Engineering
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Dr. Won-Joon Lee from the ADD Wins the Jeong Hun Cho Award
Dr. Won-Joon Lee from the Agency for Defense Development (ADD) became the 17th Jeong Hun Cho Award recipient. KAIST PhD candidate Sok-Min Choi from the Department of Aerospace Engineering, Master’s-PhD combined course student Hyong-Won Choi from Korea University, and Chong-Ho Park from Kongju National University High School were also selected.
The award recognizes promising young scientists who makes significant achievements in the field of aerospace engineering in honor of Jeong Hun Cho, the former PhD candidate in the Department of Aerospace Engineering who died in a lab accident in May in 2003. Cho’s family endowed the award and scholarship to honor him. Three scholarship recipients from Cho’s alma mater, KAIST, Korea University, and Kongju National High School are selected every year.
Dr. Lee from the ADD has conducted research on shape design methods and radar absorbing structures for unmanned aerial vehicles, publishing more than 24 articles in SCI-level journals and 17 at academic conferences.
Dr. Lee was awarded 25 million KRW in prize money. The two students from KAIST and Korea University each received a 4 million KRW scholarship and Park received 3 million KRW.
2021.05.17 View 4221 -
Prof. Sang Yup Lee Elected as a Foreign Member of the Royal Society
Vice President for Research Distinguished Professor Sang Yup Lee was elected as a foreign member of the Royal Society in the UK. On May 6, the Society announced the list of distinguished new 52 fellows and 10 foreign members who achieved exceptional contributions to science. Professor Lee and Professor V. Narry Kim from Seoul National University are the first foreign members ever elected from Korea.
The Royal Society, established in 1660, is one of the most prestigious national science academies and a fellowship of 1,600 of the world’s most eminent scientists. From Newton to Darwin, Einstein, Hawking, and beyond, pioneers and paragons in their fields are elected by their peers. To date, there are 280 Nobel prize winners among the fellows.
Distinguished Professor Lee from the Department of Chemical and Biomolecular Engineering at KAIST is one of the Highly Cited Researchers (HCRs) who pioneered systems metabolic engineering and developed various micro-organisms for producing a wide range of fuels, chemicals, materials, and natural compounds.
His seminal scholarship and research career have already been recognized worldwide. He is the first Korean ever elected into the National Academy of Inventors (NAI) in the US and one of 13 scholars elected as an International Member of both the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US. With this fellowship, he added one more accolade of being the first non-US and British Commonwealth scientist elected into the three most prestigious science academies: the NAS, the NAE, and the Royal Society.
2021.05.07 View 8974 -
Professor Byungha Shin Named Scientist of the Month
Professor Byungha Shin from the Department of Materials Science and Engineering won the Scientist of the Month Award presented by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF) on May 4. Professor Shin was recognized for his research in the field of next-generation perovskite solar cells and received 10 million won in prize money.
To achieve ‘carbon neutrality,’ which many countries across the globe including Korea hope to realize, the efficiency of converting renewable energies to electricity must be improved. Solar cells convert solar energy to electricity. Since single solar cells show lower efficiency, the development of ‘tandem solar cells’ that connect two or more cells together has been popular in recent years.
However, although ‘perovskite’ received attention as a next-generation material for tandem solar cells, it is sensitive to the external environment including light and moisture, making it difficult to maintain stability.
Professor Shin discovered that, theoretically, adding certain anion additives to perovskite solar cells would allow the control of the electrical and structural properties of the two-dimensional stabilization layer that forms inside the film. He confirmed this through high-resolution transmission electron microscopy. Controlling the amount of anions in the additives allowed the preservation of over 80% of the initial stability even after 1000 hours of continuous exposure to sunlight.
Based on this discovery, Professor Shin combined silicon with solar cells to create a tandem solar cell with 26.7% energy convergence efficiency. Considering that the highest-efficiency tandem solar cell in existence showed 29.5% efficiency, this figure is quite high. Professor Shin’s perovskite solar cell is also combinable with the CIGS (Cu(In,Ga)Se2) thin-film solar cell composed of copper (Cu), indium (In), gallium (Ga), and selenium (Se2).
Professor Shin’s research results were published in the online edition of the journal Science in April of last year.
“This research is meaningful for having suggested a direction for solar cell material stabilization using additives,” said Professor Shin. “I look forward to this technique being applied to a wide range of photoelectrical devices including solar cells, LEDs, and photodetectors,” he added.
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2021.05.07 View 7965 -
T-GPS Processes a Graph with Trillion Edges on a Single Computer
Trillion-scale graph processing simulation on a single computer presents a new concept of graph processing
A KAIST research team has developed a new technology that enables to process a large-scale graph algorithm without storing the graph in the main memory or on disks. Named as T-GPS (Trillion-scale Graph Processing Simulation) by the developer Professor Min-Soo Kim from the School of Computing at KAIST, it can process a graph with one trillion edges using a single computer.
Graphs are widely used to represent and analyze real-world objects in many domains such as social networks, business intelligence, biology, and neuroscience. As the number of graph applications increases rapidly, developing and testing new graph algorithms is becoming more important than ever before. Nowadays, many industrial applications require a graph algorithm to process a large-scale graph (e.g., one trillion edges). So, when developing and testing graph algorithms such for a large-scale graph, a synthetic graph is usually used instead of a real graph. This is because sharing and utilizing large-scale real graphs is very limited due to their being proprietary or being practically impossible to collect.
Conventionally, developing and testing graph algorithms is done via the following two-step approach: generating and storing a graph and executing an algorithm on the graph using a graph processing engine.
The first step generates a synthetic graph and stores it on disks. The synthetic graph is usually generated by either parameter-based generation methods or graph upscaling methods. The former extracts a small number of parameters that can capture some properties of a given real graph and generates the synthetic graph with the parameters. The latter upscales a given real graph to a larger one so as to preserve the properties of the original real graph as much as possible.
The second step loads the stored graph into the main memory of the graph processing engine such as Apache GraphX and executes a given graph algorithm on the engine. Since the size of the graph is too large to fit in the main memory of a single computer, the graph engine typically runs on a cluster of several tens or hundreds of computers. Therefore, the cost of the conventional two-step approach is very high.
The research team solved the problem of the conventional two-step approach. It does not generate and store a large-scale synthetic graph. Instead, it just loads the initial small real graph into main memory. Then, T-GPS processes a graph algorithm on the small real graph as if the large-scale synthetic graph that should be generated from the real graph exists in main memory. After the algorithm is done, T-GPS returns the exactly same result as the conventional two-step approach.
The key idea of T-GPS is generating only the part of the synthetic graph that the algorithm needs to access on the fly and modifying the graph processing engine to recognize the part generated on the fly as the part of the synthetic graph actually generated.
The research team showed that T-GPS can process a graph of 1 trillion edges using a single computer, while the conventional two-step approach can only process of a graph of 1 billion edges using a cluster of eleven computers of the same specification. Thus, T-GPS outperforms the conventional approach by 10,000 times in terms of computing resources. The team also showed that the speed of processing an algorithm in T-GPS is up to 43 times faster than the conventional approach. This is because T-GPS has no network communication overhead, while the conventional approach has a lot of communication overhead among computers.
Professor Kim believes that this work will have a large impact on the IT industry where almost every area utilizes graph data, adding, “T-GPS can significantly increase both the scale and efficiency of developing a new graph algorithm.”
This work was supported by the National Research Foundation (NRF) of Korea and Institute of Information & communications Technology Planning & Evaluation (IITP).
Publication:
Park, H., et al. (2021) “Trillion-scale Graph Processing Simulation based on Top-Down Graph Upscaling,” Presented at the IEEE ICDE 2021 (April 19-22, 2021, Chania, Greece)
Profile:
Min-Soo Kim
Associate Professor
minsoo.k@kaist.ac.kr
http://infolab.kaist.ac.kr
School of Computing
KAIST
2021.05.06 View 6554 -
Distinguished Professor Sang Yup Lee Honored with Charles D. Scott Award
Vice President for Research Sang Yup Lee received the 2021 Charles D. Scott Award from the Society for Industrial Microbiology and Biotechnology. Distinguished Professor Lee from the Department of Chemical and Biomolecular Engineering at KAIST is the first Asian awardee.
The Charles D. Scott Award, initiated in 1995, recognizes individuals who have made significant contributions to enable and further the use of biotechnology to produce fuels and chemicals. The award is named in honor of Dr. Charles D. Scott, who founded the Symposium on Biomaterials, Fuels, and Chemicals and chaired the conference for its first ten years.
Professor Lee has pioneered systems metabolic engineering and developed various micro-organisms capable of producing a wide range of fuels, chemicals, materials, and natural compounds, many of them for the first time. Some of the breakthroughs include the microbial production of gasoline, diacids, diamines, PLA and PLGA polymers, and several natural products.
More recently, his team has developed a microbial strain capable of the mass production of succinic acid, a monomer for manufacturing polyester, with the highest production efficiency to date, as well as a Corynebacterium glutamicum strain capable of producing high-level glutaric acid. They also engineered for the first time a bacterium capable of producing carminic acid, a natural red colorant that is widely used for food and cosmetics.
Professor Lee is one of the Highly Cited Researchers (HCR), ranked in the top 1% by citations in their field by Clarivate Analytics for four consecutive years from 2017. He is the first Korean fellow ever elected into the National Academy of Inventors in the US and one of 13 scholars elected as an International Member of both the National Academy of Sciences and the National Academy of Engineering in the USA.
The awards ceremony will take place during the Symposium on Biomaterials, Fuels, and Chemicals held online from April 26.
2021.04.27 View 7850 -
Mobile Clinic Module Wins Red Dot and iF Design Awards
The Mobile Clinic Module (MCM), an inflatable negative pressure ward building system developed by the Korea Aid for Respiratory Epidemic (KARE) initiative at KAIST, gained international acclaim by winning the prestigious Red Dot Design Award and iF Design Award.
The MCM was recognized as one of the Red Dot Product Designs of the Year. It also won four iF Design Awards in communication design, interior architecture, user interface, and user experience. Winning the two most influential design awards demonstrates how product design can make a valuable contribution to help contain pandemics and reflects new consumer trends for dealing with pandemics.
Designed to be patient friendly, even in the extreme medical situations such as pandemics or triage, the MCM is the result of collaborations among researchers in a variety of fields including mechanical engineering, computing, industrial and systems engineering, medical hospitals, and engineering companies. The research team was led by Professor Tek-Jin Nam from the Department of Industrial Design.
The MCM is expandable, moveable, and easy to store through a combination of negative pressure frames, air tents, and multi-functional panels. Positive air pressure devices supply fresh air from outside the tent. An air pump and controller maintain air beam pressure, while filtering exhausted air from inside. An internal air information monitoring system efficiently controls inside air pressure and purifies the air. It requires only one-fourth of the volume of existing wards and takes up approximately 40% of their weight. The unit can be transported in a 40-foot container truck.
MCMs are now located at the Korea Institute of Radiological & Medical Sciences and Jeju Vaccine Center and expect to be used at many other facilities. KARE is developing antiviral solutions and devices such as protective gear, sterilizers, and test kits to promptly respond to the pandemic. More than 100 researchers at KAIST are collaborating with industry and clinical hospitals to develop antiviral technologies that will improve preventive measures, diagnoses, and treatments.
Professor Nam said, “Our designers will continue to identify the most challenging issues, and try to resolve them by realizing user-friendly functions. We believe this will significantly contribute to relieving the drastic need for negative pressure beds and provide a place for monitoring patients with moderate symptoms. We look forward to the MCM upgrading epidemic management resources around the globe.”
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2021.04.21 View 7513 -
Centrifugal Multispun Nanofibers Put a New Spin on COVID-19 Masks
KAIST researchers have developed a novel nanofiber production technique called ‘centrifugal multispinning’ that will open the door for the safe and cost-effective mass production of high-performance polymer nanofibers. This new technique, which has shown up to a 300 times higher nanofiber production rate per hour than that of the conventional electrospinning method, has many potential applications including the development of face mask filters for coronavirus protection.
Nanofibers make good face mask filters because their mechanical interactions with aerosol particles give them a greater ability to capture more than 90% of harmful particles such as fine dust and virus-containing droplets.
The impact of the COVID-19 pandemic has further accelerated the growing demand in recent years for a better kind of face mask. A polymer nanofiber-based mask filter that can more effectively block harmful particles has also been in higher demand as the pandemic continues.
‘Electrospinning’ has been a common process used to prepare fine and uniform polymer nanofibers, but in terms of safety, cost-effectiveness, and mass production, it has several drawbacks. The electrospinning method requires a high-voltage electric field and electrically conductive target, and this hinders the safe and cost-effective mass production of polymer nanofibers.
In response to this shortcoming, ‘centrifugal spinning’ that utilizes centrifugal force instead of high voltage to produce polymer nanofibers has been suggested as a safer and more cost-effective alternative to the electrospinning. Easy scalability is another advantage, as this technology only requires a rotating spinneret and a collector.
However, since the existing centrifugal force-based spinning technology employs only a single rotating spinneret, productivity is limited and not much higher than that of some advanced electrospinning technologies such as ‘multi-nozzle electrospinning’ and ‘nozzleless electrospinning.’ This problem persists even when the size of the spinneret is increased.
Inspired by these limitations, a research team led by Professor Do Hyun Kim from the Department of Chemical and Biomolecular Engineering at KAIST developed a centrifugal multispinning spinneret with mass-producibility, by sectioning a rotating spinneret into three sub-disks. This study was published as a front cover article of ACS Macro Letters, Volume 10, Issue 3 in March 2021.
Using this new centrifugal multispinning spinneret with three sub-disks, the lead author of the paper PhD candidate Byeong Eun Kwak and his fellow researchers Hyo Jeong Yoo and Eungjun Lee demonstrated the gram-scale production of various polymer nanofibers with a maximum production rate of up to 25 grams per hour, which is approximately 300 times higher than that of the conventional electrospinning system. The production rate of up to 25 grams of polymer nanofibers per hour corresponds to the production rate of about 30 face mask filters per day in a lab-scale manufacturing system.
By integrating the mass-produced polymer nanofibers into the form of a mask filter, the researchers were able to fabricate face masks that have comparable filtration performance with the KF80 and KF94 face masks that are currently available in the Korean market. The KF80 and KF94 masks have been approved by the Ministry of Food and Drug Safety of Korea to filter out at least 80% and 94% of harmful particles respectively.
“When our system is scaled up from the lab scale to an industrial scale, the large-scale production of centrifugal multispun polymer nanofibers will be made possible, and the cost of polymer nanofiber-based face mask filters will also be lowered dramatically,” Kwak explained.
This work was supported by the KAIST-funded Global Singularity Research Program for 2020.
Publication:
Byeong Eun Kwak, Hyo Jeong Yoo, Eungjun Lee, and Do Hyun Kim. (2021) Large-Scale Centrifugal Multispinning Production of Polymer Micro- and Nanofibers for Mask Filter Application with a Potential of Cospinning Mixed Multicomponent Fibers. ACS Macro Letters, Volume No. 10, Issue No. 3, pp. 382-388. Available online at https://doi.org/10.1021/acsmacrolett.0c00829
Profile:
Do Hyun Kim, Sc.D.
Professor
dohyun.kim@kaist.edu
http://procal.kaist.ac.kr/
Process Analysis Laboratory
Department of Chemical and Biomolecular Engineering
https:/kaist.ac.kr/en/
Korea Advanced Institute of Science and Technology (KAIST)Daejeon 34141, Korea
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2021.04.12 View 10831 -
Microbial Production of a Natural Red Colorant Carminic Acid
Metabolic engineering and computer-simulated enzyme engineering led to the production of carminic acid, a natural red colorant, from bacteria for the first time
A research group at KAIST has engineered a bacterium capable of producing a natural red colorant, carminic acid, which is widely used for food and cosmetics. The research team reported the complete biosynthesis of carminic acid from glucose in engineered Escherichia coli. The strategies will be useful for the design and construction of biosynthetic pathways involving unknown enzymes and consequently the production of diverse industrially important natural products for the food, pharmaceutical, and cosmetic industries.
Carminic acid is a natural red colorant widely being used for products such as strawberry milk and lipstick. However, carminic acid has been produced by farming cochineals, a scale insect which only grows in the region around Peru and Canary Islands, followed by complicated multi-step purification processes. Moreover, carminic acid often contains protein contaminants that cause allergies so many people are unwilling to consume products made of insect-driven colorants. On that account, manufacturers around the world are using alternative red colorants despite the fact that carminic acid is one of the most stable natural red colorants.
These challenges inspired the metabolic engineering research group at KAIST to address this issue. Its members include postdoctoral researchers Dongsoo Yang and Woo Dae Jang, and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering. This study entitled “Production of carminic acid by metabolically engineered Escherichia coli” was published online in the Journal of the American Chemical Society (JACS) on April 2.
This research reports for the first time the development of a bacterial strain capable of producing carminic acid from glucose via metabolic engineering and computer simulation-assisted enzyme engineering. The research group optimized the type II polyketide synthase machinery to efficiently produce the precursor of carminic acid, flavokermesic acid.
Since the enzymes responsible for the remaining two reactions were neither discovered nor functional, biochemical reaction analysis was performed to identify enzymes that can convert flavokermesic acid into carminic acid. Then, homology modeling and docking simulations were performed to enhance the activities of the two identified enzymes. The team could confirm that the final engineered strain could produce carminic acid directly from glucose. The C-glucosyltransferase developed in this study was found to be generally applicable for other natural products as showcased by the successful production of an additional product, aloesin, which is found in aloe leaves.
“The most important part of this research is that unknown enzymes for the production of target natural products were identified and improved by biochemical reaction analyses and computer simulation-assisted enzyme engineering,” says Dr. Dongsoo Yang. He explained the development of a generally applicable C-glucosyltransferase is also useful since C-glucosylation is a relatively unexplored reaction in bacteria including Escherichia coli. Using the C-glucosyltransferase developed in this study, both carminic acid and aloesin were successfully produced from glucose.
“A sustainable and insect-free method of producing carminic acid was achieved for the first time in this study. Unknown or inefficient enzymes have always been a major problem in natural product biosynthesis, and here we suggest one effective solution for solving this problem. As maintaining good health in the aging society is becoming increasingly important, we expect that the technology and strategies developed here will play pivotal roles in producing other valuable natural products of medical or nutritional importance,” said Distinguished Professor Sang Yup Lee.
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries of the Ministry of Science and ICT (MSIT) through the National Research Foundation (NRF) of Korea and the KAIST Cross-Generation Collaborative Lab project; Sang Yup Lee and Dongsoo Yang were also supported by Novo Nordisk Foundation in Denmark.
Publication:
Dongsoo Yang, Woo Dae Jang, and Sang Yup Lee. Production of carminic acid by metabolically engineered Escherichia coli. at the Journal of the American Chemical Society. https://doi.org.10.1021/jacs.0c12406
Profile:
Sang Yup Lee, PhD
Distinguished Professor
leesy@kaist.ac.kr
http://mbel.kaist.ac.kr
Metabolic &Biomolecular Engineering National Research Laboratory
Department of Chemical and Biomolecular Engineering
KAIST
2021.04.06 View 10288 -
Streamlining the Process of Materials Discovery
The materials platform M3I3 reduces the time for materials discovery by reverse engineering future materials using multiscale/multimodal imaging and machine learning of the processing-structure-properties relationship
Developing new materials and novel processes has continued to change the world. The M3I3 Initiative at KAIST has led to new insights into advancing materials development by implementing breakthroughs in materials imaging that have created a paradigm shift in the discovery of materials. The Initiative features the multiscale modeling and imaging of structure and property relationships and materials hierarchies combined with the latest material-processing data.
The research team led by Professor Seungbum Hong analyzed the materials research projects reported by leading global institutes and research groups, and derived a quantitative model using machine learning with a scientific interpretation. This process embodies the research goal of the M3I3: Materials and Molecular Modeling, Imaging, Informatics and Integration.
The researchers discussed the role of multiscale materials and molecular imaging combined with machine learning and also presented a future outlook for developments and the major challenges of M3I3. By building this model, the research team envisions creating desired sets of properties for materials and obtaining the optimum processing recipes to synthesize them.
“The development of various microscopy and diffraction tools with the ability to map the structure, property, and performance of materials at multiscale levels and in real time enabled us to think that materials imaging could radically accelerate materials discovery and development,” says Professor Hong.
“We plan to build an M3I3 repository of searchable structural and property maps using FAIR (Findable, Accessible, Interoperable, and Reusable) principles to standardize best practices as well as streamline the training of early career researchers.”
One of the examples that shows the power of structure-property imaging at the nanoscale is the development of future materials for emerging nonvolatile memory devices. Specifically, the research team focused on microscopy using photons, electrons, and physical probes on the multiscale structural hierarchy, as well as structure-property relationships to enhance the performance of memory devices.
“M3I3 is an algorithm for performing the reverse engineering of future materials. Reverse engineering starts by analyzing the structure and composition of cutting-edge materials or products. Once the research team determines the performance of our targeted future materials, we need to know the candidate structures and compositions for producing the future materials.”
The research team has built a data-driven experimental design based on traditional NCM (nickel, cobalt, and manganese) cathode materials. With this, the research team expanded their future direction for achieving even higher discharge capacity, which can be realized via Li-rich cathodes.
However, one of the major challenges was the limitation of available data that describes the Li-rich cathode properties. To mitigate this problem, the researchers proposed two solutions: First, they should build a machine-learning-guided data generator for data augmentation. Second, they would use a machine-learning method based on ‘transfer learning.’ Since the NCM cathode database shares a common feature with a Li-rich cathode, one could consider repurposing the NCM trained model for assisting the Li-rich prediction. With the pretrained model and transfer learning, the team expects to achieve outstanding predictions for Li-rich cathodes even with the small data set.
With advances in experimental imaging and the availability of well-resolved information and big data, along with significant advances in high-performance computing and a worldwide thrust toward a general, collaborative, integrative, and on-demand research platform, there is a clear confluence in the required capabilities of advancing the M3I3 Initiative.
Professor Hong said, “Once we succeed in using the inverse “property−structure−processing” solver to develop cathode, anode, electrolyte, and membrane materials for high energy density Li-ion batteries, we will expand our scope of materials to battery/fuel cells, aerospace, automobiles, food, medicine, and cosmetic materials.”
The review was published in ACS Nano in March. This study was conducted through collaborations with Dr. Chi Hao Liow, Professor Jong Min Yuk, Professor Hye Ryung Byon, Professor Yongsoo Yang, Professor EunAe Cho, Professor Pyuck-Pa Choi, and Professor Hyuck Mo Lee at KAIST, Professor Joshua C. Agar at Lehigh University, Dr. Sergei V. Kalinin at Oak Ridge National Laboratory, Professor Peter W. Voorhees at Northwestern University, and Professor Peter Littlewood at the University of Chicago (Article title: Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics, and Integration).This work was supported by the KAIST Global Singularity Research Program for 2019 and 2020.
Publication:
“Reducing Time to Discovery: Materials and Molecular Modeling, Imaging, Informatics and Integration,” S. Hong, C. H. Liow, J. M. Yuk, H. R. Byon, Y. Yang, E. Cho, J. Yeom, G. Park, H. Kang, S. Kim, Y. Shim, M. Na, C. Jeong, G. Hwang, H. Kim, H. Kim, S. Eom, S. Cho, H. Jun, Y. Lee, A. Baucour, K. Bang, M. Kim, S. Yun, J. Ryu, Y. Han, A. Jetybayeva, P.-P. Choi, J. C. Agar, S. V. Kalinin, P. W. Voorhees, P. Littlewood, and H. M. Lee, ACS Nano 15, 3, 3971–3995 (2021) https://doi.org/10.1021/acsnano.1c00211
Profile:
Seungbum Hong, PhD
Associate Professor
seungbum@kaist.ac.kr
http://mii.kaist.ac.kr
Department of Materials Science and Engineering
KAIST
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2021.04.05 View 11125 -
Plasma Jets Stabilize Water to Splash Less
< High-speed shadowgraph movie of water surface deformations induced by plasma impingement. >
A study by KAIST researchers revealed that an ionized gas jet blowing onto water, also known as a ‘plasma jet’, produces a more stable interaction with the water’s surface compared to a neutral gas jet. This finding reported in the April 1 issue of Nature will help improve the scientific understanding of plasma-liquid interactions and their practical applications in a wide range of industrial fields in which fluid control technology is used, including biomedical engineering, chemical production, and agriculture and food engineering.
Gas jets can create dimple-like depressions in liquid surfaces, and this phenomenon is familiar to anyone who has seen the cavity produced by blowing air through a straw directly above a cup of juice. As the speed of the gas jet increases, the cavity becomes unstable and starts bubbling and splashing.
“Understanding the physical properties of interactions between gases and liquids is crucial for many natural and industrial processes, such as the wind blowing over the surface of the ocean, or steelmaking methods that involve blowing oxygen over the top of molten iron,” explained Professor Wonho Choe, a physicist from KAIST and the corresponding author of the study.
However, despite its scientific and practical importance, little is known about how gas-blown liquid cavities become deformed and destabilized.
In this study, a group of KAIST physicists led by Professor Choe and the team’s collaborators from Chonbuk National University in Korea and the Jožef Stefan Institute in Slovenia investigated what happens when an ionized gas jet, also known as a ‘plasma jet’, is blown over water. A plasma jet is created by applying high voltage to a nozzle as gas flows through it, which causes the gas to be weakly ionized and acquire freely-moving charged particles.
The research team used an optical technique combined with high-speed imaging to observe the profiles of the water surface cavities created by both neutral helium gas jets and weakly ionized helium gas jets. They also developed a computational model to mathematically explain the mechanisms behind their experimental discovery.
The researchers demonstrated for the first time that an ionized gas jet has a stabilizing effect on the water’s surface. They found that certain forces exerted by the plasma jet make the water surface cavity more stable, meaning there is less bubbling and splashing compared to the cavity created by a neutral gas jet.
Specifically, the study showed that the plasma jet consists of pulsed waves of gas ionization propagating along the water’s surface so-called ‘plasma bullets’ that exert more force than a neutral gas jet, making the cavity deeper without becoming destabilized.
“This is the first time that this phenomenon has been reported, and our group considers this as a critical step forward in our understanding of how plasma jets interact with liquid surfaces. We next plan to expand this finding through more case studies that involve diverse plasma and liquid characteristics,” said Professor Choe.
This work was supported by KAIST as part of the High-Risk and High-Return Project, the National Research Foundation of Korea (NRF), and the Slovenian Research Agency (ARRS).
Image Credit: Professor Wonho Choe, KAIST
Usage Restrictions: News organizations may use or redistribute these materials, with proper attribution, as part of news coverage of this paper only.
Publication: Park, S., et al. (2021) Stabilization of liquid instabilities with ionized gas jets. Nature, Vol. No. 592, Issue No. 7852, pp. 49-53. Available online at https://doi.org/10.1038/s41586-021-03359-9
Profile:
Wonho Choe, Ph.D.
Professor
wchoe@kaist.ac.kr
https://gdpl.kaist.ac.kr/
Gas Discharge Physics Laboratory (GDPL)
Department of Nuclear and Quantum Engineering
Department of Physics
Impurity and Edge Plasma Research Center (IERC)
http://kaist.ac.kr/en/
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
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2021.04.01 View 9712 -
Acoustic Graphene Plasmons Study Paves Way for Optoelectronic Applications
- The first images of mid-infrared optical waves compressed 1,000 times captured using a highly sensitive scattering-type scanning near-field optical microscope. -
KAIST researchers and their collaborators at home and abroad have successfully demonstrated a new methodology for direct near-field optical imaging of acoustic graphene plasmon fields. This strategy will provide a breakthrough for the practical applications of acoustic graphene plasmon platforms in next-generation, high-performance, graphene-based optoelectronic devices with enhanced light-matter interactions and lower propagation loss.
It was recently demonstrated that ‘graphene plasmons’ – collective oscillations of free electrons in graphene coupled to electromagnetic waves of light – can be used to trap and compress optical waves inside a very thin dielectric layer separating graphene from a metallic sheet. In such a configuration, graphene’s conduction electrons are “reflected” in the metal, so when the light waves “push” the electrons in graphene, their image charges in metal also start to oscillate. This new type of collective electronic oscillation mode is called ‘acoustic graphene plasmon (AGP)’.
The existence of AGP could previously be observed only via indirect methods such as far-field infrared spectroscopy and photocurrent mapping. This indirect observation was the price that researchers had to pay for the strong compression of optical waves inside nanometer-thin structures. It was believed that the intensity of electromagnetic fields outside the device was insufficient for direct near-field optical imaging of AGP.
Challenged by these limitations, three research groups combined their efforts to bring together a unique experimental technique using advanced nanofabrication methods. Their findings were published in Nature Communications on February 19.
A KAIST research team led by Professor Min Seok Jang from the School of Electrical Engineering used a highly sensitive scattering-type scanning near-field optical microscope (s-SNOM) to directly measure the optical fields of the AGP waves propagating in a nanometer-thin waveguide, visualizing thousand-fold compression of mid-infrared light for the first time.
Professor Jang and a post-doc researcher in his group, Sergey G. Menabde, successfully obtained direct images of AGP waves by taking advantage of their rapidly decaying yet always present electric field above graphene. They showed that AGPs are detectable even when most of their energy is flowing inside the dielectric below the graphene.
This became possible due to the ultra-smooth surfaces inside the nano-waveguides where plasmonic waves can propagate at longer distances. The AGP mode probed by the researchers was up to 2.3 times more confined and exhibited a 1.4 times higher figure of merit in terms of the normalized propagation length compared to the graphene surface plasmon under similar conditions.
These ultra-smooth nanostructures of the waveguides used in the experiment were created using a template-stripping method by Professor Sang-Hyun Oh and a post-doc researcher, In-Ho Lee, from the Department of Electrical and Computer Engineering at the University of Minnesota.
Professor Young Hee Lee and his researchers at the Center for Integrated Nanostructure Physics (CINAP) of the Institute of Basic Science (IBS) at Sungkyunkwan University synthesized the graphene with a monocrystalline structure, and this high-quality, large-area graphene enabled low-loss plasmonic propagation.
The chemical and physical properties of many important organic molecules can be detected and evaluated by their absorption signatures in the mid-infrared spectrum. However, conventional detection methods require a large number of molecules for successful detection, whereas the ultra-compressed AGP fields can provide strong light-matter interactions at the microscopic level, thus significantly improving the detection sensitivity down to a single molecule.
Furthermore, the study conducted by Professor Jang and the team demonstrated that the mid-infrared AGPs are inherently less sensitive to losses in graphene due to their fields being mostly confined within the dielectric. The research team’s reported results suggest that AGPs could become a promising platform for electrically tunable graphene-based optoelectronic devices that typically suffer from higher absorption rates in graphene such as metasurfaces, optical switches, photovoltaics, and other optoelectronic applications operating at infrared frequencies.
Professor Jang said, “Our research revealed that the ultra-compressed electromagnetic fields of acoustic graphene plasmons can be directly accessed through near-field optical microscopy methods. I hope this realization will motivate other researchers to apply AGPs to various problems where strong light-matter interactions and lower propagation loss are needed.”
This research was primarily funded by the Samsung Research Funding & Incubation Center of Samsung Electronics. The National Research Foundation of Korea (NRF), the U.S. National Science Foundation (NSF), Samsung Global Research Outreach (GRO) Program, and Institute for Basic Science of Korea (IBS) also supported the work.
Publication:
Menabde, S. G., et al. (2021) Real-space imaging of acoustic plasmons in large-area graphene grown by chemical vapor deposition. Nature Communications 12, Article No. 938. Available online at https://doi.org/10.1038/s41467-021-21193-5
Profile:
Min Seok Jang, MS, PhD
Associate Professorjang.minseok@kaist.ac.krhttp://jlab.kaist.ac.kr/
Min Seok Jang Research GroupSchool of Electrical Engineering
http://kaist.ac.kr/en/Korea Advanced Institute of Science and Technology (KAIST)Daejeon, Republic of Korea
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2021.03.16 View 12240 -
Rare Mutations May Have Big Impact on Schizophrenia Pathology
- Somatic mutations found only in brain cells disrupt synaptic function. -
Schizophrenia is a neurodevelopmental disorder that disrupts brain activity, producing hallucinations, delusions, and other cognitive disturbances. Researchers have long searched for genetic influences in the disease, but genetic mutations have been identified in only a small fraction—fewer than a quarter—of sequenced patients. Now a study shows that “somatic” gene mutations in brain cells could account for some of the disease’s neuropathology.
The results of the study, led by Professor Jeong Ho Lee at the Graduate School of Medical Science and Engineering in collaboration with the Stanley Medical Research Institute in the US, appeared in Biological Psychiatry.
Traditional genetic mutations, called germline mutations, occur in sperm or egg cells and are passed on to offspring by their parents. Somatic mutations, in contrast, occur in an embryo after fertilization, and they can show up throughout the body or in isolated pockets of tissues, making them much harder to detect from blood or saliva samples, which are typically used for such sequencing studies.
Recently, more-advanced genetic sequencing techniques have allowed researchers to detect somatic mutations and studies have shown that even mutations present at very low levels can have functional consequences. A previous study hinted that brain somatic mutations were associated with schizophrenia, but it was not powerful enough to cement an association between brain somatic mutations and schizophrenia.
In the current study, the researchers used deep whole-exome sequencing to determine the genetic code of all exomes, the parts of genes that encode proteins. The scientists sequenced postmortem samples from brain, liver, spleen, or heart tissue of 27 people with schizophrenia and 31 control participants allowing them to compare the sequences in the two tissues. Using a powerful analytic technique, the team identified an average of 4.9 somatic single-nucleotide variants, or mutations, in brain samples from people with schizophrenia, and 5.6 somatic single-nucleotide variants in brain samples from control subjects.
Although there were no significant quantitative differences in somatic single-nucleotide variants between schizophrenia and control tissue samples, the researchers found that the mutations in schizophrenia patients were found in genes already associated with schizophrenia. Of the germline mutations that had previously been associated with schizophrenia, the genes affected encode proteins associated with synaptic neural communication, particularly in a brain region called the dorsolateral prefrontal cortex.
In the new analysis, the researchers determined which proteins might be affected by the newly identified somatic mutations. Remarkably, a protein called GRIN2B emerged as highly affected and two patients with schizophrenia carried somatic mutations on the GRIN2B gene itself. GRIN2B is a protein component of NMDA-type glutamate receptors, which are critical for neural signaling. Faulty glutamate receptors have long been suspected of contributing to schizophrenia pathology; GRIN2B ranks among the most-studied genes in schizophrenia. The somatic mutations identified in the study had a variant allele frequency of only ~1%, indicating that the mutations were rare among brain cells as a whole. Nevertheless, they have the potential to create widespread cortical dysfunction.
Professor Lee said, “Besides the comprehensive genetic analysis of brain-only mutations in postmortem tissues from schizophrenia patients, this study experimentally showed the biological consequence of identified somatic mutations, which led to neuronal abnormalities associated with schizophrenia. Thus, this study suggests that brain somatic mutations can be a hidden major contributor to schizophrenia and provides new insights into the molecular genetic architecture of schizophrenia.
John Krystal, MD, editor of Biological Psychiatry, said of the work, "The genetics of schizophrenia has received intensive study for several decades. Now a new possibility emerges, that in some cases, mutations in the DNA of brain cells contributes to the biology of schizophrenia. Remarkably this new biology points to an old schizophrenia story: NMDA glutamate receptor dysfunction. Perhaps the path through which somatic mutations contribute to schizophrenia converges with other sources of abnormalities in glutamate signaling in this disorder."
Professor Lee and the team next want to assess the functional consequences of the somatic mutations. Because of the location of the GRIN2B mutations found in schizophrenia patients, the researchers hypothesized that they might interfere with the receptors’ localization on neurons. Experiments on the cortical neurons of mice showed that the mutations indeed disrupted the receptors’ usual localization to dendrites, the “listening” ends of neurons, which in turn prevented the formation of normal synapses in the neurons. This finding suggests that the somatic mutations could disrupt neural communication, contributing to schizophrenia pathology.
- Profile:
Professor Jeong Ho Lee
Translational Neurogenetics Laboratory ( https://tnl.kaist.ac.kr/)
The Graduate School of Medical Science and Engineering
KAIST
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2021.03.11 View 6817