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KAIST Awarded Presidential Commendation for Contributions in Software Industry
- At the “25th Software Industry Day” celebration held in the afternoon on Monday, December 2nd, 2024 at Yangjae L Tower in Seoul - KAIST was awarded the “Presidential Commendation” for its contributions for the advancement of the Software Industry in the Group Category - Korea’s first AI master’s and doctoral degree program opened at KAIST Kim Jaechul Graduate School of AI - Focus on training non-major developers through SW Officer Training Academy "Jungle", Machine Learning Engineer Bootcamp, etc., talents who can integrate development and collaboration, and advanced talents in the latest AI technologies. - Professor Minjoon Seo of KAIST Kim Jaechul Graduate School of AI received Prime Minister’s Commendation for his contributions for the advancement of the software industry. < Photo 1. Professor Kyung-soo Kim, the Senior Vice President for Planning and Budget (second from the left) and the Manager of Planning Team, Mr. Sunghoon Jung, stand at the stage after receiving the Presidential Commendation as KAIST was selected as one of the groups that contributed to the advancement of the software industry at the "25th Software Industry Day" celebration. > “KAIST has been leading the way in achieving the grand goal of fostering 1 million AI talents in Korea by services that pan from providing various educational opportunities, from developing the capabilities of experts with no computer science specialty to fostering advanced professionals. I would like to thank all members of KAIST community who worked hard to achieve the great feat of receiving the Presidential Commendations.” (KAIST President Kwang Hyung Lee) KAIST (President Kwang Hyung Lee) announced on December 3rd that it was selected as a group that contributed to the advancement of the software industry at the “2024 Software Industry Day” celebration held at the Yangjae El Tower in Seoul on the 2nd of December and received a presidential commendation. The “Software Industry Day”, hosted by the Ministry of Science and ICT and organized by the National IT Industry Promotion Agency and the Korea Software Industry Association, is an event designed to promote the status of software industry workers in Korea and to honor their achievements. Every year, those who have made significant contributions to policy development, human resource development, and export growth for industry revitalization are selected and awarded the ‘Software Industry Development Contribution Award.’ KAIST was recognized for its contribution to developing a demand-based, industrial field-centric curriculum and fostering non-major developers and convergence talents with the goal of expanding software value and fostering excellent human resources. < Photo 2. Senior Vice President for Planning and Budget Kyung-soo Kim receiving the commendation as the representative of KAIST > Specifically, it first opened the SW Officer Training Academy "Jungle" to foster convergent program developers equipped with the abilities to handle both the computer coding and human interactions for collaborations. This is a non-degree program that provides intensive study and assignments for 5 months for graduates and intellectuals without prior knowledge of computer science. KAIST Kim Jaechul Graduate School of AI opened and operated Korea’s first master's and doctoral degree program in the field of artificial intelligence. In addition, it planned a “Machine Learning Engineers’ Boot Camp” and conducted lectures and practical training for a total of 16 weeks on the latest AI technologies such as deep learning basics and large language models. It aims to strengthen the practical capabilities of start-up companies while lowering the threshold for companies to introduce AI technology. Also, KAIST was selected to participate in the 1st and 2nd stages of the Software-centered University Project and has been taking part in the project since 2016. Through this, it was highly evaluated for promoting curriculum based on latest technology, an autonomous system where students directly select integrated education, and expansion of internships. < Photo 3. Professor Minjoon Seo of Kim Jaechul Graduate School of AI, who received the Prime Minister's Commendation for his contribution to the advancement of the software industry on the same day > At the awards ceremony that day, Professor Minjoon Seo of KAIST Kim Jaechul Graduate School of AI also received the Prime Minister's Commendation for his contribution to the advancement of the software industry. Professor Seo was recognized for his leading research achievements in the fields of AI and natural language processing by publishing 28 papers in top international AI conferences over the past four years. At the same time, he was noted for his contributions to enhancing the originality and innovation of language model research, such as △knowledge encoding, △knowledge access and utilization, and △high-dimensional inference performance, and for demonstrating leadership in the international academic community. President Kwang Hyung Lee of KAIST stated, “Our university will continue to do its best to foster software talents with global competitiveness through continuous development of cutting-edge curriculum and innovative degree systems.”
2024.12.03
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KAIST Develops a Multifunctional Structural Battery Capable of Energy Storage and Load Support
Structural batteries are used in industries such as eco-friendly, energy-based automobiles, mobility, and aerospace, and they must simultaneously meet the requirements of high energy density for energy storage and high load-bearing capacity. Conventional structural battery technology has struggled to enhance both functions concurrently. However, KAIST researchers have succeeded in developing foundational technology to address this issue. < Photo 1. (From left) Professor Seong Su Kim, PhD candidates Sangyoon Bae and Su Hyun Lim of the Department of Mechanical Engineering > < Photo 2. (From left) Professor Seong Su Kim and Master's Graduate Mohamad A. Raja of KAIST Department of Mechanical Engineering > KAIST (represented by President Kwang Hyung Lee) announced on the 19th of November that Professor Seong Su Kim's team from the Department of Mechanical Engineering has developed a thin, uniform, high-density, multifunctional structural carbon fiber composite battery* capable of supporting loads, and that is free from fire risks while offering high energy density. *Multifunctional structural batteries: Refers to the ability of each material in the composite to simultaneously serve as a load-bearing structure and an energy storage element. Early structural batteries involved embedding commercial lithium-ion batteries into layered composite materials. These batteries suffered from low integration of their mechanical and electrochemical properties, leading to challenges in material processing, assembly, and design optimization, making commercialization difficult. To overcome these challenges, Professor Kim's team explored the concept of "energy-storing composite materials," focusing on interface and curing properties, which are critical in traditional composite design. This led to the development of high-density multifunctional structural carbon fiber composite batteries that maximize multifunctionality. The team analyzed the curing mechanisms of epoxy resin, known for its strong mechanical properties, combined with ionic liquid and carbonate electrolyte-based solid polymer electrolytes. By controlling temperature and pressure, they were able to optimize the curing process. The newly developed structural battery was manufactured through vacuum compression molding, increasing the volume fraction of carbon fibers—serving as both electrodes and current collectors—by over 160% compared to previous carbon-fiber-based batteries. This greatly increased the contact area between electrodes and electrolytes, resulting in a high-density structural battery with improved electrochemical performance. Furthermore, the team effectively controlled air bubbles within the structural battery during the curing process, simultaneously enhancing the battery's mechanical properties. Professor Seong Su Kim, the lead researcher, explained, “We proposed a framework for designing solid polymer electrolytes, a core material for high-stiffness, ultra-thin structural batteries, from both material and structural perspectives. These material-based structural batteries can serve as internal components in cars, drones, airplanes, and robots, significantly extending their operating time with a single charge. This represents a foundational technology for next-generation multifunctional energy storage applications.” < Figure 2. Supplementary cover of ACS Applied Materials & Interfaces > Mohamad A. Raja, a master’s graduate of KAIST’s Department of Mechanical Engineering, participated as the first author of this research, which was published in the prestigious journal ACS Applied Materials & Interfaces on September 10. The paper was recognized for its excellence and selected as a supplementary cover article. (Paper title: “Thin, Uniform, and Highly Packed Multifunctional Structural Carbon Fiber Composite Battery Lamina Informed by Solid Polymer Electrolyte Cure Kinetics.” https://doi.org/10.1021/acsami.4c08698) This research was supported by the National Research Foundation of Korea’s Mid-Career Researcher Program and the National Semiconductor Research Laboratory Development Program.
2024.11.27
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KAIST Office of Global Initiative Hosts 2024 Global Startup Internship Seminar
< Photo of ImpriMed CEO Sungwon Lim’s lecture > The Office of Global Initiative at KAIST successfully hosted the 2024 Global Startup Internship Seminar (GSIS) from Wednesday, November 20, to Friday, November 22. Now in its third year, following the 2022 Global Startup Internship Fair, the GSIS aims to introduce KAIST students to internship opportunities at U.S.-based startups and encourage participation in global internship programs, particularly for students with entrepreneurial aspirations. This year’s seminar featured notable startups including ImpriMed, a precision medical AI company; Klleon, an AI culture tech firm; and Bear Robotics, renowned for its autonomous serving robots. Approximately 80 KAIST students attended the event through prior registration. A key highlight of this year’s seminar was the participation of the CEOs from Bear Robotics and ImpriMed, two prominent Silicon Valley startups. Both CEOs, who had previously participated in the 2024 Global Entrepreneurship Summer School (GESS) last June, offered insights into their companies, provided one-on-one career counseling sessions, and discussed the concept of global entrepreneurship with students interested in U.S. startup internships. In addition to company presentations, the seminar offered practical workshops on resume and email writing tailored for U.S. internships, testimonials from current KAIST students and alumni who interned at Silicon Valley startups, and a J1 Visa Information Session, all aimed at preparing students for internships in the United States. So Young Kim, Vice President of the International Office and Director of the Office of Global Initiative, expressed her hopes for the event, stating, “through this event, KAIST students will be inspired by the global entrepreneurial spirit of mentors who have started businesses abroad, and that it will help further spread a culture of challenging adversity and overcoming the risks of failure.” She further added that KAIST is committed to continuously developing programs that cultivate a global entrepreneurial mindset among its students. The 2024 Global Startup Internship Seminar successfully concluded, providing KAIST students with vision and opportunities in global entrepreneurship.
2024.11.25
View 177
KAIST Secures Core Technology for Ultra-High-Resolution Image Sensors
A joint research team from Korea and the United States has developed next-generation, high-resolution image sensor technology with higher power efficiency and a smaller size compared to existing sensors. Notably, they have secured foundational technology for ultra-high-resolution shortwave infrared (SWIR) image sensors, an area currently dominated by Sony, paving the way for future market entry. KAIST (represented by President Kwang Hyung Lee) announced on the 20th of November that a research team led by Professor SangHyeon Kim from the School of Electrical Engineering, in collaboration with Inha University and Yale University in the U.S., has developed an ultra-thin broadband photodiode (PD), marking a significant breakthrough in high-performance image sensor technology. This research drastically improves the trade-off between the absorption layer thickness and quantum efficiency found in conventional photodiode technology. Specifically, it achieved high quantum efficiency of over 70% even in an absorption layer thinner than one micrometer (μm), reducing the thickness of the absorption layer by approximately 70% compared to existing technologies. A thinner absorption layer simplifies pixel processing, allowing for higher resolution and smoother carrier diffusion, which is advantageous for light carrier acquisition while also reducing the cost. However, a fundamental issue with thinner absorption layers is the reduced absorption of long-wavelength light. < Figure 1. Schematic diagram of the InGaAs photodiode image sensor integrated on the Guided-Mode Resonance (GMR) structure proposed in this study (left), a photograph of the fabricated wafer, and a scanning electron microscope (SEM) image of the periodic patterns (right) > The research team introduced a guided-mode resonance (GMR) structure* that enables high-efficiency light absorption across a wide spectral range from 400 nanometers (nm) to 1,700 nanometers (nm). This wavelength range includes not only visible light but also light the SWIR region, making it valuable for various industrial applications. *Guided-Mode Resonance (GMR) Structure: A concept used in electromagnetics, a phenomenon in which a specific (light) wave resonates (forming a strong electric/magnetic field) at a specific wavelength. Since energy is maximized under these conditions, it has been used to increase antenna or radar efficiency. The improved performance in the SWIR region is expected to play a significant role in developing next-generation image sensors with increasingly high resolutions. The GMR structure, in particular, holds potential for further enhancing resolution and other performance metrics through hybrid integration and monolithic 3D integration with complementary metal-oxide-semiconductor (CMOS)-based readout integrated circuits (ROIC). < Figure 2. Benchmark for state-of-the-art InGaAs-based SWIR pixels with simulated EQE lines as a function of TAL variation. Performance is maintained while reducing the absorption layer thickness from 2.1 micrometers or more to 1 micrometer or less while reducing it by 50% to 70% > The research team has significantly enhanced international competitiveness in low-power devices and ultra-high-resolution imaging technology, opening up possibilities for applications in digital cameras, security systems, medical and industrial image sensors, as well as future ultra-high-resolution sensors for autonomous driving, aerospace, and satellite observation. Professor Sang Hyun Kim, the lead researcher, commented, “This research demonstrates that significantly higher performance than existing technologies can be achieved even with ultra-thin absorption layers.” < Figure 3. Top optical microscope image and cross-sectional scanning electron microscope image of the InGaAs photodiode image sensor fabricated on the GMR structure (left). Improved quantum efficiency performance of the ultra-thin image sensor (red) fabricated with the technology proposed in this study (right) > The results of this research were published on 15th of November, in the prestigious international journal Light: Science & Applications (JCR 2.9%, IF=20.6), with Professor Dae-Myung Geum of Inha University (formerly a KAIST postdoctoral researcher) and Dr. Jinha Lim (currently a postdoctoral researcher at Yale University) as co-first authors. (Paper title: “Highly-efficient (>70%) and Wide-spectral (400 nm -1700 nm) sub-micron-thick InGaAs photodiodes for future high-resolution image sensors”) This study was supported by the National Research Foundation of Korea.
2024.11.22
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KAIST’s RAIBO2 becomes the World’s First Robo-dog to Successfully Complete a Full-course Marathon
KAIST's quadrupedal walking robot "RAIBO", which can run seamlessly on sandy beaches, has now evolved into "RAIBO2"and achieved the groundbreaking milestone by becomeing the world's first quadrupedal robot to successfully complete a full-course marathon in an official event. < Photo 1. A group photo of RAIBO2 and the team after completing the full-course marathon > KAIST (President Kwang Hyung Lee) announced on the 17th of November that Professor Je Min Hwangbo's research team of the Department of Mechanical Engineering participated in the 22nd Sangju Dried-Persimmon Marathon and completed the full-course race (42.195 km) with a time of 4 hours 19 minutes and 52 seconds. < Photo 2. RAIBO2 after completing the full-course marathon with its official record presented on the photo wall > The Sangju Dried Persimmon Marathon is known for its challenging course featuring two 50 m elevation climbs, each at the 14 km and 28 km marks, making it defficult for amateur runners. This made it an especially demanding challenge for the walking robot, as unexpected losses in efficiency could occur. < Photo 3. RAIBO2 with the completion medal around its neck > To prepare RAIBO2, Professor Hwangbo's team developed a walking controller using reinforcement learning algorithms within their proprietary simulation environment "RaiSim". This simulator allowed the team to simlate diverse terrains such as slopes, stairs, and icy roads to ensure stable walking performance. In particular, RAIBO2's high torque transparency joint mechanism enable the robot to efficiently harvest energy on the downhill slopes to regain some of the energy used in climbing up steep hill. In addition, the stability of the robot was greatly improved through the collaboration with RAION ROBOTICS Inc., a company founded by the researchers from Professor Hwangbo’s lab. < Figure 1. Conceptual diagram of power flow employed by the quadrupedal robot > < Figure 2. The process of leg posture change of RAIBO2 walking at the most efficient walking speed of 3 m/s. By reducing the ground contact speed of the feet, the collision energy loss was reduced, and by minimizing the slipperiness of the foot upon contact, the body's kinetic energy was maintained towards the direction of the movement. > Due to the nature of walking, pedal robots must employ highly complex systems that can withstand periodic vibrations from the frequent impacts that occur upon contact with the ground surface. Immediately after development, high efficiency was already recorded in short-distance experiments in the laboratory at the beginning of the year, but the manufacturing technology of RAION ROBOTICS significantly bolstered RAIBO's performance in running safely for a prolonged time of more than 4 hours among random pack of people in an actual marathon. Compared to previous studies on improving walking efficiency, where external parts or software could not be changed and only limited improvements were made in some areas, Professor Hwangbo’s research team cited the fact that they were able to comprehensively solve problems by developing all steps and parts in-house, including mechanism design, electrical design, software, and artificial intelligence, as a key factor in improving efficiency. Following the development of RAIBO1, the research team developed RAIBO2 and optimized all aspects of the robot. In particular, the team integrated the motor driver circuitry directly into the robot to minimize actuator losses and increase the control bandwidth, greatly improving walking efficiency and stability. < Photo 4. RAIBO2 running the full-course marathon along human participants > Choongin Lee, a Ph.D. Student that co-first author of the studies on RAIBO, said, “Through the marathon project, we demonstrated that RAIBO2 has the walking performance to stably execute services such as delivery and patrol in urban environments with many people and random objects,” and “In follow-up research, we will add autonomous navigation functions to RAIBO and strive to achieve the world’s best walking performance in mountainous and disaster environments.” < Photo 5. RAIBO2 and co-first authors of the related research at the Ph.D. program of the Department of Mechanical Engineering at KAIST. (From left) Choongin Lee, Donghoon Youm, and Jeongsoo Park > This research was conducted with the support of Samsung Electronics Future Technology Promotion Center and RAION ROBOTICS Inc.
2024.11.17
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KAIST Unveils New Possibilities for Treating Intractable Brain Tumors
< Photo 1. (From left) Professor Heung Kyu Lee, KAIST Department of Biological Sciences, and Dr. Keun Bon Ku > Immunotherapy, which enhances the immune system's T cell response to eliminate cancer cells, has emerged as a key approach in cancer treatment. However, in the case of glioblastoma, an aggressive and treatment-resistant brain tumor, numerous clinical trials have failed to confirm their efficacy. Korean researchers have recently analyzed the mechanisms that cause T cell exhaustion, which is characterized by a loss of function or a weakened response following prolonged exposure to antigens in such intractable cancers, identifying key control factors in T cell activation and clarifying the mechanisms that enhance therapeutic effectiveness. KAIST (represented by President Kwang Hyung Lee) announced on the 6th of November that Professor Heung Kyu Lee’s team from the Department of Biological Sciences, in collaboration with the Korea Research Institute of Chemical Technology (represented by President Young Kuk Lee), has confirmed improved survival rates in a glioblastoma mouse model. By removing the inhibitory Fc gamma receptor (FcγRIIB), the research team was able to restore the responsiveness of cytotoxic T cells to immune checkpoint inhibitors, leading to enhanced anticancer activity. The research team examined the effect of FcγRIIB, an inhibitory receptor recently found in cytotoxic T cells, on tumor-infiltrating T cells and the therapeutic effectiveness of the anti-PD-1 immune checkpoint inhibitor. < Figure 1. Study results on improved survival rate due to increased antitumor activity of anti-PD-1 treatment in inhibitory Fc gamma receptor(Fcgr2b) ablation mice with murine glioblastoma. > Their findings showed that deleting FcγRIIB induced the increase of tumor antigen-specific memory T cells, which helps to suppress exhaustion, enhances stem-like qualities, and reactivates T cell-mediated antitumor immunity, particularly in response to anti-PD-1 treatment. Furthermore, FcγRIIB deletion led to an increase in antigen-specific memory T cells that maintained continuous infiltration into the tumor tissue. This study presents a new therapeutic target for tumors unresponsive to immune checkpoint inhibitors and demonstrates that combining FcγRIIB inhibition with anti-PD-1 treatment can produce synergistic effects, potentially improving therapeutic outcomes for tumors like glioblastoma, which typically show resistance to anti-PD-1 therapy. < Figure 2. Overview of the study on the enhanced response to anti-PD-1 therapy for glioblastoma brain tumors upon deletion of the inhibitory Fc gamma receptor (FcγRIIB) in tumor microenvironment. When the inhibitory Fc gamma receptor (FcγRIIB) of cytotoxic T cells is deleted, an increase in tumor-specific memory T cells (Ttsms) was observed. In addition, this T cell subset is identified as originating from the tumor-draining lymph nodes(TdLNs) and leads to persistent infiltration into the tumor tissue. Anti-PD-1 therapy leads to an increased anti-tumor immune response via Ttsms, which is confirmed by increased tumor cell toxicity and increased cell division and decreased cell de-migration indices. Ultimately, the increased cytotoxic T cell immune response leads to an increase in the survival rate of glioblastoma. > Professor Heung Kyu Lee explained, "This study offers a way to overcome clinical failures in treating brain tumors with immune checkpoint therapy and opens possibilities for broader applications to other intractable cancers. It also highlights the potential of utilizing cytotoxic T cells for tumor cell therapy." The study, led by Dr. Keun Bon Ku of KAIST (currently a senior researcher at the Korea Research Institute of Chemical Technology's Center for Infectious Disease Diagnosis and Prevention), along with Chae Won Kim, Yumin Kim, Byeong Hoon Kang, Jeongwoo La, In Kang, Won Hyung Park, Stephen Ahn, and Sung Ki Lee, was published online on October 26 in the Journal for ImmunoTherapy of Cancer, an international journal in tumor immunology and therapy from the Society for Immunotherapy of Cancer. (Paper title: “Inhibitory Fcγ receptor deletion enhances CD8 T cell stemness increasing anti-PD-1 therapy responsiveness against glioblastoma,” http://dx.doi.org/10.1136/jitc-2024-009449). This research received support from the National Research Foundation of Korea, the Bio & Medical Technology Development Program, and the Samsung Science & Technology Foundation.
2024.11.15
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KAIST’s Beach-Roaming Quadrupedal Robot “RAIBO” to Run a Marathon!
“RAIBO”, KAIST’s four-legged robot featuring remarkable agility even on challenging terrains like sandy beaches, is now set to be the first in the world to complete a full marathon. < Photo 1. A group photo of the research team of Professor Je Min Hwangbo (second from the right in the front row) of the Department of Mechanical Engineering who participated in the marathon event at 2024 Geumsan Insam Festival last September > On the 17th of November, KAIST (represented by President Kwang Hyung Lee) announced that Professor Je Min Hwangbo’s team from the Department of Mechanical Engineering has developed an upgraded version, “RAIBO2,” which will take on the full 42.195-kilometer course at the "Sangju Dried-Persimmon Marathon". This is over double the previous maximum distance achieved by quadruped robots, which was limited to around 20 kilometers. The KAIST team has successfully developed a robot that can walk continuously for 43 kilometers on a single charge, completing the course in 4 hours and 40 minutes by following a GPS-guided path on the university’s main athletic field. Through this marathon, the team aims to demonstrate RAIBO2’s walking performance in an actual urban environment. Previously, most measurements of walking robots’ travel distances were confined to controlled laboratory conditions or theoretical data. This marathon challenge is thus significant in that the robot will run alongside the general public in a real urban setting, marking the first attempt to validate the practical potential of four-legged robots in real environments. Quadruped robots have shown advantages in challenging terrains, such as ice, sand, and mountainous areas, where they can walk stably. However, limited travel distance and running time have long been obstacles to wider applications. < Figure 1. Conceptual diagram of power flow employed by the quadruped robot > Professor Hwangbo’s team designed every component of the robot, from its actuators to its mechanical structure, to overcome these limitations. Notably, they implemented an efficient walking control system based on reinforcement learning using their proprietary dynamic simulator “RaiSim”. The team also collected and analyzed walking data from outdoor environments, creating a model to address walking losses. This model was then used to iteratively improve walking efficiency over one full year. < Figure 2. The leg posture change process of RAIBO2 walking at the most efficient walking speed of 3 m/s. By reducing the ground contact speed of the feet, the collision energy loss was reduced, and by minimizing the slipperiness of the foot upon contact, the body's kinetic energy was maintained towards the direction of the movement. > This is the team’s second attempt. Their first was during the marathon event at “Geumsan Insam Festival” in September when the robot’s battery ran out at the 37-kilometer mark, falling short of completion. The battery drained 10 kilometers earlier than expected due to frequent speed changes as the robot adjusted to the pacing of other runners on the course. Following the initial attempt, the team focused on technical improvements for a successful finish. They enhanced control efficiency by implementing joint stiffness control directly onto the motor actuator and increased battery capacity by 33% by refining the internal structure. These improvements enabled the robot to cover a maximum distance of 67 kilometers on straight paths. < Figure 3. Data from completing 43 km on a single charge at the main sports field on campus. Left) GPS data of the driving course used during autonomous running. Middle) Covered distance by the hour. Right) Energy consumption by module > Choongin Lee, a Ph.D. student of RAI Lab who is one of the co-first author of this study, explained, “Our comprehensive analysis of walking losses in terms of mechanics, electrical systems, and walking methods was crucial to improving walking efficiency. This research marks an important milestone in extending the operating range of quadruped robots to urban environments.” < Photo 2. A Photo from Practice Run> This research was supported by the Samsung Electronics Future Technology Development Center and RAION ROBOTICS Co., Ltd. < Photo 3. A Photo from Practice Run >
2024.11.15
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KAIST Researchers Suggest an Extraordinary Alternative to Petroleum-based PET - Bacteria!
< (From left) Dr. Cindy Pricilia, Ph.D. Candidate Cheon Woo Moon, Distinguished Professor Sang Yup Lee > Currently, the world is suffering from environmental problems caused by plastic waste. The KAIST research team has succeeded in producing a microbial-based plastic that is biodegradable and can replace existing PET bottles, making it a hot topic. Our university announced on the 7th of November that the research team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering has succeeded in developing a microbial strain that efficiently produces pseudoaromatic polyester monomer to replace polyethylene terephthalate (PET) using systems metabolic engineering. Pseudoaromatic dicarboxylic acids have better physical properties and higher biodegradability than aromatic polyester (PET) when synthesized as polymers, and are attracting attention as an eco-friendly monomer* that can be synthesized into polymers. The production of pseudoaromatic dicarboxylic acids through chemical methods has the problems of low yield and selectivity, complex reaction conditions, and the generation of hazardous waste. *Monomer: A material for making polymers, which is used to synthesize polymers by polymerizing monomers together < Figure. Overview of pseudoaromatic dicarboxylic acid production using metabolically engineered C. glutamicum. > To solve this problem, Professor Sang Yup Lee's research team used metabolic engineering to develop a microbial strain that efficiently produces five types of pseudoaromatic dicarboxylic acids, including 2-pyrone-4,6-dicarboxylic acid and four types of pyridine dicarboxylic acids (2,3-, 2,4-, 2,5-, 2,6-pyridine dicarboxylic acids), in Corynebacterium, a bacterium mainly used for amino acid production. The research team used metabolic engineering techniques to build a platform microbial strain that enhances the metabolic flow of protocatechuic acid, which is used as a precursor for several pseudoaromatic dicarboxylic acids, and prevents the loss of precursors. Based on this, the genetic manipulation target was discovered through transcriptome analysis, producing 76.17 g/L of 2-pyrone-4,6-dicarboxylic acid, and by newly discovering and constructing three types of pyridine dicarboxylic acid production metabolic pathways, successfully producing 2.79 g/L of 2,3-pyridine dicarboxylic acid, 0.49 g/L of 2,4-pyridine dicarboxylic acid, and 1.42 g/L of 2,5-pyridine dicarboxylic acid. In addition, the research team confirmed the production of 15.01 g/L through the construction and reinforcement of the 2,6-pyridine dicarboxylic acid biosynthesis pathway, successfully producing a total of five similar aromatic dicarboxylic acids with high efficiency. In conclusion, the team succeeded in producing 2,4-, 2,5-, and 2,6-pyridine dicarboxylic acids at the world's highest concentration. In particular, 2,4-, 2,5-pyridine dicarboxylic acid achieved production on the scale of g/L, which was previously produced in extremely small amounts (mg/L). Based on this study, it is expected that it will be applied to various polyester production industrial processes, and it is also expected that it will be actively utilized in research on the production of similar aromatic polyesters. Professor Sang Yup Lee, the corresponding author, said, “The significance lies in the fact that we have developed an eco-friendly technology that efficiently produces similar aromatic polyester monomers based on microorganisms,” and “This study will help the microorganism-based bio-monomer industry replace the petrochemical-based chemical industry in the future.” The results of this study were published in the international academic journal, the Proceedings of the National Academy of Sciences of United States of America (PNAS) on October 30th. ※ Paper title: Metabolic engineering of Corynebacterium glutamicum for the production of pyrone and pyridine dicarboxylic acids ※ Author information: Jae Sung Cho (co-first author), Zi Wei Luo (co-first author), Cheon Woo Moon (co-first author), Cindy Prabowo (co-author), Sang Yup Lee (corresponding author) - a total of 5 people This study was conducted with the support of the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project leader: Professor Sang Yup Lee) from the National Research Foundation supported by the Ministry of Science and Technology and ICT of Korea.
2024.11.08
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KAIST Researchers Introduce New and Improved, Next-Generation Perovskite Solar Cell
- KAIST-Yonsei university researchers developed innovative dipole technology to maximize near-infrared photon harvesting efficiency - Overcoming the shortcoming of existing perovskite solar cells that cannot utilize approximately 52% of total solar energy - Development of next-generation solar cell technology with high efficiency and high stability that can absorb near-infrared light beyond the existing visible light range with a perovskite-dipole-organic semiconductor hybrid structure < Photo. (From left) Professor Jung-Yong Lee, Ph.D. candidate Min-Ho Lee, and Master’s candidate Min Seok Kim of the School of Electrical Engineering > Existing perovskite solar cells, which have the problem of not being able to utilize approximately 52% of total solar energy, have been developed by a Korean research team as an innovative technology that maximizes near-infrared light capture performance while greatly improving power conversion efficiency. This greatly increases the possibility of commercializing next-generation solar cells and is expected to contribute to important technological advancements in the global solar cell market. The research team of Professor Jung-Yong Lee of the School of Electrical Engineering at KAIST (President Kwang-Hyung Lee) and Professor Woojae Kim of the Department of Chemistry at Yonsei University announced on October 31st that they have developed a high-efficiency and high-stability organic-inorganic hybrid solar cell production technology that maximizes near-infrared light capture beyond the existing visible light range. The research team suggested and advanced a hybrid next-generation device structure with organic photo-semiconductors that complements perovskite materials limited to visible light absorption and expands the absorption range to near-infrared. In addition, they revealed the electronic structure problem that mainly occurs in the structure and announced a high-performance solar cell device that dramatically solved this problem by introducing a dipole layer*. *Dipole layer: A thin material layer that controls the energy level within the device to facilitate charge transport and forms an interface potential difference to improve device performance. Existing lead-based perovskite solar cells have a problem in that their absorption spectrum is limited to the visible light region with a wavelength of 850 nanometers (nm) or less, which prevents them from utilizing approximately 52% of the total solar energy. To solve this problem, the research team designed a hybrid device that combined an organic bulk heterojunction (BHJ) with perovskite and implemented a solar cell that can absorb up to the near-infrared region. In particular, by introducing a sub-nanometer dipole interface layer, they succeeded in alleviating the energy barrier between the perovskite and the organic bulk heterojunction (BHJ), suppressing charge accumulation, maximizing the contribution to the near-infrared, and improving the current density (JSC) to 4.9 mA/cm². The key achievement of this study is that the power conversion efficiency (PCE) of the hybrid device has been significantly increased from 20.4% to 24.0%. In particular, this study achieved a high internal quantum efficiency (IQE) compared to previous studies, reaching 78% in the near-infrared region. < Figure. The illustration of the mechanism of improving the electronic structure and charge transfer capability through Perovskite/organic hybrid device structure and dipole interfacial layers (DILs). The proposed dipole interfacial layer forms a strong interfacial dipole, effectively reducing the energy barrier between the perovskite and organic bulk heterojunction (BHJ), and suppressing hole accumulation. This technology improves near-infrared photon harvesting and charge transfer, and as a result, the power conversion efficiency of the solar cell increases to 24.0%. In addition, it achieves excellent stability by maintaining performance for 1,200 hours even in an extremely humid environment. > In addition, this device showed high stability, showing excellent results of maintaining more than 80% of the initial efficiency in the maximum output tracking for more than 800 hours even under extreme humidity conditions. Professor Jung-Yong Lee said, “Through this study, we have effectively solved the charge accumulation and energy band mismatch problems faced by existing perovskite/organic hybrid solar cells, and we will be able to significantly improve the power conversion efficiency while maximizing the near-infrared light capture performance, which will be a new breakthrough that can solve the mechanical-chemical stability problems of existing perovskites and overcome the optical limitations.” This study, in which KAIST School of Electrical Engineering Ph.D. candidate Min-Ho Lee and Master's candidate Min Seok Kim participated as co-first authors, was published in the September 30th online edition of the international academic journal Advanced Materials. (Paper title: Suppressing Hole Accumulation Through Sub-Nanometer Dipole Interfaces in Hybrid Perovskite/Organic Solar Cells for Boosting Near-Infrared Photon Harvesting). This study was conducted with the support of the National Research Foundation of Korea.
2024.10.31
View 1237
KAIST Proposes AI Training Method that will Drastically Shorten Time for Complex Quantum Mechanical Calculations
- Professor Yong-Hoon Kim's team from the School of Electrical Engineering succeeded for the first time in accelerating quantum mechanical electronic structure calculations using a convolutional neural network (CNN) model - Presenting an AI learning principle of quantum mechanical 3D chemical bonding information, the work is expected to accelerate the computer-assisted designing of next-generation materials and devices The close relationship between AI and high-performance scientific computing can be seen in the fact that both the 2024 Nobel Prizes in Physics and Chemistry were awarded to scientists for their AI-related research contributions in their respective fields of study. KAIST researchers succeeded in dramatically reducing the computation time for highly sophisticated quantum mechanical computer simulations by predicting atomic-level chemical bonding information distributed in 3D space using a novel AI approach. KAIST (President Kwang-Hyung Lee) announced on the 30th of October that Professor Yong-Hoon Kim's team from the School of Electrical Engineering developed a 3D computer vision artificial neural network-based computation methodology that bypasses the complex algorithms required for atomic-level quantum mechanical calculations traditionally performed using supercomputers to derive the properties of materials. < Figure 1. Various methodologies are utilized in the simulation of materials and materials, such as quantum mechanical calculations at the nanometer (nm) level, classical mechanical force fields at the scale of tens to hundreds of nanometers, continuum dynamics calculations at the macroscopic scale, and calculations that mix simulations at different scales. These simulations are already playing a key role in a wide range of basic research and application development fields in combination with informatics techniques. Recently, there have been active efforts to introduce machine learning techniques to radically accelerate simulations, but research on introducing machine learning techniques to quantum mechanical electronic structure calculations, which form the basis of high-scale simulations, is still insufficient. > The quantum mechanical density functional theory (DFT) calculations using supercomputers have become an essential and standard tool in a wide range of research and development fields, including advanced materials and drug design, as they allow fast and accurate prediction of material properties. *Density functional theory (DFT): A representative theory of ab initio (first principles) calculations that calculate quantum mechanical properties from the atomic level. However, practical DFT calculations require generating 3D electron density and solving quantum mechanical equations through a complex, iterative self-consistent field (SCF)* process that must be repeated tens to hundreds of times. This restricts its application to systems with only a few hundred to a few thousand atoms. *Self-consistent field (SCF): A scientific computing method widely used to solve complex many-body problems that must be described by a number of interconnected simultaneous differential equations. Professor Yong-Hoon Kim’s research team questioned whether recent advancements in AI techniques could be used to bypass the SCF process. As a result, they developed the DeepSCF model, which accelerates calculations by learning chemical bonding information distributed in a 3D space using neural network algorithms from the field of computer vision. < Figure 2. The deepSCF methodology developed in this study provides a way to rapidly accelerate DFT calculations by avoiding the self-consistent field process (orange box) that had to be performed repeatedly in traditional quantum mechanical electronic structure calculations through artificial neural network techniques (green box). The self-consistent field process is a process of predicting the 3D electron density, constructing the corresponding potential, and then solving the quantum mechanical Cohn-Sham equations, repeating tens to hundreds of times. The core idea of the deepSCF methodology is that the residual electron density (δρ), which is the difference between the electron density (ρ) and the sum of the electron densities of the constituent atoms (ρ0), corresponds to chemical bonding information, so the self-consistent field process is replaced with a 3D convolutional neural network model. > The research team focused on the fact that, according to density functional theory, electron density contains all quantum mechanical information of electrons, and that the residual electron density — the difference between the total electron density and the sum of the electron densities of the constituent atoms — contains chemical bonding information. They used this as the target for machine learning. They then adopted a dataset of organic molecules with various chemical bonding characteristics, and applied random rotations and deformations to the atomic structures of these molecules to further enhance the model’s accuracy and generalization capabilities. Ultimately, the research team demonstrated the validity and efficiency of the DeepSCF methodology on large, complex systems. < Figure 3. An example of applying the deepSCF methodology to a carbon nanotube-based DNA sequence analysis device model (top left). In addition to classical mechanical interatomic forces (bottom right), the residual electron density (top right) and quantum mechanical electronic structure properties such as the electronic density of states (DOS) (bottom left) containing information on chemical bonding are rapidly predicted with an accuracy corresponding to the standard DFT calculation results that perform the SCF process. > Professor Yong-Hoon Kim, who supervised the research, explained that his team had found a way to map quantum mechanical chemical bonding information in a 3D space onto artificial neural networks. He noted, “Since quantum mechanical electron structure calculations underpin materials simulations across all scales, this research establishes a foundational principle for accelerating material calculations using artificial intelligence.” Ryong-Gyu Lee, a PhD candidate in the School of Electrical Engineering, served as the first author of this research, which was published online on October 24 in Npj Computational Materials, a prestigious journal in the field of material computation. (Paper title: “Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints”) This research was conducted with support from the KAIST High-Risk Research Program for Graduate Students and the National Research Foundation of Korea’s Mid-career Researcher Support Program.
2024.10.30
View 1085
A KAIST Team Develops Face-Conforming LED Mask Showing 340% Improved Efficacy in Deep Skin Elasticity
- A KAIST research team led by Professor Keon Jae Lee has developed a deep skin-stimulating LED mask which has been verified in clinical trials to improve dermis elasticity by 340%. < Figure 1. Overall concept of face-fit surface-lighting micro-LEDs (FSLED) mask. a. Optical image of the FSLED mask showing uniform surface-lighting. schematic illustration of the FSLED mask. The 2D to 3D transformation procedure b. Difference in cosmetic effect on deep skin elasticity, wrinkles, and sagging between FSLED mask and CLED mask. (improvement percentage in eight weeks) > Conventional LED masks, with their rigid design, fail to conform closely to the skin's contours. This limitation causes substantial light reflection, with up to 90% reflected over a distance of 2 cm, reducing light penetration and limiting stimulation of the deep skin layers essential for effective skin rejuvenation. To address these challenges, Professor Lee's team developed a face-conforming surface lighting micro-LED (FSLED) mask, which can provide uniform photostimulation to the dermis. The key technology lies in the mask's ability to deliver uniform light to deep skin tissues while maintaining a conformal skin attachment. This is achieved through a 3D origami structure, integrated with 3,770 micro-LEDs and flexible surface light-diffusion layer, minimizing the gaps between the light source and the skin. In clinical trials involving 33 participants, the FSLED mask demonstrated a 340% improvement in deep skin elasticity compared to conventional LED masks, proving its efficacy in significantly reducing skin wrinkles, sagging and aging. Professor Keon Jae Lee said, “The FSLED mask provides cosmetic benefits to the entire facial dermis without the side effects of low-temperature burns, making home-care anti-aging treatment that enhances the quality of human life possible. The product is being manufactured by Fronics, KAIST startup company, and will be distributed globally through Amorepacific's network, with sales starting in November.” This result titled “Clinical Validation of Face-fit Surface-lighting Micro Light-emitting Diode Mask for Skin Anti-aging Treatment”, in which Min Seo Kim, a student of the Master-Doctorate integrated program, and Jaehun An, a Ph.D. candidate, in the Department of Materials Science and Engineering of KAIST, took part as co-first authors, was published in Advanced Materials on October 22nd, 2024 (DOI: 10.1002/adma.202411651). Introductory Video: Face-conforming surface LED mask for skin anti-aging ( https://www.youtube.com/watch?v=kSccLwx8N_w )
2024.10.29
View 1476
Team KAIST Crowned Champion for their World’s Best Ironman, Winning their 2nd Consecutive Win at the Cyborg Olympics
< Group photo of our research team participating in the 3rd Cybathlon > The Cybathlon is an international competition, which aims to help overcome disabilities through the use of robotics technology. KAIST researchers came in third, winning the bronze medal, at their 1st participation in 2016, won their first gold medal at the 2nd competition in 2020, and took back the gold medal at this year’s 3rd competition, successfully defending their champion title. KAIST (President Kwang-Hyung Lee) announced on the 28th of October that the wearable robot ‘WalkON Suit F1’ developed by the joint research team of KAIST EXO-Lab, Move Lab, and Angel Robotics, led by Professor Kyoungchul Kong of the Department of Mechanical Engineering (Chairman of Angel Robotics), won gold medal in Cybathlon 2024 held on the 27th. < Seunghwan Kim, the Paraplegic Pilot of Team KAIST, cheering after completing all the missions > Cybathlon is an international competition first held in Switzerland that challenges teams to develop assistive technologies with the purpose of overcoming disabilities, and is also called the Cyborg Olympics. Right after each competition, the missions for the next competition are announced, and research teams from around the world research and develop the right assistive technology for next four years to accomplish the given mission. Aside from the Exoskeleton Race, competitions in a total of eight disciplines are held, including Arm Prosthesis Race, Leg Prosthesis Race, and Wheelchair Race. A total of 71 teams from 26 countries participated in the 3rd Cybathlon event. Professor Kyoungchul Kong’s research team participated in the Exoskeleton Race, the same discipline they took part in the previous competition. The Exoskeleton Race is the highlight of the event that can be called the core of the Cybathlon. In the prosthetic arm or leg events, disabled athletes wearing traditional assistive devices instead of powered devices often win depending more on the ability of the athletes rather than the technology behind the tools. However, the exoskeleton event requires individuals with paraplegic disability to walk completely dependent on the robotic device to perform various missions, so the technical difficulty and the dependence on robotics technology is high. In fact, many teams gave up on participating after seeing the missions for this competition, and more than half of the research teams declared withdrawal during the developmental process. In the end, only six teams from Korea, Thailands, Switzerland, Germany, and the Netherlands participated in the actual competition. Even the research team from the Swiss headquarters declared forfeiture midway as the competition date drew nearer. < Cybathlon 2024 – Exoskeleton Race Mission Description > The reason why many teams gave up in the exoskeleton discipline was because the difficulty of the missions was unusually high. Most research teams have the skills to make paraplegic athletes walk, but there were many other difficult tasks, such as making them walk without crutches or using both hands, while standing free on both legs on the exoskeleton, to cut a lump of sponge block, as in imitating food preparing process. The reason why the difficulty of the missions increased like this is because Professor Kong's research team completed all the missions given to them too quickly in the last competition. In fact, in the last competition, there was even a question asked whether Kim Byeong-Uk (paraplegic) wearing the WalkON Suit F1 was really disabled. Professor Kong's research team developed WalkON Suit F1 to successfully complete the missions. The number of motorized joints increased from six to twelve, and the output of the motor itself was more than doubled compared to the previous model that ran in the competition back in 2020. The 6-channel ground reaction force sensor on the foot measured the robot's balance 1,000 times per second to maintain balance. Cameras were installed to detect obstacles, and an AI board for implementation of AI neural network was also installed. On top of the technologies required to complete the competition missions, a function was implemented that allows the users to wear the robot by themselves and dock on to it right from their wheelchair. In the process, all parts were domestically produced and all basic technologies were internalized. The outer design of the robot was done by Professor Hyunjoon Park of KAIST, and the harmony between people and robots was pursued. In the end, the results of the competition were as expected. The only team that could successfully perform all of the mission tasks, which were originally designed to challenge Professor Kong's research team, was Professor Kong's team. They successfully completed missions such as moving by sidesteps between narrow chairs, moving boxes, walking freely unassisted by crutches, passing through a narrow door and closing it behind, and working on food preparation in the kitchen, recording 6 minutes and 41 seconds to complete all six tasks. The Swiss and Thai teams that took 2nd and 3rd places were all given 10 minutes, but only were able to perform two missions, each earning twenty points. It was an unevenly matched race to begin with. The Cybathlon broadcast team was more surprised and interested in the performance of WalkON Suit F1 than in result of the race. < Team KAIST’s Paraplegic Pilot Seunghwan Kim (left), and Professor Kyoungchul Kong (right) > Researcher Jeongsu Park, the captain of Team KAIST, said, “We came into this competition thinking of it as a competition against ourselves to begin with and focused on showing the technological gap. Now, we are very happy and proud that our endeavors achieved such good result as well.” He added, “We plan to continue to showcase various functions of the WalkON Suit F1 that have not yet been publicly introduced.” Researcher Seunghwan Kim, the paraplegic athlete of the team, said, “I am so touched that I was able to introduce the world’s best wearable robot technology of Korea with my own body.” On a different note, Professor Kong’s research team has successfully commercialized wearable robots through Angel Robotics Co., Ltd. since the 2020 competition. In 2022, they began distributing “ANGEL LEGS M20,” the first wearable robot to be covered by health insurance, and as a result, Angel Robotics Co., Ltd. was successfully listed on KOSDAQ this March. The various know-how and core technologies accumulated while preparing for this competition is to contribute to further development and propagation of wearable robots, provoking imagination to draw on the future of wearable robots and on how it may change our daily lives. Final Match (Self-filmed): https://youtu.be/3ASAtvkiOhw Final Match and Interview (Official Video): https://youtu.be/FSfxOTpDjSE Final Match and Interview (Summary): https://youtu.be/Sb_vd5-3f_0
2024.10.28
View 2204
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