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KAIST Develops Sodium Battery Capable of Rapid Charging in Just a Few Seconds
Sodium (Na), which is over 500 times more abundant than lithium (Li), has recently garnered significant attention for its potential in sodium-ion battery technologies. However, existing sodium-ion batteries face fundamental limitations, including lower power output, constrained storage properties, and longer charging times, necessitating the development of next-generation energy storage materials.
On the 11th of April, KAIST (represented by President Kwang Hyung Lee) announced that a research team led by Professor Jeung Ku Kang from the Department of Materials Science and Engineering had developed a high-energy, high-power hybrid sodium-ion battery capable of rapid charging.
The innovative hybrid energy storage system integrates anode materials typically used in batteries with cathodes suitable for supercapacitors. This combination allows the device to achieve both high storage capacities and rapid charge-discharge rates, positioning it as a viable next-generation alternative to lithium-ion batteries.
However, the development of a hybrid battery with high energy and high power density requires an improvement to the slow energy storage rate of battery-type anodes as well as the enhancement of the relatively low capacity of supercapacitor-type cathode materials.
< Figure 1. Schematic synthetic procedures of high-capacity/high-rate anode and cathode materials for a sodium-ion hybrid energy storages (SIHES) and their proposed energy storage mechanisms. Synthetic procedures for (a) ultrafine iron sulfide-embedded S-doped carbon/graphene (FS/C/G) anode and (b) zeolitic imidazolate framework-derived porous carbon (ZDPC) cathode materials. (c) Proposed energy storage mechanisms of Na+ ions in FS/C/G anode and ClO-4 ions in ZDPC cathode for an SIHES. >
To account for this, Professor Kang's team utilized two distinct metal-organic frameworks for the optimized synthesis of hybrid batteries. This approach led to the development of an anode material with improved kinetics through the inclusion of fine active materials in porous carbon derived from metal-organic frameworks. Additionally, a high-capacity cathode material was synthesized, and the combination of the cathode and anode materials allowed for the development of a sodium-ion storage system optimizing the balance and minimizing the disparities in energy storage rates between the electrodes.
The assembled full cell, comprising the newly developed anode and cathode, forms a high-performance hybrid sodium-ion energy storage device. This device surpasses the energy density of commercial lithium-ion batteries and exhibits the characteristics of supercapacitors' power density. It is expected to be suitable for rapid charging applications ranging from electric vehicles to smart electronic devices and aerospace technologies.
< Figure 2. Electrochemical characterizations of FS/C/G-20//ZDPC SIHES full cells (left). Ragone plots for FS/C/G-20//ZDPC (this work) and other previously reported sodium-ion electrochemical energy storage devices (right). >
Professor Kang noted that the hybrid sodium-ion energy storage device, capable of rapid charging and achieving an energy density of 247 Wh/kg and a power density of 34,748 W/kg, represents a breakthrough in overcoming the current limitations of energy storage systems. He anticipates broader applications across various electronic devices, including electric vehicles.
This research, co-authored by KAIST doctoral candidates Jong Hui Choi and Dong Won Kim, was published in the international journal Energy Storage Materials on March 29 with the title "Low-crystallinity conductive multivalence iron sulfide-embedded S-doped anode and high-surface-area O-doped cathode of 3D porous N-rich graphitic carbon frameworks for high-performance sodium-ion hybrid energy storages."
The study was conducted with support from the Ministry of Science and ICT and the National Research Foundation of Korea through the Nanomaterial Technology Development Project.
2024.04.18 View 14435 -
A KAIST-SNUH Team Devises a Way to Make Mathematical Predictions to find Metabolites Related to Somatic Mutations in Cancers
Cancer is characterized by abnormal metabolic processes different from those of normal cells. Therefore, cancer metabolism has been extensively studied to develop effective diagnosis and treatment strategies. Notable achievements of cancer metabolism studies include the discovery of oncometabolites* and the approval of anticancer drugs by the U.S. Food and Drug Administration (FDA) that target enzymes associated with oncometabolites. Approved anticancer drugs such as ‘Tibsovo (active ingredient: ivosidenib)’ and ‘Idhifa (active ingredient: enasidenib)’ are both used for the treatment of acute myeloid leukemia. Despite such achievements, studying cancer metabolism, especially oncometabolites, remains challenging due to time-consuming and expensive methodologies such as metabolomics. Thus, the number of confirmed oncometabolites is very small although a relatively large number of cancer-associated gene mutations have been well studied.
*Oncometabolite: A metabolite that shows pro-oncogenic function when abnormally accumulated in cancer cells. An oncometabolite is often generated as a result of gene mutations, and this accumulation promotes the growth and survival of cancer cells. Representative oncometabolites include 2-hydroxyglutarate, succinate, and fumarate.
On March 18th, a KAIST research team led by Professor Hyun Uk Kim from the Department of Chemical and Biomolecular Engineering developed a computational workflow that systematically predicts metabolites and metabolic pathways associated with somatic mutations in cancer through collaboration with research teams under Prof Youngil Koh, Prof. Hongseok Yun, and Prof. Chang Wook Jeong from Seoul National University Hospital.
The research teams have successfully reconstructed patient-specific genome-scale metabolic models (GEMs)* for 1,043 cancer patients across 24 cancer types by integrating publicly available cancer patients’ transcriptome data (i.e., from international cancer genome consortiums such as PCAWG and TCGA) into a generic human GEM. The resulting patient-specific GEMs make it possible to predict each patient’s metabolic phenotypes.
*Genome-scale metabolic model (GEM): A computational model that mathematically describes all of the biochemical reactions that take place inside a cell. It allows for the prediction of the cell’s metabolic phenotypes under various genetic and/or environmental conditions.
< Figure 1. Schematic diagram of a computational methodology for predicting metabolites and metabolic pathways associated with cancer somatic mutations. of a computational methodology for predicting metabolites and metabolic pathways associated with cancer somatic mutations. >
The team developed a four-step computational workflow using the patient-specific GEMs from 1,043 cancer patients and somatic mutation data obtained from the corresponding cancer patients. This workflow begins with the calculation of the flux-sum value of each metabolite by simulating the patient-specific GEMs. The flux-sum value quantifies the intracellular importance of a metabolite. Next, the workflow identifies metabolites that appear to be significantly associated with specific gene mutations through a statistical analysis of the predicted flux-sum data and the mutation data. Finally, the workflow selects altered metabolic pathways that significantly contribute to the biosynthesis of the predicted oncometabolite candidates, ultimately generating metabolite-gene-pathway sets as an output.
The two co-first authors, Dr. GaRyoung Lee (currently a postdoctoral fellow at the Dana-Farber Cancer Institute and Harvard Medical School) and Dr. Sang Mi Lee (currently a postdoctoral fellow at Harvard Medical School) said, “The computational workflow developed can systematically predict how genetic mutations affect cellular metabolism through metabolic pathways. Importantly, it can easily be applied to different types of cancer based on the mutation and transcriptome data of cancer patient cohorts.”
Prof. Kim said, “The computational workflow and its resulting prediction outcomes will serve as the groundwork for identifying novel oncometabolites and for facilitating the development of various treatment and diagnosis strategies”.
This study, which was supported by the National Research Foundation of Korea, has been published online in Genome Biology, a representative journal in the field of biotechnology and genetics, under the title "Prediction of metabolites associated with somatic mutations in cancers by using genome‑scale metabolic models and mutation data".
2024.03.18 View 4256 -
KAIST Develops Healthcare Device Tracking Chronic Diabetic Wounds
A KAIST research team has developed an effective wireless system that monitors the wound healing process by tracking the spatiotemporal temperature changes and heat transfer characteristics of damaged areas such as diabetic wounds.
On the 5th of March, KAIST (represented by President Kwang Hyung Lee) announced that the research team led by Professor Kyeongha Kwon from KAIST’s School of Electrical Engineering, in association with Chung-Ang University professor Hanjun Ryu, developed digital healthcare technology that tracks the wound healing process in real time, which allows appropriate treatments to be administered.
< Figure 1. Schematic illustrations and diagrams of real-time wound monitoring systems. >
The skin serves as a barrier protecting the body from harmful substances, therefore damage to the skin may cause severe health risks to patients in need of intensive care. Especially in the case of diabetic patients, chronic wounds are easily formed due to complications in normal blood circulation and the wound healing process. In the United States alone, hundreds of billions of dollars of medical costs stem from regenerating the skin from such wounds. While various methods exist to promote wound healing, personalized management is essential depending on the condition of each patient's wounds.
Accordingly, the research team tracked the heating response within the wound by utilizing the differences in temperature between the damaged area and the surrounding healthy skin. They then measured heat transfer characteristics to observe moisture changes near the skin surface, ultimately establishing a basis for understanding the formation process of scar tissue. The team conducted experiments using diabetic mice models regarding the delay in wound healing under pathological conditions, and it was demonstrated that the collected data accurately tracks the wound healing process and the formation of scar tissue.
To minimize the tissue damage that may occur in the process of removing the tracking device after healing, the system integrates biodegradable sensor modules capable of natural decomposition within the body. These biodegradable modules disintegrate within the body after use, thus reducing the risk of additional discomfort or tissue damage upon device removal. Furthermore, the device could one day be used for monitoring inside the wound area as there is no need for removal.
Professor Kyeongha Kwon, who led the research, anticipates that continuous monitoring of wound temperature and heat transfer characteristics will enable medical professionals to more accurately assess the status of diabetic patients' wounds and provide appropriate treatment. He further predicted that the implementation of biodegradable sensors allows for the safe decomposition of the device after wound healing without the need for removal, making live monitoring possible not only in hospitals but also at home.
The research team plans to integrate antimicrobial materials into this device, aiming to expand its technological capabilities to enable the observation and prevention of inflammatory responses, bacterial infections, and other complications. The goal is to provide a multi-purpose wound monitoring platform capable of real-time antimicrobial monitoring in hospitals or homes by detecting changes in temperature and heat transfer characteristics indicative of infection levels.
< Image 1. Image of the bioresorbable temperature sensor >
The results of this study were published on February 19th in the international journal Advanced Healthcare Materials and selected as the inside back cover article, titled "Materials and Device Designs for Wireless Monitoring of Temperature and Thermal Transport Properties of Wound Beds during Healing."
This research was conducted with support from the Basic Research Program, the Regional Innovation Center Program, and the BK21 Program.
2024.03.11 View 4382 -
The World’s First Hacking-preventing Cryptographic Semiconductor Chip
With the dramatic increase in the amount of information exchanged between components or devices in the 5G/6G era, such as for the Internet of Things (IoT) and autonomous driving, hacking attacks are becoming more sophisticated. Consequently, enhancing security functions is essential for safely transmitting data between and among devices.
On February 29th, a KAIST research team led by Professors Yang-gyu Choi and Seung-tak Ryu from the School of Electrical Engineering announced the successful development of the world's first security cryptographic semiconductor.
The team has developed the Cryptoristor, a cryptographic transistor based on FinFET technology, produced through a 100% silicon-compatible process, for the first time in the world. Cryptoristor is a random number generator (RNG) with unparalleled characteristics, featuring a unique structure comprising a single transistor and a distinctive mechanism.
In all security environments, including artificial intelligence, the most crucial element is the RNG. In the most commonly used security chip, the Advanced Encryption Standard (AES), the RNG is a core component, occupying approximately 75% of the total chip area and more than 85% of its energy consumption. Hence, there is an urgent need for the development of low-power/ultra-small RNGs suitable for mobile or IoT devices.
Existing RNGs come with limitations as they lack compatibility with silicon CMOS processes and circuit-based RNGs occupy a large surface area.
In contrast, the team’s newly developed Cryptoristor, a cryptographic semiconductor based on a single-component structure, consumes and occupies less than .001 of the power and area compared to the current chips being used. Utilizing the inherent randomness of FinFETs, fabricated on a Silicon-on-Insulator (SOI) substrate with an insulating layer formed beneath the silicon, the team developed an RNG that unpredictably produces zeroes and ones.
< Figure 1. Conceptual diagram of the security cryptographic transistor device. >
Generally speaking, preventing hackers from predicting the encrypted algorithms during data exchanges through mobile devices is pivotal. Therefore, this method ensures unpredictability by generating random sequences of zeroes and ones that change every time.
Moreover, while the Cryptoristor-based RNG research is the world's first of its kind without any international implementation cases, it shares the same transistor structure as existing logic or memory components. This enables 100% production through rapid mass production processes using existing semiconductor facilities at a low cost.
Seung-il Kim, a PhD student who led the research, explained the significance of the study, stating, "As a cryptographic semiconductor, the ultra-small/low-power random number generator enhances security through its distinctive unpredictability, supporting safe hyperconnectivity with secure transmissions between chips or devices. Particularly, compared to previous research, it offers excellent advantages in terms of energy consumption, integration density, and cost, making it suitable for IoT device environments."
This research, with master’s student Hyung-jin Yoo as the co-author, was officially published in the online edition of Science Advances, a sister journal of Science, in February 2024 (research paper title: Cryptographic transistor for true random number generator with low power consumption).
This research received support from the Next-Generation Intelligent Semiconductor Technology Development Project and the Core Technology Development Project for the National Semiconductor Research Laboratory.
2024.03.07 View 5315 -
KAIST Team Develops an Insect-Mimicking Semiconductor to Detect Motion
The recent development of an “intelligent sensor” semiconductor that mimics the optic nerve of insects while operating at ultra-high speeds and low power offers extensive expandability into various innovative technologies. This technology is expected to be applied to various fields including transportation, safety, and security systems, contributing to both industry and society.
On February 19, a KAIST research team led by Professor Kyung Min Kim from the Department of Materials Science and Engineering (DMSE) announced the successful developed an intelligent motion detector by merging various memristor* devices to mimic the visual intelligence** of the optic nerve of insects.
*Memristor: a “memory resistor” whose state of resistance changes depending on the input signal
**Visual intelligence: the ability to interpret visual information and perform calculations within the optic nerve
With the recent advances in AI technology, vision systems are being improved by utilizing AI in various tasks such as image recognition, object detection, and motion analysis. However, existing vision systems typically recognize objects and their behaviour from the received image signals using complex algorithms. This method requires a significant amount of data traffic and higher power consumption, making it difficult to apply in mobile or IoT devices.
Meanwhile, insects are known to be able to effectively process visual information through an optic nerve circuit called the elementary motion detector, allowing them to detect objects and recognize their motion at an advanced level. However, mimicking this pathway using conventional silicon integrated circuit (CMOS) technology requires complex circuits, and its implementation into actual devices has thus been limited.
< Figure 1. Working principle of a biological elementary motion detection system. >
Professor Kyung Min Kim’s research team developed an intelligent motion detecting sensor that operates at a high level of efficiency and ultra-high speeds. The device has a simple structure consisting of only two types of memristors and a resistor developed by the team. The two different memristors each carry out a signal delay function and a signal integration and ignition function, respectively. Through them, the team could directly mimic the optic nerve of insects to analyze object movement.
< Figure 2. (Left) Optical image of the M-EMD device in the left panel (scale bar 200 μm) and SEM image of the device in the right panel (scale bar: 20 μm). (Middle) Responses of the M-EMD in positive direction. (Right) Responses of the M-EMD in negative direction. >
To demonstrate its potential for practical applications, the research team used the newly developed motion detector to design a neuromorphic computing system that can predict the path of a vehicle. The results showed that the device used 92.9% less energy compared to existing technology and predicted motion with more accuracy.
< Figure 3. Neuromorphic computing system configuration based on motion recognition devices >
Professor Kim said, “Insects make use of their very simple visual intelligence systems to detect the motion of objects at a surprising high speed. This research is significant in that we could mimic the functions of a nerve using a memristor device.” He added, “Edge AI devices, such as AI-topped mobile phones, are becoming increasingly important. This research can contribute to the integration of efficient vision systems for motion recognition, so we expect it to be applied to various fields such as autonomous vehicles, vehicle transportation systems, robotics, and machine vision.”
This research, conducted by co-first authors Hanchan Song and Min Gu Lee, both Ph.D. candidates at KAIST DMSE, was published in the online issue of Advanced Materials on January 29.
This research was supported by the Mid-Sized Research Project by the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Project, the PIM Artificial Intelligence Semiconductor Core Technology Development Project, the National Nano Fab Center, and the Leap Research Project by KAIST.
2024.02.29 View 5012 -
KAIST to begin Joint Research to Develop Next-Generation LiDAR System with Hyundai Motor Group
< (From left) Jong-Soo Lee, Executive Vice President at Hyundai Motor, Sang-Yup Lee, Senior Vice President for Research at KAIST >
The ‘Hyundai Motor Group-KAIST On-Chip LiDAR Joint Research Lab’ was opened at KAIST’s main campus in Daejeon to develop LiDAR sensors for advanced autonomous vehicles.
The joint research lab aims to develop high-performance and compact on-chip sensors and new signal detection technology, which are essential in the increasingly competitive autonomous driving market. On-chip sensors, which utilize semiconductor manufacturing technology to add various functions, can reduce the size of LiDAR systems compared to conventional methods and secure price competitiveness through mass production using semiconductor fabrication processes.
The joint research lab will consist of about 30 researchers, including the Hyundai-Kia Institute of Advanced Technology Development research team and KAIST professors Sanghyeon Kim, Sangsik Kim, Wanyeong Jung, and Hamza Kurt from KAIST’s School of Electrical Engineering, and will operate for four years until 2028.
KAIST will be leading the specialized work of each research team, such as for the development of silicon optoelectronic on-chip LiDAR components, the fabrication of high-speed, high-power integrated circuits to run the LiDAR systems, and the optimization and verification of LiDAR systems.
Hyundai Motor and Kia, together with Hyundai NGV, a specialized industry-academia cooperation institution, will oversee the operation of the joint research lab and provide support such as monitoring technological trends, suggesting research directions, deriving core ideas, and recommending technologies and experts to enhance research capabilities.
A Hyundai Motor Group official said, "We believe that this cooperation between Hyundai Motor Company and Kia, the leader in autonomous driving technology, and KAIST, the home of world-class technology, will hasten the achievement of fully autonomous driving." He added, "We will do our best to enable the lab to produce tangible results.”
Professor Sanghyeon Kim said, "The LiDAR sensor, which serves as the eyes of a car, is a core technology for future autonomous vehicle development that is essential for automobile companies to internalize."
2024.02.27 View 6207 -
A Korean research team develops a new clinical candidate for fatty liver disease
A team of Korean researchers have succeeded in developing a new drug candidate for the treatment of non-alcoholic fatty liver disease (NAFLD) acting on peripheral tissues. To date, there has not been an optimal treatment for non-alcoholic steatohepatitis (NASH), and this discovery is expected to set the grounds for the development of new drugs that can safely suppress both liver fat accumulation and liver fibrosis at the same time.
A joint research team led by Professor Jin Hee Ahn from Gwangju Institute of Science and Technology (GIST) and Professor Hail Kim from the KAIST Graduate School of Medical Science and Engineering developed a new chemical that can suppress disease-specific protein (HTR2A) through years of basic research. The team also revealed to have verified its efficacy and safety through preclinical tests (animal tests) at JD Bioscience Inc., a start-up company founded by Professor Ahn.
Although NAFLD has a prevalence rate as high as 20-30%, and about 5% of the global adult population suffers from NASH, there are no commercial drugs targeting them to date. NAFLD is a chronic disease that starts from the fatty liver and progresses into steatohepatitis, fibrosis, cirrhosis, and liver cancer. The mortality rate of patients increases with accompanied cardiovascular diseases and liver-related complications, and appropriate treatment in the early stage is hence necessary.
< Figure 1. Strategy and history of 5HT2A antagonists. Library and rational design for the development of compound 11c as a potent 5HT2A antagonist. Previous research efforts were discontinued due to limited oral absorption and safety. A therapeutic candidate to overcome this problem was identified and phase 1 clinical trials are currently in progress. >
The new synthetic chemical developed by the joint GIST-KAIST research is an innovative drug candidate that shows therapeutic effects on NASH based on a dual action mechanism that inhibits the accumulation of fat in the liver and liver fibrosis by suppressing the serotonin receptor protein 5HT2A.
The research team confirmed its therapeutic effects in animal models for NAFLD and NASH, in which hepatic steatosis and liver fibrosis* caused by fat accumulation in the liver were suppressed simultaneously by 50-70%.
*fibrosis: stiffening of parts of the liver, also used as a major indicator to track the prognosis of steatosis
The research team explained that the material was designed with optimal polarity and lipid affinity to minimize its permeability across the blood-brain barrier. It therefore does not affect the brain, and causes little side effects in the central nervous system (CNS) such as depression and suicidal ideations, while demonstrating excellent inhibition on its target protein present in tissues outside brain (IC50* = 14 nM). The team also demonstrated its superior efficacy in improving liver fibrosis when compared to similar drugs in the phase 3 clinical trial.
*IC50 (half maximal inhibitory concentration): the concentration at which a chemical suppresses 50% of a particular biological function
< Figure 2. GM-60106 (11c)'s effect on obesity: When GM-60106 was administered to an obese animal model (mice) for 2 months, body weight, body fat mass, and blood sugar were significantly reduced (a-d). In addition, the steatohepatitis level (NAFLD Activity Score) and the expression of genes of the treated mice involved in adipogenesis along with blood/liver fat decreased (e-h) >
Based on the pharmacological data obtained through preclinical trials, the team evaluated the effects of the drug on 88 healthy adults as part of their phase 1 clinical trial, where the side effects and the safe dosage of a drug are tested against healthy adults. Results showed no serious side effects and a good level of drug safety.
In addition, a preliminary efficacy evaluation on eight adults with steatohepatitis is currently underway.
Professor Jin Hee Ahn said, “The aim of this research is to develop a treatment for NASH with little side effects and guaranteed safety by developing a new target. The developed chemical is currently going through phase 1 of the global clinical trial in Australia through JD Bioscience Inc., a bio venture company for innovative drug development.” he added, “The candidate material the research team is currently developing shows not only a high level of safety and preventative effects by suppressing fat accumulation in the liver, but also a direct therapeutic effect on liver fibrosis. This is a strength that distinguishes our material from other competing drugs.”
< Figure 3. Efficacy of GM-60106 (11c) on liver fibrosis: When GM-60106 was administered to a steatohepatitis model (mice) for 3 months, the expression of genes associated with tissue fibrosis was significantly reduced (b-c). As a result of a detailed analysis of the tissues of the animal model, it was confirmed that the rate of tissue fibrosis was reduced and the expression rate of genes related to tissue fibrosis and inflammation was also significantly reduced (e-h). >
Professor Hail Kim from KAIST said, “Until now, this disease did not have a method of treatment other than weight control, and there has been no attempt to develop a drug that can be used for non-obese patients.” He added, “Through this research, we look forward to the development of various treatment techniques targeting a range of metabolic diseases including NASH that do not affect the weight of the patient.”
This study, conducted together by the research teams led by Professor Ahn from GIST and Professor Kim from KAIST, as well as the research team from JD Bioscience Inc., was supported by the Ministry of Science and ICT, and the National New Drug Development Project. The results of this research were published by Nature Communications on January 20.
The team also presented the results of their clinical study on the candidate material coded GM-60106 targeting metabolic abnormality-related MASH* at NASH-TAG Conference 2024, which was held in Utah for three days starting on January 4, which was selected as an excellent abstract.
*MASH (Metabolic Dysfunction-Associated Steatohepatitis): new replacement term for NASH
2024.02.21 View 6032 -
Genome Sequencing Unveils Mutational Impacts of Radiation on Mammalian Cells
Recent release of the waste water from Japan's Fukushima nuclear disaster stirred apprehension regarding the health implications of radiation exposure. Classified as a Group 1 carcinogen, ionizing radiation has long been associated with various cancers and genetic disorders, as evidenced by survivors and descendants of atomic bombings and the Chernobyl disaster. Despite much smaller amount, we remain consistently exposed to low levels of radiation in everyday life and medical procedures.
Radiation, whether in the form of high-energy particles or electromagnetic waves, is conventionally known to break our cellular DNA, leading to cancer and genetic disorders. Yet, our understanding of the quantitative and qualitative mutational impacts of ionizing radiation has been incomplete.
On the 14th, Professor Young Seok Ju and his research team from KAIST, in collaboration with Dr. Tae Gen Son from the Dongnam Institute of Radiological and Medical Science, and Professors Kyung Su Kim and Ji Hyun Chang from Seoul National University, unveiled a breakthrough. Their study, led by joint first authors Drs. Jeonghwan Youk, Hyun Woo Kwon, Joonoh Lim, Eunji Kim and Tae-Woo Kim, titled "Quantitative and qualitative mutational impact of ionizing radiation on normal cells," was published in Cell Genomics.
Employing meticulous techniques, the research team comprehensively analyzed the whole-genome sequences of cells pre- and post-radiation exposure, pinpointing radiation-induced DNA mutations. Experiments involving cells from different organs of humans and mice exposed to varying radiation doses revealed mutation patterns correlating with exposure levels. (Figure 1)
Notably, exposure to 1 Gray (Gy) of radiation resulted in on average 14 mutations in every post-exposure cell. (Figure 2) Unlike other carcinogens, radiation-induced mutations primarily comprised short base deletions and a set of structural variations including inversions, translocations, and various complex genomic rearrangements. (Figure 3) Interestingly, experiments subjecting cells to low radiation dose rate over 100 days demonstrated that mutation quantities, under equivalent total radiation doses, mirrored those of high-dose exposure.
"Through this study, we have clearly elucidated the effects of radiation on cells at the molecular level," said Prof. Ju at KAIST. "Now we understand better how radiation changes the DNA of our cells," he added.
Dr. Son from the Dongnam Institute of Radiological and Medical Science stated, "Based on this study, we will continue to research the effects of very low and very high doses of radiation on the human body," and further remarked, "We will advance the development of safe and effective radiation therapy techniques."
Professors Kim and Chang from Seoul National University College of Medicine expressed their views, saying, "Through this study, we believe we now have a tool to accurately understand the impact of radiation on human DNA," and added, "We hope that many subsequent studies will emerge using the research methodologies employed in this study."
This research represents a significant leap forward in radiation studies, made possible through collaborative efforts and interdisciplinary approaches. This pioneering research engaged scholars from diverse backgrounds, spanning from the Genetic Engineering Research Institute at Seoul National University, the Cambridge Stem Cell Institute in the UK, the Institute for Molecular Biotechnology in Austria (IMBA), and the Genome Insight Inc. (a KAIST spin-off start-up). This study was supported by various institutions including the National Research Foundation of Korea, Dongnam Institute of Radiological and Medical Science (supported by Ministry of Science and ICT, the government of South Korea), the Suh Kyungbae Foundation, the Human Frontier Science Program (HFSP), and the Korea University Anam Hospital Korea Foundation for the Advancement of Science and Creativity, the Ministry of Science and ICT, and the National R&D Program.
2024.02.15 View 5384 -
Team KAIST placed among top two at MBZIRC Maritime Grand Challenge
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.
2024.02.09 View 8290 -
A KAIST Research Team Develops a Novel “Bone Bandage” Material for Cracked Bones
Bone regeneration is a complex process, and existing methods to aid regeneration including transplants and growth factor transmissions face limitations such as the high cost. But recently, a piezoelectric material that can promote the growth of bone tissue has been developed.
A KAIST research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering (DMSE) announced on January 25 the development of a biomimetic scaffold that generates electrical signals upon the application of pressure by utilizing the unique osteogenic ability of hydroxyapatite (HAp). This research was conducted in collaboration with a team led by Professor Jangho Kim from the Department of Convergence Biosystems Engineering at Chonnam National University.
HAp is a basic calcium phosphate material found in bones and teeth. This biocompatible mineral substance is also known to prevent tooth decay and is often used in toothpaste.
Previous studies on piezoelectric scaffolds confirmed the effects of piezoelectricity on promoting bone regeneration and improving bone fusion in various polymer-based materials, but were limited in simulating the complex cellular environment required for optimal bone tissue regeneration. However, this research suggests a new method for utilizing the unique osteogenic abilities of HAp to develop a material that mimics the environment for bone tissue in a living body.
< Figure 1. Design and characterization of piezoelectrically and topographically originated biomimetic scaffolds. (a) Schematic representation of the enhanced bone regeneration mechanism through electrical and topographical cues provided by HAp-incorporated P(VDF-TrFE) scaffolds. (b) Schematic diagram of the fabrication process. >
The research team developed a manufacturing process that fuses HAp with a polymer film. The flexible and free-standing scaffold developed through this process demonstrated its remarkable potential for promoting bone regeneration through in-vitro and in-vivo experiments in rats.
The team also identified the principles of bone regeneration that their scaffold is based on. Using atomic force microscopy (AFM), they analysed the electrical properties of the scaffold and evaluated the detailed surface properties related to cell shape and cell skeletal protein formation. They also investigated the effects of piezoelectricity and surface properties on the expression of growth factors.
Professor Hong from KAIST’s DMSE said, “We have developed a HAp-based piezoelectric composite material that can act like a ‘bone bandage’ through its ability to accelerate bone regeneration.” He added, “This research not only suggests a new direction for designing biomaterials, but is also significant in having explored the effects of piezoelectricity and surface properties on bone regeneration.”
This research, conducted by co-first authors Soyun Joo and Soyeon Kim from Professor Hong’s group, was published on ACS Applied Materials & Interfaces on January 4 under the title “Piezoelectrically and Topographically Engineered Scaffolds for Accelerating Bone Regeneration”. From Professor Kim’s group, Ph.D. candidate Yonghyun Gwon also participated as co-first author, and Professor Kim himself as a corresponding author.
< Figure 2. Analysis of piezoelectric and surface properties of the biomimetic scaffolds using atomic force microscopy. (a) PFM amplitude and phase images of box-poled composite scaffolds. The white bar represents 2 μm. (b) 3D representations of composite scaffolds paired with typical 2D line sections. (c) In vivo bone regeneration micro-CT analysis, (d) schematic representation of filler-derived electrical origins in bone regeneration. >
This research was supported by the KAIST Research and Development Team, the KUSTAR-KAIST Joint Research Center, the KAIST Global Singularity Project, and the government-funded Basic Research Project by the National Research Foundation of Korea.
2024.02.01 View 5512 -
KAIST Professor Jiyun Lee becomes the first Korean to receive the Thurlow Award from the American Institute of Navigation
< Distinguished Professor Jiyun Lee from the KAIST Department of Aerospace Engineering >
KAIST (President Kwang-Hyung Lee) announced on January 27th that Distinguished Professor Jiyun Lee from the KAIST Department of Aerospace Engineering had won the Colonel Thomas L. Thurlow Award from the American Institute of Navigation (ION) for her achievements in the field of satellite navigation.
The American Institute of Navigation (ION) announced Distinguished Professor Lee as the winner of the Thurlow Award at its annual awards ceremony held in conjunction with its international conference in Long Beach, California on January 25th. This is the first time a person of Korean descent has received the award.
The Thurlow Award was established in 1945 to honor Colonel Thomas L. Thurlow, who made significant contributions to the development of navigation equipment and the training of navigators. This award aims to recognize an individual who has made an outstanding contribution to the development of navigation and it is awarded to one person each year. Past recipients include MIT professor Charles Stark Draper, who is well-known as the father of inertial navigation and who developed the guidance computer for the Apollo moon landing project.
Distinguished Professor Jiyun Lee was recognized for her significant contributions to technological advancements that ensure the safety of satellite-based navigation systems for aviation. In particular, she was recognized as a world authority in the field of navigation integrity architecture design, which is essential for ensuring the stability of intelligent transportation systems and autonomous unmanned systems. Distinguished Professor Lee made a groundbreaking contribution to help ensure the safety of satellite-based navigation systems from ionospheric disturbances, including those affected by sudden changes in external factors such as the solar and space environment.
She has achieved numerous scientific discoveries in the field of ionospheric research, while developing new ionospheric threat modeling methods, ionospheric anomaly monitoring and mitigation techniques, and integrity and availability assessment techniques for next-generation augmented navigation systems. She also contributed to the international standardization of technology through the International Civil Aviation Organization (ICAO).
Distinguished Professor Lee and her research group have pioneered innovative navigation technologies for the safe and autonomous operation of unmanned aerial vehicles (UAVs) and urban air mobility (UAM). She was the first to propose and develop a low-cost navigation satellite system (GNSS) augmented architecture for UAVs with a near-field network operation concept that ensures high integrity, and a networked ground station-based augmented navigation system for UAM. She also contributed to integrity design techniques, including failure monitoring and integrity risk assessment for multi-sensor integrated navigation systems.
< Professor Jiyoon Lee upon receiving the Thurlow Award >
Bradford Parkinson, professor emeritus at Stanford University and winner of the 1986 Thurlow Award, who is known as the father of GPS, congratulated Distinguished Professor Lee upon hearing that she was receiving the Thurlow Award and commented that her innovative research has addressed many important topics in the field of navigation and her solutions are highly innovative and highly regarded.
Distinguished Professor Lee said, “I am very honored and delighted to receive this award with its deep history and tradition in the field of navigation.” She added, “I will strive to help develop the future mobility industry by securing safe and sustainable navigation technology.”
2024.01.26 View 4632 -
KAIST Research Team Breaks Down Musical Instincts with AI
Music, often referred to as the universal language, is known to be a common component in all cultures. Then, could ‘musical instinct’ be something that is shared to some degree despite the extensive environmental differences amongst cultures?
On January 16, a KAIST research team led by Professor Hawoong Jung from the Department of Physics announced to have identified the principle by which musical instincts emerge from the human brain without special learning using an artificial neural network model.
Previously, many researchers have attempted to identify the similarities and differences between the music that exist in various different cultures, and tried to understand the origin of the universality. A paper published in Science in 2019 had revealed that music is produced in all ethnographically distinct cultures, and that similar forms of beats and tunes are used. Neuroscientist have also previously found out that a specific part of the human brain, namely the auditory cortex, is responsible for processing musical information.
Professor Jung’s team used an artificial neural network model to show that cognitive functions for music forms spontaneously as a result of processing auditory information received from nature, without being taught music. The research team utilized AudioSet, a large-scale collection of sound data provided by Google, and taught the artificial neural network to learn the various sounds. Interestingly, the research team discovered that certain neurons within the network model would respond selectively to music. In other words, they observed the spontaneous generation of neurons that reacted minimally to various other sounds like those of animals, nature, or machines, but showed high levels of response to various forms of music including both instrumental and vocal.
The neurons in the artificial neural network model showed similar reactive behaviours to those in the auditory cortex of a real brain. For example, artificial neurons responded less to the sound of music that was cropped into short intervals and were rearranged. This indicates that the spontaneously-generated music-selective neurons encode the temporal structure of music. This property was not limited to a specific genre of music, but emerged across 25 different genres including classic, pop, rock, jazz, and electronic.
< Figure 1. Illustration of the musicality of the brain and artificial neural network (created with DALL·E3 AI based on the paper content) >
Furthermore, suppressing the activity of the music-selective neurons was found to greatly impede the cognitive accuracy for other natural sounds. That is to say, the neural function that processes musical information helps process other sounds, and that ‘musical ability’ may be an instinct formed as a result of an evolutionary adaptation acquired to better process sounds from nature.
Professor Hawoong Jung, who advised the research, said, “The results of our study imply that evolutionary pressure has contributed to forming the universal basis for processing musical information in various cultures.” As for the significance of the research, he explained, “We look forward for this artificially built model with human-like musicality to become an original model for various applications including AI music generation, musical therapy, and for research in musical cognition.” He also commented on its limitations, adding, “This research however does not take into consideration the developmental process that follows the learning of music, and it must be noted that this is a study on the foundation of processing musical information in early development.”
< Figure 2. The artificial neural network that learned to recognize non-musical natural sounds in the cyber space distinguishes between music and non-music. >
This research, conducted by first author Dr. Gwangsu Kim of the KAIST Department of Physics (current affiliation: MIT Department of Brain and Cognitive Sciences) and Dr. Dong-Kyum Kim (current affiliation: IBS) was published in Nature Communications under the title, “Spontaneous emergence of rudimentary music detectors in deep neural networks”.
This research was supported by the National Research Foundation of Korea.
2024.01.23 View 4650