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KAIST Employs Image-recognition AI to Determine Battery Composition and Conditions
An international collaborative research team has developed an image recognition technology that can accurately determine the elemental composition and the number of charge and discharge cycles of a battery by examining only its surface morphology using AI learning.
KAIST (President Kwang-Hyung Lee) announced on July 2nd that Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with the Electronics and Telecommunications Research Institute (ETRI) and Drexel University in the United States, has developed a method to predict the major elemental composition and charge-discharge state of NCM cathode materials with 99.6% accuracy using convolutional neural networks (CNN)*.
*Convolutional Neural Network (CNN): A type of multi-layer, feed-forward, artificial neural network used for analyzing visual images.
The research team noted that while scanning electron microscopy (SEM) is used in semiconductor manufacturing to inspect wafer defects, it is rarely used in battery inspections. SEM is used for batteries to analyze the size of particles only at research sites, and reliability is predicted from the broken particles and the shape of the breakage in the case of deteriorated battery materials.
The research team decided that it would be groundbreaking if an automated SEM can be used in the process of battery production, just like in the semiconductor manufacturing, to inspect the surface of the cathode material to determine whether it was synthesized according to the desired composition and that the lifespan would be reliable, thereby reducing the defect rate.
< Figure 1. Example images of true cases and their grad-CAM overlays from the best trained network. >
The researchers trained a CNN-based AI applicable to autonomous vehicles to learn the surface images of battery materials, enabling it to predict the major elemental composition and charge-discharge cycle states of the cathode materials. They found that while the method could accurately predict the composition of materials with additives, it had lower accuracy for predicting charge-discharge states. The team plans to further train the AI with various battery material morphologies produced through different processes and ultimately use it for inspecting the compositional uniformity and predicting the lifespan of next-generation batteries.
Professor Joshua C. Agar, one of the collaborating researchers of the project from the Department of Mechanical Engineering and Mechanics of Drexel University, said, "In the future, artificial intelligence is expected to be applied not only to battery materials but also to various dynamic processes in functional materials synthesis, clean energy generation in fusion, and understanding foundations of particles and the universe."
Professor Seungbum Hong from KAIST, who led the research, stated, "This research is significant as it is the first in the world to develop an AI-based methodology that can quickly and accurately predict the major elemental composition and the state of the battery from the structural data of micron-scale SEM images. The methodology developed in this study for identifying the composition and state of battery materials based on microscopic images is expected to play a crucial role in improving the performance and quality of battery materials in the future."
< Figure 2. Accuracies of CNN Model predictions on SEM images of NCM cathode materials with additives under various conditions. >
This research was conducted by KAIST’s Materials Science and Engineering Department graduates Dr. Jimin Oh and Dr. Jiwon Yeom, the co-first authors, in collaboration with Professor Josh Agar and Dr. Kwang Man Kim from ETRI. It was supported by the National Research Foundation of Korea, the KAIST Global Singularity project, and international collaboration with the US research team. The results were published in the international journal npj Computational Materials on May 4. (Paper Title: “Composition and state prediction of lithium-ion cathode via convolutional neural network trained on scanning electron microscopy images”)
2024.07.02 View 2597 -
Novel High-performance and Sustainable Paper Coating Material created by KAIST-Yonsei University Research Team to reduce microplastic pollution
What if there is a biodegradable packaging material with high performance without leaving microplastics?
Plastic pollution presents a global challenge that must be solved. In particular, packaging accounts for 30-50% of the total plastic consumption. While paper packaging is eco-friendly, it lacks crucial functionalities like moisture resistance and strength. Traditional coating materials exacerbate plastic pollution, prompting the need for sustainable alternatives.
Polyethylene (PE) and ethylene vinyl alcohol (EVOH) are typically used as coating materials to improve the low barrier properties of paper packaging, but these substances do not decompose and worsen microplastic pollution when disposed of in the natural environment. In response to this problem, packaging materials made from bio-based substances and biodegradable plastics have been developed, but in most cases, as the packaging performance improves, the biodegradability diminishes rapidly.
KAIST announced that a joint research team led by Professor Jaewook Myung of the Department of Civil and Environmental Engineering, Professor Hanseul Yang of the Department of Life Sciences, and Professor Jongcheol Seo of the Department of Packaging and Logistics <Figure 4. Back cover art of Green Chemistry journal of the latest volume, describing the boric acid cross-linked poly(vinyl alcohol) coated paper featuring marine biodegradability, biocompatibility, high barrier properties, and robustness developed through this study.>
at Yonsei University tackled the challenge of balancing packaging performance and sustainability. They successfully developed a sustainable, marine biodegradable, high-performance paper coating material.
* Biodegradable plastic: A plastic that can be decomposed by microorganisms in natural environments such as soil and ocean or artificial conditions such as industrial composting and anaerobic digestion by microorganisms.
*Microplastics: Tiny pieces of plastic less than 5 mm, produced during the decomposition of bulk plastic materials. Microplastics can persist in the sea for more than decades, causing severe marine pollution.
The team utilized boric acid-crosslinked poly(vinyl alcohol) (PVA), a biodegradable plastic, to coat the paper, thereby enhancing its biodegradability, barrier properties, and strength. The resulting coated paper exhibited superior performance compared to conventional plastics, with excellent barrier properties and physical strength, even in humid conditions.
<Figure 1. (a) Chemical structure of boric acid-crosslinked poly(vinyl alcohol) coating on paper, (b-c) Oxygen and water vapor barrier properties, (d-f) Tensile strength in dry and moist conditions. OTR: Oxygen transmission rate, WVTR: Water vapor transmission rate.>
The team also conducted an in-depth examination of biodegradation and biocompatibility to systematically evaluate the sustainability of the newly developed coated paper. Biodegradation was assessed by simulating the marine environment, known for its challenging biodegradability conditions. The team employed a respiratory system-based bioreactor to measure the degree of carbon mineralization into carbon dioxide. After 111 days of biodegradation, it was found that the coated papers achieved 59-82% biodegradation depending on the coating component. The phenomenon in which marine bacteria are decomposing the coating material was captured through a scanning electron microscope. In addition, in vitro biocompatibility was confirmed through human embryonic kidney and mouse embryonic fibroblast cells, as well as high in-vivo biocompatibility of the coated paper was verified through mouse experiments.
Through this study, the joint research team proposed a coating strategy that can improve packaging performance while upholding sustainability to address the drawbacks of paper packaging. The boric acid-crosslinked PVA-coated paper eliminates the need for artificial composting conditions or sewage treatment facilities. Being biodegradable in natural environments and characterized by low toxicity, this newly coated paper does not exacerbate environmental pollution when accidentally discarded. Thus, it presents a sustainable substitute for plastic packaging materials.
<Figure 2. (a) Normal paper and boric acid-crosslinked poly(vinyl alcohol) coated paper, (b) Biodegradation of the coated paper by marine bacteria, (c) Result of cytotoxicity test using human embryonic kidney and mouse embryonic fibroblast cells. (d) Vital organs after one-month exposure of the coated papers to mice.>
Professor Jaewook Myung at KAIST, who led the sustainability study of coated paper, said, "The development of a marine biodegradable high-performance paper coating is the result of combining the innovative technologies of three leading research teams in each field." He said, “We will continue to develop sustainable materials with excellent performance.” Meanwhile, Professor Jongchul Seo of Yonsei University, who led the research on the development of high-performance paper coating, mentioned, “Through this research, we have developed a sustainable paper packaging technology that can replace non-degradable plastic packaging, and we expect the research outcome will be applied in industry,”.
<Figure 3. End-of-life scenario of papers coated by BA-crosslinked PVA in the marine environment. The coated papers potentially be disintegrated by marine microorganisms and ocean waves and tides. The depolymerization of PVA coating and paper is then mediated by extracellular depolymerases such as oxidases and cellulases, after which the small subunits (oligomers and monomers) are assimilated by microbial cells. The carbon components in the coated papers are ultimately mineralized into CO2, posing no harm in the ocean.>
The work was published in Green Chemistry and Food Chemistry journals. This study was conducted with the support of the Korea Research Foundation and the Korea Institute for Agriculture, Food and Rural Affairs Technology Planning and Evaluation, etc.
*Title of paper published in Green Chemistry: Boric acid-crosslinked poly(vinyl alcohol): biodegradable, biocompatible, robust, and high-barrier paper coating
※ Selected as the article for the back cover of the journal .
- Authors: Shinhyeong Choe, Seulki You, Kitae Park, Youngju Kim, Jehee Park, Yongjun Cho, Jongchul Seo, Hanseul Yang, and Jaewook Myung)
- Date: April 17, 2024
- DOI: 10.1039/D4GC00618F
*Title of paper published in Food Chemistry: Effect of epichlorohydrin treatment on the coating process and performance of high-barrier paper packaging
- Authors: Kitae Park, Shinhyeong Choe, Kambiz Sadeghi, Pradeep Kumar Panda, Jaewook Myung, Dowan Kim, and Jongchul Seo
- Date: February 19, 2024
- DOI: 10.1016/j.foodchem.2024.138772
<Figure 4. Back cover art of Green Chemistry journal of the latest volume, describing the boric acid cross-linked poly(vinyl alcohol) coated paper featuring marine biodegradability, biocompatibility, high barrier properties, and robustness developed through this study.>
2024.05.22 View 3944 -
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 12309 -
KAIST researchers developed a novel ultra-low power memory for neuromorphic computing
A team of Korean researchers is making headlines by developing a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and its ultra-low power consumption.
KAIST (President Kwang-Hyung Lee) announced on April 4th that Professor Shinhyun Choi's research team in the School of Electrical Engineering has developed a next-generation phase change memory* device featuring ultra-low-power consumption that can replace DRAM and NAND flash memory.
☞ Phase change memory: A memory device that stores and/or processes information by changing the crystalline states of materials to be amorphous or crystalline using heat, thereby changing its resistance state.
Existing phase change memory has the problems such as expensive fabrication process for making highly scaled device and requiring substantial amount of power for operation. To solve these problems, Professor Choi’s research team developed an ultra-low power phase change memory device by electrically forming a very small nanometer (nm) scale phase changeable filament without expensive fabrication processes. This new development has the groundbreaking advantage of not only having a very low processing cost but also of enabling operating with ultra-low power consumption.
DRAM, one of the most popularly used memory, is very fast, but has volatile characteristics in which data disappears when the power is turned off. NAND flash memory, a storage device, has relatively slow read/write speeds, but it has non-volatile characteristic that enables it to preserve the data even when the power is cut off.
Phase change memory, on the other hand, combines the advantages of both DRAM and NAND flash memory, offering high speed and non-volatile characteristics. For this reason, phase change memory is being highlighted as the next-generation memory that can replace existing memory, and is being actively researched as a memory technology or neuromorphic computing technology that mimics the human brain.
However, conventional phase change memory devices require a substantial amount of power to operate, making it difficult to make practical large-capacity memory products or realize a neuromorphic computing system. In order to maximize the thermal efficiency for memory device operation, previous research efforts focused on reducing the power consumption by shrinking the physical size of the device through the use of the state-of-the-art lithography technologies, but they were met with limitations in terms of practicality as the degree of improvement in power consumption was minimal whereas the cost and the difficulty of fabrication increased with each improvement.
In order to solve the power consumption problem of phase change memory, Professor Shinhyun Choi’s research team created a method to electrically form phase change materials in extremely small area, successfully implementing an ultra-low-power phase change memory device that consumes 15 times less power than a conventional phase change memory device fabricated with the expensive lithography tool.
< Figure 1. Illustrations of the ultra-low power phase change memory device developed through this study and the comparison of power consumption by the newly developed phase change memory device compared to conventional phase change memory devices. >
Professor Shinhyun Choi expressed strong confidence in how this research will span out in the future in the new field of research saying, "The phase change memory device we have developed is significant as it offers a novel approach to solve the lingering problems in producing a memory device at a greatly improved manufacturing cost and energy efficiency. We expect the results of our study to become the foundation of future electronic engineering, enabling various applications including high-density three-dimensional vertical memory and neuromorphic computing systems as it opened up the possibilities to choose from a variety of materials.” He went on to add, “I would like to thank the National Research Foundation of Korea and the National NanoFab Center for supporting this research.”
This study, in which See-On Park, a student of MS-PhD Integrated Program, and Seokman Hong, a doctoral student of the School of Electrical Engineering at KAIST, participated as first authors, was published on April 4 in the April issue of the renowned international academic journal Nature. (Paper title: Phase-Change Memory via a Phase-Changeable Self-Confined Nano-Filament)
This research was conducted with support from the Next-Generation Intelligent Semiconductor Technology Development Project, PIM AI Semiconductor Core Technology Development (Device) Project, Excellent Emerging Research Program of the National Research Foundation of Korea, and the Semiconductor Process-based Nanomedical Devices Development Project of the National NanoFab Center.
2024.04.04 View 4465 -
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 3323 -
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 4472 -
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 3935 -
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 6502 -
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 4288 -
KAIST and Hyundai Motors Collaborate to Develop Ultra-Fast Hydrogen Leak Detection within 0.6 Seconds
Recently, as the spread of eco-friendly hydrogen cars increases, the importance of hydrogen sensors is also on the rise. In particular, achieving technology to detect hydrogen leaks within one second remains a challenging task. Accordingly, the development of the world's first hydrogen sensor that meets the performance standards of the U.S. Department of Energy has become a hot topic.
A team at KAIST led by Dr. Min-Seung Jo from Professor Jun-Bo Yoon's team in the Department of Electrical and Electronic Engineering has successfully achieved all of its desired performance indicators, meeting globally recognized standards through collaboration with the Electromagnetic Energy Materials Research Team at Hyundai Motor Company's Basic Materials Research Center and Professor Min-Ho Seo of Pusan National University. On January 10th, the research group announced that the world's first hydrogen sensor with a speed of less than 0.6 seconds had been developed.
In order to secure faster and more stable hydrogen detection technology than existing commercialized hydrogen sensors, the KAIST team began developing a next-generation hydrogen sensor in 2021 together with Hyundai Motor Company, and succeeded after two years of development.
< Figure 1. (Left) The conceptual drawing of the structure of the coplanar heater-integrated hydrogen sensor. Pd nanowire is stably suspended in the air even with its thickness of 20 nm. (Right) A graph of hydrogen sensor performance operating within 0.6 seconds for hydrogen at a concentration of 0.1 to 4% >
Existing hydrogen sensor research has mainly focused on sensing materials, such as catalytic treatments or the alloying of palladium (Pd) materials, which are widely used in hydrogen sensors. Although these studies showed excellent performance with certain performance indicators, they did not meet all of the desired performance indicators and commercialization was limited due to the difficulty of batch processing.
To overcome this, the research team developed a sensor that satisfied all of the performance indicators by combining independent micro/nano structure design and process technology based on pure palladium materials. In addition, considering future mass production, pure metal materials with fewer material restrictions were used rather than synthetic materials, and a next-generation hydrogen sensor was developed that can be mass-produced based on a semiconductor batch process.
The developed device is a differential coplanar device in which the heater and sensing materials are integrated side by side on the same plane to overcome the uneven temperature distribution of existing gas sensors, which have a structure where the heater, insulating layer, and sensing materials are stacked vertically. The palladium nanomaterial, which is a sensing material, has a completely floating structure and is exposed to air from beneath, maximizing the reaction area with a gas to ensure a fast reaction speed. In addition, the palladium sensing material operates at a uniform temperature throughout the entire area, and the research team was able to secure a fast operation speed, wide sensing concentration, and temperature/humidity insensitivity by accurately controlling temperature-sensitive sensing performance.
< Figure 2. Electron microscopy of the coplanar heater-integrated hydrogen sensor (left) Photo of the entire device (top right) Pd nanowire suspended in the air (bottom right) Cross section of Pd nanowire >
The research team packaged the fabricated device with a Bluetooth module to create an integrated module that wirelessly detects hydrogen leaks within one second and then verified its performance. Unlike existing high-performance optical hydrogen sensors, this one is highly portable and can be used in a variety of applications where hydrogen energy is used.
Dr. Min-Seung Jo, who led the research, said, “The results of this research are of significant value as they not only operate at high speeds by exceeding the performance limits of existing hydrogen sensors, but also secure the reliability and stability necessary for actual use, and can be used in various places such as automobiles, hydrogen charging stations, and homes.” He also revealed his future plans, saying, “Through the commercialization of this hydrogen sensor technology, I would like to contribute to advancing the safe and eco-friendly use of hydrogen energy.”
< Figure 3. (Left) Real-time hydrogen detection results from the coplanar heater-integrated hydrogen sensor integrated and packaged in wireless communication and an app for mobile phone. (Middle) LED blinking cycle control in accordance with the hydrogen concentration level. (Right) Results of performance confirmation of the detection within 1 second in a real-time hydrogen leak demo >
The research team is currently working with Hyundai Motor Company to manufacture the device on a wafer scale and then mount it on a vehicle module to further verify detection and durability performance.
This research, conducted by Dr. Min-Seung Jo as the first author, has three patent applications filed in the U.S. and Korea, and was published in the renowned international academic journal 'ACS Nano'. (Paper title: Ultrafast (∼0.6 s), Robust, and Highly Linear Hydrogen Detection up to 10% Using Fully Suspended Pure Pd Nanowire). (Impact Factor: 18.087). ( https://pubs.acs.org/doi/10.1021/acsnano.3c06806?fig=fig1&ref=pdf )
The research was conducted through support from the National Research Foundation of Korea's Nano and Materials Technology Development Project and support and joint development efforts from Hyundai Motor Company's Basic Materials Research Center.
2024.01.25 View 3177 -
North Korea and Beyond: AI-Powered Satellite Analysis Reveals the Unseen Economic Landscape of Underdeveloped Nations
- A joint research team in computer science, economics, and geography has developed an artificial intelligence (AI) technology to measure grid-level economic development within six-square-kilometer regions.
- This AI technology is applicable in regions with limited statistical data (e.g., North Korea), supporting international efforts to propose policies for economic growth and poverty reduction in underdeveloped countries.
- The research team plans to make this technology freely available for use to contribute to the United Nations' Sustainable Development Goals (SDGs).
The United Nations reports that more than 700 million people are in extreme poverty, earning less than two dollars a day. However, an accurate assessment of poverty remains a global challenge. For example, 53 countries have not conducted agricultural surveys in the past 15 years, and 17 countries have not published a population census. To fill this data gap, new technologies are being explored to estimate poverty using alternative sources such as street views, aerial photos, and satellite images.
The paper published in Nature Communications demonstrates how artificial intelligence (AI) can help analyze economic conditions from daytime satellite imagery. This new technology can even apply to the least developed countries - such as North Korea - that do not have reliable statistical data for typical machine learning training.
The researchers used Sentinel-2 satellite images from the European Space Agency (ESA) that are publicly available. They split these images into small six-square-kilometer grids. At this zoom level, visual information such as buildings, roads, and greenery can be used to quantify economic indicators. As a result, the team obtained the first ever fine-grained economic map of regions like North Korea. The same algorithm was applied to other underdeveloped countries in Asia: North Korea, Nepal, Laos, Myanmar, Bangladesh, and Cambodia (see Image 1).
The key feature of their research model is the "human-machine collaborative approach," which lets researchers combine human input with AI predictions for areas with scarce data. In this research, ten human experts compared satellite images and judged the economic conditions in the area, with the AI learning from this human data and giving economic scores to each image. The results showed that the Human-AI collaborative approach outperformed machine-only learning algorithms.
< Image 1. Nightlight satellite images of North Korea (Top-left: Background photo provided by NASA's Earth Observatory). South Korea appears brightly lit compared to North Korea, which is mostly dark except for Pyongyang. In contrast, the model developed by the research team uses daytime satellite imagery to predict more detailed economic predictions for North Korea (top-right) and five Asian countries (Bottom: Background photo from Google Earth). >
The research was led by an interdisciplinary team of computer scientists, economists, and a geographer from KAIST & IBS (Donghyun Ahn, Meeyoung Cha, Jihee Kim), Sogang University (Hyunjoo Yang), HKUST (Sangyoon Park), and NUS (Jeasurk Yang). Dr Charles Axelsson, Associate Editor at Nature Communications, handled this paper during the peer review process at the journal.
The research team found that the scores showed a strong correlation with traditional socio-economic metrics such as population density, employment, and number of businesses. This demonstrates the wide applicability and scalability of the approach, particularly in data-scarce countries. Furthermore, the model's strength lies in its ability to detect annual changes in economic conditions at a more detailed geospatial level without using any survey data (see Image 2).
< Image 2. Differences in satellite imagery and economic scores in North Korea between 2016 and 2019. Significant development was found in the Wonsan Kalma area (top), one of the tourist development zones, but no changes were observed in the Wiwon Industrial Development Zone (bottom). (Background photo: Sentinel-2 satellite imagery provided by the European Space Agency (ESA)). >
This model would be especially valuable for rapidly monitoring the progress of Sustainable Development Goals such as reducing poverty and promoting more equitable and sustainable growth on an international scale. The model can also be adapted to measure various social and environmental indicators. For example, it can be trained to identify regions with high vulnerability to climate change and disasters to provide timely guidance on disaster relief efforts.
As an example, the researchers explored how North Korea changed before and after the United Nations sanctions against the country. By applying the model to satellite images of North Korea both in 2016 and in 2019, the researchers discovered three key trends in the country's economic development between 2016 and 2019. First, economic growth in North Korea became more concentrated in Pyongyang and major cities, exacerbating the urban-rural divide. Second, satellite imagery revealed significant changes in areas designated for tourism and economic development, such as new building construction and other meaningful alterations. Third, traditional industrial and export development zones showed relatively minor changes.
Meeyoung Cha, a data scientist in the team explained, "This is an important interdisciplinary effort to address global challenges like poverty. We plan to apply our AI algorithm to other international issues, such as monitoring carbon emissions, disaster damage detection, and the impact of climate change."
An economist on the research team, Jihee Kim, commented that this approach would enable detailed examinations of economic conditions in the developing world at a low cost, reducing data disparities between developed and developing nations. She further emphasized that this is most essential because many public policies require economic measurements to achieve their goals, whether they are for growth, equality, or sustainability.
The research team has made the source code publicly available via GitHub and plans to continue improving the technology, applying it to new satellite images updated annually. The results of this study, with Ph.D. candidate Donghyun Ahn at KAIST and Ph.D. candidate Jeasurk Yang at NUS as joint first authors, were published in Nature Communications under the title "A human-machine collaborative approach measures economic development using satellite imagery."
< Photos of the main authors. 1. Donghyun Ahn, PhD candidate at KAIST School of Computing 2. Jeasurk Yang, PhD candidate at the Department of Geography of National University of Singapore 3. Meeyoung Cha, Professor of KAIST School of Computing and CI at IBS 4. Jihee Kim, Professor of KAIST School of Business and Technology Management 5. Sangyoon Park, Professor of the Division of Social Science at Hong Kong University of Science and Technology 6. Hyunjoo Yang, Professor of the Department of Economics at Sogang University >
2023.12.07 View 4638 -
The Relentless Rain: East Asia's Recent Floods and What Lies Beneath
In just a month's time, East Asia witnessed torrential downpours that would usually span an entire season. Japan, battered by three times its usual monthly rainfall, faced landslides and flooding that claimed over 200 lives. Meanwhile, South Korea grappled with its longest monsoon in seven years, leaving more than 40 individuals dead or missing. But these events, as harrowing as they sound, are more than just weather anomalies. They're telltale signs, symptoms of a larger malaise that has gripped our planet.
Diving deep into these rain-soaked mysteries, a recently published paper in the journal Science Advances offers a fresh perspective. Led by a research team at the Korea Advanced Institute of Science and Technology (KAIST), Korea, the research unpacks the influence of human-induced climate changes on the East Asia Summer Monsoon frontal system.
Heavy summer rain has a significant impact on agriculture and industry, and can be said to be one of the greatest threats to human society by causing disasters such as floods and landslides, affecting the local ecosystem. It has been reported from all over the world that the intensity of summer heavy rain has changed over the past few decades. However, summer rain in East Asia is caused by various forms such as typhoons, extratropical cyclones, and fronts, and efforts to study heavy frontal rain, which account for more than 40% of summer rainfall, is still insufficient. In addition, because heavy rain is also influenced by natural fluctuations or coincidences in the climate system, it is not yet known to what extent warming due to human activities affects the intensity of heavy frontal precipitation.
An international joint research team consisting of eight institutions from Korea, the United States, and Japan, including KAIST, Tokyo University, Tokyo Institute of Technology, Chonnam National University, GIST, and Utah State University, confirmed the intensity of heavy rain caused by the weather fronts in East Asia using observation data for the past 60 years and found that the coast of southeastern China. It was found that the intensity of heavy rain increased by about 17% across the Korean Peninsula and Japan. To investigate the cause of these changes, the research team used the Earth Metaverse experiment, which simulated Earth with and without greenhouse gas emissions due to human activities, and found that heavy rain intensity was strengthened by about 6% due to greenhouse gas emissions, and the changes discovered were has succeeded for the first time in the world in showing that warming cannot be explained without the effects of human activities.
< Figure 1. (Left) Observed difference in frontal rainfall intensity (FRI) from the later (1991–2015) to the earlier periods (1958–1982) (Right) Visualization of the impact of anthropogenic warming on the intensity of heavy frontal rain analyzed using the Earth Metaverse experiment. >
"It's not just about connecting the dots," said Moon, the first author of the paper, "it's about seeing the larger pattern. Our data analysis reveals a clear and intensified trend in East Asia's frontal rainfall, one that's intertwined with human actions and increasingly harmful for lives and property."
One of the intriguing finds from the study is the mechanics behind this intensification. The team found increased moisture transport due to a warmer climate, which, when coupled with the strengthening of a gigantic weather system called the West North Pacific Subtropical High, results in enhanced frontal rainfall. It’s akin to the climate dialing up the volume on rain events. As the atmosphere warms, it holds more moisture, leading to heavier downpours when conditions are right.
Nobuyuki Utsumi, another voice from the team, makes the science accessible for all, saying, "Monsoon rain isn't just rain anymore. The frequency, the intensity, it's changing. And our actions, our carbon footprint, are casting a larger shadow than we anticipated."
While the devastating news of floods fills headlines, Professor Simon Wang of Utah State University, reminds us of the underlying importance of their study. "It's like reading a detective novel. To solve the mystery of these floods, one has to trace them back to their roots. This work hints at a future where such intense rain events aren't the exception but might become an everyday reality."
Hyungjun Kim, the principal investigator of the team throws in a note of caution, "Understanding this is just the first step. Predicting and preparing for these extremes is the real challenge. Every amplified rainfall event is a message from the future, urging us to adapt." So far, predicting rainfall intensity and locations remains a challenging task for even the most sophisticated weather models.
< Figure 2. Comparison of rates of change in Anthropocene fingerprints. The horizontal axis shows the long-term change slope of the Anthropocene fingerprint signal (1958 to 2015). Shows the probability distribution of slopes extracted from the non-warming experiment (blue) and the warming experiment (red). The vertical solid lines are the slope of the Anthropocene fingerprint signal extracted from observational data. >
The researchers say, “Facing climate change, the narrative of this new study is more than mere numbers and data. It's a story of our planet, our actions, and the rain-soaked repercussions we're beginning to face. As we mop up the aftermath of another flood, research like Moon's beckons us to look deeper, understand better, and act wiser.”
< Figure 3. Comparison of water vapor convergence and rate of change of the western North Pacific high pressure. Shows the gradient of change in water vapor convergence (horizontal axis) and the Northwestern Pacific-East Asia pressure gradient (vertical axis) extracted from warming (red) and non-warming (blue) experiments. Shows the distribution of slope changes of the two indices during the period 1958 to 1982 (P1) and 1991 to 2015 (P2). >
The results of this study were published on November 24 in Science Advances. (Paper title: Anthropogenic warming induced intensification of summer monsoon frontal precipitation over East Asia)
This research was conducted with support from the National Research Foundation of Korea's Overseas Scientist Attraction Project (BP+) and the Anthropocene Research Center.
2023.12.05 View 3149