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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 775 -
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 3893 -
KAIST Research Team Develops an AI Framework Capable of Overcoming the Strength-Ductility Dilemma in Additive-manufactured Titanium Alloys
<(From Left) Ph.D. Student Jaejung Park and Professor Seungchul Lee of KAIST Department of Mechanical Engineering and , Professor Hyoung Seop Kim of POSTECH, and M.S.–Ph.D. Integrated Program Student Jeong Ah Lee of POSTECH. >
The KAIST research team led by Professor Seungchul Lee from Department of Mechanical Engineering, in collaboration with Professor Hyoung Seop Kim’s team at POSTECH, successfully overcame the strength–ductility dilemma of Ti 6Al 4V alloy using artificial intelligence, enabling the production of high strength, high ductility metal products. The AI developed by the team accurately predicts mechanical properties based on various 3D printing process parameters while also providing uncertainty information, and it uses both to recommend process parameters that hold high promise for 3D printing.
Among various 3D printing technologies, laser powder bed fusion is an innovative method for manufacturing Ti-6Al-4V alloy, renowned for its high strength and bio-compatibility. However, this alloy made via 3D printing has traditionally faced challenges in simultaneously achieving high strength and high ductility. Although there have been attempts to address this issue by adjusting both the printing process parameters and heat treatment conditions, the vast number of possible combinations made it difficult to explore them all through experiments and simulations alone.
The active learning framework developed by the team quickly explores a wide range of 3D printing process parameters and heat treatment conditions to recommend those expected to improve both strength and ductility of the alloy. These recommendations are based on the AI model’s predictions of ultimate tensile strength and total elongation along with associated uncertainty information for each set of process parameters and heat treatment conditions. The recommended conditions are then validated by performing 3D printing and tensile tests to obtain the true mechanical property values. These new data are incorporated into further AI model training, and through iterative exploration, the optimal process parameters and heat treatment conditions for producing high-performance alloys were determined in only five iterations. With these optimized conditions, the 3D printed Ti-6Al-4V alloy achieved an ultimate tensile strength of 1190 MPa and a total elongation of 16.5%, successfully overcoming the strength–ductility dilemma.
Professor Seungchul Lee commented, “In this study, by optimizing the 3D printing process parameters and heat treatment conditions, we were able to develop a high-strength, high-ductility Ti-6Al-4V alloy with minimal experimentation trials. Compared to previous studies, we produced an alloy with a similar ultimate tensile strength but higher total elongation, as well as that with a similar elongation but greater ultimate tensile strength.” He added, “Furthermore, if our approach is applied not only to mechanical properties but also to other properties such as thermal conductivity and thermal expansion, we anticipate that it will enable efficient exploration of 3D printing process parameters and heat treatment conditions.”
This study was published in Nature Communications on January 22 (https://doi.org/10.1038/s41467-025-56267-1), and the research was supported by the National Research Foundation of Korea’s Nano & Material Technology Development Program and the Leading Research Center Program.
2025.02.21 View 14840 -
Metaverse Factory Center to Improve SME’s Competitiveness
The center is expected to enhance the manufacturing competitiveness of SMEs and root industry
KAIST opened the ‘Metaverse Factory Experience Center for Manufacturing AI’ on November 1 at the KAIST Bigdata Center for Manufacturing AI. The AI-powered manufacturing metaverse factory will provide real-life experiences for the analysis and application of manufacturing data. Funded by the Ministry of SMEs and Startups, the center is a collaboration with Digiforet, which donated the software system to KAIST.
The center allows users to experience the collection, analysis, and utilization process of manufacturing data equivalent to that of real manufacturing sites. Users can connect to the service from anywhere in the world using AR/VR/XR equipment and a metaverse solution, which allows small and middle-sized domestic manufacturing companies to overcome the challenges of entering and selling their production lines overseas in the post-COVID-19 era. The platform is an opportunity for such companies to introduce and export their excellent manufacturing techniques.
With the same manufacturing and AI processes of real production sites, the injection molding metaverse factory for plastic screw production runs simulations of the products they will make. Based on the data collection parameters (temperature, pressure, speed, location, time, etc.) built into the Korea AI Manufacturing Platform, an AI-powered SME manufacturing platform, the metaverse factory can detect causes of defects, provide analysis, and guide improvements in productivity and product quality.
Starting with the injection molding equipment metaverse factory, the platform aims to expand into plating, welding, molding, casting, forging, and annealing, and become a root industry to contribute greatly to enhancing the manufacturing competitiveness of Korea’s small and middle-sized root industries.
Il-Joong Kim, head of the KAIST Manufacturing AI Bigdata Center where the metaverse factory is located, said, “To successfully incorporate manufacturing AI into production sites, it is indispensable that various AI algorithms are tested to optimize decisions. The platform allows users to collect manufacturing data and to experience and test AI analysis simultaneously without interrupting the production process, making it highly effective.”
KAIST President Kwang Hyung Lee said, “We will support the close academic-industrial cooperation with Digiforet such as this collaborative for improving SMEs’ competitiveness.”
Digiforet CEO Sunghoon Park, who donated a whole HW/SW interface for the construction of the Metaverse Factory Experience Center for Manufacturing AI, said, “I will do my best to realize the best “Metaverse Factory for Manufacturing AI” in the world by combining the AI and bigdata accumulated at KAIST and Digiforet’s XR metaverse technology.”
2021.11.03 View 12301 -
The 8th KINC Fusion Research Awardees
The KAIST Institute for NanoCentury held the 8th KINC Fusion Research Award in order to encourage professors’ convergence studies and instill students’ willingness to research. The award ceremony took place in the KI Building at KAIST on March 13.
The KINC Fusion Research Award selects the most outstanding convergence studies among research undertaken last year, and awards researchers who participated in that research.
The 8th KINC Fusion Research Award went to Professor Yoon Sung Nam from the Department of Materials Science and Engineering and Professor Inkyu Park from the Department of Mechanical Engineering. Their research reported the spontaneous self-biomineralization of palladium (Pd) ions on a filamentous virus to form ligand-free Pd nanowires without reducing reagents or using additional surface stabilizers (Title: Virus-Templated Self-Mineralization of Ligand-Free Colloidal Palladium Nanostructures for High Surface Activity and Stability, Advanced Functional Materials (2017)).
Professor Hee-Tae Jung, the Director of KAIST Institute for the NanoCentury and the host of the KINC Fusion Research Award said, “Convergence will be the crucial keyword that will lead to revolutionary change. Hence, the importance of convergence study should be improved. We will put every effort into creating a research environment for increasing convergence study.
The KAIST Institute for the NanoCentury was established in June 2006 under the KAIST Institute with a mission of creating convergence study by tearing down boarders among departments and carrying out interdisciplinary joint research. Currently, approximately 90 professors from 14 departments participate the institute. It aims to become a hub of university institutes for nano-fusion research.
2018.03.19 View 21122 -
3D Printer Developed by KAIST Undergraduate Students
More than 100 Pre-orders Prior to Product Launch Made
KAIST undergraduate students received more than 100 pre-orders before the launch for 3D printers they developed and became a hot topic of interest.
KAIST Research Institute for Social Technology and Innovations (Head Hong-Kyu Lee) had a launch party at Daejeon Riviera Hotel on 17 November 2014 for “Commercial Delta 3D Printer” developed by KAIST undergraduate students inviting around 50 businesses, buyers and representatives of 3D Printing Industry Association.
“3D Printer” uses blueprints of products such as toys, mug cups and chairs to make 3D objects and is thought to be revolutionary technology in manufacturing industry. The interest has grown as recent printers could print even fruits and cosmetics.
The printing structure of 3D printer can be divided roughly into horizontal Mendel method and Delta method. KAIST students focused on the Delta method to give a differentiated product from 90% of commercial products that use Mendel method.
First, the students focused on lowering the cost of unit price by using self-developed components. The carriage (transport machine) of the product is replaced by self-developed components instead of bearing to reduce the noise and the linking method was changed to beads from loop guide to increase the completeness of the printed product. Also, an auto-levelling is loaded to ensure the nozzle and the bed is parallel and hence increasing convenience for the users. Further, the printer, designed by a product designer in Germany, is linked to a smartphone application for blueprints.
A student in the development team, Seokhyeon Seo (Department of Computer Science, 3rd Year Undergraduate) said, “The biggest merits of the product are lowering the price to a 1/3 by using self-developed components and reducing the noise.” He continued, “By using a smartphone application, anyone can easily design the product. So it is applicable to use for education or at home”
In the exhibit, “3D Printing Korea 2014,” in Coex, Seoul the printer had a preview demonstration, and received more than 100 pre-orders from educational and business training institutions. Further, buyers from Canada and the US requested opening agencies in their countries.
KAIST Research Institute for Social Technology and Innovations Head Hong-Kyu Lee said, “3D printing is an innovative technology that could bring the 3rd industrial revolution.” He continued, “It is still early days but the demand will increase exponentially.”
This project was a research project of KAIST Research Institute for Social Technology and Innovations led by a development team consisting of 4 undergraduate students of KAIST, one student from University of Oxford and one German product designer.
Students in the picture below are Won-Hoi Kim (Department of Mechanical Engineering), Sung-Hyun Cho (Department of Mechanical Engineering), and Suk-Hyun Seo (Department of Computer Science) from left to right.
2014.11.19 View 15236 -
KAIST Develops Core Technology to Synthesize a Helical Nanostructure
Professor Dong-Ki Yoon’s research team of the Graduate School of Nanoscience and Technology (GSNT) at KAIST has developed helical nanostructures using self-assembly processes. The results were published in the Proceedings of the National Academy of Sciences of the United States of America(PNAS) on the October 7th.
This technology enables the synthesis of various helical structures on a relatively large confined area. Its synthesis is often considered the most arduous for three dimensional structures. Formed from liquid crystal, the structure holds a regular helical structure within the confined space of 20 to 300 nanometers. Also, the distance between each pattern increased as the diameter of the nanostructure increased.
Liquid crystals have a unique property of responding sensitively to the surrounding electromagnetic field. The technology, in combination with the electromagnetic property of liquid crystal, is expected to foster the development of highly efficient optoelectronic devices.
Using this technology, it is possible to develop three dimensional patterning technology beyond the current semiconductor manufacturing technology which uses two dimensional photolithography processes. Three-dimensional semiconductor devices are expected to store hundred times more data than current devices. They will also lower costs by simplifying manufacturing processes.
The essence of this research, “self-assembly in confined space,” refers to controlling complex nanostructures, which can be synthesized from materials such as macromolecules, liquid crystal molecules, and biomolecules in relation to surrounding environments including the temperature, concentration, and pH.
The research team produced a confined space with a length of tens of nanometers by using a porous anodized aluminum membrane induced from an electrochemical reaction. They successfully synthesized independently controlled helical nanostructures by forming the helical structures from liquid crystal molecules within that space.
Professor Yoon said, “This research examines the physicochemical principle of controlling helical nanostructures.” He highlighted the significance of the research and commented, “The technology enables the control of complex nanostructures from organic molecules by using confined space and surface reforming.”
He added that, “When grafted with nanotechnology or information technology, this technology will spur new growth to liquid crystal-related industries such as the LCD.”
The research was led by two Ph.D. candidates, Hanim Kim and Sunhee Lee, under the guidance of Professor Yoon. Dr. Tae-Joo Shin of the Pohang Accelerator Laboratory, Professor Sang-Bok Lee of the University of Maryland, and Professor Noel Clark of the University of Colorado also participated.
Picture 1. Electron Microscopy Pictures and Conceptual Diagrams of Helical Nanostructures
Picture 2. Electron Microscopy Pictures of Manufactured Helical Nanostructures
2014.10.29 View 12281 -
Tae-Wan Kim, a doctoral candidate, receives the best paper award from ECTC
The 2014 Electronic Components and Technology Conference (ECTC) will take place on May 27-30 in Florida, USA. Tae-Wan Kim, a Ph.D. candidate at the Department of Materials Science Engineering (MSE), KAIST, will receive the Intel Best Student Paper Award at the conference.ECTC is the premier international conference that brings together the best researchers and engineers in packaging, components and microelectronic systems science, technology and education in an environment of cooperation and technical exchange. The conference is sponsored by the Components, Packaging and Manufacturing Technology (CPMT) Society of IEEE (Institute of Electrical and Electronics Engineering).The paper describes research on novel nanofiber anisotropic conductive films for ultra fine pitch electronic package application, which was written under the guidance of Professor Kyung-Wook Paik of the MSE Department. In the past ten years, two of his students have received the best paper award from ECTC.
2014.03.14 View 18240 -
Ultra High Speed Nanomaterial Synthesis Process Developed Using Laser
Dr. Jun-Yeop, Yeo and the research team led by Professor Seung-Hwan, Ko (both of the Department of Mechanical Engineering) successfully developed a process enabling the location-determinable, ultra high speed synthesis of nanomaterials using concentrated laser beams.
The result of the research effort was published as the frontispiece in the July 9th issue of Advanced Functional Materials, a world renowned material science and engineering academic journal.
Application of the technology reduced the time needed to process nanomaterial synthesis from a few hours to a mere five minutes. In addition, unlike conventional nanomaterial synthesis processes, it is simple enough to enable mass production and commercialization.
Conventional processes require the high temperatures of 900~1,000 °C and the use of toxic or explosive vapors. Complex processes such as separation after synthesis and patterning are needed for application in electronic devices. The multi-step, expensive, environmentally unfriendly characteristics of nanomaterial synthesis served as road blocks to its mass production and commercialization.
Exposing the precursor to concentrated continuous laser beam (green wavelength) resulted in the synthesis of nanowires in the desired location; the first instance in the world to accomplish this feat. The technology, according to the research team, makes possible the production, integration and patterning of nanomaterials using a single process. Applicable to various surfaces and substrates, nanowires have been successfully synthesized on flexible plastic substrates and controlled patterning on the surface of 3-dimensional structures.
Dr. Yeo commented that the research effort has “yielded the creation of a nanomaterial synthesis process capable of synthesis, integration, pattern, and material production using light energy” and has “reduced the synthesis process time of nanomaterial to one tenths of the conventional process.” Dr. Yeo continues to devise steps to commercialize the new multifunctional electronic material and methods for mass production.
The research effort, led by Dr. Yeo and Professor Ko, received contribution from Professor Hyung-Jin Sung (KAIST Department of Mechanical Engineering), Seok-Joon Hong, a Ph.D. candidate, Hyun-Wook Kang, also a Ph.D. candidate, Professor Costas Grigoropoulos of UC Berkeley, and Dr. Dae Ho Lee. In addition, the team received support from the National Research Foundation, Ministry of Knowledge Economy, Global Frontier Program, and KAIST EEWS.
Picture I: Synthesized nanomaterials produced at a desirable location by laser beams
Picture 2: Synthesized nanomaterials built on the 3D structure by using the developed technology
Picture 3: Functional electric circuit made with synthesized nanomaterials
Picture 4: Cover page of July 9th issue of Advanced Functional Materials
2013.08.23 View 15070 -
High Speed Nanomanufacturing Process Developed using Laser
Dr. Yeo Jun Yeop from KAIST’s Department of Mechanical Engineering, in a joint research project with Prof. Seung Hwan Ko, has developed a technology that speeds up the nanomanufacturing process by using lasers. Their research is published in the frontispiece of Advanced Functional Materials (July 9th issue).
Fig. The frontispiece of Advanced Functional Materials(July 9th issue)
The research group put a nanomaterial precursor on the board, illuminated it with a continuous-wave laser in the green wavelength range, and succeeded in synthesizing a nanowire at the point they wanted for the first time in the world.
Currently nanomaterials are difficult to mass produce and commercialize due to their complex and costly manufacturing processes which also use toxic gases. However, their new technology simplified the process and so reduced the manufacturing time from some hours to five minutes (1/10th times reduced).
Furthermore, this technology will apply regardless of the type of the board. Such nanometerials can be synthesized at any point on a flexible plastic board or even in three dimensional structures by illuminating them with a simple laser. Academics and industries expect mass production and commercialization of nanomaterials in near future.
Dr. Yeo said he intends to research further to promote early commercialization of multifunctional electronic devices by combining various nanomaterials
This research is sponsored by the National Research Foundation of Korea, the Ministry of Trade, Industry and Energy and KAIST EEWS
Fig. A nanomaterial synthesized after illuminated by lasers
Fig. A nanomaterial synthesized on a three dimensional structure using the developed technology
Fig. Functional electron device manufactured by using the synthesized nanomaterials
2013.08.02 View 12885 -
Professor Hwang Kyu Young and Professor Yang Dong Yeol Receives Engineer of Korea Award
Emeritus Professor Hwang Kyu Young (Department of Computer Sciences) and Professor Yang Dong Yeol (Department of Mechanical Engineering) were named as the 2012 Engineer of Korea by the Ministry of Education, Science, and Technology and Korea Science Foundation.
The Engineer of Korea Award is awarded biannually to scientists and engineers that have contributed to the development of Korea’s science and technology and national economy.
Professor Hwang’s work with DBMS and close coupling architecture of information search and overall new theories and application technology development in the field of database system has aided the opening and expansion of IT software industry development and the advent of internet information culture era.
Professor Yang is a word renowned scholar in the field of net shape manufacturing and is considered to have opened a new page in the field of nano-molding technique.
In addition, Professor Eum Sang Il (Department of Mathematical Science) has been selected as the 2012 Young Scientist Award.
2013.01.22 View 18996 -
KAIST Professors win 2012 Korea Engineering Award
Distinguished Professor Hwang Gyu Young (Department of Computer Science) and Professor Yang Dong Yol (Department of Mechanical Engineering) from KAIST received the 2012 ‘Korea Engineering Award’ hosted by the Ministry of Education, Science and Technology and the Korea Research Foundation.
The ‘Korea Engineering Award’ is given biennially to researchers who have accomplished world class research and have contributed greatly to Korea’s development in the field of Science and Technology. The award started in 1994 and a total of 24 recipients were recognized in various fields such as electronics, mechanics, chemistry, construction, etc. The recipients of the award areawarded the Presidential award as well as 50million won as prize money.
Professor Hwang was recognized for his research on DBMS close-coupling architecture as well as other new data base system theories, contributing to the development of the IT software industry in Korea. Professor Yang was praised for his work in precision shape creation and manufacturing, especially for his work in the nano-stereolithography process.
In addition, Professor Oum Sang-il from the Deparment of Mathematical Science received the 2012 ‘Young Scientist Award’ hosted by the Ministry of Education, Science and Technology and the Korean Academy of Science and Technology.
The ceremony for ‘Korea Engineering Award’ and the ‘Young Scientist Award’ was held in Seoul Press Center Press Club on the 21st of December.
2012.12.26 View 21558