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KAIST Develops a Genetic Switch That Works in Both Bacteria and Yeast
Microbial cell factories that produce pharmaceutical ingredients and other useful compounds include both the bacterium Escherichia coli and yeast, the organism used to leaven bread and ferment alcohol. The two organisms turn genes on by different rules, so a production design built for one has been hard to transfer to the other. A KAIST research team has now built a gene control element that works in both and tested it using a green pigment whose production requires several genes working together. The work is expected to help researchers select the microbe best suited to producing a target compound.
KAIST (President Choongsik Bae) announced on September 28 that a research team led by Professor Juyoung Lee from the Graduate School of Engineering Biology has developed a "hybrid promoter," a gene control element that works in both E. coli and yeast, two very different types of microorganism.
For a microbe to make a target compound, the genes responsible for producing it must be turned on. A promoter is the stretch of DNA located in front of a gene that controls how strongly that gene works.
The challenge is that E. coli and yeast turn genes on in different ways, and a promoter that performs well in E. coli may not work at all in yeast. Making the same compound in a different microbe has therefore required choosing a promoter suited to that host and retuning the output of each gene from the beginning.
The team's hybrid promoter combines, within a single sequence, DNA elements that E. coli and yeast each recognize. It is, in effect, a shared control element designed so that each organism can find the signals it needs even though the two read genes differently. By varying the combination of these elements, the researchers built a series of promoters spanning a range of strength from weak to strong.
The promoters worked in both hosts, and combinations that were strong in E. coli were generally strong in yeast as well. That does not mean the two microbes make equal amounts of a compound; it means the relative ranking of promoter strengths from weak to strong is preserved across hosts.
The team then tested whether the new control element could do more than turn on a single gene and could also be used for actual compound production. For this, they chose a green pigment whose production requires three genes acting in sequence. Under the strong control element, pigment output was about 3.1 times higher in E. coli and about 2.6 times higher in yeast than under the weak one. The result shows that the system can control the amount of a compound produced in both microbes. The team also confirmed that the promoters worked in other types of bacteria and yeast.
The approach could help researchers identify which microbe is best suited to producing a given compound, since the same gene control design can be applied across several microbes and the production results can be compared. It may reduce the need to redesign control elements from scratch whenever the host changes, although improving actual output will still require host-specific tuning.
"What matters about this work is that it gives us a common design principle, one that lets us predict a promoter's relative strength even when the microbe changes," said Professor Juyoung Lee. She added that she expects the approach to speed up biomanufacturing by making it faster to design and compare a range of microbial cell factories.
So-Hee Son, Soo Young Moon, and Nan-Yeong An of KAIST are co-first authors on the paper, which was published in Nucleic Acids Research on September 23 and first appeared online on September 8.
Paper title: Modular synthetic cross-kingdom promoters enable coordinated expression in Escherichia coli and Saccharomyces cerevisiae,
DOI: https://doi.org/10.1093/nar/gkag868
This work was supported by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF) through the Bio & Medical Technology Development Program (RS-2024-00445145) and the Basic Science Research Program (RS-2025-00518119), with additional support from the Korea-US Collaborative Research Fund (KUCRF), funded by MSIT and the Ministry of Health & Welfare (RS-2024-00468410).
2026.09.28 View 1746 -
KAIST Develops a Strategy to Balance Radical Generation and Catalyst Regeneration, Enabling Challenging Chemical Reactions
Radicals, atoms or molecules that readily react with other substances to form new bonds, are useful tools for building complex substances such as pharmaceuticals. But even when a radical is generated efficiently, the reaction cannot continue unless the catalyst returns to its original state. A KAIST research team has developed a new strategy that balances radical generation and catalyst regeneration, broadening the possibility of using even substrates that are difficult to activate to synthesize the complex molecules needed for pharmaceuticals and other applications.
KAIST (President Choongsik Bae) announced on September 20 that a research team led by Professor Sarah Yunmi Lee from the Department of Chemistry has developed a method that uses a ligand, a molecule that attaches to a metal catalyst and controls its properties, to effectively regulate the process by which a copper catalyst generates a radical and then returns to its original state.
The team used a cyclopropenimine (CPI)-based ligand to tune the copper catalyst’s redox behavior, helping it generate radicals and return to its active state.
In this study, the team used tertiary alkyl halides, compounds where bromine or chlorine is attached to a tertiary carbon center, as starting materials. When the copper catalyst breaks this bond, a highly reactive radical is generated, and this radical then forms a new carbon–carbon bond with another part of the same molecule, creating a ring-shaped structure. The process is similar to tying the two loose ends of a string together to form a loop. This is called a radical cyclization reaction.
When the team compared several types of ligands, they found that that generating more radicals did not necessarily lead to more of the desired product. Some ligands were very effective at generating radicals but produced almost none of the final product.
The best-performing CPI-based ligand, however, allowed radical generation and catalyst regeneration to proceed in balance. If the catalyst is compared to a worker performing a task repeatedly, the CPI ligand acts as a helper that lets the worker move on to the next task without stopping after finishing one.
As a result, the team synthesized in high yields 3,3-disubstituted oxindoles, compounds with a ring framework relevant to medicinal chemistry used in pharmaceuticals and bioactive substances.
Notably, substrates bearing bromine reacted efficiently even at room temperature. The team also succeeded in reacting substrates with strong carbon-chlorine bonds that do not break easily. This demonstrated that even tertiary alkyl chlorides, which had previously been difficult to handle, can now be used to synthesize a range of oxindole compounds that were difficult to make before.
The key finding of this study is that generating radicals well is not enough on its own. Rather than simply raising the reactivity of a single step, the team showed that balancing the entire catalytic cycle, including both radical generation and catalyst regeneration, makes it possible to design more efficient catalysts and extend the approach to new reactions.
This principle could expand the range of challenging substrates available for chemical synthesis. It may also help researchers develop more efficient methods for constructing complex molecules relevant to pharmaceuticals and other bioactive compounds under milder conditions.
Professor Sarah Yunmi Lee said, " This study shows that efficient radical generation alone is not sufficient and that the different processes within a catalytic cycle must proceed in balance." She added, "We expect this approach can be applied to the development of new radical-based catalytic reactions that make use of challenging substrates that have previously been difficult to activate."
The study, with Sarah Jang, a student in the integrated master’s–PhD program in the Department of Chemistry at KAIST, and Seongryeol Jeung, who earned a master’s degree at Yonsei University, as co-first authors, and with Sumin Kim, an integrated master's and PhD student in the Department of Chemistry at KAIST, also participating, was published online on August 3 in the Journal of the American Chemical Society (JACS), an international journal published by the American Chemical Society (ACS).
Paper title: Cyclopropenimine-Enabled Redox Control in Copper-Catalyzed Radical Cyclization to 3,3-Disubstituted Oxindoles
DOI: 10.1021/jacs.6c09015
Author information: Sarah Jang (KAIST, co-first author), Seongryeol Jeung (Yonsei University, co-first author), Sumin Kim (KAIST, third author), Sarah Yunmi Lee (KAIST, corresponding author)
This research was supported by the Samsung Science and Technology Foundation under Project SSTF-BA2202-06.
2026.09.21 View 2505 -
KAIST Develops Microbially Produced Adhesive Materials from Glucose Instead of Petroleum
KAIST researchers have demonstrated the potential of using microorganisms to produce a bio-based alternative to petroleum-derived materials for hot-melt adhesives. These heat-activated glues are widely used in packaging, furniture, electronics, and automobiles. Using Escherichia coli, the team produced a new polymer from glucose and demonstrated adhesive performance and thermal properties that support its potential use as a hot-melt adhesive.
KAIST (President Choongsik Bae) announced on September 17 that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering developed a microbial cell factory by engineering E. coli to produce the new aromatic polyhydroxyalkanoate (PHA) polymers from glucose for adhesive applications.
The research team applied systems metabolic engineering, an approach that redesigns a microorganism's overall metabolism to produce a target compound, to re-engineer the metabolic pathways of E. coli. Through this approach, the researchers successfully produced two new adhesive materials from glucose, poly(4HB-co-PhLA) and poly(3HB-co-4HB-co-PhLA), both belonging to the PHA family of biodegradable polymers.
Adhesives are essential materials used in a wide range of industries, including packaging materials, electronics, automobiles, and construction materials. In particular, hot-melt adhesives (HMAs) are solid adhesives that are melted with heat for bonding and then solidify as they cool. Because they do not require separate organic solvents and enable rapid bonding, they are widely used in industry.
However, most hot-melt adhesives currently in use are based on petroleum-derived polymers such as ethylene-vinyl acetate (EVA). Although they offer excellent adhesive performance, most do not readily degrade in nature and can cause waste and microplastic problems. In particular, even when biodegradable packaging materials are used, if the adhesive does not degrade, the biodegradability and recyclability of the entire product may be reduced.
To address this problem, the research team focused on PHA, a type of biodegradable plastic produced by microorganisms. PHA can be produced by microorganisms using renewable feedstocks such as glucose. It also has the advantage that properties such as polymer flexibility, strength, and heat resistance can be adjusted in various ways depending on which components are included and in what proportions.
Using this principle, the research team incorporated 4-hydroxybutyrate (4HB) and phenyllactate (PhLA) into a single polymer. 4HB contributes to the material’s softness and adhesion, while PhLA increases the material’s rigidity and heat resistance. When the research team varied the relative proportions of the two components, the thermal properties and adhesive performance of the polymers also changed. In particular, polymers containing approximately 24–34 mol% 4HB showed excellent adhesive performance.
The research team designed intracellular metabolic pathways so that E. coli consumes glucose, produces 4HB and PhLA on its own, and then links them together into polymers.
To address metabolic imbalances that arise when multiple monomers are produced simultaneously, the team adjusted the strength and timing of gene expression, added a CoA transferase to facilitate the reactions, and used a genome-scale metabolic model to identify and optimize metabolic pathways associated with insufficient precursor supply and production bottlenecks.
As a result, through fed-batch fermentation, in which nutrients are continuously supplied during microbial cultivation, the team successfully produced 10.2 g of poly(4HB-co-PhLA) per liter of culture medium. By additionally introducing a biosynthetic pathway for producing 3HB, the team successfully produced up to 52.8 g/L of poly(3HB-co-4HB-co-PhLA).
The research team also tested whether the produced polymers could be used as hot-melt adhesives.
In a lap shear adhesion test using stainless steel as the substrate, poly(4HB-co-PhLA) recorded a lap-shear strength of 4.58 MPa. This is higher than the 4.20 MPa achieved by a commercial EVA adhesive. Poly(3HB-co-4HB-co-PhLA) also showed performance comparable to EVA in a wood adhesion test.
In addition, poly(4HB-co-PhLA) retained a substantial level of adhesive strength even after repeated melting and rebonding. The incorporation of the PhLA component improved heat resistance.
Furthermore, after treatment with lipase, an enzyme that breaks down fats, surface damage to the polymers was observed, while the molecular weight and overall mass of the polymers also decreased. These results indicate that the newly developed aromatic PHA can be degraded by enzymes.
This study is significant not only for the development of an eco-friendly adhesive but also for demonstrating the potential of metabolic engineering to produce functional materials with tunable properties. Going forward, this approach could be extended into a biomanufacturing technology that tunes polymer properties, such as adhesion strength, flexibility, and heat resistance, to meet specific application needs, and produces such materials using microorganisms.
The approach also makes it possible to produce functional polymers that have traditionally been produced through petrochemical processes, from renewable feedstocks such as glucose instead. This is expected to serve as a sustainable production technology not only for adhesives but for a wide range of functional polymer materials going forward.
Distinguished Professor Sang Yup Lee said, “This study demonstrates that by engineering microbial metabolism, it is possible to go beyond simply producing polymers and directly produce functional materials,” adding, “In the future, by utilizing various non-natural monomers and microbial cell factories, this approach could be expanded into biomanufacturing technologies for the sustainable production not only of petroleum-based adhesive alternatives but also of a wide range of functional polymers.”
The study, co-authored by Ph.D. student Minju Kang, Dr. Youngjoon Lee, and Dr. Gi Bae Kim of the KAIST Department of Chemical and Biomolecular Engineering, was published online on July 20 in the international journal Nature Communications.
Paper title: Synthesis of poly(4HB-co-PhLA) and poly(3HB-co-4HB-co-PhLA) as sustainable hot-melt adhesives using engineered Escherichia coli
DOI: 10.1038/s41467-026-75809-9
Author information: Minju Kang (KAIST), Youngjoon Lee (KAIST), Gi Bae Kim (KAIST), Sang Yup Lee (KAIST, corresponding author)
This research was supported by the National Research Foundation of Korea through a grant funded by the Ministry of Science and ICT. (Grant No. 2022M3J5A1056117).
2026.09.17 View 4470 -
KAIST Identifies Cause of Artifacts in Battery Nanoscale Analysis, Paving the Way for More Reliable Measurements
A signal that appears to show ions moving inside a battery may, in fact, be an illusion caused by an uneven surface. A KAIST research team has identified the origin of this type of artifacts, which can lead researchers to misinterpret what is happening inside a battery, and has developed a method to reduce it. The findings are expected to enable more accurate analysis of ion movement and improve the reliability of next-generation battery-material development, including that of solid-state and sodium-ion batteries.
KAIST (President Choongsik Bae) announced on September 7 that a research team led by Professor Seungbum Hong from the Department of Materials Science and Engineering, in collaboration with the research groups of Professor Jong Min Yuk from the same department and Professor Nam-Soon Choi from the Department of Chemical and Biomolecular Engineering, has identified the cause of a measurement artifact in nanoscale battery analysis that can be mistaken for actual ion transport. The team also proposed a method for effectively reducing this artifact.
During charging and discharging, lithium or sodium ions move back and forth within a battery. The speed and ease with which these ions move affect the battery’s performance and lifespan. Developing better batteries therefore requires researchers to precisely determine where ions can move freely and where their movement is hindered.
One technique used for this type of analysis is Electrochemical Strain Microscopy (ESM), which is based on Atomic Force Microscopy (AFM). ESM scans the surface of a battery material with an extremely fine tip and measures nanoscale changes in the material associated with ion movement, allowing researchers to indirectly track ion transport.
The problem is that when the surface of a battery material is rough, similar signals can appear even in the absence of actual ion movement. If these signals are interpreted as evidence of ion transport, researchers may incorrectly identify where ions are moving within the material.
To investigate the origin of theseartifactss, the team created fine trenches on the surface of an ionically inactive single-crystal silicon sample. This provided an experimental environment in which no ions were moving, while the sample surface remained uneven.
The results quantitatively demonstrated that variations in surface height alone can alter the degree of contact between the microscope tip and the sample, producing signals similar to those generated by actual ion movement.
The same phenomenon was also observed in actual battery materials. When the team analyzed a graphite anode and the sodium solid electrolyte Na₂Zn₂TeO₆, the ESM signals likewise varied according to surface topography. This confirmed that the issue is not limited to a particular material but is a phenomenon that researchers must account for when conducting nanoscale analyses of a wide range of battery materials.
As a solution, the team proposed making the surfaces of battery materials as smooth and flat as possible. To achieve this, the researchers used a cooling cross-section polisher (CCP), which employs an argon (Ar) ion beam to precisely polish sample cross sections. Because argon is chemically inert under most conditions, this technique allows the surface to be processed precisely without significantly altering the properties of the sample.
This treatment substantially reduced surface roughness and, in turn, decreased measurement artifacts caused by uneven surfaces. The mechanism is comparable to a car moving up and down while traveling over a bumpy road: as the scanning tip passes over height variations on the surface of a battery material, the degree of contact between the tip and the sample changes. These changes can generate signals resembling those produced by actual ion movement.
In particular, the team examined signals detected at grain boundaries—the interfaces at which the small crystals that make up a battery material meet, much like the seams between adjacent tiles.
Before the surface was smoothed, strong ESM signals appeared at these grain boundaries. After the surface was polished, however, the enhanced signals disappeared. This finding indicates that some signals previously interpreted as evidence of “pathways that facilitate ion transport” may actually have resulted from variations in surface height rather than genuine ion movement.
This study is significant because it experimentally demonstrates how this type of measurement artifact arises in nanoscale battery analysis and shows that it can be reduced using the practical approach of smoothing battery-material surfaces.
The findings are expected to provide a more accurate understanding of where ions move freely and where their movement is hindered within a battery. Such insights could provide an important foundation for designing battery materials that facilitate ion transport, thereby enabling faster charging and longer battery life.
The team expects this analytical approach to be applicable not only to widely used lithium-ion batteries but also to next-generation battery systems. These include solid-state batteries, which use solid rather than liquid electrolytes, and sodium-ion batteries, which use sodium ions in place of lithium ions. The approach could help researchers more accurately understand how these batteries operate and support the design of new materials.
Furthermore, the accumulation of reliable nanoscale analysis data could provide high-quality training datasets for artificial intelligence (AI) and machine-learning research aimed at designing new battery materials and predicting their performance.
“This research clearly demonstrates how variations in surface height affect the results of nanoscale battery-material analysis,” said Professor Hong. “We expect our findings to enable more accurate tracking of ion movement within batteries and contribute to understanding the operating mechanisms of next-generation battery materials and designing improved materials.”
Dongyan Chen, a PhD student in the Department of Materials Science and Engineering, served as the first author of the study, which was published in Small Methods, an international journal specializing in materials science and nanotechnology.
Paper title: Quantitative Analysis of Topographic Crosstalk in DART-ESM Arising from Feedback-Loop-Delay-Induced Contact Stiffness Variations in Battery Materials
DOI: https://doi.org/10.1002/smtd.70763
This work was supported by National Research Foundation of Korea (NRF) grants funded by the Korean government’s Ministry of Science and ICT (MSIT) (Nos. RS-2026-25468150 and RS-2023-00247245).
2026.09.07 View 2976 -
KAIST Opens the Era of Industrial-Scale Microbial Foods, Proposing Growth Strategies for the Next-Generation Protein Market
The question is no longer whether microbial foods can be made. The question now is who can turn them into an industry first. KAIST researchers have comprehensively analyzed the conditions required for the microbial food industry to succeed across manufacturing, markets, and regulation, and have proposed growth strategies for the next-generation protein industry.
KAIST (President Choongsik Bae) announced on the 31st of July that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, together with researchers from SilicoBio, a KAIST faculty startup, has comprehensively analyzed the conditions needed for the microbial food industry to succeed in terms of manufacturing, market entry, and regulatory readiness, and has presented an industrialization strategy and roadmap.
This study is significant in that it did not develop a new microorganism or production technology, but instead systematically analyzed the key challenges involved in connecting laboratory-based core technologies to real-world industry. In particular, by presenting an integrated perspective that encompasses manufacturing readiness, market entry strategies, and regulatory responses, the study proposes a direction for developing microbial foods beyond the next-generation protein industry into a future biomanufacturing platform. It is expected to serve as an important milestone for strengthening national biomanufacturing competitiveness and fostering the global sustainable food industry.
The researchers analyzed that competition in the microbial food industry is shifting from productivity at the laboratory level to manufacturing readiness. They identified stable raw material supply and quality control, control and safety assurance of non-model microorganisms, reduction of downstream processing costs, and regulatory compliance for byproduct recycling as key factors that will determine the pace of commercialization. Manufacturing Readiness refers to the level at which a laboratory technology can be reliably produced at industrial scale. Non-model microorganisms are microorganisms with high industrial potential but insufficient accumulated research infrastructure. Downstream processing refers to the processes of separating, purifying, concentrating, and drying target components after fermentation.
The researchers particularly emphasized that future competitiveness will depend less on the excellence of any single technology and more on the ability to build integrated manufacturing platforms. An Integrated Manufacturing Platform refers to a production system that operates the entire process as one connected framework, from strain development and large-scale fermentation to purification, quality control, and product formulation. Even for the same microbial food product, the choice of raw material can affect pretreatment costs and quality variability, while the choice of strain and fermentation process can greatly influence production cost, energy use, and product quality. The researchers therefore concluded that future industrial competitiveness will depend on how quickly companies can build manufacturing platforms that optimize these factors in an integrated way.
On the market side, the researchers also identified the conditions needed for the microbial food industry to succeed. Based on consumer surveys and industry cases, they found that microbial foods cannot spread simply by emphasizing environmental sustainability. Consumers place importance on taste, texture, familiarity, and safety, while food manufacturers value functionality that can be applied to actual products. Companies and investors, meanwhile, consider the predictability of regulatory approval procedures and speed of market entry to be especially important. In other words, the microbial food market has entered an industrial stage where not only technology, but also product development capability and regulatory readiness are evaluated together.
The researchers also argued that microbial foods should not be viewed merely as an alternative protein industry. They suggested that microbial foods have the potential to develop into a core platform for precision fermentation-based functional food ingredients, high-value biomaterials, and circular biomanufacturing. Precision Fermentation is a technology that uses microorganisms to selectively produce specific proteins or functional substances. Circular Biomanufacturing refers to a sustainable manufacturing system that uses byproducts and renewable resources to produce new bio-based products. This means that microbial foods could become not only a future food source, but also a new production system connecting the global food, materials, and biomanufacturing industries.
The industrialization strategy proposed in this study is also closely aligned with the business direction of SilicoBio, which participated in the joint research. Based on the manufacturing readiness strategy presented in the study, SilicoBio is working to build a platform that connects microbial proteins and functional food ingredients to industrial-scale fermentation, scale-up, and product development. Scale-up refers to the process of expanding production from laboratory scale to industrial scale.
Distinguished Professor Sang Yup Lee of KAIST said, “As global competition surrounding synthetic biology and biomanufacturing intensifies, microbial foods are growing into a key industry that will shape national biomanufacturing competitiveness beyond future food.” He added, “Going forward, competitiveness will be determined by how quickly we can build an industrialization ecosystem that connects core technologies to real production and markets.”
A SilicoBio representative said, “Our goal is to connect the industrialization strategy proposed in this study to actual production and commercialization,” adding, “We will build a platform capable of stably producing microbial-based next-generation foods and functional biomaterials.”
This study, with Seok Yeong Jung, a doctoral student in the Department of Chemical and Biomolecular Engineering, as first author and researchers from SilicoBio participating as co-authors, was published on July 17 in the international journal One Earth (Impact Factor 15.3, JCR top 2.07%).
Paper title: Microbial foods as scalable platforms toward a circular protein economy for sustainable nutrition
DOI: https://doi.org/10.1016/j.oneear.2026.101772
Authors: Sang Yup Lee (KAIST, corresponding author), Seok Yeong Jung (KAIST, first author), Sol Choi (SilicoBio, second author), Jun-Woo Kim (SilicoBio and Inha University, third author), and two others
SilicoBio is a KAIST faculty startup founded in June 2025 by Distinguished Professor Sang Yup Lee, a world-renowned scholar in synthetic biology. The company focuses on connecting laboratory-level achievements in systems metabolic engineering to real industrialization. By combining KAIST’s core technologies with the industrialization experience of personnel from CJ BIO, SilicoBio has built a team capable of reviewing not only strain design, but also industrial-scale fermentation and scale-up, material purification and product development, pilot production, and process validation. Based on this foundation, SilicoBio is pursuing a phased commercialization strategy, starting with next-generation protein products and expanding into functional ingredients and eventually new drug and novel material candidates.
This research was supported by the “Development of Next-Generation Biorefinery Core Technologies to Lead the Biochemical Industry” project under the Petroleum-Alternative Eco-Friendly Chemical Technology Development Program funded by the Ministry of Science and ICT, and by the “Advancement of a Synthetic Biology-Based Industrial Cell Factory Platform and Commercialization of High-Value Functional Biomaterials” project under the Deep Science Startup Activation Support Program funded by the Commercialization Promotion Agency for R&D Outcome.
2026.08.31 View 2830 -
KAIST Develops a Molecular Platform for the Selective Control of Oxygen Reaction Pathways
Controlling how oxygen reacts is important for improving technologies such as batteries, fuel cells, and environmentally sustainable chemical processes. A KAIST research team has developed a new molecular system that can selectively switch the pathway through which electrons are transferred during oxygen activation. The findings are expected to provide a fundamental design principle for next-generation catalysts and energy-conversion technologies.
KAIST (President Choongsik Bae) announced on the 22nd of July that a research team led by Professor Seung Jun Hwang from the Department of Chemistry has developed a molecular system capable of directing oxygen activation along a selected electron-transfer pathway. By combining germanium with a molecular framework that can store and transfer electrons, the team established a design principle for selectively switching oxygen activation between two- and four-electron pathways.
Catalysts for controlling oxygen reactions have traditionally been developed around transition-metal centers such as iron, cobalt, and nickel. Germanium, by contrast, is a main-group element in the same group of the periodic table as silicon and has generally been considered less suitable for reactions requiring the coordinated transfer of several electrons.
To overcome this limitation, the research team combined germanium with a redox-active ligand, a molecular framework capable of storing, accepting, and transferring electrons. The ligand serves as an electron reservoir and cooperates with the germanium center, allowing the entire molecular structure to participate in multielectron reactions.
When oxygen reacts, the products and reaction outcomes depend on whether two or four electrons are transferred. In general, two-electron oxygen reduction produces hydrogen peroxide, while four-electron reduction produces water. Selectively controlling these pathways is therefore an important challenge in the development of batteries, fuel cells, and greener chemical catalysts.
The study presents a rare example of a main-group molecular system in which two- and four-electron reactivity can be selectively accessed within the same underlying molecular framework. This approach broadens the range of elements that may be considered in catalyst design and provides an alternative strategy to relying exclusively on transition metals.
The team also succeeded in isolating and analyzing a germanium compound representing the two-electron stage of the reaction, which they stabilized by attaching a methyl group to the germanium complex. Remarkably, the germanium atom in this compound could both donate and accept electrons, providing an important clue to how the system controls different reaction pathways.
The team also confirmed the practical potential of the new system. Under mild, light-free conditions, the germanium complex removed halogen atoms such as bromine and chlorine from organic compounds and regenerated alkenes (organic compounds containing a carbon-carbon double bond), which are widely used as raw materials for pharmaceuticals, plastics, and other chemical products. These results suggest that useful chemical feedstocks could be produced through simpler and potentially more energy-efficient processes.
“We expect these findings to inform the development of next-generation catalysts for energy conversion and to contribute to more selective and efficient chemical processes.” said Professor Hwang.
The study was conducted by Sung Gyu Kim and Jinrok Oh, currently postdoctoral researchers in the KAIST Department of Chemistry, and Dae Eui Choi, a student in the combined master’s and doctoral program in the Department of Chemistry at POSTECH. The results were published online in the international journal Chem on July 6.
Paper title: Germanium Ligand Redox Cooperativity: A Key to Ambiphilicity and Switchable Two- and Four-Electron Transfer
DOI: 10.1016/j.chempr.2026.103127
This work was supported by National Research Foundation of Korea grants funded by the Korean government through the Ministry of Science and ICT (NRF-2021R1C1C1010220 and RS-2025-02216980), and by the Samsung Science and Technology Foundation under Project No. SSTF-BA2101-09. Sung Gyu Kim received research fellowship support from the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (RS-2024-00415390).
2026.07.22 View 3968 -
KAIST Brings the Era of Microbial Cell Factories One Step Closer
The era of "biomanufacturing", in which microbes, not petroleum, produce chemical products, is one step closer. A KAIST research team has analyzed the key challenges limiting the commercialization of biomanufacturing and proposed an AI-driven strategy for industrialization.
KAIST (President Choongsik Bae) announced on the 14th of July that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering has comprehensively analyzed the key bottlenecks to commercializing biomanufacturing and proposed an industrialization strategy and a roadmap for future growth to address them.
Most chemical products today — including plastics, textiles, and pharmaceutical raw materials — are produced from petroleum. But as concerns over carbon emissions and environmental pollution grow, biomanufacturing, which uses microbes to produce chemicals, is drawing attention as a next-generation manufacturing technology. Still, scaling up lab-developed technologies into economically viable mass production at actual factories remains a major challenge.
Systems metabolic engineering, a core technology in biomanufacturing, designs and optimizes microbial metabolic pathways to build "microbial cell factories" that produce desired chemicals. But technologies that show high productivity in the lab often perform worse once moved to industrial settings — productivity drops, production costs rise, and many fail to achieve price competitiveness, ultimately failing to commercialize.
The research team analyzed succinic acid, a bio-based chemical feedstock, and polyhydroxyalkanoate (PHA), a biodegradable plastic, as representative cases illustrating this "gap between the lab and industry," often called the "valley of death."
Succinic acid is a key raw material for producing eco-friendly plastics and various chemical materials. The team explained that for succinic acid to compete with existing petrochemical products, competitiveness depends not just on production volume, but also on raw material and separation/purification costs, the fermentation process, and market size — all of which must be weighed together. The team also suggested that a phased strategy — entering high-value markets such as pharmaceuticals, cosmetics, and food ingredients first — could be a realistic solution.
PHA is a biodegradable plastic that microbes accumulate inside their cells, an eco-friendly material that breaks down naturally in the environment after use. But PHA is currently less price-competitive than conventional plastics due to high production and recovery costs, and its intrinsic material properties pose a separate barrier: the archetypal polymer P(3HB) is highly crystalline, becomes brittle with age, and has a narrow window between its melting and decomposition temperatures, meaning PHAs are generally not suitable as direct "drop-in" replacements.The team found that a phased approach is needed — simplifying the production process and first applying it to high-value fields such as medical applications and food packaging before expanding into general-purpose markets.
The team predicted that artificial intelligence will become a key to industrializing biomanufacturing going forward. AI can optimize the entire biomanufacturing process — from enzyme and microbial design to digital twins that virtually simulate production processes, and technologies that simultaneously analyze economic feasibility and environmental impact. The team explained that this can shorten development timelines, reduce production costs, and increase the likelihood of successful commercialization.
The team also proposed that techno-economic analysis (TEA) and life cycle assessment (LCA) should be applied as design criteria from the earliest stages of research, rather than as evaluations conducted only after research is complete. The team further emphasized that supply chain resilience — accounting for raw material availability and shifts in the international landscape — should be considered a new design standard for biomanufacturing.
This study is significant not for developing a new production technology, but for comprehensively analyzing the conditions for successful biomanufacturing industrialization and presenting an industrialization roadmap spanning the entire cycle — from securing raw materials to microbial design, fermentation, separation and purification, and market entry. The team expects the study to accelerate the commercialization of the bio-based chemical industry and, over the long term, contribute to shifting the petroleum-centered chemical industry toward an eco-friendly bioeconomy.
The paper, with Ji Yeon Kim and Hye Eun Yu as co-first authors, both Ph.D. candidates in KAIST's Department of Chemical and Biomolecular Engineering, was published online on May 30 in the international journal Nature Communications.
※ Paper title: Beyond petrochemicals: challenges and opportunities in industrial-scale biomanufacturing
※ DOI: 10.1038/s41467-026-73835-1
※ Authors: Ji Yeon Kim (KAIST, co-first author), Hye Eun Yu (KAIST, co-first author), Min Ho Kim (KAIST), Sang Yup Lee (KAIST, corresponding author)
This research was supported by the National Research Foundation of Korea, funded by the Ministry of Science and ICT, through the “Development of Platform Technologies of Microbial Cell Factories for Next-Generation Biorefineries” project (Project No. 2022M3J5A1056117) and the “Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry” project (Project No. RS-2024-00399424).
2026.07.14 View 3912 -
KAIST: Dementia-Causing Substance Turns On a Therapeutic “Switch”
A substance that worsens dementia has become a “switch” that initiates treatment. KAIST researchers have developed a new therapeutic approach that uses hydrogen peroxide (H₂O₂), a reactive oxygen species that damages cells and increases in the brains of patients with Alzheimer’s disease, to activate a drug selectively in diseased brain tissue. The team also confirmed improvements in cognitive function through animal experiments, presenting a new possibility for next-generation dementia treatment.
KAIST announced on the 2nd that a research team led by Professor Mi Hee Lim of the Department of Chemistry, in collaboration with Professor Mingeun Kim of Chonnam National University, Dr. Chul-Ho Lee and Dr. Kyoung-Shim Kim of the Korea Research Institute of Bioscience and Biotechnology, and Dr. Young-Ho Lee of the Korea Basic Science Institute, has developed a prodrug that is activated selectively in the diseased brain in Alzheimer’s disease and confirmed its therapeutic effects through animal experiments.
A prodrug is a drug that initially has minimal therapeutic effect but is converted into an active therapeutic agent only under specific conditions inside the body. In this study, the prodrug was designed to be activated only when it encounters hydrogen peroxide, which increases in the brains of patients with Alzheimer’s disease, allowing it to function as a “smart therapeutic agent” that selectively acts in diseased brain tissue.
In the brains of Alzheimer’s disease patients, hydrogen peroxide, which damages cells, is elevated above normal levels. Until now, it has generally been regarded only as a harmful substance that should be removed. However, the research team devised a method to use it instead as a signal that activates a drug.
The prodrugs developed by the research team, BE-1 and BE-2, are designed to remain minimally reactive in a healthy brain. However, when they encounter hydrogen peroxide in a brain affected by dementia, they are converted into active therapeutic compounds, AP-1 and AP-2. Through this process, they reduce reactive oxygen species, including hydrogen peroxide, while also preventing amyloid beta (Aβ) peptides — peptides known as a major cause of dementia that accumulate in the brain and damage nerve cells — from aggregating into highly toxic clumps.
Using advanced analytical techniques, the research team confirmed that the activated drug alters the morphology of amyloid beta aggregates and suppresses their growth into large aggregates.
These effects were also confirmed in Alzheimer’s disease mouse models. The drug crossed the blood-brain barrier (BBB), a protective barrier that controls whether substances in the blood can enter the brain, and was converted into the therapeutic compound inside the diseased brain. In mice that received long-term drug administration, oxidative stress in the hippocampus, which is responsible for memory, was reduced, and amyloid beta accumulation in the brain also decreased. In behavioral experiments assessing the ability to recognize new objects and navigate mazes, cognitive function was also found to improve.
This study is significant in that the drug was designed to operate only where needed by using the environment of the diseased brain itself. This approach presents a new strategy for dementia treatment that can enhance therapeutic efficacy while reducing side effects, and it is expected to be applicable to the treatment of other neurodegenerative diseases, such as Parkinson’s disease.
Professor Mi Hee Lim of KAIST’s Department of Chemistry said, “This study is meaningful in that hydrogen peroxide, which had previously been regarded only as something to be eliminated, was used as a signal to activate a drug. We expect this strategy, which activates drugs in diseased tissue, to become a new platform for treating complex diseases such as Alzheimer’s disease more safely and effectively.”
This study was co-first-authored by Jimin Lee and Eunseo Hong, Ph.D. candidates in KAIST’s Department of Chemistry, and was published online on May 31, 2026, in the international journal Small (Impact Factor: 12.1, top 10% in the field of chemistry).
※ Paper title: A Prodrug Approach for Activity-Based Chemical Modulation toward Multiple Pathological Targets in Alzheimer’s Disease
DOI: 10.1002/smll.74013
This research was supported by the National Research Foundation of Korea’s Leader Researcher Program, Global Leading Research Center Program, Sejong Science Fellowship, Graduate Student Research Encouragement Program, and institutional programs of KRIBB and KBSI.
2026.07.03 View 6508 -
"KAIST to Produce 'Janus-Faced' Nanomaterials... Paving the Way for New Materials to Selectively Capture Radioactive Pollutants"
<(From Left) Professor Ho Jin Ryu, Dr. Hyun Woo Seong, Dr. Minseok Lee>
The way has been paved for the development of multi-functional materials for applications such as removing radioactive pollutants and shielding electromagnetic waves. A KAIST research team has succeeded, for the first time in the world, in synthesizing the core raw material for fabricating asymmetric MXene, a so-called "Janus-faced" nanomaterial that can implement distinct functions due to differing atomic compositions on its two sides.
<AI-Generated Research Image>
KAIST announced on June 11th that a research team led by Professor Ho Jin Ryu from the Department of Nuclear and Quantum Engineering has successfully synthesized experimentally an asymmetric layered ceramic (a ceramic with an asymmetric structure where atomic layers are stacked on top of each other), which is a required precursor for fabricating asymmetric MXene (a two-dimensional nanomaterial with different atomic compositions on its two sides).
MXene is a two-dimensional nanomaterial with excellent electrical conductivity and high surface reactivity, drawing significant attention in various advanced technology sectors including energy storage devices and sensors. However, the MXenes developed so far possess a symmetric structure with identical atomic compositions on both sides, which has limited the functions they can implement.
In contrast, asymmetric MXenes have different atomic compositions on their two sides, allowing each side to perform distinct functions. This asymmetry enables the emergence of new properties that are difficult to achieve with conventional symmetric-structured materials. In particular, it is expected to be utilized in developing next-generation functional materials, such as adsorption filters for removing radionuclides and materials for absorbing and shielding electromagnetic waves.
Until now, however, the existence of asymmetric MXene had mostly been suggested only through computer simulations, and its actual implementation remained difficult because the raw materials required for manufacturing had not been secured.
To solve this problem, the research team applied a high-entropy material design strategy (a material design approach that mixes multiple elements to achieve new properties). By simultaneously mixing six elements—titanium (Ti), zirconium (Zr), hafnium (Hf), tantalum (Ta), aluminum (Al), and tin (Sn)—they discovered that a stable asymmetric structure, in which the composition of the outer metal atomic layers is arranged differently due to differences in atomic size, forms naturally. This is evaluated as a new structure-forming mechanism that has never been reported in conventional MXene raw materials.
The asymmetric layered ceramic synthesized by the research team acts as a precursor (a raw material for making the final material) that can be converted into asymmetric MXene with different atomic compositions on its two sides when subjected to chemical etching (a process that selectively removes only specific atomic layers).
< Experimental Observations of the Asymmetric Ceramic Structure Synthesized in This Study >
This achievement holds great significance as it establishes the foundation for actually implementing asymmetric MXene, which had previously remained confined to theory. In particular, it presents the possibility of expanding into various advanced technology fields that were difficult to achieve with existing symmetric structures, such as radionuclide capturing, electromagnetic wave shielding, sensors, and piezoelectric devices (devices that convert pressure or vibration into electrical energy).
The research team has currently filed patent applications in South Korea, the United States, and Japan for the asymmetric layered ceramic and the asymmetric MXene utilizing it. They plan to verify the actual radioactive ion removal performance and electromagnetic wave shielding performance through follow-up studies.
Professor Ho Jin Ryu said, "This study is an instance of realizing an asymmetric atomic structure, which was difficult to achieve using conventional crystallography, through a high-entropy material design strategy. We expect that it can be developed into a core original technology in the fields of safety and the environment, such as radionuclide capturing and electromagnetic wave shielding, in the future."
Dr. Minseok Lee of KAIST (currently at the Korea Atomic Energy Research Institute) participated as the first author, and Dr. Hyun Woo Seong of KAIST (currently at the Korea Atomic Energy Research Institute) participated as a co-author. The study was published in the world-renowned scientific journal 'Nature Communications' on April 30. ※ Paper Title: An Asymmetrically Out-of-Plane Ordered MAX Phase as a Precursor for Janus MXenes, DOI : 10.1038/s41467-026-72561-y
Meanwhile, this research was conducted with support from the Nuclear Energy Basic Research Support Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT.
2026.06.11 View 3946 -
KAIST Researchers Unveil Technical Principles Behind Antibacterial Graphene Toothbrushes with 10 Million Units Sold
< (From left) Professor Hyun Jung Chung , Ph.D candidate Ju Yeon Chung, Ph.D candidate Sujin Cha, Professor Sang Ouk Kim >
Hygiene in everyday items that touch the body—such as clothing, masks, and toothbrushes—is critically important. The underlying principle of how graphene selectively eliminates only bacteria has now been revealed. A KAIST research team has presented the potential for a next-generation antibacterial material that is safe for the human body and capable of replacing antibiotics.
KAIST announced on March 25th that a joint research team, led by Professor Sang Ouk Kim from the Department of Materials Science and Engineering and Professor Hyun Jung Chung from the Department of Biological Sciences, has identified the mechanism by which Graphene Oxide (GO) exhibits powerful antibacterial effects against bacteria while remaining harmless to human cells. Graphene oxide is a nanomaterial consisting of an atomic level carbon layer (graphene) with oxygen attached; it is characterized by its ability to mix well with water and implement various functions.
This study is highly significant as it provides molecular-level proof of graphene's antibacterial action, which had not been clearly understood until now.
The research team confirmed that graphene oxide performs "selective antibacterial action" by attaching to and destroying only the membranes of bacteria, much like a magnet attaches only to specific metals, while leaving human cells untouched. This occurs because the oxygen functional groups on the surface of graphene oxide selectively bind with a specific component (POPG) found only in bacterial cell membranes. Simply put, it recognizes a "target" present only in bacterial membranes to attach and destroy the structure. In this context, phospholipids are fatty components that make up the membrane surrounding a cell, and POPG is a component primarily present in bacteria.
< Schematic diagram of the selective interaction between graphene oxide and cell membranes >
< Identification of selective interaction mechanisms at the molecular level through microscopic and chemical analysis of artificial lipid vesicles mimicking cell membranes >
Nanofibers applying this principle effectively inhibited the growth of various pathogenic bacteria, including superbugs resistant to antibiotics. Animal experiments also confirmed its effectiveness in promoting wound healing without inducing inflammation.
< Verification of antibacterial and wound healing enhancement effects in a porcine infected wound model >
Furthermore, fibers using this material maintained their antibacterial functions even after multiple washes, showing potential for use in various industrial fields such as apparel and medical textiles.
This technology is already being applied to consumer products. The graphene antibacterial toothbrush, released through the original patents of the faculty-led startup 'Materials Creation Co., Ltd.,' has sold over 10 million units, proving its commercial viability. Additionally, GrapheneTex—textile materiala incorporating this technology—was used in the uniforms of the Taekwondo demonstration team at the 2024 Paris Olympics and is expected to play an active role in functional sportswear at upcoming international sporting events like the 2026 Asian Games.
< Commercially available graphene toothbrush >
< Graphene material image (AI-generated image) >
Professor Sang Ouk Kim explained, "This study is an example of scientifically uncovering why graphene can selectively kill bacteria while remaining safe for the human body." He emphasized, "By utilizing this principle, we can expand beyond safe clothing without harsh chemicals to an infinite range of applications, including wearable devices and medical textile systems."
Sujin Cha (PhD program, Department of Materials Science and Engineering) and Ju Yeon Chung (Integrated MS/PhD program, Department of Biological Sciences) participated as first authors. Professor Hyun Jung Chung participated as a co-corresponding author. The research was published on March 2nd in the prestigious materials science journal, Advanced Functional Materials.
※ Paper Title: Biocompatible but Antibacterial Mechanism of Graphene Oxide for Sustainable Antibiotics, DOI: 10.1002/adfm.202313583
Additionally, Nanowerk (http://www.nanowerk.com/), a global portal for nanotechnology, featured these findings as a 'Spotlight' titled "Graphene oxide destroys bacteria without harming human tissue."
This research was conducted with support from the 'Nano/Material Technology Development (R&D)' program, the 'Individual Basic Research' program, and the 'Mid-Career Researcher Support Program' funded by the Ministry of Science and ICT.
2026.03.26 View 7062 -
World’s First AI-Managed Unmanned Factory Implemented... Construction of Physical AI KAIROS
< Integrated Operation of Heterogeneous Logistics Robot Systems >
KAIST announced on March 23rd that Professor Young Jae Jang's team from the Department of Industrial and Systems Engineering has constructed ‘KAIROS’ (KAIST AI Robot Orchestration Systems), a physical AI testbed that integrates and controls heterogeneous robots, sensors, facilities, and digital twins into a single system.
KAIROS is a 100% unmanned factory platform based on physical AI and is the first integrated testbed of its kind in Korea, developed with support from the Ministry of Science and ICT (MSIT). It is particularly noteworthy as a domestic integrated solution aimed at exporting "Dark Factories" in the future.
The most significant feature of KAIROS is its structure, which integrates and controls various factory equipment through a single AI agent-based Operating System (OS). While existing factory automation was operated around individual devices, KAIROS integrates Autonomous Mobile Robots (AMR), humanoid robots, collaborative robots, and automation facilities into a single intelligent platform. Through this, the concept of ‘Physical AI-based factory operation’—where the entire factory is operated like a single AI system—has been realized.
The core of this testbed is the 100% domestic integration of the entire process from sensors and control to data processing. By integrating key elements of a Dark Factory—including logistics robots (AMR), OHT, 3D shuttles, humanoid robots, collaborative robots, industrial sensors and PC controllers, wireless charging systems, digital twins and simulations, and AI-based integrated control and safety management systems—using domestic technology, the project has replaced factory automation equipment and software that were heavily dependent on foreign technology and laid the foundation for a ‘K-Manufacturing Factory Export Model.’
As part of the Physical AI Pre-verification Project, the MSIT has supported the establishment of a demonstration lab within the KAIST Industrial Management Building. On March 23, Vice Minister Bae Gyeong-hoon (Minister of Science and ICT) visited KAIST to announce the National Physical AI Strategy (Draft) and unveil the KAIROS-based Dark Factory demonstration site.
At the event, the factory operating system of the KAIST demonstration lab, joint physical AI demonstration results with Chonbuk National University, and the direction of the ‘Team Korea Physical AI (TK-PAI)’ alliance—a cooperative structure of domestic companies—were discussed.
< KAIROS Operation Plan Announcement >
< KAIROS Demonstration >
< KAIROS Factory Site >
KAIST plans to further advance the next-generation factory operating system (OS), covering the design, construction, and operation of Dark Factories through KAIROS, and to develop simulation and virtual verification environments.
In addition, the university intends to utilize the platform as a testing and evaluation site where domestic robot and automation companies can pre-verify highly reliable equipment, thereby increasing industrial applicability. Furthermore, the goal is to develop physical AI-based Dark Factory solutions capable of competing with global companies such as Siemens (Germany), FANUC (Japan), and Yaskawa (Japan) to pursue entry into the global market.
Kwang Hyung Lee, President of KAIST, stated, “KAIROS is the beginning of a new industrial paradigm where AI directly operates factories. KAIST will lead manufacturing innovation based on physical AI and contribute to ensuring South Korea’s leadership in global industrial competition.”
Professor Young Jae Jang, who led the construction of KAIROS, explained, “KAIROS goes beyond individual automation technologies to implement the concept of a factory operating system (OS) that integrates diverse robots and facilities into one system. It will serve as a foundation for domestic companies to verify physical AI technologies applicable to actual industrial sites and expand into the global market.”
2026.03.23 View 7687 -
KAIST, AI judges manufacturing beyond craftsmanship and language barriers
<(From Left) M.S candidate Inhyo Lee, Ph.D candidate Heekyu Kim, Ph.D candidate joonyoung Kim, Professor Seunghwa Ryu>
Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce identical items. However, even slight changes in conditions can lead to defects, so the process has long relied on the intuition of highly skilled workers. Now, KAIST researchers have proposed an AI-based solution that autonomously optimizes processes and transfers manufacturing knowledge, addressing concerns that expertise could be lost due to the retirement of skilled workers and the increase in foreign labor.
KAIST (President Kwang Hyung Lee) announced on the 22nd of December that a research team led by Professor Seunghwa Ryu from the Department of Mechanical Engineering · InnoCORE PRISM-AI Center has, for the first time in the world, developed generative AI technology that autonomously optimizes injection molding processes, along with an LLM-based knowledge transfer system that makes on-site expertise accessible to anyone. The team also reported that these achievements were published consecutively in an internationally renowned journal.
The first achievement is a generative AI–based process inference technology that automatically infers optimal process conditions based on environmental changes or quality requirements. Previously, whenever temperature, humidity, or desired quality levels changed, skilled workers had to rely on trial and error to readjust conditions.
The research team implemented a diffusion model–based approach that reverse-engineers process conditions satisfying target quality requirements, using environmental data and process parameters collected over several months from an actual injection molding factory.
In addition, the team built a surrogate model that substitutes for actual production, enabling quality prediction without running the real process. As a result, they achieved an error rate of just 1.63%, significantly lower than the 23~44% error rates of representative existing technologies such as GAN* and VAE** models traditionally used for process prediction. Experiments applying the AI-generated conditions to real processes confirmed successful production of acceptable products, demonstrating practical applicability.
*GAN (Generative Adversarial Network): a method in which two AI models compete with each other to generate data
**VAE (Variational Autoencoder): a method that compresses and learns common patterns in data and then reconstructs them
<Figure 1. Generative AI–Based Process Reasoning Technology>
The second achievement is the IM-Chat, an LLM-based knowledge transfer system designed to address skilled worker retirement and multilingual work environments. IM-Chat is a multi-agent AI system that combines large language models (LLMs) with retrieval-augmented generation (RAG), serving as an AI assistant for manufacturing sites by providing appropriate solutions to problems encountered by novice or foreign workers.
When a worker asks a question in natural language, the AI understands it and, if necessary, automatically calls the generative process inference AI, simultaneously providing optimal process condition calculations along with relevant standards and background explanations.
For example, when asked, “What is the appropriate injection pressure when the factory humidity is 43.5%?”, the AI calculates the optimal condition and presents the supporting manual references as well. With support for multilingual interfaces, foreign workers can receive the same level of decision-making support.
This research is regarded as a core manufacturing AI transformation (AX) technology that can be extended beyond injection molding to molds, presses, extrusion, 3D printing, batteries, bio-manufacturing, and other industries.
In particular, the work is significant in that it presents a paradigm for autonomous manufacturing AI, integrating generative AI and LLM agents through a Tool-Calling approach*, enabling AI to make its own judgments and invoke necessary functions.
*Tool-Calling approach: a method in which AI autonomously calls and uses the functions or programs required for a given situation
<Figure 2. Large Language Model–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 3. Example of Operation of the Large Language Model (LLM)–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat>
<Figure 4. Illustration of the Application of an LLM-Based Multilingual Knowledge Transfer Multi-Agent IM-Chat (AI-Generated)>
Professor Seunghwa Ryu explained, “This is a case where we addressed fundamental problems in manufacturing in a data-driven way by combining AI that autonomously optimizes processes with LLMs that make on-site knowledge accessible to anyone,” adding, “We will continue expanding this approach to various manufacturing processes to accelerate intelligence and autonomy across the industry.”
This research involved doctoral candidates Junhyeong Lee, Joon-Young Kim, and Heekyu Kim from the Department of Mechanical Engineering as co–first authors, with Professor Seunghwa Ryu as the corresponding author. The results were published consecutively in the April and December issues of Journal of Manufacturing Systems (JCR 1/69, IF 14.2), the world’s top-ranked international journal in engineering and industrial fields.
※ Paper 1: “Development of an Injection Molding Production Condition Inference System Based on Diffusion Model,” DOI: https://doi.org/10.1016/j.jmsy.2025.01.008 ※ Paper 2: “IM-Chat: A multi-agent LLM framework integrating tool-calling and diffusion modeling for knowledge transfer in injection molding industry,” DOI: https://doi.org/10.1016/j.jmsy.2025.11.007
This research was supported by the Ministry of Science and ICT, the Ministry of SMEs and Startups, and the Ministry of Trade, Industry and Energy.
2025.12.22 View 6285