received a lot of attention as an eco-friendly technology can contribute to reducing greenhouse gases and achieve carbon neutrality. KAIST (President Kwang Hyung Lee) announced on the 30th that the joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering succeeded in developing a technology that produces bioplastics from CO2 with high efficiency by developing a hybrid system that interlinked the electrochemical CO2 conversion and microbial bio conversion methods together. The results of the research, which showed the world's highest productivity by more than 20 times compared to similar systems, were published online on March 27th in the "Proceedings of the National Academy of Sciences (PNAS)". ※ Paper title: Biohybrid CO2 electrolysis for the direct synthesis of polyesters from CO2 ※ Author information: Jinkyu Lim (currently at Stanford Linear Accelerator Center, co-first author), So Young Choi (KAIST, co-first author), Jae Won Lee (KAIST, co-first author), Hyunjoo Lee (KAIST, corresponding author), Sang Yup Lee (KAIST, corresponding author) For the efficient conversion of CO2, high-efficiency electrode catalysts and systems are actively being developed. As conversion products, only compounds containing one or up to three carbon atoms are produced on a limited basis. Compounds of one carbon, such as CO, formic acid, and ethylene, are produced with relatively high efficiency. Liquid compounds of several carbons, such as ethanol, acetic acid, and propanol, can also be produced by these systems, but due to the nature of the chemical reaction that requires more electrons, there are limitations involving the conversion efficiency and the product selection. Accordingly, a joint research team led by Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a technology to produce bioplastics from CO2 by linking electrochemical conversion technology with bioconversion method that uses microorganisms. This electrochemical-bio hybrid system is in the form of having an electrolyzer, in which electrochemical conversion reactions occur, connected to a fermenter, in which microorganisms are cultured. When CO2 is converted to formic acid in the electrolyzer, and it is fed into the fermenter in which the microbes like the Cupriavidus necator, in this case, consumes the carbon source to produce polyhydroxyalkanoate (PHA), a microbial-derived bioplastic. According to the research results of the existing hybrid concepts, there was a disadvantage of having low productivity or stopping at a non-continuous process due to problems of low efficiency of the electrolysis and irregular results arising from the culturing conditions of the microbes. In order to overcome these problems, the joint research team made formic acid with a gas diffusion electrode using gaseous CO2. In addition, the team developed a 'physiologically compatible catholyte' that can be used as a culture medium for microorganisms as well as an electrolyte that allows the electrolysis to occur sufficiently without inhibiting the growth of microorganisms, without having to have a additional separation and purification process, which allowed the acide to be supplied directly to microorganisms. Through this, the electrolyte solution containing formic acid made from CO2 enters the fermentation tank, is used for microbial culture, and enters the electrolyzer to be circulated, maximizing the utilization of the electrolyte solution and remaining formic acid. In addition, a filter was installed to ensure that only the electrolyte solution with any and all microorganisms that can affect the electrosis filtered out is supplied back to the electrolyzer, and that the microorganisms exist only in the fermenter, designing the two system to work well together with utmost efficiency. Through the developed hybrid system, the produced bioplastic, poly-3-hydroxybutyrate (PHB), of up to 83% of the cell dry weight was produced from CO2, which produced 1.38g of PHB from a 4 cm2 electrode, which is the world's first gram(g) level production and is more than 20 times more productive than previous research. In addition, the hybrid system is expected to be applied to various industrial processes in the future as it shows promises of the continuous culture system. The corresponding authors, Professor Hyunjoo Lee and Distinguished Professor Sang Yup Lee noted that “The results of this research are technologies that can be applied to the production of various chemical substances as well as bioplastics, and are expected to be used as key parts needed in achieving carbon neutrality in the future.” This research was received and performed with the supports from the CO2 Reduction Catalyst and Energy Device Technology Development Project, the Heterogeneous Atomic Catalyst Control Project, and the Next-generation Biorefinery Source Technology Development Project to lead the Biochemical Industry of the Oil-replacement Eco-friendly Chemical Technology Development Program by the Ministry of Science and ICT. Figure 1. Schematic diagram and photo of the biohybrid CO2 electrolysis system. (A) A conceptual scheme and (B) a photograph of the biohybrid CO2 electrolysis system. (C) A detailed scheme of reaction inside the system. Gaseous CO2 was converted to formate in the electrolyzer, and the formate was converted to PHB by the cells in the fermenter. The catholyte was developed so that it is compatible with both CO2 electrolysis and fermentation and was continuously circulated.
Using light to throw and catch atoms to open up a new chapter for quantum computing
The technology to move and arrange atoms, the most basic component of a quantum computer, is very important to Rydberg quantum computing research. However, to place the atoms at the desired location, the atoms must be captured and transported one by one using a highly focused laser beam, commonly referred to as an optical tweezer. and, the quantum information of the atoms is likely to change midway. KAIST (President Kwang Hyung Lee) announced on the 27th that a research team led by Professor Jaewook Ahn of the Department of Physics developed a technology to throw and receive rubidium atoms one by one using a laser beam. The research team developed a method to throw and receive atoms which would minimize the time the optical tweezers are in contact with the atoms in which the quantum information the atoms carry may change. The research team used the characteristic that the rubidium atoms, which are kept at a very low temperature of 40μK below absolute zero, move very sensitively to the electromagnetic force applied by light along the focal point of the light tweezers. The research team accelerated the laser of an optical tweezer to give an optical kick to an atom to send it to a target, then caught the flying atom with another optical tweezer to stop it. The atom flew at a speed of 65 cm/s, and traveled up to 4.2 μm. Compared to the existing technique of guiding the atoms with the optical tweezers, the technique of throwing and receiving atoms eliminates the need to calculate the transporting path for the tweezers, and makes it easier to fix the defects in the atomic arrangement. As a result, it is effective in generating and maintaining a large number of atomic arrangements, and when the technology is used to throw and receive flying atom qubits, it will be used in studying new and more powerful quantum computing methods that presupposes the structural changes in quantum arrangements. "This technology will be used to develop larger and more powerful Rydberg quantum computers," says Professor Jaewook Ahn. “In a Rydberg quantum computer,” he continues, “atoms are arranged to store quantum information and interact with neighboring atoms through electromagnetic forces to perform quantum computing. The method of throwing an atom away for quick reconstruction the quantum array can be an effective way to fix an error in a quantum computer that requires a removal or replacement of an atom.” The research, which was conducted by doctoral students Hansub Hwang and Andrew Byun of the Department of Physics at KAIST and Sylvain de Léséleuc, a researcher at the National Institute of Natural Sciences in Japan, was published in the international journal, Optica, 0n March 9th. (Paper title: Optical tweezers throw and catch single atoms). This research was carried out with the support of the Samsung Science & Technology Foundation. <Figure 1> A schematic diagram of the atom catching and throwing technique. The optical tweezer on the left kicks the atom to throw it into a trajectory to have the tweezer on the right catch it to stop it.
KAIST researchers devises a technology to utilize ultrahigh-resolution micro-LED with 40% reduced self-generated heat
In the digitized modern life, various forms of future displays, such as wearable and rollable displays are required. More and more people are wanting to connect to the virtual world whenever and wherever with the use of their smartglasses or smartwatches. Even further, we’ve been hearing about medical diagnosis kit on a shirt and a theatre-hat. However, it is not quite here in our hands yet due to technical limitations of being unable to fit as many pixels as a limited surface area of a glasses while keeping the power consumption at the a level that a hand held battery can supply, all the while the resolution of 4K+ is needed in order to perfectly immerse the users into the augmented or virtual reality through a wireless smartglasses or whatever the device. KAIST (President Kwang Hyung Lee) announced on the 22nd that Professor Sang Hyeon Kim's research team of the Department of Electrical and Electronic Engineering re-examined the phenomenon of efficiency degradation of micro-LEDs with pixels in a size of micrometers (μm, one millionth of a meter) and found that it was possible to fundamentally resolve the problem by the use of epitaxial structure engineering. Epitaxy refers to the process of stacking gallium nitride crystals that are used as a light emitting body on top of an ultrapure silicon or sapphire substrate used for μLEDs as a medium. μLED is being actively studied because it has the advantages of superior brightness, contrast ratio, and lifespan compared to OLED. In 2018, Samsung Electronics commercialized a product equipped with μLED called 'The Wall'. And there is a prospect that Apple may be launching a μLED-mounted product in 2025. In order to manufacture μLEDs, pixels are formed by cutting the epitaxial structure grown on a wafer into a cylinder or cuboid shape through an etching process, and this etching process is accompanied by a plasma-based process. However, these plasmas generate defects on the side of the pixel during the pixel formation process. Therefore, as the pixel size becomes smaller and the resolution increases, the ratio of the surface area to the volume of the pixel increases, and defects on the side of the device that occur during processing further reduce the device efficiency of the μLED. Accordingly, a considerable amount of research has been conducted on mitigating or removing sidewall defects, but this method has a limit to the degree of improvement as it must be done at the post-processing stage after the grown of the epitaxial structure is finished. The research team identified that there is a difference in the current moving to the sidewall of the μLED depending on the epitaxial structure during μLED device operation, and based on the findings, the team built a structure that is not sensitive to sidewall defects to solve the problem of reduced efficiency due to miniaturization of μLED devices. In addition, the proposed structure reduced the self-generated heat while the device was running by about 40% compared to the existing structure, which is also of great significance in commercialization of ultrahigh-resolution μLED displays. This study, which was led by Woo Jin Baek of Professor Sang Hyeon Kim's research team at the KAIST School of Electrical and Electronic Engineering as the first author with guidance by Professor Sang Hyeon Kim and Professor Dae-Myeong Geum of the Chungbuk National University (who was with the team as a postdoctoral researcher at the time) as corresponding authors, was published in the international journal, 'Nature Communications' on March 17th. (Title of the paper: Ultra-low-current driven InGaN blue micro light-emitting diodes for electrically efficient and self-heating relaxed microdisplay). Professor Sang Hyeon Kim said, "This technological development has great meaning in identifying the cause of the drop in efficiency, which was an obstacle to miniaturization of μLED, and solving it with the design of the epitaxial structure.“ He added, ”We are looking forward to it being used in manufacturing of ultrahigh-resolution displays in the future." This research was carried out with the support of the Samsung Future Technology Incubation Center. Figure 1. Image of electroluminescence distribution of μLEDs fabricated from epitaxial structures with quantum barriers of different thicknesses while the current is running Figure 2. Thermal distribution images of devices fabricated with different epitaxial structures under the same amount of light. Figure 3. Normalized external quantum efficiency of the device fabricated with the optimized epitaxial structure by sizes.
KAIST research team develops clathrin assembly for targeted protein delivery to cancer cells
In order to effectively treat cancer without additional side effects, we need a way to deliver drugs specifically to tumor cells. Protein assemblies have been widely used for drug delivery in the field of cancer treatment, but to use them for drug delivery they must first be functionalized, meaning they must be bound to the protein that recognizes the target tumor cell and deliver a drug that kills it. However, the functionalization process of protein assemblies is very complex, inefficient, and limited to small-sized chemical drugs, which limits their real-life applicability. On March 14, a KAIST research team led by Professor Hak-Sung Kim from the KAIST Department of Biological Sciences reported the development of a clathrin assembly that can specifically deliver drugs to cancer cells. Clathrin assemblies transport materials efficiently through endocytosis in living organisms. They are formed by the self-assembly of triskelion units, which are composed of three heavy chains bonded with three light chains. Inspired by this mechanism, the research team designed a clathrin chain to facilitate the functionalization of tumor cell recognition proteins and toxin proteins in order to deliver drugs specifically to tumor cells. From this, the team created a new type of clathrin assembly. Figure 1. (Upper) Schematic diagram of the development of a new clathrin assembly that simultaneously functionalizes two types of proteins (cancer cell recognition protein and toxin protein) on heavy and light chains of clathrin in a one-pot reaction (bottom, left) Electron microscopy image of clathrin assembly: formation of an assembly with a diameter of about 28 nanometers (bottom, right) Cancer cell killing effect of CLA: CLA functionalized with epidermal growth factor receptor (EGFR) recognition protein and toxin protein kills only the cancer cells that overexpress EGFR. The newly developed clathrin assembly requires a one-pot reaction, meaning both the toxin and tumor-recognition proteins can be functionalized simultaneously and show high efficiency. As a result, this technique is expected to be used in a wide variety of applications in the fields of biology and medicine including drug delivery, vaccine development, and diagnosing illnesses. In this research, an epidermal growth factor receptor (EGFR), a common tumor marker, was used as the recognition protein, allowing drug delivery only to tumor cells. The clathrin assemblies that were functionalized to recognize EGFR showed a bonding strength 900-times stronger than it normally would due to the avidity effect. Based on this finding, the research team confirmed that treatment with toxin-functionalized clathrin assembly led to effective cell death for tumor cells, while it showed no such effect on healthy cells. This research by Dr. Hong-Sik Kim and his colleagues was published in Small volume 19, issue 8 on February 22 under the title, "Construction and Functionalization of a Clathrin Assembly for a Targeted Protein Delivery", and it was selected as the cover paper. Figure 2. Cover Paper: This study was published in the international journal 'Small' on February 22nd, Volume 19, No. 8, and was selected as the cover paper. First author Dr. Hong-Sik Kim said, “Clathrin is difficult to functionalize, and since it is extracted from mammals, realistic applications have been limited.” He added, “But the new clathrin assembly we designed for this research can be functionalized with two different types of proteins through a single-step reaction, and can be produced from E. coli, meaning it can become an applicable protein assembly technology for a wide range of biomedical fields.” This research was funded by the Global Ph.D. Fellowship and the Mid-career Researcher Grant of the National Research Foundation.
KAIST leads AI-based analysis on drug-drug interactions involving Paxlovid
KAIST (President Kwang Hyung Lee) announced on the 16th that an advanced AI-based drug interaction prediction technology developed by the Distinguished Professor Sang Yup Lee's research team in the Department of Biochemical Engineering that analyzed the interaction between the PaxlovidTM ingredients that are used as COVID-19 treatment and other prescription drugs was published as a thesis. This paper was published in the online edition of 「Proceedings of the National Academy of Sciences of America」 (PNAS), an internationally renowned academic journal, on the 13th of March. * Thesis Title: Computational prediction of interactions between Paxlovid and prescription drugs (Authored by Yeji Kim (KAIST, co-first author), Jae Yong Ryu (Duksung Women's University, co-first author), Hyun Uk Kim (KAIST, co-first author), and Sang Yup Lee (KAIST, corresponding author)) In this study, the research team developed DeepDDI2, an advanced version of DeepDDI, an AI-based drug interaction prediction model they developed in 2018. DeepDDI2 is able to compute for and process a total of 113 drug-drug interaction (DDI) types, more than the 86 DDI types covered by the existing DeepDDI. The research team used DeepDDI2 to predict possible interactions between the ingredients (ritonavir, nirmatrelvir) of Paxlovid*, a COVID-19 treatment, and other prescription drugs. The research team said that while among COVID-19 patients, high-risk patients with chronic diseases such as high blood pressure and diabetes are likely to be taking other drugs, drug-drug interactions and adverse drug reactions for Paxlovid have not been sufficiently analyzed, yet. This study was pursued in light of seeing how continued usage of the drug may lead to serious and unwanted complications. * Paxlovid: Paxlovid is a COVID-19 treatment developed by Pfizer, an American pharmaceutical company, and received emergency use approval (EUA) from the US Food and Drug Administration (FDA) in December 2021. The research team used DeepDDI2 to predict how Paxrovid's components, ritonavir and nirmatrelvir, would interact with 2,248 prescription drugs. As a result of the prediction, ritonavir was predicted to interact with 1,403 prescription drugs and nirmatrelvir with 673 drugs. Using the prediction results, the research team proposed alternative drugs with the same mechanism but low drug interaction potential for prescription drugs with high adverse drug events (ADEs). Accordingly, 124 alternative drugs that could reduce the possible adverse DDI with ritonavir and 239 alternative drugs for nirmatrelvir were identified. Through this research achievement, it became possible to use an deep learning technology to accurately predict drug-drug interactions (DDIs), and this is expected to play an important role in the digital healthcare, precision medicine and pharmaceutical industries by providing useful information in the process of developing new drugs and making prescriptions. Distinguished Professor Sang Yup Lee said, "The results of this study are meaningful at times like when we would have to resort to using drugs that are developed in a hurry in the face of an urgent situations like the COVID-19 pandemic, that it is now possible to identify and take necessary actions against adverse drug reactions caused by drug-drug interactions very quickly.” This research was carried out with the support of the KAIST New-Deal Project for COVID-19 Science and Technology and the Bio·Medical Technology Development Project supported by the Ministry of Science and ICT. Figure 1. Results of drug interaction prediction between Paxlovid ingredients and representative approved drugs using DeepDDI2
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