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KAIST Listed as Top 100 Global Innovator by Clarivate
KAIST was named as one of the Top 100 Global Innovators 2021 by Clarivate. Among the top 100, 42 US corporations, including Amazon, Apple, Google, and Facebook, and 29 Japanese corporations made the list. The list included four Korean corporations Samsung Electronics, LG Electronics, LS Electronics, and SK Telecommunications. KAIST, the only university listed as a global innovator, regained its place in the Top 100 Global Innovators this year after last being named in 2013. Industrywide, the electronics and semiconductor sectors took the majority of the top global innovators spots with 21 and 12 corporations respectively.
President Kwang Hyung Lee received the trophy from Clarivate Korea Regional Director Seongsik Ahn on May 12 at KAIST’s main campus. President Lee said, “We are glad that our continued innovation efforts are receiving worldwide recognition and will continue to strive for sustainable growth as a university that creates global value and impact.”
Every year since 2012, the Top 100 Global Innovators has identified companies and institutions at the pinnacle of the global innovation landscape by measuring the ideation culture that produces patents and puts them at the forefront. Clarivate tracks innovation based on four factors: 1. volume of patents 2. influence 3. Success and 4. globalization using patents, patents indices, and citation index solutions.
For measuring the patent volume, the Top 100 candidate must meet a threshold of 100 granted patents received in the past five years and more than 500 in the Derwent World Patents Index over any time period. Clarivate assesses the level of influence of the patented ideas by reviewing the number of external citations their inventions received over the past five years. For measuring success, they look at how successful each candidate has been getting their applications for patent protection approved by patent offices around the world over past five years. Globalization measures the investment levels of each candidate in their patent applications, a metric designed to assess both the importance of invention to the companies as well as the footprint of commercialization.
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2021.05.12 View 5384 -
Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.
Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface.
Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.
“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.
The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.
The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.
“The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.
“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”
The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.
Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.
Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”
This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.
-Publication
Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang
“Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography”
Nature Communications
-Profile
Professor Yongsoo Yang
Department of Physics
Multi-Dimensional Atomic Imaging Lab (MDAIL)
http://mdail.kaist.ac.kr
KAIST
2021.05.12 View 11524 -
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 10831 -
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 9627 -
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 9302 -
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 9480 -
KAIST Teams Up with Yozma Group to Nurture Startups
KAIST has joined hands with Israeli venture capital investor Yozma Group to help campus-based startups grow and build success. The two signed a memorandum of understanding (MOU) on joint technology value creation initiatives at the signing ceremony that was held at KAIST’s main campus in Daejeon on April 8.
Under the MOU, Yozma Group will make investments and implement acceleration programs for startups established by KAIST professors, graduates, and students, as well as those invested in by the university.
Yozma Group already launched a $70 million fund to help grow companies in Korea and Israel. Yozma Group will use the fund as well as its global acceleration know-how and network of over 400 R&D centers across Israel to help promising KAIST startups enter overseas markets.
Moreover, Yozma Group also plans to discover and support KAIST startups that need technology from the Weizmann Institute of Science, Israel’s leading multidisciplinary basic research institution in natural and exact sciences.
KAIST is also in talks to locate Yozma Group’s branch office on the university’s campus to ensure seamless collaborations.
KAIST President Kwang Hyung Lee explained to Yozma Group’s Founder and Chairman Yigal Erlich and Head of Asia Pacific Won-Jae Lee at the MOU signing ceremony that “startup and technology commercialization are the crucial areas where KAIST will make innovations.”
“Cooperation with Yozma Group will help KAIST startups transform their ideas and technologies into real businesses and build a global presence,” he added.
Yozma Group started as Yozma Fund, created in conjunction with the Israeli government in 1993 to support the globalization of Israeli startups and to foster the growth of Israel’s venture capital industry. The Fund, which was privatized in 1998, has supported 97 Israeli tech ventures joining the Nasdaq, leading Israel to become a global innovation hub that has the third-most companies listed on the Nasdaq.
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2021.04.20 View 7364 -
COVID-Update: KAIST on High Alert amid Spring Resurgence
COVID-19 Task Force responds 24-7 and ISSS provides returning international students with a comfort package during 14-day mandatory quarantine
In response to the upsurge of COVID-19 cases in the proximate college districts in Daejeon, KAIST announced the enforcement of stricter health and safety regulations. Korean health authorities expected another surge of COVID-19 cases this spring as Korea’s daily new COVID-19 cases have rebounded to the high 600s and over 700 in April, which is the most in over three months.
New guidelines issued on April 5 banned faculty, staff, and students from engaging in off-campus activities and utilizing external public facilities. Such facilities include, but are not limited to, bars, cafes, clubs, gyms, karaoke rooms, PC rooms, restaurants, and other crowded indoor spaces. All class and research activities, work meetings, and school events were moved exclusively online, and working from home and flexible working hours were highly encouraged in order to minimize face-to-face interactions on campus. In particular, having meals outside of KAIST cafeterias in groups of two or more was prohibited, while food delivery and take-outs were allowed.
Executive Vice President and Provost Seung Seob Lee said in a letter to the KAIST community on April 5 that “the school considers the risk of the current situation to be very high, likely the highest since the outbreak of COVID-19.” Provost Lee then called for more team efforts to contain the current phase of the pandemic and asked everyone to do their part.
The school installed new temperature scanners equipped with hand sanitizer dispensers in front of the dormitory entrances to further control the spread of the disease on campus, following confirmed COVID-19 cases among dormitory residents.
As the COVID-19 pandemic continues with no clear end in sight, the Task Force for the Prevention of COVID-19 and the International Scholar and Student Services (ISSS) Team at KAIST are working around the clock to reduce the risk of infection spread not only within the campus, but also coming from outside the campus.
Under strict health and safety guidelines, KAIST has allowed international students to come back to campus. Currently about 600 international students, mostly graduate students reside on campus. All returning students should complete the mandatory 14-day self-quarantine required by the Korean government at their own expense.
The KAIST COVID-19 Task Force is in charge of enacting on-campus health and safety guidelines, responding to reports and inquiries from the KAIST community 24-7, and controlling outsider access, among other responsibilities.
The ISSS Team requires returning international students to fill out an entry authorization form and receive approval from the KAIST COVID-19 Task Force prior to returning to campus from their home countries. Once students arrive at their designated quarantine facility, the KAIST ISSS Team sends care packages, which includes some toiletries, instant food, a multipot, a thermometer, and other daily necessities. During the quarantine period, returning students are also advised to follow the directions given by government officials and to coordinate with the ISSS Team. The team also provides useful Korean phrases for international students to help them with communication.
The self-quarantine period ends at 12 p.m. 14 days after arrival. Within two days of finishing the 14 days of self-isolation, these students are required to undergo a polymerase chain reaction (PCR) test for COVID-19 at the nearest health center. After confirmed negative, they are allowed to move into on-campus accommodations. KAIST will maintain the current method of remote education and distancing methods until further notice.
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2021.04.16 View 9819 -
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 11971 -
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 13157 -
ACS Nano Special Edition Highlights Innovations at KAIST
- The collective intelligence and technological innovation of KAIST was highlighted with case studies including the Post-COVID-19 New Deal R&D Initiative Project. -
KAIST’s innovative academic achievements and R&D efforts for addressing the world’s greatest challenges such as the COVID-19 pandemic were featured in ACS Nano as part of its special virtual issue commemorating the 50th anniversary of KAIST. The issue consisted of 14 review articles contributed by KAIST faculty from five departments, including two from Professor Il-Doo Kim from the Department of Materials Science and Engineering, who serves as an associate editor of the ACS Nano.
ACS Nano, the leading international journal in nanoscience and nanotechnology, published a special virtual issue last month, titled ‘Celebrating 50 Years of KAIST: Collective Intelligence and Innovation for Confronting Contemporary Issues.’
This special virtual issue introduced KAIST’s vision of becoming a ‘global value-creative leading university’ and its progress toward this vision over the last 50 years. The issue explained how KAIST has served as the main hub for advanced scientific research and technological innovation in South Korea since its establishment in 1971, and how its faculty and over 69,000 graduates played a key role in propelling the nation’s rapid industrialization and economic development.
The issue also emphasized the need for KAIST to enhance global cooperation and the exchange of ideas in the years to come, especially during the post-COVID era intertwined with the Fourth Industrial Revolution (4IR). In this regard, the issue cited the first ‘KAIST Emerging Materials e-Symposium (EMS)’, which was held online for five days in September of last year with a global audience of over 10,000 participating live via Zoom and YouTube, as a successful example of what academic collaboration could look like in the post-COVID and 4IR eras.
In addition, the “Science & Technology New Deal Project for COVID-19 Response,” a project conducted by KAIST with support from the Ministry of Science and ICT (MSIT) of South Korea, was also introduced as another excellent case of KAIST’s collective intelligence and technological innovation. The issue highlighted some key achievements from this project for overcoming the pandemic-driven crisis, such as: reusable anti-virus filters, negative-pressure ambulances for integrated patient transport and hospitalization, and movable and expandable negative-pressure ward modules.
“We hold our expectations high for the outstanding achievements and progress KAIST will have made by its centennial,” said Professor Kim on the background of curating the 14 review articles contributed by KAIST faculty from the fields of Materials Science and Engineering (MSE), Chemical and Biomolecular Engineering (CBE), Nuclear and Quantum Engineering (NQE), Electrical Engineering (EE), and Chemistry (Chem).
Review articles discussing emerging materials and their properties covered photonic carbon dots (Professor Chan Beum Park, MSE), single-atom and ensemble catalysts (Professor Hyunjoo Lee, CBE), and metal/metal oxide electrocatalysts (Professor Sung-Yoon Chung, MSE).
Review articles discussing materials processing covered 2D layered materials synthesis based on interlayer engineering (Professor Kibum Kang, MSE), eco-friendly methods for solar cell production (Professor Bumjoon J. Kim, CBE), an ex-solution process for the synthesis of highly stable catalysts (Professor WooChul Jung, MSE), and 3D light-patterning synthesis of ordered nanostructures (Professor Seokwoo Jeon, MSE, and Professor Dongchan Jang, NQE).
Review articles discussing advanced analysis techniques covered operando materials analyses (Professor Jeong Yeong Park, Chem), graphene liquid cell transmission electron microscopy (Professor Jong Min Yuk, MSE), and multiscale modeling and visualization of materials systems (Professor Seungbum Hong, MSE).
Review articles discussing practical state-of-the-art devices covered chemiresistive hydrogen sensors (Professor Il-Doo Kim, MSE), patient-friendly diagnostics and implantable treatment devices (Professor Steve Park, MSE), triboelectric nanogenerators (Professor Yang-Kyu Choi, EE), and next-generation lithium-air batteries (Professor Hye Ryung Byon, Chem, and Professor Il-Doo Kim, MSE).
In addition to Professor Il-Doo Kim, post-doctoral researcher Dr. Jaewan Ahn from the KAIST Applied Science Research Institute, Dean of the College of Engineering at KAIST Professor Choongsik Bae, and ACS Nano Editor-in-Chief Professor Paul S. Weiss from the University of California, Los Angeles also contributed to the publication of this ACS Nano special virtual issue.
The issue can be viewed and downloaded from the ACS Nano website at https://doi.org/10.1021/acsnano.1c01101.
Image credit: KAIST
Image usage restrictions: News organizations may use or redistribute this image,with proper attribution, as part of news coverage of this paper only.
Publication:
Ahn, J., et al. (2021) Celebrating 50 Years of KAIST: Collective Intelligence and Innovation for Confronting Contemporary Issues. ACS Nano 15(3): 1895-1907. Available online at https://doi.org/10.1021/acsnano.1c01101
Profile:
Il-Doo Kim, Ph.D
Chair Professor
idkim@kaist.ac.kr
http://advnano.kaist.ac.kr
Advanced Nanomaterials and Energy Lab.
Department of Materials Science and Engineering
Membrane Innovation Center for Anti-Virus and Air-Quality Control
https://kaist.ac.kr/
Korea Advanced Institute of Science and Technology (KAIST) Daejeon, Republic of Korea
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2021.03.05 View 29507 -
Deep-Learning and 3D Holographic Microscopy Beats Scientists at Analyzing Cancer Immunotherapy
Live tracking and analyzing of the dynamics of chimeric antigen receptor (CAR) T-cells targeting cancer cells can open new avenues for the development of cancer immunotherapy. However, imaging via conventional microscopy approaches can result in cellular damage, and assessments of cell-to-cell interactions are extremely difficult and labor-intensive. When researchers applied deep learning and 3D holographic microscopy to the task, however, they not only avoided these difficultues but found that AI was better at it than humans were.
Artificial intelligence (AI) is helping researchers decipher images from a new holographic microscopy technique needed to investigate a key process in cancer immunotherapy “live” as it takes place. The AI transformed work that, if performed manually by scientists, would otherwise be incredibly labor-intensive and time-consuming into one that is not only effortless but done better than they could have done it themselves. The research, conducted by the team of Professor YongKeun Park from the Department of Physics, appeared in the journal eLife last December.
A critical stage in the development of the human immune system’s ability to respond not just generally to any invader (such as pathogens or cancer cells) but specifically to that particular type of invader and remember it should it attempt to invade again is the formation of a junction between an immune cell called a T-cell and a cell that presents the antigen, or part of the invader that is causing the problem, to it. This process is like when a picture of a suspect is sent to a police car so that the officers can recognize the criminal they are trying to track down. The junction between the two cells, called the immunological synapse, or IS, is the key process in teaching the immune system how to recognize a specific type of invader.
Since the formation of the IS junction is such a critical step for the initiation of an antigen-specific immune response, various techniques allowing researchers to observe the process as it happens have been used to study its dynamics. Most of these live imaging techniques rely on fluorescence microscopy, where genetic tweaking causes part of a protein from a cell to fluoresce, in turn allowing the subject to be tracked via fluorescence rather than via the reflected light used in many conventional microscopy techniques.
However, fluorescence-based imaging can suffer from effects such as photo-bleaching and photo-toxicity, preventing the assessment of dynamic changes in the IS junction process over the long term. Fluorescence-based imaging still involves illumination, whereupon the fluorophores (chemical compounds that cause the fluorescence) emit light of a different color. Photo-bleaching or photo-toxicity occur when the subject is exposed to too much illumination, resulting in chemical alteration or cellular damage.
One recent option that does away with fluorescent labelling and thereby avoids such problems is 3D holographic microscopy or holotomography (HT). In this technique, the refractive index (the way that light changes direction when encountering a substance with a different density—why a straw looks like it bends in a glass of water) is recorded in 3D as a hologram.
Until now, HT has been used to study single cells, but never cell-cell interactions involved in immune responses. One of the main reasons is the difficulty of “segmentation,” or distinguishing the different parts of a cell and thus distinguishing between the interacting cells; in other words, deciphering which part belongs to which cell.
Manual segmentation, or marking out the different parts manually, is one option, but it is difficult and time-consuming, especially in three dimensions. To overcome this problem, automatic segmentation has been developed in which simple computer algorithms perform the identification.
“But these basic algorithms often make mistakes,” explained Professor YongKeun Park, “particularly with respect to adjoining segmentation, which of course is exactly what is occurring here in the immune response we’re most interested in.”
So, the researchers applied a deep learning framework to the HT segmentation problem. Deep learning is a type of machine learning in which artificial neural networks based on the human brain recognize patterns in a way that is similar to how humans do this. Regular machine learning requires data as an input that has already been labelled. The AI “learns” by understanding the labeled data and then recognizes the concept that has been labelled when it is fed novel data. For example, AI trained on a thousand images of cats labelled “cat” should be able to recognize a cat the next time it encounters an image with a cat in it. Deep learning involves multiple layers of artificial neural networks attacking much larger, but unlabeled datasets, in which the AI develops its own ‘labels’ for concepts it encounters.
In essence, the deep learning framework that KAIST researchers developed, called DeepIS, came up with its own concepts by which it distinguishes the different parts of the IS junction process. To validate this method, the research team applied it to the dynamics of a particular IS junction formed between chimeric antigen receptor (CAR) T-cells and target cancer cells. They then compared the results to what they would normally have done: the laborious process of performing the segmentation manually. They found not only that DeepIS was able to define areas within the IS with high accuracy, but that the technique was even able to capture information about the total distribution of proteins within the IS that may not have been easily measured using conventional techniques.
“In addition to allowing us to avoid the drudgery of manual segmentation and the problems of photo-bleaching and photo-toxicity, we found that the AI actually did a better job,” Professor Park added.
The next step will be to combine the technique with methods of measuring how much physical force is applied by different parts of the IS junction, such as holographic optical tweezers or traction force microscopy.
-Profile
Professor YongKeun Park
Department of Physics
Biomedical Optics Laboratory
http://bmol.kaist.ac.kr
KAIST
2021.02.24 View 12050