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KAIST Scientifically Identifies a Method to Prevent Dental Erosion from Carbonated Drinks
A Korean research team, which had previously visualized and scientifically proven the harmful effects of carbonated drinks like cola on dental health using nanotechnology, has now identified a mechanism for an effective method to prevent tooth damage caused by these beverages.
KAIST (represented by President Kwang Hyung Lee) announced on the 5th of December that a team led by Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with Seoul National University's School of Dentistry (Departments of Pediatric Dentistry and Oral Microbiology) and Professor Hye Ryung Byon’s research team from the Department of Chemistry, has revealed through nanotechnology that silver diamine fluoride (SDF)* forms a fluoride-containing protective layer on the tooth surface, effectively inhibiting cola-induced erosion.
*SDF (Silver Diamine Fluoride): A dental agent primarily used for the treatment and prevention of tooth decay. SDF strengthens carious lesions, suppresses bacterial growth, and halts the progression of cavities.
The team analyzed the surface morphology and mechanical properties of tooth enamel on a nanoscale using atomic force microscopy (AFM). They also examined the chemical properties of the nano-film formed by SDF treatment using X-ray photoelectron spectroscopy (XPS)* and Fourier-transform infrared spectroscopy (FTIR)*.
*XPS (X-ray Photoelectron Spectroscopy): A powerful surface analysis technique used to investigate the chemical composition and electronic structure of materials.
*FTIR (Fourier-Transform Infrared Spectroscopy): An analytical method that identifies the molecular structure and composition of materials by analyzing how they absorb or transmit infrared light.
The findings showed significant differences in surface roughness and elastic modulus between teeth exposed to cola with and without SDF treatment. Teeth treated with SDF exhibited minimal changes in surface roughness due to erosion (from 64 nm to 70 nm) and maintained a high elastic modulus (from 215 GPa to 205 GPa).
This was attributed to the formation of a fluoroapatite* layer by SDF, which acted as a protective shield.
*Fluoroapatite: A phosphate mineral with the chemical formula Ca₅(PO₄)₃F (calcium fluoro-phosphate). It can occur naturally or be synthesized biologically/artificially and plays a crucial role in strengthening teeth and bones.
< Figure 1. Schematic of the workflow. Surface morphology and mechanical properties of untreated and treated silver diamine fluoride (SDF) treated enamel exposed to cola were analyzed over time using atomic force microscopy (AFM). >
Professor Young J. Kim from Seoul National University's Department of Pediatric Dentistry noted, "This technology could be applied to prevent dental erosion and strengthen teeth for both children and adults. It is a cost-effective and accessible dental treatment."
< Figure 2. Changes in surface roughness and elastic modulus according to time of exposure to cola for SDF untreated and treated teeth. After 1 hour, the surface roughness of the SDF untreated teeth rapidly became rougher from 83 nm to 287 nm and the elastic modulus weakened from 125 GPa to 13 GPa, whereas the surface roughness of the SDF treated teeth changed only slightly from 64 nm to 70 nm and the elastic modulus barely changed from 215 GPa to 205 GPa, maintaining a similar state to the initial state. >
Professor Seungbum Hong emphasized, "Dental health significantly impacts quality of life. This research offers an effective non-invasive method to prevent early dental erosion, moving beyond traditional surgical treatments. By simply applying SDF, dental erosion can be prevented and enamel strengthened, potentially reducing pain and costs associated with treatment."
This study, led by the first author Aditi Saha, a PhD student in KAIST’s Department of Materials Science and Engineering, was published in the international journal Biomaterials Research on November 7 under the title "Nanoscale Study on Noninvasive Prevention of Dental Erosion of Enamel by Silver Diamine Fluoride". The research was supported by the National Research Foundation of Korea.
2024.12.11 View 2430 -
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 View 2993 -
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 1363 -
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 View 2786 -
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 View 2806 -
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 View 5610 -
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 4239 -
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 3278 -
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 4241 -
KAIST Professor Uichin Lee Receives Distinguished Paper Award from ACM
< Photo. Professor Uichin Lee (left) receiving the award >
KAIST (President Kwang Hyung Lee) announced on the 25th of October that Professor Uichin Lee’s research team from the School of Computing received the Distinguished Paper Award at the International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computing (Ubicomp / ISWC) hosted by the Association for Computing Machinery (ACM) in Melbourne, Australia on October 8.
The ACM Ubiquitous Computing Conference is the most prestigious international conference where leading universities and global companies from around the world present the latest research results on ubiquitous computing and wearable technologies in the field of human-computer interaction (HCI).
The main conference program is composed of invited papers published in the Proceedings of the ACM (PACM) on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), which covers the latest research in the field of ubiquitous and wearable computing.
The Distinguished Paper Award Selection Committee selected eight papers among 205 papers published in Vol. 7 of the ACM Proceedings (PACM IMWUT) that made outstanding and exemplary contributions to the research community. The committee consists of 16 prominent experts who are current and former members of the journal's editorial board which made the selection after a rigorous review of all papers for a period that stretched over a month.
< Figure 1. BeActive mobile app to promote physical activity to form active lifestyle habits >
The research that won the Distinguished Paper Award was conducted by Dr. Junyoung Park, a graduate of the KAIST Graduate School of Data Science, as the 1st author, and was titled “Understanding Disengagement in Just-in-Time Mobile Health Interventions”
Professor Uichin Lee’s research team explored user engagement of ‘Just-in-Time Mobile Health Interventions’ that actively provide interventions in opportune situations by utilizing sensor data collected from health management apps, based on the premise that these apps are aptly in use to ensure effectiveness.
< Figure 2. Traditional user-requested digital behavior change intervention (DBCI) delivery (Pull) vs. Automatic transmission (Push) for Just-in-Time (JIT) mobile DBCI using smartphone sensing technologies >
The research team conducted a systematic analysis of user disengagement or the decline in user engagement in digital behavior change interventions. They developed the BeActive system, an app that promotes physical activities designed to help forming active lifestyle habits, and systematically analyzed the effects of users’ self-control ability and boredom-proneness on compliance with behavioral interventions over time.
The results of an 8-week field trial revealed that even if just-in-time interventions are provided according to the user’s situation, it is impossible to avoid a decline in participation. However, for users with high self-control and low boredom tendency, the compliance with just-in-time interventions delivered through the app was significantly higher than that of users in other groups.
In particular, users with high boredom proneness easily got tired of the repeated push interventions, and their compliance with the app decreased more quickly than in other groups.
< Figure 3. Just-in-time Mobile Health Intervention: a demonstrative case of the BeActive system: When a user is identified to be sitting for more than 50 mins, an automatic push notification is sent to recommend a short active break to complete for reward points. >
Professor Uichin Lee explained, “As the first study on user engagement in digital therapeutics and wellness services utilizing mobile just-in-time health interventions, this research provides a foundation for exploring ways to empower user engagement.” He further added, “By leveraging large language models (LLMs) and comprehensive context-aware technologies, it will be possible to develop user-centered AI technologies that can significantly boost engagement."
< Figure 4. A conceptual illustration of user engagement in digital health apps. Engagement in digital health apps consists of (1) engagement in using digital health apps and (2) engagement in behavioral interventions provided by digital health apps, i.e., compliance with behavioral interventions. Repeated adherences to behavioral interventions recommended by digital health apps can help achieve the distal health goals. >
This study was conducted with the support of the 2021 Biomedical Technology Development Program and the 2022 Basic Research and Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT.
< Figure 5. A conceptual illustration of user disengagement and engagement of digital behavior change intervention (DBCI) apps. In general, user engagement of digital health intervention apps consists of two components: engagement in digital health apps and engagement in behavioral interventions recommended by such apps (known as behavioral compliance or intervention adherence). The distinctive stages of user can be divided into adoption, abandonment, and attrition. >
< Figure 6. Trends of changes in frequency of app usage and adherence to behavioral intervention over 8 weeks, ● SC: Self-Control Ability (High-SC: user group with high self-control, Low-SC: user group with low self-control) ● BD: Boredom-Proneness (High-BD: user group with high boredom-proneness, Low-BD: user group with low boredom-proneness). The app usage frequencies were declined over time, but the adherence rates of those participants with High-SC and Low-BD were significantly higher than other groups. >
2024.10.25 View 4284 -
KAIST Introduces a Wearable Robot that Walks and Puts itself on to Disabled Persons
< Photo 1. WalkON Suit F1 - walking demonstration >
KAIST researchers have unveiled a new wearable robot developed for completely paralyzed persons that can walk to them so that the user can wear it right out of their wheelchairs without the help from others. Also, it was announced that Professor Kyoungchul Kong's team from KAIST will be participating in the wearable robot category of the 3rd Cybathlon, which is being held four years after the team’s gold medal win in 2020.
KAIST (President Kwang-Hyung Lee) announced this new version of the wearable robot for paraplegic people, WalkON Suit F1, by Professor Kyoungchul Kong (CEO and founder of Angel Robotics) of KAIST Department of Mechanical Engineering on the 24th of October.
< Photo 2. (From left) Professor Kyoungchul Kong of the Department of Mechanical Engineering, Researcher Seunghwan Kim (the competing athlete), and PhD candidate Jeongsu Park (the leader of Team KAIST) >
WalkON Suit is a wearable robot for people suffering with paraplegic disabilities that the research team has been continuously researching since 2015. This robot targets to assist persons with American Spinal Injury Association (ASIA) Impairment Scale – A (complete paralysis) grade injury, the most severe level of paraplegia. Therefore, its development purpose is different from that of other rehabilitation therapy and muscle strength assisting robots currently being supplied nationally by Angel Robotics.
Professor Kong's research team first announced WalkON Suit 1 in 2016, and then introduced WalkON Suit 4 in 2020, increasing the walking speed to 3.2 km/h, achieving the normal walking speed of people with no disabilities. In addition, it demonstrated the ability to pass through obstacles such as narrow passages, doors, and stairs that can be encountered in daily life.
However, it had the same fundamental problem all wearable robots have, which is that they require the help of others to wear the robot. While you can walk without help from others once you are wearing the robot, you needed someone's help to put it on to begin with.
The newly released WalkON Suit F1 presented a technical solution to this fundamental problem. It applied a frontal-docking method instead of a rear-sitting method so that you can wear the robot right away without getting out of the wheelchair and into the robot, which would require help from others mid-transition.
< Photo 3. WalkON Suit F1 - suiting-up demonstration >
In addition, before wearing the robot, it can walk on its own like a humanoid robot and approaches the user. It is also implemented a function that actively controls the center of its weight against the pull of gravity so that it maintains balance without falling over even if the user pushes the robot otherwise. The outer design of the WalkON Suit F1, which crosses between a humanoid and a wearable robot, was done by Professor Hyunjoon Park of the Department of Industrial Design at KAIST.
The original function of the wearable robot has also been greatly improved. The performance of the balance control was improved to allow the free use of both hands in upright state, as well as the freedom to take several steps without a cane.
Technological advancements at the components level are also noteworthy. Through close collaboration with Angel Robotics, all core components of the robot, such as the motor, reducer, motor driver, and main circuit, have been domestically produced. The output density of the motor and reducer modules has been improved by about two folds (based on power per weight) compared to the research team's existing technology, and the control performance of the motor driver has been improved by about three times (based on frequency response speed) compared to the best overseas technology.
In particular, the embedded software technology of the motor driver has been significantly improved so that advanced motion control algorithms can be stably implemented without using expensive higher-level controllers. In addition, visual recognition system for obstacle detection and an AI board for neural network application have been installed.
< Figure 1. WalkON Suit F1 shape and main specifications >
Professor Kong explained, “WalkON Suit is the culmination of wearable robot technology for the disabled,” and added, “The numerous components, control, and module technologies derived from WalkON Suit are setting the standard for the entire wearable robot industry.”
Professor Kong’s research team revealed WalkON Suit F1 and announced that they will be participating in the 3rd Cybathlon, which is being held after four years since the last event. In this competition, which will be held on October 27, Professor Kong’s lab, the Exo Lab will be participating with Jeongsu Park, a Ph.D. Student, as the leader and Seunghwan Kim, the lab’s staff researcher with complete paralysis, as the competing athlete.
The difficulty of the missions in this competition has been significantly increased compared to the previous competition, and the number of missions has increased from six to ten. Some missions have been criticized for being overly challenging, going beyond the level that can be encountered in everyday life.
< Photo 4. Cybathlon stadium (Angel Robotics Asia Hub) >
Regarding this, the team leader Jeongsu Park expressed his ambition, saying, “Since we already won first place in the previous competition, our goal in this competition is to show the technological gap rather than competing for rankings.”
The Cybathlon is a cyborg Olympics held every four years in Switzerland. This competition will be held in a hybrid format, with some participants taking part in Switzerland while others broadcasting live from stadiums in their own country on October 27. Professor Kong's research team will be participating via live broadcast from the competition facilities installed in Angel Robotics' Advanced Research Institute (Planet Daejeon).
< Photo 5. Photo of Team KAIST participating in Cybathlon 2024 >
The demonstration video of WalkON Suit F1 can be viewed through the link below.
Link: https://www.youtube.com/@KyoungchulKong_EXO-Lab
2024.10.24 View 8377 -
KAIST Develops a Fire-risk Free Self-Powered Hydrogen Production System
KAIST researchers have developed a new hydrogen production system that overcomes the current limitations of green hydrogen production. By using a water-splitting system with an aqueous electrolyte, this system is expected to block fire risks and enable stable hydrogen production.
KAIST (represented by President Kwang Hyung Lee) announced on the 22nd of October that a research team led by Professor Jeung Ku Kang from the Department of Materials Science and Engineering developed a self-powered hydrogen production system based on a high-performance zinc-air battery*.
*Zinc-air battery: A primary battery that absorbs oxygen from the air and uses it as an oxidant. Its advantage is long life, but its low electromotive force is a disadvantage.
Hydrogen (H₂) is a key raw material for synthesizing high-value-added substances, and it is gaining attention as a clean fuel with an energy density (142 MJ/kg) more than three times higher than traditional fossil fuels (gasoline, diesel, etc.). However, most current hydrogen production methods impose environmental burden as they emit carbon dioxide (CO₂).
While green hydrogen can be produced by splitting water using renewable energy sources such as solar cells and wind power, these sources are subject to irregular power generation due to weather and temperature fluctuations, leading to low water-splitting efficiency.
To overcome this, air batteries that can emit sufficient voltage (greater than 1.23V) for water splitting have been gaining attention. However, achieving sufficient capacity requires expensive precious metal catalysts and the performance of the catalyst materials becomes significantly degraded during prolonged charge and discharge cycles. Thus, it is essential to develop catalysts that are effective for the water-splitting reactions (oxygen and hydrogen evolution) and materials that can stabilize the repeated charge and discharge reactions (oxygen reduction and evolution) in zinc-air battery electrodes.
In response, Professor Kang's research team proposed a method to synthesize a non-precious metal catalyst material (G-SHELL) that is effective for three different catalytic reactions (oxygen evolution, hydrogen evolution, and oxygen reduction) by growing nano-sized, metal-organic frameworks on graphene oxide.
The team incorporated the developed catalyst material into the air cathode of a zinc-air battery, confirming that it achieved approximately five times higher energy density (797Wh/kg), high power characteristics (275.8mW/cm²), and long-term stability even under repeated charge and discharge conditions compared to conventional batteries.
Additionally, the zinc-air battery, which operates using an aqueous electrolyte, is safe from fire risks. It is expected that this system can be applied as a next-generation energy storage device when linked with water electrolysis systems, offering an environmentally friendly method for hydrogen production.
< Figure 1. Illustrations of a trifunctional graphene-sandwiched heterojunction-embedded layered lattice (G-SHELL) structure. Schematic representation of a) synthesis procedures of G-SHELL from a zeolitic imidazole framework, b) hollow core-layered shell structure with trifunctional sites for oxygen reduction evolution (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER), and c) heterojunctions, eterojunction-induced internal electric fields, and the corresponding band structure. >
Professor Kang explained, "By developing a catalyst material with high activity and durability for three different electrochemical catalytic reactions at low temperatures using simple methods, the self-powered hydrogen production system we implemented based on zinc-air batteries presents a new breakthrough to overcome the current limitations of green hydrogen production."
<Figure 2. Electrochemical performance of a ZAB-driven water-splitting cell with G-SHELL. Diagram of a self-driven water-splitting cell integrated by combining a ZAB with an alkaline water electrolyzer.>
PhD candidate Dong Won Kim and Jihoon Kim, a master's student in the Department of Materials Science and Engineering at KAIST, were co-first authors of this research, which was published in the international journal Advanced Science on September 17th in the multidisciplinary field of materials science. (Paper Title: “Trifunctional Graphene-Sandwiched Heterojunction-Embedded Layered Lattice Electrocatalyst for High Performance in Zn-Air Battery-Driven Water Splitting”)
This research was supported by the Nano and Material Technology Development Program of the Ministry of Science and ICT and the National Research Foundation of Korea’s Future Technology Research Laboratory.
2024.10.22 View 3337