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KAIST solves solar cell dilemma… achieving over 25% efficiency and long lifespan simultaneously
<(Upper Left) Dr. Chansu Moon,(From Left) Dr. Namjoong Jeon, Ph.D candidate Jaehee Lee, M.S candidate Hajin Na, Professor Jangwon Seo>
A KAIST research team has solved the “solar cell dilemma,” in which increasing efficiency shortens lifespan, while extending lifespan lowers efficiency. The team developed a technology to precisely control the internal structure of a surface passivation layer in perovskite solar cells, successfully achieving both high efficiency exceeding 25% and long-term stability at the same time.
KAIST (President Kwang Hyung Lee) announced on the 24th that a research team led by Distinguished Professor Jangwon Seo of the Department of Chemical and Biomolecular Engineering, in joint research with the Korea Research Institute of Chemical Technology (KRICT) (President Young-guk Lee), developed a 2D passivation layer design technology that simultaneously improves the efficiency and long-term stability of perovskite solar cells.
<Research Concept Diagram (AI-Generated Image)>
As the need to respond to the climate crisis and transition energy systems grows, improving the efficiency of solar power generation and securing long-term reliability have emerged as important challenges. In particular, perovskite solar cells, which are attracting attention as next-generation high-efficiency solar cells, have recently achieved rapid efficiency improvements. However, they have been pointed out as having commercialization barriers due to performance degradation under high temperature, high humidity, or prolonged light exposure.
Previously, a “3D/2D structure” strategy—adding a 2D layer on top of a 3D perovskite layer—has been used. This method helps reduce surface defects and improve stability. However, if the structure of the 2D layer is not sufficiently robust, it has limitations in that the structure may deform over time or performance may gradually decline.
To address this, the research team introduced a structurally more stable Dion–Jacobson (DJ) type 2D perovskite passivation layer and proposed a design strategy that precisely controls the “n value,” which refers to the number of stacked perovskite layers within the passivation layer. The DJ structure enhances structural stability by firmly connecting perovskite layers with organic molecules on both sides. In simple terms, it is similar to binding bricks together with a stronger adhesive so that the structure does not easily collapse.
The research team controlled the stacking structure (n value) of perovskite layers inside the 2D passivation layer in a desired manner by adjusting heat treatment conditions, analogous to how controlling temperature and time during the curing of adhesive after stacking bricks results in a more solid and orderly structure.
As a result, charge transport became more efficient, improving solar cell efficiency, and the robust characteristics of the DJ structure also enhanced long-term stability. In addition, the team experimentally revealed that during the heat treatment process, the internal structure of the 2D passivation layer changes as the structure is rearranged at the interface where different materials meet. They also presented the principles for controlling the passivation layer structure and reproducible process conditions.
The perovskite solar cell applying this design strategy recorded a high power conversion efficiency of 25.56% (certified efficiency of 25.59%). It also maintained a high level of performance under conditions of 85°C and 85% relative humidity (85% RH) as well as continuous light exposure, confirming long-term stability. The research team further applied this technology to the fabrication of large-area modules and verified excellent performance.
<Schematic Diagram of Structure Formation Strategy (left) and Structural Evolution (right)>
Distinguished Professor Jangwon Seo stated, “This study demonstrates that the longstanding challenge—where increasing efficiency reduces lifespan and increasing lifespan lowers efficiency—can be solved simultaneously through structural design of the surface passivation layer.” He added, “This technology operates relatively stably even under changes in process conditions, making it helpful for large-area manufacturing processes for commercialization.”
This study, co-first-authored by Jaehee Lee (integrated M.S./Ph.D. student at KAIST) and Dr. Chansu Moon (KRICT), was published in the international energy journal Joule (IF 35.4) on February 24, 2026.
※ Paper title: “Tailored n value engineering of Dion-Jacobson 2D layers enables efficient and stable perovskite solar cells,” DOI: 10.1016/j.joule.2025.102301
※ Author information: Jaehee Lee (integrated M.S./Ph.D. program, KAIST, co-first author), Chansu Moon (former KRICT, co-first author), Dr. Namjoong Jeon (KRICT, corresponding author), Distinguished Professor Jangwon Seo (KAIST, corresponding author)
This research was supported by the National Research Foundation of Korea (NRF) (Nano and Materials Technology Development Program [Materials Hub], Basic Research Program [Mid-career], Engineering Research Center [ERC]) and the core program of KRICT. Some experiments were supported by beamlines at the Pohang Accelerator Laboratory (PAL).
2026.03.26 View 608 -
KAIST Develops Self-Regenerating Catalyst That Restores Its Own Performance, Opening a Breakthrough for CO₂ Conversion Technology
<(From Left) Professor Dong Young Chung, Ph.D Candidate Hongmin An, Hanjoo Kim>
Technologies that convert carbon dioxide (CO₂) emitted from factories and power plants into useful chemical feedstocks are considered key to achieving carbon neutrality. However, rapid degradation of catalyst performance has long hindered commercialization. KAIST researchers have now developed a “self-regenerating” catalyst that restores its activity during operation, offering a potential solution to this challenge.
KAIST (President Kwang Hyung Lee) announced on the 11th of March that a research team led by Professor Dong Young Chung from the Department of Chemical and Biomolecular Engineering has identified the fundamental cause of catalyst degradation in electrochemical reactions that convert CO₂ into useful materials and has developed a new design strategy that allows catalysts to maintain their active state during the reaction.
<Schematic Illustration of Copper Catalyst Reconstruction>
The research team focused particularly on copper (Cu) catalysts, which are widely used in CO₂ conversion reactions. Copper catalysts are known not to simply degrade during reactions but instead undergo a process called surface reconstruction, in which their surface structure continuously changes. The study revealed that the performance and lifetime of the catalyst vary significantly depending on how this reconstruction occurs.
The researchers discovered that copper catalyst reconstruction occurs mainly through two different mechanisms. The first involves formation and reduction of oxide layers on the catalyst surface. While this temporarily increases catalytic activity, it ultimately leads to long-term degradation of catalyst performance.
The second mechanism involves partial dissolution of the catalyst metal into the electrolyte followed by redeposition onto the catalyst surface. During this process, new reactive sites—known as active sites—are continuously created on the catalyst surface.
Based on this mechanism, the team proposed a method that allows the catalyst to maintain its active state during the reaction. By introducing a trace amount of copper ions into the electrolyte, dissolution and redeposition of copper occur in a balanced cycle on the catalyst surface. This continuous cycle generates new active sites, enabling the catalyst to maintain stable performance over extended periods.
Importantly, this technology can be implemented without complex additional processes or high-voltage conditions, significantly reducing energy consumption while enabling stable production of high-value C₂ compounds such as ethylene and ethanol. C₂ compounds are molecules containing two carbon atoms and are industrially important chemicals used as feedstocks for plastics, fuels, and other materials.
This research is significant because it proposes a new design concept in which catalysts are not merely optimized at the initial stage but are engineered to maintain their optimal state throughout the reaction process. The concept is expected to be applicable not only to CO₂ conversion technologies but also to a wide range of electrochemical energy conversion systems.
Professor Dong Young Chung stated, “This research approached catalyst degradation not as an inevitable phenomenon but as a controllable process,” adding, “We proposed a new strategy that allows catalysts to continuously maintain optimal activity during the reaction.”
The study was led by Hanjoo Kim, a doctoral student at KAIST, and Hongmin An, a combined master’s-doctoral student, as co-first authors. The research was published online on February 5 in the Journal of the American Chemical Society (JACS), one of the world’s most prestigious journals in chemistry.
※ Paper title: “Dynamic Interface Engineering via Mechanistic Understanding of Copper Reconstruction in Electrochemical CO₂ Reduction Reaction” DOI: 10.1021/jacs.5c16244
This research was supported by the Global Young Connect Program for Materials and the National Strategic Materials Technology Development Program funded through the National Research Foundation of Korea.
2026.03.11 View 1001 -
Unveiling the Oxygen Usage of Catalysts to Eliminate Greenhouse Gases Views
<(From Left) Professor Hyunjoo Lee, Ph. D candidate Yunji Choi, Ph. D candidate Jaebeom Han, Professor Jeong Young Park>
As the climate crisis becomes a part of daily life with unprecedented heatwaves and cold snaps, technology to effectively remove greenhouse gases is emerging as a critical global challenge. In particular, catalytic technology that decomposes harmful gases using oxygen is a key element of eco-friendly purification. South Korean researchers have identified the principle that catalysts—which were previously vaguely thought to simply ‘use oxygen well’—can selectively utilize different oxygen sources depending on the reaction environment, presenting a new standard for catalyst design.
A joint research team consisting of Professor Hyunjoo Lee from KAIST Department of Chemical and Biomolecular Engineering, Professor Jeong Woo Han from Seoul National University, and Professor Jeong Young Park from KAIST announced on February 4th that they have identified for the first time in the world that ceria (CeO₂), widely used as an eco-friendly catalyst, completely changes its method of using oxygen depending on its size. *Ceria (CeO₂): A compound formed by the combination of the metal cerium and oxygen.
Ceria is a metal oxide catalyst enables high catalytic performance while reducing the need for expensive precious metal catalysts. It is called an ‘oxygen tank’ in the field of catalysis because it can store oxygen and release it when needed. However, until now, it had not been clearly identified where the oxygen came from and under what conditions it was used in the reaction.
The research team focused on a new concept of a catalyst that ‘chooses and uses oxygen according to the situation,’ rather than just a catalyst that ‘uses oxygen well.’ To this end, they fabricated catalysts with precisely controlled ceria sizes, ranging from ultra-small nano-sizes to relatively large sizes, and systematically analyzed the oxygen movement and reaction processes.
<Schematic Diagram of the Oxygen Transport Mechanism According to Seria Size>
As a result, it was confirmed that small ceria catalysts operate as an ‘agility type’ that quickly takes in oxygen from the air and uses it immediately for reactions, while large ceria catalysts play an ‘endurance type’ role that pulls oxygen stored inside to the surface and supplies it continuously. In other words, the design principle was revealed for the first time that by simply adjusting the size of the catalyst, one can choose whether to use oxygen from the air or oxygen stored internally depending on the reaction conditions. The research team proved this mechanism simultaneously through advanced experimental analysis and artificial intelligence-based simulations.
The research team applied this principle to methane removal. Methane is a greenhouse gas with a global warming effect dozens of times stronger than carbon dioxide, and it is removed through a catalytic oxidation reaction that converts it into carbon dioxide and water using oxygen. The experimental results showed that the small ceria catalyst, by immediately utilizing oxygen from the air, demonstrated stable performance in removing methane even in low-temperature and high-humidity environments. This shows that it is possible to significantly reduce the use of expensive precious metals (platinum and palladium) while actually improving performance.
This achievement is expected to lead to the development of highly durable catalysts that maintain performance even in realistic industrial environments such as rain and moisture, as well as reducing the manufacturing cost of environmental purification equipment, thereby accelerating the commercialization of eco-friendly energy and environmental technologies.
<Schematic Illustration of Ceria Catalyst Applications>
Professor Hyunjoo Lee stated, “This research is an achievement that clearly distinguishes the two core mechanisms of how oxygen operates in catalysts for the first time,” and added, “It has opened a new path to custom-design high-efficiency catalysts required for responding to the climate crisis according to reaction conditions.”
Ph. D candidate Yunji Choi from KAIST, Dr. Seokhyun Choung from Seoul National University, and Ph. D candidate Jaebeom Han from KAIST participated as joint first authors of this study. The research results, also co-authored by Jae-eon Hwang, Hyeon Jin, Yunkyung Kim, and Jeongjin Kim, were published in the international academic journal 'Nature Communications' on January 9th.
This research was supported by the National Research Foundation of Korea (Global Leader Grant, Mid-Career Research Program) funded by the Ministry of Education, Science and Technology, Republic of Korea.
2026.02.09 View 5000 -
KAIST Proposes AI-Driven Strategy to Solve Long-Standing Mystery of Gene Function
<(From Left) Distinguisehd Professor Sang Yup Lee, Dr. Gi Bae Kim, Professor Bernhard O. Palsson>
“We know the genes, but not their functions.” To resolve this long-standing bottleneck in microbial research, a joint research team has proposed a cutting-edge research strategy that leverages Artificial Intelligence (AI) to drastically accelerate the discovery of microbial gene functions.
KAIST announced on January 12th that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Bernhard Palsson from the Department of Bioengineering at UCSD, has published a comprehensive review paper. The study systematically analyzes and organizes the latest AI-based research approaches aimed at revolutionizing the speed of gene function discovery.
Since the early 2000s, when whole-genome sequencing became a reality, there were high expectations that the genetic blueprint of life would be fully decoded. However, even twenty years later, the roles of a significant portion of genes within microbial genomes remain unknown.
While various experimental methods—such as gene deletion, analysis of gene expression profiles, and in vitro activity assays—have been employed, discovering gene functions remains a time-consuming and costly endeavor. This is primarily due to the limitations of large-scale experimentation, complex biological interactions, and the discrepancy between laboratory results and actual in vivo responses.
To overcome these hurdles, the research team emphasized that an AI-driven approach combining computational biology with experimental biology is essential.
In this paper, the team provides a comprehensive overview of computational biology approaches that have facilitated gene function discovery, ranging from traditional sequence similarity analysis to the latest deep-learning-based AI models.
Notably, 3D protein structure prediction technologies such as AlphaFold (developed by Google DeepMind) and RoseTTAFold (developed by the University of Washington) have opened new doors. These tools go beyond simple functional estimation, offering the potential to understand the underlying mechanisms of how gene functions operate. Furthermore, generative AI is now extending research boundaries toward designing proteins with specifically desired functions.
Focusing on transcription factors (proteins that act as genetic switches) and enzymes (proteins that catalyze chemical reactions), the team presented various application cases and future research directions that integrate gene sequence analysis, protein structure prediction, and diverse metagenomic analyses.
<Schematic illustration of computational biology methods for enzyme function prediction>
2026.01.12 View 1648 -
Breakthrough in Intractable Intestinal Disease Treatment Using Xenogeneic-Free Intestinal Stem Cells
< (From left) Professor Sung Gap Im (KAIST), Dr. Seonghyeon Park (KAIST), M.S candidate Sang Yu Sun (KAIST), Dr. Mi-Young Son (KRIBB), (Top right) Dr. Tae Geol Lee (KRISS), Dr. Jin Gyeong Son (KRISS) >
Intestinal Stem Cells (ISCs) derived from a patient's own cells have garnered significant attention as a new alternative for treating intractable intestinal diseases due to their low risk of rejection. However, clinical application has been limited by safety and regulatory issues arising from conventional culture methods that rely on animal-derived components (xenogeneic components). A KAIST research team has developed an advanced culture technology that stably grows ISCs without animal components while simultaneously enhancing their migration to damaged tissues and regenerative capabilities.
KAIST announced on December 23rd that a joint research team—led by Professor Sung Gap Im from the Department of Chemical and Biomolecular Engineering, Dr. Tae Geol Lee from the Nano-Bio Measurement Group at the Korea Research Institute of Standards and Science and Dr. Mi-Young Son from the Stem Cell Convergence Research Center at the Korea Research Institute of Bioscience and Biotechnology has developed a polymer-based culture platform that dramatically improves the migration and regeneration of ISCs in a xenogeneic-free environment.
To overcome obstacles in the clinical application of stem cell therapies—such as the risk of virus transmission to patients when using substances derived from mouse fibroblasts or Matrigel—the joint research team developed "PLUS" (Polymer-coated Ultra-stable Surface). This polymer-based culture surface technology functions effectively without any animal-derived materials.
< Figure 1. Precise control of polymer coating and surface modification via initiated Chemical Vapor Deposition (iCVD) process >
PLUS is a synthetic polymer surface coated via a vapor deposition method. By precisely controlling surface energy and chemical composition, it significantly enhances the adhesion and mass-culture efficiency of ISCs. Notably, it maintains identical culture performance even after being stored at room temperature for three years, securing industrial scalability and storage convenience for stem cell therapeutics.
Through proteomics analysis*, the research team identified that the expression of proteins related to cytoskeletal reorganization significantly increased in ISCs cultured on the PLUS environment.
Proteomics Analysis: A method used to simultaneously analyze the types and quantitative changes of all proteins present within a cell or tissue.
Specifically, the team confirmed that increased expression of cytoskeleton-binding and actin-binding proteins leads to a stable restructuring of the internal cellular architecture. This provides the power source for stem cells to move faster and more actively across the substrate.
< Figure 2. Elucidation of the mechanism for enhanced ISC migration through precision proteomics analysis >
Real-time observations using holotomography microscopy revealed that ISCs cultured on PLUS exhibited a migration speed approximately twice as fast as those on conventional surfaces. Furthermore, in a damaged tissue model, the cells demonstrated outstanding regenerative performance, repairing more than half of the damage within a single week. This proves that PLUS activates the cytoskeletal activity of stem cells, thereby boosting their practical tissue regeneration capabilities.
The newly developed PLUS culture platform is evaluated as a technology that will significantly enhance the safety, mass production, and clinical feasibility of ISCs derived from human pluripotent stem cells (hPSCs). By elucidating the mechanism that simultaneously strengthens the survival, migration, and regeneration of stem cells in a xenogeneic-free environment, the team has established a foundation to fundamentally resolve safety, regulatory, and productivity issues in stem cell therapy.
Professor Sung Gap Im of KAIST stated, "This research provides a synthetic culture platform that eliminates the dependence on xenogeneic components—which has hindered the clinical application of stem cell therapies—while maximizing the migration and regenerative capacity of stem cells. It will serve as a catalyst for a paradigm shift in the field of regenerative medicine."
Dr. Seonghyeon Park (KAIST), Sang Yu Sun (KAIST), and Dr. Jin Gyeong Son (KRISS) participated as first authors. The research findings were published online on November 26th in Advanced Materials, the leading academic journal in materials science.
Paper Title: Tailored Xenogeneic-Free Polymer Surface Promotes Dynamic Migration of Intestinal Stem Cells
DOI: 10.1002/adma.202513371
This research was conducted with support from the Ministry of Science and ICT, the Ministry of SMEs and Startups, the National Research Foundation of Korea, the National Council of Science and Technology Research, KRISS, KRIBB, and the National NanoFab Center.
2025.12.23 View 1478 -
Chemobiological Platform Enables Renewable Conversion of Sugars into Core Aromatic Hydrocarbons of Petroleum
<(From Left) Professor Sun Kyu Han, Ph.D candidate Tae Wan Kim, Professor Kyeong Rok Choi, Professor Sang Yup Lee>
With growing concerns over fossil fuel depletion and the environmental impacts of petrochemical production, scientists are actively exploring renewable strategies to produce essential industrial chemicals. A collaborative research team—led by Distinguished Professor Sang Yup Lee, Senior Vice President for Research, from the Department of Chemical and Biomolecular Engineering, together with Professor Sunkyu Han from the Department of Chemistry at the Korea Advanced Institute of Science and Technology (KAIST)—has developed an integrated chemobiological platform that converts renewable carbon sources such as glucose and glycerol into oxygenated precursors, which are subsequently deoxygenated in the same solvent system to yield benzene, toluene, ethylbenzene, and p-xylene (BTEX), which are fundamental aromatic hydrocarbons used in fuels, polymers, and consumer products.
<Figure 1. Schematic representation of the chemobiological synthesis of BTEX from glucose or glycerol in Escherichia coli>
From Sugars to Aromatic Hydrocarbons of Petroleum
The researchers designed four metabolically engineered strains of Escherichia coli, each programmed to produce a specific oxygenated precursor—phenol, benzyl alcohol, 2-phenylethanol, or 2,5-xylenol. These intermediates are generated through tailored genetic modifications, such as deletion of feedback-regulated enzymes, overexpression of pathway-specific genes, and introduction of heterologous enzymes to expand metabolic capabilities.
During fermentation, the products were continuously extracted into the organic solvent isopropyl myristate (IPM). Acting as a dual-function solvent, IPM not only mitigated the toxic effects of aromatic compounds on cell growth but also served directly as the reaction medium for downstream chemical upgrading. By eliminating the need for intermediate purification, solvent exchange, or distillation, this solvent-integrated system streamlined the conversion of renewable feedstocks into valuable aromatics.
Overcoming Chemical Barriers in An Unconventional Solvent
A central innovation of this work lies in adapting chemical deoxygenation reactions to function efficiently within IPM—a solvent rarely used in organic synthesis. Traditional catalysts and reagents often proved ineffective under these conditions due to solubility limitations or incompatibility with biologically derived impurities.
Through systematic optimization, the team established mild and selective catalytic strategies compatible with IPM. For example, phenol was successfully deoxygenated to benzene in up to 85% yield using a palladium-based catalytic system, while benzyl alcohol was efficiently converted to toluene after activated charcoal pretreatment of the IPM extract. More challenging transformations, such as converting 2-phenylethanol to ethylbenzene, were achieved through a mesylation–reduction sequence adapted to the IPM phase. Likewise, 2,5-xylenol derived from glycerol was converted to p-xylene in 62% yield via a two-step reaction, completing the renewable synthesis of the full BTEX spectrum.
A Sustainable, Modular Framework
Beyond producing BTEX, the study establishes a generalizable framework for integrating microbial biosynthesis with chemical transformations in a continuous solvent environment. This modular approach reduces energy demand, minimizes solvent waste, and enables process intensification—key factors for scaling up renewable chemical production.
The high boiling point of IPM (>300 °C) simplifies product recovery, as BTEX compounds can be isolated by fractional distillation while the solvent is readily recycled. Such a design is consistent with the principles of green chemistry and the circular economy, providing a practical alternative to fossil-based petrochemical processes.
Toward A Carbon-Neutral Future
Dr. Xuan Zou, the first author of this paper, explaind, “By coupling the selectivity of microbial metabolism with the efficiency of chemical catalysis, this platform establishes a renewable pathway to some of the most widely used building blocks in the chemical industry. Future efforts will focus on optimizing metabolic fluxes, extending the platform to additional aromatic targets, and adopting greener catalytic systems.”
In addition, Distinguished Professor Sang Yup Lee noted “As the global demand for BTEX and related chemicals continues to grow, this innovation provides both a scientific and industrial foundation for reducing reliance on petroleum-based processes. It marks an important step toward lowering the carbon footprint of the fuel and chemical sectors while ensuring a sustainable supply of essential aromatic hydrocarbons.”
This research was supported by the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries Project (2022M3J5A1056117) and the Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry Project (RS-2024-00399424), funded by the National Research Foundation supported by the Korean Ministry of Science and ICT. This study was published in the latest issue of the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
2025.10.13 View 2596 -
World's First Quantum Computing for Lego-like Design of Porous Materials
<(From Left to Right)Professor Jihan Kim, Ph.D. candidate Sinyoung Kang, Ph.D. candidate Younghoon Kim from the Department of Chemical and Biomolecular Engineering>
Multivariate Porous Materials (MTV) are like a 'collection of Lego blocks,' allowing for customized design at a molecular level to freely create desired structures. Using these materials enables a wide range of applications, including energy storage and conversion, which can significantly contribute to solving environmental problems and advancing next-generation energy technologies. Our research team has, for the first time in the world, introduced quantum computing to solve the difficult problem of designing complex MTVs, opening an innovative path for the development of next-generation catalysts, separation membranes, and energy storage materials.
On September 9, Professor Jihan Kim's research team at our university's Department of Chemical and Biomolecular Engineering announced the development of a new framework that uses a quantum computer to efficiently explore the design space of millions of multivariate porous materials (hereafter, MTV).
MTV porous materials are structures formed by the combination of two or more organic ligands (linkers) and building block materials like metal clusters. They have great potential for use in the energy and environmental fields. Their diverse compositional combinations llow for the design and synthesis of new structures. Examples include gas adsorption, mixed gas separation, sensors, and catalysts.
However, as the number of components increases, the number of possible combinations grows exponentially. It has been impossible to design and predict the properties of complex MTV structures using the conventional method of checking every single structure with a classical computer.
The research team represented the complex porous structure as a 'network (graph) drawn on a map' and then converted each connection point and block type into qubits that a quantum computer can handle. They then asked the quantum computer to solve the problem: "Which blocks should be arranged at what ratio to create the most stable structure?"
<Figure1. Overall schematics of the quantum computing algorithm to generate feasible MTV porous materials. The algorithm consists of two mapping schemes (qubit mapping and topology mapping) to allocate building blocks in a given connectivity. Different configurations go through a predetermined Hamiltonian, which is comprised of a ratio term, occupancy term, and balance term, to capture the most feasible MTV porous material>
Because quantum computers can calculate multiple possibilities simultaneously, it's like spreading out millions of Lego houses at once and quickly picking out the sturdiest one. This allows them to explore a vast number of possibilities—which a classical computer would have to calculate one by one—with far fewer resources.
The research team also conducted experiments on four different MTV structures that have been previously reported. The results from the simulation and the IBM quantum computer were identical, demonstrating that the method "actually works well."
<Figure2. VQE sampling results for experimental structures and the structures that reproduce them, using IBM Qiskit's classical simulator. The experimental structure is predicted to be the most probable outcome of the VQE algorithm's calculation, meaning it will be generated as the most stable form of the structure.>
In the future, the team plans to combine this method with machine learning to expand it into a platform that considers not only simple structural design but also synthesis feasibility, gas adsorption performance, and electrochemical properties simultaneously.
Professor Jihan Kim said, "This research is the first case to solve the bottleneck of complex multivariate porous material design using quantum computing." He added, "This achievement is expected to be widely applied as a customized material design technology in fields where precise composition is key, such as carbon capture and separation, selective catalytic reactions, and ion-conducting electrolytes, and it can be flexibly expanded to even more complex systems in the future."
Ph.D. candidates Sinyoung Kang and Younghoon Kim of the Department of Chemical and Biomolecular Engineering participated as co-first authors in this study. The research results were published in the online edition of the international journal ACS Central Science on August 22.
Paper Title: Quantum Computing Based Design of Multivariate Porous Materials
DOI: https://doi.org/10.1021/acscentsci.5c00918
Meanwhile, this research was supported by the Ministry of Science and ICT's Mid-Career Researcher Support Program and the Heterogeneous Material Support Program.
2025.09.09 View 2384 -
KAIST Develops Bioelectrosynthesis Platform for Switch-Like Precision Control of Cell Signaling
<(From left)Professor Jimin Park, Ph.D candidate Myeongeun Lee, Ph.D cadidate Jaewoong Lee,Professor Jihan Kim>
Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally. A KAIST research team has developed a platform that generates specific signaling molecules in situ from a single precursor under an applied electrical signal, enabling switch-like, precise spatiotemporal control of cellular responses. This approach could provide a foundation for future medical technologies such as electroceuticals, electrogenetics, and personalized cell therapies.
KAIST (President Kwang Hyung Lee) announced on August 11 that a research team led by Professor Jimin Park from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Jihan Kim's group, has developed a 'Bioelectrosynthesis Platform' capable of producing either nitric oxide or ammonia on demand using only an electrical signal. The platform allows control over the timing, spatial range, and duration of cell responses.
Inspired by enzymes involved in nitrite reduction, the researchers implemented an electrochemical strategy that selectively produces nitric oxide or ammonia from a single precursor, nitrite (NO₂⁻). By changing the catalyst, the team generated ammonia or nitric oxide from nitrite using a copper-molybdenum-sulfur catalyst (Cu2MoS4) and an iron-incorporated catalyst (FeCuMS4), respectively.
Through electrochemical measurements and computer simulations, the team revealed that Fe sites in the FeCuMoS4 catalyst bind nitric oxide intermediates more strongly, shifting product selectivity toward nitric oxide. Under the same electrical conditions, the Fe-containing catalyst preferentially produces nitric oxide, whereas the Cu2MoS4 catalyst favors ammonia production.
<Figure 1. Schematic diagram of a bio-electrosynthesis platform that synthesizes a desired signaling substance with an electrical signal (left) and the results of precise cell control using it (right)>
The research team demonstrated biological functionality by using the platform to activate ion channels in human cells. Specifically, electrochemically produced nitric oxide activated TRPV1 channels (responsive to heat and chemical stimuli), while electrochemically produced ammonia induced intracellular alkalinization and activated OTOP1 proton channels. By tuning the applied voltage and electrolysis duration, the team modulated the onset time, spatial extent, and termination of cellular responses, which effectively turned cellular signaling on and off like a switch.
<Figure 2. Experimental results showing the change in the production ratio of nitric oxide and ammonia signaling substances according to the type of catalyst (left) and computational simulation results showing the strong bond between iron and nitric oxide (right)>
Professor Jimin Park said, "This work is significant because it enables precise cellular control by selectively producing signaling molecules with electricity. We believe it has strong potential for applications in electroceutical technologies targeting the nervous system or metabolic disorders."
Myeongeun Lee and Jaewoong Lee, Ph.D. students in the Department of Chemical and Biomolecular Engineering at KAIST, served as the co-first authors. Professor Jihan Kim is a co-author. The paper was published online in 'Angewandte Chemie International Edition' on July 8, 2025 (DOI: 10.1002/ange.202508192).
Reference: https://doi.org/10.1002/ange.202508192
Authors: Myeongeun Lee†, Jaewoong Lee†, Yongha Kim, Changho Lee, Sang Yeon Oh, Prof. Jihan Kim, Prof. Jimin Park*
†These authors contributed equally. *Corresponding author.
2025.08.12 View 3757 -
A KAIST Team Engineers a Microbial Platform for Efficient Lutein Production
<(From Left) Ph.D. Candidate Hyunmin Eun, Distinguished Professor Sang Yup Lee, , Dr. Cindy Pricilia Surya Prabowo>
The application of systems metabolic engineering strategies, along with the construction of an electron channeling system, has enabled the first gram-per-liter scale production of lutein from Corynebacterium glutamicum, providing a viable alternative to plant-derived lutein production.
A research group at KAIST has successfully engineered a microbial strain capable of producing lutein at industrially relevant levels. The team, led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, developed a novel C. glutamicum strain using systems metabolic engineering strategies to overcome the limitations of previous microbial lutein production efforts. This research is expected to be beneficial for the efficient production of other industrially important natural products used in food, pharmaceuticals, and cosmetics.
Lutein is a xanthophyll carotenoid found in egg yolk, fruits, and vegetables, known for its role in protecting our eyes from oxidative stress and reducing the risk of macular degeneration and cataracts. Currently, commercial lutein is predominantly extracted from marigold flowers; however, this approach has several drawbacks, including long cultivation times, high labor costs, and inefficient extraction yields, making it economically unfeasible for large-scale production. These challenges have driven the demand for alternative production methods.
To address these issues, KAIST researchers, including Ph.D. Candidate Hyunmin Eun, Dr. Cindy Pricilia Surya Prabowo, and Distinguished Professor Sang Yup Lee, applied systems metabolic engineering strategies to engineer C. glutamicum, a GRAS (Generally Recognized As Safe) microorganism widely used in industrial fermentation. Unlike Escherichia coli, which was previously explored for microbial lutein production, C. glutamicum lacks endotoxins, making it a safer and more viable option for food and pharmaceutical applications.
The team’s work, entitled “Gram-per-litre scale production of lutein by engineered Corynebacterium,” was published in Nature Synthesis on 04 July , 2025.
This research details the high-level production of lutein using glucose as a renewable carbon source via systems metabolic engineering. The team focused on eliminating metabolic bottlenecks that previously limited microbial lutein synthesis. By employing enzyme scaffold-based electron channeling strategies, the researchers improved metabolic flux towards lutein biosynthesis while minimizing unwanted byproducts.
<Lutein production metabolic pathway engineering>
To enhance productivity, bottleneck enzymes within the metabolic pathway were identified and optimized. It was determined that electron-requiring cytochrome P450 enzymes played a major role in limiting lutein biosynthesis. To overcome this limitation, an electron channeling strategy was implemented, where engineered cytochrome P450 enzymes and their reductase partners were spatially organized on synthetic scaffolds, allowing more efficient electron transfer and significantly increasing lutein production.
The engineered C. glutamicum strain was further optimized in fed-batch fermentation, achieving a record-breaking 1.78 g/L of lutein production within 54 hours, with a content of 19.51 mg/gDCW and a productivity of 32.88 mg/L/h—the highest lutein production performance in any host reported to date. This milestone demonstrates the feasibility of replacing plant-based lutein extraction with microbial fermentation technology.
“We can anticipate that this microbial cell factory-based mass production of lutein will be able to replace the current plant extraction-based process,” said Ph.D. Candidate Hyunmin Eun. He emphasized that the integrated metabolic engineering strategies developed in this study could be broadly applied for the efficient production of other valuable natural products used in pharmaceuticals and nutraceuticals.
<Schematic diagram of microbial-based lutein production platform>
“As maintaining good health in an aging society becomes increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other medically and nutritionally significant natural products,” added Distinguished Professor Sang Yup Lee.
This work is supported by the Development of Next-generation Biorefinery Platform Technologies for Leading Bio-based Chemicals Industry project 2022M3J5A1056072 and the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries project 2022M3J5A1056117 from the National Research Foundation supported by the Korean Ministry of Science and ICT.
Source:
Hyunmin Eun (1st), Cindy Pricilia Surya Prabowo (co-1st), and Sang Yup Lee (Corresponding). “Gram-per-litre scale production of lutein by engineered Corynebacterium”. Nature Synthesis (Online published)
For further information:
Sang Yup Lee, Distinguished Professor of Chemical and Biomolecular Engineering, KAIST (leesy@kaist.ac.kr, Tel: +82-42-350-3930)
2025.07.14 View 5072 -
KAIST Presents a Breakthrough in Overcoming Drug Resistance in Cancer – Hope for Treating Intractable Diseases like Diabetes
<(From the left) Prof. Hyun Uk Kim, Ph.D candiate Hae Deok Jung, Ph.D candidate Jina Lim, Prof.Yoosik Kim from the Department of Chemical and Biomolecular Engineering>
One of the biggest obstacles in cancer treatment is drug resistance in cancer cells. Conventional efforts have focused on identifying new drug targets to eliminate these resistant cells, but such approaches can often lead to even stronger resistance. Now, researchers at KAIST have developed a computational framework to predict key metabolic genes that can re-sensitize resistant cancer cells to treatment. This technique holds promise not only for a variety of cancer therapies but also for treating metabolic diseases such as diabetes.
On the 7th of July, KAIST (President Kwang Hyung Lee) announced that a research team led by Professors Hyun Uk Kim and Yoosik Kim from the Department of Chemical and Biomolecular Engineering had developed a computational framework that predicts metabolic gene targets to re-sensitize drug-resistant breast cancer cells. This was achieved using a metabolic network model capable of simulating human metabolism.
Focusing on metabolic alterations—key characteristics in the formation of drug resistance—the researchers developed a metabolism-based approach to identify gene targets that could enhance drug responsiveness by regulating the metabolism of drug-resistant breast cancer cells.
< Computational framework that can identify metabolic gene targets to revert the metabolic state of the drug-resistant cells to that of the drug-sensitive parental cells>
The team first constructed cell-specific metabolic network models by integrating proteomic data obtained from two different types of drug-resistant MCF7 breast cancer cell lines: one resistant to doxorubicin and the other to paclitaxel. They then performed gene knockout simulations* on all of the metabolic genes and analyzed the results.
*Gene knockout simulation: A computational method to predict changes in a biological network by virtually removing specific genes.
As a result, they discovered that suppressing certain genes could make previously resistant cancer cells responsive to anticancer drugs again. Specifically, they identified GOT1 as a target in doxorubicin-resistant cells, GPI in paclitaxel-resistant cells, and SLC1A5 as a common target for both drugs.
The predictions were experimentally validated by suppressing proteins encoded by these genes, which led to the re-sensitization of the drug-resistant cancer cells.
Furthermore, consistent re-sensitization effects were also observed when the same proteins were inhibited in other types of breast cancer cells that had developed resistance to the same drugs.
Professor Yoosik Kim remarked, “Cellular metabolism plays a crucial role in various intractable diseases including infectious and degenerative conditions. This new technology, which predicts metabolic regulation switches, can serve as a foundational tool not only for treating drug-resistant breast cancer but also for a wide range of diseases that currently lack effective therapies.”
Professor Hyun Uk Kim, who led the study, emphasized, “The significance of this research lies in our ability to accurately predict key metabolic genes that can make resistant cancer cells responsive to treatment again—using only computer simulations and minimal experimental data. This framework can be widely applied to discover new therapeutic targets in various cancers and metabolic diseases.”
The study, in which Ph.D. candidates JinA Lim and Hae Deok Jung from KAIST participated as co-first authors, was published online on June 25 in Proceedings of the National Academy of Sciences (PNAS), a leading multidisciplinary journal that covers top-tier research in life sciences, physics, engineering, and social sciences.
※ Title: Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets ※ DOI: https://doi.org/10.1073/pnas.2425384122 ※ Authors: JinA Lim (KAIST, co-first author), Hae Deok Jung (KAIST, co-first author), Han Suk Ryu (Seoul National University Hospital, corresponding author), Yoosik Kim (KAIST, corresponding author), Hyun Uk Kim (KAIST, corresponding author), and five others.
This research was supported by the Ministry of Science and ICT through the National Research Foundation of Korea, and the Electronics and Telecommunications Research Institute (ETRI).
2025.07.08 View 5673 -
Algorithm Identifies Optimal Pairs for Composing Metal-Organic Frameworks
The integration of metal-organic frameworks (MOFs) and other metal nanoparticles has increasingly led to the creation of new multifunctional materials. Many researchers have integrated MOFs with other classes of materials to produce new structures with synergetic properties.
Despite there being over 70,000 collections of synthesized MOFs that can be used as building blocks, the precise nature of the interaction and the bonding at the interface between the two materials still remains unknown. The question is how to sort out the right matching pairs out of 70,000 MOFs.
An algorithmic study published in Nature Communications by a KAIST research team presents a clue for finding the perfect pairs. The team, led by Professor Ji-Han Kim from the Department of Chemical and Biomolecular Engineering, developed a joint computational and experimental approach to rationally design MOF@MOFs, a composite of MOFs where an MOF is grown on a different MOF.
Professor Kim’s team, in collaboration with UNIST, noted that the metal node of one MOF can coordinately bond with the linker of a different MOF and the precisely matched interface configurations at atomic and molecular levels can enhance the likelihood of synthesizing MOF@MOFs.
They screened thousands of MOFs and identified optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal node of one MOF can form coordination bonds with the linkers of the second MOF. Six pairs predicted from the computational algorithm successfully grew into single crystals.
This computational workflow can readily extend into other classes of materials and can lead to the rapid exploration of the composite MOFs arena for accelerated materials development. Even more, the workflow can enhance the likelihood of synthesizing MOF@MOFs in the form of large single crystals, and thereby demonstrated the utility of rationally designing the MOF@MOFs.
This study is the first algorithm for predicting the synthesis of composite MOFs, to the best of their knowledge. Professor Kim said, “The number of predicted pairs can increase even more with the more general 2D lattice matching, and it is worth investigating in the future.”
This study was supported by Samsung Research Funding & Incubation Center of Samsung Electronics.
(Figure: An example of a rationally synthesized MOF@MOFs (cubic HKUST-1@MOF-5 ))
2019.08.30 View 22333 -
Researchers Describe a Mechanism Inducing Self-Killing of Cancer Cells
(Professor Kim (left) and lead author Lee)
Researchers have described a new mechanism which induces the self-killing of cancer cells by perturbing ion homeostasis. A research team from the Department of Biochemical Engineering has developed helical polypeptide potassium ionophores that lead to the onset of programmed cell death. The ionophores increase the active oxygen concentration to stress endoplasmic reticulum to the point of cellular death.
The electrochemical gradient between extracellular and intracellular conditions plays an important role in cell growth and metabolism. When a cell’s ion homeostasis is disturbed, critical functions accelerating the activation of apoptosis are inhibited in the cell.
Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death have been unclear and the bio-applicability has been limited. In the study featured at Advanced Science, the team presented an alpha helical peptide-based anticancer agent that is capable of transporting potassium ions with water solubility. The cationic, hydrophilic, and potassium ionic groups were combined at the end of the peptide side chain to provide both ion transport and hydrophilic properties.
These peptide-based ionophores reduce the intracellular potassium concentration and at the same time increase the intracellular calcium concentration. Increased intracellular calcium concentrations produce intracellular reactive oxygen species, causing endoplasmic reticulum stress, and ultimately leading to apoptosis.
Anticancer effects were evaluated using tumor-bearing mice to confirm the therapeutic effect, even in animal models. It was found that tumor growth was strongly inhibited by endoplasmic stress-mediated apoptosis.
Lead author Dr. Dae-Yong Lee said, “A peptide-based ionophore is more effective than conventional chemotherapeutic agents because it induces apoptosis via elevated reactive oxygen species levels. Professor Yeu-Chun Kim said he expects this new mechanism to be widely used as a new chemotherapeutic strategy. This research was funded by the National Research Foundation.
2019.08.28 View 26663