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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 791 -
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 947 -
KAIST Develops Thread-like, Flexible Thermoelectric Materials Applicable in Extreme Environments
A team of Korean researchers developed a thermoelectric material that can be used in wearable devices, such as smart clothing, and while maintaining stable thermal energy performance even in extreme environments. It has dramatically resolved the dilemma of striking the balance between achieving good performance and the mechanical flexibility of thermoelectric materials, which has been a long-standing challenge in the field of thermoelectric materials, and has also proven the possibility of commercialization.
KAIST (President Kwang-Hyung Lee) announced on the 21st that a joint research team of Professor Yeon Sik Jung of the Department of Materials Science and Engineering and Professor Inkyu Park of the Department of Mechanical Engineering, in collaboration with the research teams of Professor Min-Wook Oh of Hanbat National University (President Yong Jun Oh) and Dr. Jun-Ho Jeong of the Korea Institute of Machinery and Materials (President Seoghyun Ryu), have successfully developed ‘bismuth telluride (Bi2Te3) thermoelectric fibers,’ an innovative energy harvesting solution for next-generation flexible electronic devices.
Thermoelectric materials are materials that generate voltage when there is a temperature difference and convert thermal energy into electrical energy. Currently, about 70% of energy being lost as wasted heat, so due attention is being given to research on these as sustainable energy materials that can recover and harvesting energy from this waste heat.
Most of the heat sources around us are curved, such as the human body, vehicle exhaust pipes, and cooling fins. Inorganic thermoelectric materials based on ceramic materials boast high thermoelectric performance, but they are fragile and difficult to produce in curved shapes. On the other hand, flexible thermoelectric materials using existing polymer binders can be applied to surfaces of various shapes, but their performance was limited due to the low electrical conductivity and high thermal resistance of the polymer.
Existing flexible thermoelectric materials contain polymer additives, but the inorganic thermoelectric material developed by the research team is not flexible, so they overcame these limitations by twisting nano ribbons instead of additives to produce a thread-shaped thermoelectric material. Inspired by the flexibility of inorganic nano ribbons, the research team used a nanomold-based electron beam deposition technique to continuously deposit nano ribbons and then twisted them into a thread shape to create bismuth telluride (Bi2Te3) inorganic thermoelectric fibers.
These inorganic thermoelectric fibers have higher bending strength than existing thermoelectric materials, and showed almost no change in electrical properties even after repeated bending and tensile tests of more than 1,000 times. The thermoelectric device created by the research team generates electricity using temperature differences, and if clothes are made with fiber-type thermoelectric devices, electricity can be generated from body temperature to operate other electronic devices.
< Figure 1. Schematic diagram and actual image of the all-inorganic flexible thermoelectric yarn made without polymer additives >
In fact, the possibility of commercialization was proven through a demonstration of collecting energy by embedding thermoelectric fibers in life jackets or clothing. In addition, it opened up the possibility of building a high-efficiency energy harvesting system that recycles waste heat by utilizing the temperature difference between the hot fluid inside a pipe and the cold air outside in industrial settings.
Professor Yeon Sik Jung said, "The inorganic flexible thermoelectric material developed in this study can be used in wearable devices such as smart clothing, and it can maintain stable performance even in extreme environments, so it has a high possibility of being commercialized through additional research in the future." Professor Inkyu Park also emphasized, "This technology will become the core of next-generation energy harvesting technology, and it is expected to play an important role in various fields from waste heat utilization in industrial sites to personal wearable self-power generation devices."
This study, in which Hanhwi Jang, a Ph.D. student at KAIST's Department of Materials Science and Engineering, Professor Junseong Ahn of Korea University, Sejong Campus, and Dr. Yongrok Jeong of Korea Atomic Energy Research Institute contributed equally as joint first authors, was published in the online edition of the international academic journal Advanced Materials on September 17, and was selected as the back-cover paper in recognition of its excellence. (Paper title: Flexible All-Inorganic Thermoelectric Yarns)
Meanwhile, this study was conducted through the Mid-career Researcher Support Program and the Future Materials Discovery Program of the National Research Foundation of Korea, and the support from the Global Bio-Integrated Materials Center, the Ministry of Trade, Industry and Energy, and the Korea Institute of Industrial Technology Evaluation and Planning (KEIT) upon the support by the Ministry of Science and ICT.
2024.10.21 View 808 -
KAIST Develops Technology for the Precise Diagnosis of Electric Vehicle Batteries Using Small Currents
Accurately diagnosing the state of electric vehicle (EV) batteries is essential for their efficient management and safe use. KAIST researchers have developed a new technology that can diagnose and monitor the state of batteries with high precision using only small amounts of current, which is expected to maximize the batteries’ long-term stability and efficiency.
KAIST (represented by President Kwang Hyung Lee) announced on the 17th of October that a research team led by Professors Kyeongha Kwon and Sang-Gug Lee from the School of Electrical Engineering had developed electrochemical impedance spectroscopy (EIS) technology that can be used to improve the stability and performance of high-capacity batteries in electric vehicles.
EIS is a powerful tool that measures the impedance* magnitude and changes in a battery, allowing the evaluation of battery efficiency and loss. It is considered an important tool for assessing the state of charge (SOC) and state of health (SOH) of batteries. Additionally, it can be used to identify thermal characteristics, chemical/physical changes, predict battery life, and determine the causes of failures. *Battery Impedance: A measure of the resistance to current flow within the battery that is used to assess battery performance and condition.
However, traditional EIS equipment is expensive and complex, making it difficult to install, operate, and maintain. Moreover, due to sensitivity and precision limitations, applying current disturbances of several amperes (A) to a battery can cause significant electrical stress, increasing the risk of battery failure or fire and making it difficult to use in practice.
< Figure 1. Flow chart for diagnosis and prevention of unexpected combustion via the use of the electrochemical impedance spectroscopy (EIS) for the batteries for electric vehicles. >
To address this, the KAIST research team developed and validated a low-current EIS system for diagnosing the condition and health of high-capacity EV batteries. This EIS system can precisely measure battery impedance with low current disturbances (10mA), minimizing thermal effects and safety issues during the measurement process.
In addition, the system minimizes bulky and costly components, making it easy to integrate into vehicles. The system was proven effective in identifying the electrochemical properties of batteries under various operating conditions, including different temperatures and SOC levels.
Professor Kyeongha Kwon (the corresponding author) explained, “This system can be easily integrated into the battery management system (BMS) of electric vehicles and has demonstrated high measurement accuracy while significantly reducing the cost and complexity compared to traditional high-current EIS methods. It can contribute to battery diagnosis and performance improvements not only for electric vehicles but also for energy storage systems (ESS).”
This research, in which Young-Nam Lee, a doctoral student in the School of Electrical Engineering at KAIST participated as the first author, was published in the prestigious international journal IEEE Transactions on Industrial Electronics (top 2% in the field; IF 7.5) on September 5th. (Paper Title: Small-Perturbation Electrochemical Impedance Spectroscopy System With High Accuracy for High-Capacity Batteries in Electric Vehicles, Link: https://ieeexplore.ieee.org/document/10666864)
< Figure 2. Impedance measurement results of large-capacity batteries for electric vehicles. ZEW (commercial EW; MP10, Wonatech) versus ZMEAS (proposed system) >
This research was supported by the Basic Research Program of the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Program of the Korea Evaluation Institute of Industrial Technology, and the AI Semiconductor Graduate Program of the Institute of Information & Communications Technology Planning & Evaluation.
2024.10.17 View 1241 -
KAIST Demonstrates AI and sustainable technologies at CES 2024
On January 2, KAIST announced it will be participating in the Consumer Electronics Show (CES) 2024, held between January 9 and 12.
CES 2024 is one of the world’s largest tech conferences to take place in Las Vegas. Under the slogan “KAIST, the Global Value Creator” for its exhibition, KAIST has submitted technologies falling under one of following themes: “Expansion of Human Intelligence, Mobility, and Reality”, and “Pursuit of Human Security and Sustainable Development”.
24 startups and pre-startups whose technologies stand out in various fields including artificial intelligence (AI), mobility, virtual reality, healthcare and human security, and sustainable development, will welcome their visitors at an exclusive booth of 232 m2 prepared for KAIST at Eureka Park in Las Vegas.
12 businesses will participate in the first category, “Expansion of Human Intelligence, Mobility, and Reality”, including MicroPix, Panmnesia, DeepAuto, MGL, Reports, Narnia Labs, EL FACTORY, Korea Position Technology, AudAi, Planby Technologies, Movin, and Studio Lab.
In the “Pursuit of Human Security and Sustainable Development” category, 12 businesses including Aldaver, ADNC, Solve, Iris, Blue Device, Barreleye, TR, A2US, Greeners, Iron Boys, Shard Partners and Kingbot, will be introduced.
In particular, Aldaver is a startup that received the Korean Business Award 2023 as well as the presidential award at the Challenge K-Startup with its biomimetic material and printing technology. It has attracted 4.5 billion KRW of investment thus far.
Narnia Labs, with its AI design solution for manufacturing, won the grand prize for K-tech Startups 2022, and has so far attracted 3.5 billion KRW of investments.
Panmnesia is a startup that won the 2024 CES Innovation Award, recognized for their fab-less AI semiconductor technology. They attracted 16 billion KRW of investment through seed round alone.
Meanwhile, student startups will also be presented during the exhibition. Studio Lab received a CES 2024 Best of Innovation Award in the AI category. The team developed the software Seller Canvas, which automatically generates a page for product details when a user uploads an image of a product.
The central stage at the KAIST exhibition booth will be used to interview members of the participating startups between Jan 9 to 11, as well as a networking site for businesses and invited investors during KAIST NIGHT on the evening of 10th, between 5 and 7 PM.
Director Sung-Yool Choi of the KAIST Institute of Technology Value Creation said, “Through CES 2024, KAIST will overcome the limits of human intelligence, mobility, and space with the deep-tech based technologies developed by its startups, and will demonstrate its achievements for realizing its vision as a global value-creating university through the solutions for human security and sustainable development.”
2024.01.05 View 5164 -
KAIST proposes alternatives to chemical factories through “iBridge”
- A computer simulation program “iBridge” was developed at KAIST that can put together microbial cell factories quickly and efficiently to produce cosmetics and food additives, and raw materials for nylons
- Eco-friendly and sustainable fermentation process to establish an alternative to chemical plants
As climate change and environmental concerns intensify, sustainable microbial cell factories garner significant attention as candidates to replace chemical plants. To develop microorganisms to be used in the microbial cell factories, it is crucial to modify their metabolic processes to induce efficient target chemical production by modulating its gene expressions. Yet, the challenge persists in determining which gene expressions to amplify and suppress, and the experimental verification of these modification targets is a time- and resource-intensive process even for experts. The challenges were addressed by a team of researchers at KAIST (President Kwang-Hyung Lee) led by Distinguished Professor Sang Yup Lee.
It was announced on the 9th by the school that a method for building a microbial factory at low cost, quickly and efficiently, was presented by a novel computer simulation program developed by the team under Professor Lee’s guidance, which is named “iBridge”. This innovative system is designed to predict gene targets to either overexpress or downregulate in the goal of producing a desired compound to enable the cost-effective and efficient construction of microbial cell factories specifically tailored for producing the chemical compound in demand from renewable biomass.
Systems metabolic engineering is a field of research and engineering pioneered by KAIST’s Distinguished Professor Sang Yup Lee that seeks to produce valuable compounds in industrial demands using microorganisms that are re-configured by a combination of methods including, but not limited to, metabolic engineering, synthetic biology, systems biology, and fermentation engineering.
In order to improve microorganisms’ capability to produce useful compounds, it is essential to delete, suppress, or overexpress microbial genes. However, it is difficult even for the experts to identify the gene targets to modify without experimental confirmations for each of them, which can take up immeasurable amount of time and resources.
The newly developed iBridge identifies positive and negative metabolites within cells, which exert positive and/or negative impact on formation of the products, by calculating the sum of covariances of their outgoing (consuming) reaction fluxes for a target chemical. Subsequently, it pinpoints "bridge" reactions responsible for converting negative metabolites into positive ones as candidates for overexpression, while identifying the opposites as targets for downregulation.
The research team successfully utilized the iBridge simulation to establish E. coli microbial cell factories each capable of producing three of the compounds that are in high demands at a production capacity that has not been reported around the world. They developed E. coli strains that can each produce panthenol, a moisturizing agent found in many cosmetics, putrescine, which is one of the key components in nylon production, and 4-hydroxyphenyllactic acid, an anti-bacterial food additive. In addition to these three compounds, the study presents predictions for overexpression and suppression genes to construct microbial factories for 298 other industrially valuable compounds.
Dr. Youngjoon Lee, the co-first author of this paper from KAIST, emphasized the accelerated construction of various microbial factories the newly developed simulation enabled. He stated, "With the use of this simulation, multiple microbial cell factories have been established significantly faster than it would have been using the conventional methods. Microbial cell factories producing a wider range of valuable compounds can now be constructed quickly using this technology."
Professor Sang Yup Lee said, "Systems metabolic engineering is a crucial technology for addressing the current climate change issues." He added, "This simulation could significantly expedite the transition from resorting to conventional chemical factories to utilizing environmentally friendly microbial factories."
< Figure. Conceptual diagram of the flow of iBridge simulation >
The team’s work on iBridge is described in a paper titled "Genome-Wide Identification of Overexpression and Downregulation Gene Targets Based on the Sum of Covariances of the Outgoing Reaction Fluxes" written by Dr. Won Jun Kim, and Dr. Youngjoon Lee of the Bioprocess Research Center and Professors Hyun Uk Kim and Sang Yup Lee of the Department of Chemical and Biomolecular Engineering of KAIST. The paper was published via peer-review on the 6th of November on “Cell Systems” by Cell Press.
This research was conducted with the support from the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project (Project Leader: Distinguished Professor Sang Yup Lee, KAIST) and Development of Platform Technology for the Production of Novel Aromatic Bioplastic using Microbial Cell Factories Project (Project Leader: Research Professor So Young Choi, KAIST) of the Korean Ministry of Science and ICT.
2023.11.09 View 4335 -
A KAIST Research Team Develops a Smart Color-Changing Flexible Battery with Ultra-high Efficiency
With the rapid growth of the smart and wearable electronic devices market, smart next-generation energy storage systems that have energy storage functions as well as additional color-changing properties are receiving a great deal of attention. However, existing electrochromic devices have low electrical conductivity, leading to low efficiency in electron and ion mobility, and low storage capacities. Such batteries have therefore been limited to use in flexible and wearable devices.
On August 21, a joint research team led by Professor Il-Doo Kim from the KAIST Department of Materials Science and Engineering (DMSE) and Professor Tae Gwang Yun from the Myongji University Department of Materials Science and Engineering announced the development of a smart electrochromic Zn-ion battery that can visually represent its charging and discharging processes using an electrochromic polymer anode incorporated with a “π-bridge spacer”, which increases electron and ion mobility efficiency.
Batteries topped with electrochromic properties are groundbreaking inventions that can visually represent their charged and discharged states using colors, and can be used as display devices that cut down energy consumption for indoor cooling by controlling solar absorbance. The research team successfully built a flexible and electrochromic smart Zn-ion battery that can maintain its excellent electrochromic and electrochemical properties, even under long-term exposure to the atmosphere and mechanical deformations.
< Figure 1. Electrochromic zinc ion battery whose anode is made of a polymer that turns dark blue when charged and transparent when discharged. >
To maximize the efficiency of electron and ion mobility, the team modelled and synthesized the first π-bridge spacer-incorporated polymer anode in the world. π-bonds can improve the mobility of electrons within a structure to speed up ion movement and maximize ion adsorption efficiency, which improves its energy storage capacity.
In anode-based batteries with a π-bridge spacer, the spacer provides room for quicker ion movement. This allows fast charging, an improved zinc-ion discharging capacity of 110 mAh/g, which is 40% greater than previously reported, and a 30% increase in electrochromic function that switches from dark blue to transparent when the device is charged/discharged. In addition, should the transparent flexible battery technology be applied to smart windows, they would display darker colors during the day while they absorb solar energy, and function as a futuristic energy storage technique that can block out UV radiation and replace curtains.
< Figure 2. A schematic diagram of the structure of the electrochromic polymer with π-π spacer and the operation of a smart flexible battery using this cathode material. >
< Figure 3. (A) Density Functional Theory (DFT) theory-based atomic and electronic structure analysis. (B) Comparison of rate characteristics for polymers with and without π-bridge spacers. (C) Electrochemical performance comparison graph with previously reported zinc ion batteries. The anode material, which has an electron donor-acceptor structure with a built-in π-bridge spacer, shows better electrochemical performance and electrochromic properties than existing zinc ion batteries and electrochromic devices. >
Professor Il-Doo Kim said, “We have developed a polymer incorporated with a π-bridge spacer and successfully built a smart Zn-ion battery with excellent electrochromic efficiency and high energy storage capacity.” He added, “This technique goes beyond the existing concept of batteries that are used simply as energy storage devices, and we expect this technology to be used as a futuristic energy storage system that accelerates innovation in smart batteries and wearable technologies.”
This research, co-first authored by the alums of KAIST Departments of Material Sciences of Engineering, Professor Tae Gwang Yun of Myongji University, Dr. Jiyoung Lee, a post-doctoral associate at Northwestern University, and Professor Han Seul Kim at Chungbuk National University, was published as an inside cover article for Advanced Materials on August 3 under the title, “A π-Bridge Spacer Embedded Electron Donor-Acceptor Polymer for Flexible Electrochromic Zn-Ion Batteries”.
< Figure 4. Advanced Materials Inside Cover (August Issue) >
This research was supported by the Nanomaterial Technology Development Project under the Korean Ministry of Science and ICT, the Nano and Material Technology Development Project under the National Research Foundation of Korea, the Successive Academic Generation Development Project under the Korean Ministry of Education, and the Alchemist Project under the Korean Ministry of Trade, Industry & Energy.
2023.09.01 View 4887 -
KAIST researchers find sleep delays more prevalent in countries of particular culture than others
Sleep has a huge impact on health, well-being and productivity, but how long and how well people sleep these days has not been accurately reported. Previous research on how much and how well we sleep has mostly relied on self-reports or was confined within the data from the unnatural environments of the sleep laboratories.
So, the questions remained: Is the amount and quality of sleep purely a personal choice? Could they be independent from social factors such as culture and geography?
< From left to right, Sungkyu Park of Kangwon National University, South Korea; Assem Zhunis of KAIST and IBS, South Korea; Marios Constantinides of Nokia Bell Labs, UK; Luca Maria Aiello of the IT University of Copenhagen, Denmark; Daniele Quercia of Nokia Bell Labs and King's College London, UK; and Meeyoung Cha of IBS and KAIST, South Korea >
A new study led by researchers at Korea Advanced Institute of Science and Technology (KAIST) and Nokia Bell Labs in the United Kingdom investigated the cultural and individual factors that influence sleep. In contrast to previous studies that relied on surveys or controlled experiments at labs, the team used commercially available smartwatches for extensive data collection, analyzing 52 million logs collected over a four-year period from 30,082 individuals in 11 countries. These people wore Nokia smartwatches, which allowed the team to investigate country-specific sleep patterns based on the digital logs from the devices.
< Figure comparing survey and smartwatch logs on average sleep-time, wake-time, and sleep durations. Digital logs consistently recorded delayed hours of wake- and sleep-time, resulting in shorter sleep durations. >
Digital logs collected from the smartwatches revealed discrepancies in wake-up times and sleep-times, sometimes by tens of minutes to an hour, from the data previously collected from self-report assessments. The average sleep-time overall was calculated to be around midnight, and the average wake-up time was 7:42 AM. The team discovered, however, that individuals' sleep is heavily linked to their geographical location and cultural factors. While wake-up times were similar, sleep-time varied by country. Individuals in higher GDP countries had more records of delayed bedtime. Those in collectivist culture, compared to individualist culture, also showed more records of delayed bedtime. Among the studied countries, Japan had the shortest total sleep duration, averaging a duration of under 7 hours, while Finland had the longest, averaging 8 hours.
Researchers calculated essential sleep metrics used in clinical studies, such as sleep efficiency, sleep duration, and overslept hours on weekends, to analyze the extensive sleep patterns. Using Principal Component Analysis (PCA), they further condensed these metrics into two major sleep dimensions representing sleep quality and quantity. A cross-country comparison revealed that societal factors account for 55% of the variation in sleep quality and 63% of the variation in sleep quantity.
Countries with a higher individualism index (IDV), which placed greater emphasis on individual achievements and relationships, had significantly longer sleep durations, which could be attributed to such societies having a norm of going to bed early. Spain and Japan, on the other hand, had the bedtime scheduled at the latest hours despite having the highest collectivism scores (low IDV). The study also discovered a moderate relationship between a higher uncertainty avoidance index (UAI), which measures implementation of general laws and regulation in daily lives of regular citizens, and better sleep quality.
Researchers also investigated how physical activity can affect sleep quantity and quality to see if individuals can counterbalance cultural influences through personal interventions. They discovered that increasing daily activity can improve sleep quality in terms of shortened time needed in falling asleep and waking up. Individuals who exercise more, however, did not sleep longer. The effect of exercise differed by country, with more pronounced effects observed in some countries, such as the United States and Finland. Interestingly, in Japan, no obvious effect of exercise could be observed. These findings suggest that the relationship between daily activity and sleep may differ by country and that different exercise regimens may be more effective in different cultures.
This research published on the Scientific Reports by the international journal, Nature, sheds light on the influence of social factors on sleep. (Paper Title "Social dimensions impact individual sleep quantity and quality" Article number: 9681)
One of the co-authors, Daniele Quercia, commented: “Excessive work schedules, long working hours, and late bedtime in high-income countries and social engagement due to high collectivism may cause bedtimes to be delayed.”
Commenting on the research, the first author Shaun Sungkyu Park said, "While it is intriguing to see that a society can play a role in determining the quantity and quality of an individual's sleep with large-scale data, the significance of this study is that it quantitatively shows that even within the same culture (country), individual efforts such as daily exercise can have a positive impact on sleep quantity and quality."
"Sleep not only has a great impact on one’s well-being but it is also known to be associated with health issues such as obesity and dementia," said the lead author, Meeyoung Cha. "In order to ensure adequate sleep and improve sleep quality in an aging society, not only individual efforts but also a social support must be provided to work together," she said. The research team will contribute to the development of the high-tech sleep industry by making a code that easily calculates the sleep indicators developed in this study available free of charge, as well as providing the benchmark data for various types of sleep research to follow.
2023.07.07 View 4878 -
Synthetic sRNAs to knockdown genes in medical and industrial bacteria
Bacteria are intimately involved in our daily lives. These microorganisms have been used in human history for food such as cheese, yogurt, and wine, In more recent years, through metabolic engineering, microorganisms been used extensively as microbial cell factories to manufacture plastics, feed for livestock, dietary supplements, and drugs. However, in addition to these bacteria that are beneficial to human lives, pathogens such as Pneumonia, Salmonella, and Staphylococcus that cause various infectious diseases are also ubiquitously present. It is important to be able to metabolically control these beneficial industrial bacteria for high value-added chemicals production and to manipulate harmful pathogens to suppress its pathogenic traits.
KAIST (President Kwang Hyung Lee) announced on the 10th that a research team led by Distinguished Professor Sang Yup Lee of the Department of Biochemical Engineering has developed a new sRNA tool that can effectively inhibit target genes in various bacteria, including both Gram-negative and Gram-positive bacteria. The research results were published online on April 24 in Nature Communications.
※ Thesis title: Targeted and high-throughput gene knockdown in diverse bacteria using synthetic sRNAs
※ Author information : Jae Sung Cho (co-1st), Dongsoo Yang (co-1st), Cindy Pricilia Surya Prabowo (co-author), Mohammad Rifqi Ghiffary (co-author), Taehee Han (co-author), Kyeong Rok Choi (co-author), Cheon Woo Moon (co-author), Hengrui Zhou (co-author), Jae Yong Ryu (co-author), Hyun Uk Kim (co-author) and Sang Yup Lee (corresponding author).
sRNA is an effective tool for synthesizing and regulating target genes in E. coli, but it has been difficult to apply to industrially useful Gram-positive bacteria such as Bacillus subtilis and Corynebacterium in addition to Gram-negative bacteria such as E. coli.
To address this issue, a research team led by Distinguished Professor Lee Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST developed a new sRNA platform that can effectively suppress target genes in various bacteria, including both Gram-negative and positive bacteria. The research team surveyed thousands of microbial-derived sRNA systems in the microbial database, and eventually designated the sRNA system derived from 'Bacillus subtilis' that showed the highest gene knockdown efficiency, and designated it as “Broad-Host-Range sRNA”, or BHR-sRNA.
A similar well-known system is the CRISPR interference (CRISPRi) system, which is a modified CRISPR system that knocks down gene expression by suppressing the gene transcription process. However, the Cas9 protein in the CRISPRi system has a very high molecular weight, and there have been reports growth inhibition in bacteria. The BHR-sRNA system developed in this study did not affect bacterial growth while showing similar gene knockdown efficiencies to CRISPRi.
< Figure 1. a) Schematic illustration demonstrating the mechanism of syntetic sRNA b) Phylogenetic tree of the 16 Gram-negative and Gram-positive bacterial species tested for gene knockdown by the BHR-sRNA system. >
To validate the versatility of the BHR-sRNA system, 16 different gram-negative and gram-positive bacteria were selected and tested, where the BHR-sRNA system worked successfully in 15 of them. In addition, it was demonstrated that the gene knockdown capability was more effective than that of the existing E. coli-based sRNA system in 10 bacteria. The BHR-sRNA system proved to be a universal tool capable of effectively inhibiting gene expression in various bacteria.
In order to address the problem of antibiotic-resistant pathogens that have recently become more serious, the BHR-sRNA was demonstrated to suppress the pathogenicity by suppressing the gene producing the virulence factor. By using BHR-sRNA, biofilm formation, one of the factors resulting in antibiotic resistance, was inhibited by 73% in Staphylococcus epidermidis a pathogen that can cause hospital-acquired infections. Antibiotic resistance was also weakened by 58% in the pneumonia causing bacteria Klebsiella pneumoniae. In addition, BHR-sRNA was applied to industrial bacteria to develop microbial cell factories to produce high value-added chemicals with better production performance. Notably, superior industrial strains were constructed with the aid of BHR-sRNA to produce the following chemicals: valerolactam, a raw material for polyamide polymers, methyl-anthranilate, a grape-flavor food additive, and indigoidine, a blue-toned natural dye.
The BHR-sRNA developed through this study will help expedite the commercialization of bioprocesses to produce high value-added compounds and materials such as artificial meat, jet fuel, health supplements, pharmaceuticals, and plastics. It is also anticipated that to help eradicating antibiotic-resistant pathogens in preparation for another upcoming pandemic. “In the past, we could only develop new tools for gene knockdown for each bacterium, but now we have developed a tool that works for a variety of bacteria” said Distinguished Professor Sang Yup Lee.
This work was supported by the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry Project and the Development of Platform Technologies of Microbial Cell Factories for the Next-generation Biorefineries Project from NRF supported by the Korean MSIT.
2023.05.10 View 4917 -
KAIST research team develops a cheap and safe redox flow battery
Redox flow batteries, one of the potential replacements for the widely used lithium-ion secondary batteries, can be utilized as new and renewable energy as well as for energy storage systems (ESS) thanks to their low cost, low flammability, and long lifetime of over 20 years. Since the price of vanadium, the most widely used active material for redox flow batteries, has been rising in recent years, scientists have been actively searching for redox materials to replace it.
On March 23, a joint research team led by Professors Hye Ryung Byon and Mu-Hyun Baik from the KAIST Department of Chemistry, and Professor Jongcheol Seo from the POSTECH Department of Chemistry announced that they had developed a highly soluble and stable organic redox-active molecule for use in aqueous redox flow batteries.
The research team focused on developing aqueous redox flow batteries by redesigning an organic molecule. It is possible to control the solubility and electrochemical redox potential of organic molecules by engineering their design, which makes them a promising active material candidate with possibly higher energy storage capabilities than vanadium. Most organic redox-active molecules have low solubilities or have slow chemical stability during redox reactions. Low solubility means low energy storage capacity and low chemical stability leads to reduced cycle performance. For this research, the team chose naphthalene diimide (NDI) as their active molecule. Until now, there was little research done on NDI despite its high chemical stability, as it shows low solubility in aqueous electrolyte solutions.
Although NDI molecules are almost insoluble in water, the research team tethered four ammonium functionalities and achieved a solubility as high as 1.5M* in water. In addition, they confirmed that when a 1M solution of NDI was used in neutral redox flow batteries for 500 cycles, 98% of its capacity was maintained. This means 0.004% capacity decay per cycle, and only 2% of its capacity would be lost if the battery were to be operated for 45 days.
Furthermore, the developed NDI molecule can save two electrons per molecule, and the team proved that 2M of electrons could be stored in every 1M of NDI solution used. For reference, vanadium used in vanadium redox flow batteries, which require a highly concentrated sulfuric acid solution, has a solubility of about 1.6M and can only hold one electron per molecule, meaning it can store a total of 1.6M of electrons. Therefore, the newly developed NDI active molecule shows a higher storage capacity compared to existing vanadium devices.
*1M (mol/L): 6.022 x 1023 active molecules are present in 1L of solution
This paper, written by co-first authors Research Professor Vikram Singh, and Ph.D. candidates Seongyeon Kwon and Yunseop Choi, was published in the online version of Advanced Materials on February 7 under the title, Controlling π-π interactions of highly soluble naphthalene diimide derivatives for neutral pH aqueous redox flow batteries. Ph.D. Candidate Yelim Yi and Professor Mi Hee Lee’s team from the KAIST Department of Chemistry also contributed to the study by conducting electron paramagnetic resonance analyses.
Professor Hye Ryung Byon said, “We have demonstrated the principles of molecular design by modifying an existing organic active molecule with low solubility and utilizing it as an active molecule for redox flow batteries. We have also shown that during a redox reaction, we can use molecular interactions to suppress the chemical reactivity of radically formed molecules.”
She added, “Should this be used later for aqueous redox flow batteries, along with its high energy density and high solubility, it would also have the advantage of being available for use in neutral pH electrolytes. Vanadium redox flow batteries currently use acidic solutions, which cause corrosion, and we expect our molecule to solve this issue. Since existing lithium ion-based ESS are flammable, we must develop safer and cheaper next-generation ESS, and our research has shown great promise in addressing this.”
This research was funded by Samsung Research Funding & Incubation Center, the Institute for Basic Science, and the National Research Foundation.
Figure 1. (a) Structures of various NDI molecules. (b) Solubility of NDI molecules in water (black bars) and aqueous electrolytes including KCl electrolyte (blue bars). (c–d) Structural changes of the molecules as the developed NDI molecule stores two electrons. (c) Illustration of cluster combination and separation of NDI molecules developed during redox reaction and (d) Snapshot of the MD simulation. NDI molecules prepared from the left, formation of bimolecular sieve and tetramolecular sieve clusters after the first reductive reaction, and a single molecule with a three-dimensional structure after the second reduction.
Figure 2. Performance results of an aqueous redox flow battery using 1M of the developed NDI molecule as the cathode electrolyte and 3.1M of ammonium iodine as the anode electrolyte. Using 1.5 M KCl solution. (a) A schematic diagram of a redox flow battery. (b) Voltage-capacity graph according to cycle in a redox flow battery. (c) Graphs of capacity and coulombs, voltage, and energy efficiency maintained at 500 cycles.
2023.04.03 View 4422 -
Overview of the 30-year history of metabolic engineering
< Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST >
A research team comprised of Gi Bae Kim, Dr. So Young Choi, Dr. In Jin Cho, Da-Hee Ahn, and Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST reported the 30-year history of metabolic engineering, highlighting examples of recent progress in the field and contributions to sustainability and health. Their paper “Metabolic engineering for sustainability and health” was published online in the 40th anniversary special issue of Trends in Biotechnology on January 10, 2023.
Metabolic engineering, a discipline of engineering that modifies cell phenotypes through molecular and genetic-level manipulations to improve cellular activities, has been studied since the early 1990s, and has progressed significantly over the past 30 years. In particular, metabolic engineering has enabled the engineering of microorganisms for the development of microbial cell factories capable of efficiently producing chemicals and materials as well as degrading recalcitrant contaminants.
This review article revisited how metabolic engineering has advanced over the past 30 years, from the advent of genetic engineering techniques such as recombinant DNA technologies to recent breakthroughs in systems metabolic engineering and data science aided by artificial intelligence. The research team highlighted momentous events and achievements in metabolic engineering, providing both trends and future directions in the field. Metabolic engineering’s contributions to bio-based sustainable chemicals and clean energy, health, and bioremediation were also reviewed. Finally, the research team shared their perspectives on the future challenges impacting metabolic engineering than must be overcome in order to achieve advancements in sustainability and health.
Distinguished Professor Sang Yup Lee said, “Replacing fossil resource-based chemical processes with bio-based sustainable processes for the production of chemicals, fuels, and materials using metabolic engineering has become our essential task for the future. By looking back on the 30+ years of metabolic engineering, we aimed to highlight the contributions of metabolic engineering to achieve sustainability and good health.” He added, “Metabolic engineering will play an increasingly important role as a key solution to the climate crisis, environmental pollution, food and energy shortages, and health problems in aging societies.”
< Figure: Metabolic Engineering Timeline >
2023.01.25 View 7558 -
A KAIST Research Team Develops Diesel Reforming Catalyst Enabling Hydrogen Production for Future Mobile Fuel Cells
This catalyst capability allowing stable hydrogen production from commercial diesel is expected to be applied in mobile fuel cell systems in the future hydrogen economy
On August 16, a joint research team led by Professors Joongmyeon Bae and Kang Taek Lee of KAIST’s Department of Mechanical Engineering and Dr. Chan-Woo Lee of Korea Institute of Energy Research (KIER) announced the successful development of a highly active and durable reforming catalyst allowing hydrogen production from commercial diesel.
Fuel reforming is a hydrogen production technique that extracts hydrogen from hydrocarbons through catalytic reactions. Diesel, being a liquid fuel, has a high storage density for hydrogen and is easy to transport and store. There have therefore been continuous research efforts to apply hydrogel supply systems using diesel reformation in mobile fuel cells, such as for auxiliary power in heavy trucks or air-independent propulsion (AIP) systems in submarines.
However, diesel is a mixture of high hydrocarbons including long-chained paraffin, double-bonded olefin, and aromatic hydrocarbons with benzene groups, and it requires a highly active catalyst to effectively break them down. In addition, the catalyst must be extremely durable against caulking and sintering, as they are often the main causes of catalyst degradation. Such challenges have limited the use of diesel reformation technologies to date.
The joint research team successfully developed a highly active and durable diesel reforming catalyst through elution (a heat treatment method used to uniformly grow active metals retained in an oxide support as ions in the form of metal nanoparticles), forming alloy nanoparticles. The design was based on the fact that eluted nanoparticles strongly interact with the support, allowing a high degree of dispersion at high temperatures, and that producing an alloy from dissimilar metals can increase the performance of catalysts through a synergistic effect.
The research team introduced a solution combustion synthesis method to produce a multi-component catalyst with a trace amount of platinum (Pt) and ruthenium (Ru) penetrated into a ceria (CeO2) lattice, which is a structure commonly used as a support for catalysts in redox reactions. When exposed to a diesel reforming reaction environment, the catalyst induces Pt-Ru alloy nanoparticle formation upon Pt and Ru elution onto the support surface.
In addition to the catalyst analysis, the research team also succeeded in characterizing the behaviour of active metal elution and alloy formation from an energetic perspective using a density functional theory-based calculation. In a performance comparison test between the Pt-Ru alloy catalyst against existing single-metal catalysts, the reforming activity was shown to have improved, as it showed a 100% fuel conversion rate even at a low temperature (600oC, compared to the original 800oC). In a long-term durability test (800oC, 200 hours), the catalyst showed commercial stability by successfully producing hydrogen from commercial diesel without performance degradation.
The study was conducted by Ph.D. candidate Jaemyung Lee of KAIST’s Department of Mechanical Engineering as the first author. Ph.D. candidate Changho Yeon of KIER, Dr. Jiwoo Oh of KAIST’s Department of Mechanical Engineering, Dr. Gwangwoo Han of KIER, Ph.D. candidate Jeong Do Yoo of KAIST’s Department of Mechanical Engineering, and Dr. Hyung Joong Yun of the Korea Basic Science Institute contributed as co-authors. Dr. Chan-Woo Lee of KIER and Professors Kang Taek Lee and Joongmyeon Bae of KAIST’s Department of Mechanical Engineering contributed as corresponding authors. The research was published in the online version of Applied Catalysis B: Environmental (IF 24.319, JCR 0.93%) on June 17, under the title “Highly Active and Stable Catalyst with Exsolved PtRu Alloy Nanoparticles for Hydrogen Production via Commercial Diesel Reforming”.
Professor Joongmyeon Bae said, “The fact that hydrogen can be stably produced from commercial diesel makes this a very meaningful achievement, and we look forward to this technology contributing to the active introduction of mobile fuel cell systems in the early hydrogen economy.” He added, “Our approach to catalyst design may be applied not only to reforming reactions, but also in various other fields.”
This research was supported by the National Research Foundation of Korea through funding from the Ministry of Science, ICT and Future Planning.
Figure. Schematic diagram of high-performance diesel reforming catalyst with eluted platinum-ruthenium alloy nanoparticles and long-term durability verification experiment results for commercial diesel reforming reaction
2022.09.07 View 8845