Kaist

Highly Flexible Organic Flash Memory for Foldable ..

A KAIST team reported ultra-flexible organic flash memory that is bendable down to a radius of 300 ?μm. The memory exhibits a significantly-long projected retention rate with a programming voltage on par with the present industrial standards. A joint research team led by Professor Seunghyup Yoo of the School of Electrical Engineering and Professor Sung Gap Im of the Department of Chemical and Biomolecular Engineering said that their memory technology can be applied to non-conventional substrates, such as plastics and papers, to demonstrate its feasibility over a wide range of applications. With Dr. Seungwon Lee and Dr. Hanul Moon playing the role of leading authors, the research was published in Nature Communications on September 28. Flash memory is a non-volatile, transistor-based data-storage device that has become essential in most electronic systems in daily life. With straightforward operation mechanisms and easy integration into NAND or NOR array architecture, flash memory has been established as the most successful and dominant non-volatile memory technology by far. Despite promising demonstrations in the early stages of organic electronics, the overall progress in this field has been far slower than that of thin-film transistors (TFTs) or other devices based on flexible materials. It has been challenging, in particular, to develop flash memory that simultaneously exhibits a significant level of flexibility and performance. This is mainly due to the scarcity of flexible dielectric layers, which are responsible for the tunneling and blocking of charges. The solution processing used for the preparation of most of the polymeric dielectric layers also makes it difficult to use them in flash memory due to the complexity involved in the formation of the bilayer dielectric structure, which is the key to flash memory operations. The research team tried to overcome these hurdles and realize highly flexible flash memory by employing thin polymeric insulators grown with initiated chemical vapor deposition (iCVD), a vapor-phase growth technique for polymers that was previously shown to be promising for the fabrication of flexible TFTs. It was further shown that these iCVD-based polymeric insulators, when coupled with rational device design and material choice, can make a significant contribution to flash memory as well. Memory using conventional polymer insulating films has often required a voltage as high as 100 V (volt) in order to attain long memory retention. If the device is made to operate at a low voltage, the short retention period of less than a month was problematic. The KAIST team produced flash memory with programming voltages around 10 V and a projected data retention time of over 10 years, while maintaining its memory performance even at a mechanical strain of 2.8％. This is a significant improvement over the existing inorganic insulation layer-based flash memory that allowed only a 1％ strain. The team demonstrated the virtually foldable memory devices by fabricating the proposed flash memory on a 6-micrometer-thick ultrathin plastic film. In addition, it succeeded in producing them on printing paper, opening a way for disposable smart electronic products such as electronic paper and electronic business card. Professor Yoo said, " This study well illustrates that even highly flexible flash memory can be made to have a practically viable level of performance, so that it contributes to full-fledged wearable electronic devices and smart electronic paper." < Figure 1. Structure of flexible flash memory > < Figure 2. Foldable flash memory >

Development of a Highly-Accurate Computational Mod..

A research team from KAIST developed a computational framework that enables the reconstruction of a comprehensive computational model of human metabolism, which allows for an accurate prediction of personal metabolic features (or phenotypes). Understanding personal metabolic phenotypes allows us to design effective therapeutic strategies for various chronic and infectious diseases. A human computational model called the genome-scale metabolic model (GEM) contains information on thousands of metabolic genes and their corresponding reactions and metabolites, and has played an important role in predicting metabolic phenotypes. Although several versions of human GEMs have been released, they had room for further development, especially as to incorporating biological information coming from a human genetics mechanism called “alternative splicing.” Alternative splicing is a genetic mechanism that allows a gene to give rise to multiple reactions, and is strongly associated with pathology. To tackle this problem, Jae Yong Ryu (a Ph.D. student), Dr. Hyun Uk Kim (Research Fellow), and Distinguished Professor Sang Yup Lee, all from the Department of Chemical and Biomolecular Engineering at KAIST, developed a computational framework that systematically generates metabolic reactions, and adds them to the human GEM. The resulting human GEM was demonstrated to accurately predict metabolic phenotypes under varied environmental conditions. The research results were published online in Proceedings of the National Academy of Sciences (PNAS) on October 24, 2017, under the title “Framework and resource for more than 11,000 gene-transcript-protein-reaction associations in human metabolism.” The research team first updated the biological contents of a previous version of the human GEM. The updated biological contents include metabolic genes and their corresponding metabolites and reactions. In particular, metabolic reactions catalyzed by already-known protein isoforms were additionally incorporated into the human GEM; protein isoforms are multiple variants of proteins generated from individual genes through the alternative splicing process. Each protein isoform is often responsible for the operation of a metabolic reaction. Although multiple protein isoforms generated from one gene can play different functions by having different sets of protein domains and/or subcellular localizations, such information was not properly considered in previous versions of human GEMs. Upon the initial update of the human GEM, named Recon 2M.1, the research team subsequently implemented a computational framework that systematically generates information on Gene-Transcript-Protein-Reaction Associations (GeTPRA) in order to identify protein isoforms that were previously not identified. This framework was developed in this study. As a result of the implementation of the framework for GeTPRA, more than 11,000 GeTPRA were automatically predicted, and thoroughly validated. Additional metabolic reactions were then added to Recon 2M.1 based on the predicted GeTPRA for the previously uncharacterized protein isoforms; Recon 2M.1 was renamed Recon 2M.2 from this upgrade. Finally, Recon 2M.2 was integrated with 446 sets of personal biological data (RNA-Seq data) in order to build patient-specific cancer models. These patient-specific cancer models were used to predict cancer metabolism activities and anticancer targets. The development of a new version of human GEMs along with the computational framework for GeTPRA is expected to boost studies in fundamental human genetics and medicine. Model files of the human GEMs Recon 2M.1 and 2M.2, a full list of the GeTPRA and the source code for the computational framework to predict the GeTPRA are all available as part of the publication of this study. Distinguished Professor Lee said, “The predicted GeTPRA from the computational framework is expected to serve as a guideline for future experiments on human genetics and biochemistry, whereas the resulting Recon 2M.2 can be used to predict drug targets for various human diseases.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation (NRF) of Korea. < Figure 1: A scheme of Recon 2M.1 development and its use in reconstructing personal genome-scale metabolic models (GEMs). (A) A concept of alternative splicing of human genes and its use in Gene-Transcript-Protein-Reaction Associations (GeTPRA) of Recon 2M.1. (B) A procedure of systematic refinement of the Recon 2Q. Recon 2Q is one of the previously released human GEMs. Biochemically inconsistent reactions include unbalanced, artificial, blocked, and/or redundant reactions. Iterative manual curation was conducted while validating the Recon 2M.1. (C) Reconstruction of cancer patient-specific GEMs using Recon 2M.1 for further simulation studies. In this study, personal biological data (RNA-Seq data) were obtained from The Cancer Genome Atlas (TCGA; https://cancergenome.nih.gov/ ) across the ten cancer types. > < Figure 2: Computational framework for the systematic generation of Gene-Transcript-Protein-Reaction Associations (GeTPRA; red box in the flowchart). Peptide sequences of metabolic genes defined in Recon 2M.1 were retrieved from a database called Ensembl. EC numbers and subcellular localizations of all the protein isoforms of metabolic genes in Recon 2M.1 were predicted using software programs EFICAz2.5 and Wolf PSort, respectively. Information on the newly predicted GeTPRA was systematically incorporated into the Recon 2M.1, thereby resulting in Recon 2M.2. >

Platinum Single Atom Catalysts for ‘Direct Formic ..

〈 Professor Hyunjoo Lee (left) and Ph.D. candidate Jiwhan Kim 〉 A research team co-led by Professor Hyunjoo Lee at the Department of Chemical and Biomolecular Engineering at KAIST and Professor Jeong Woo Han from the University of Seoul synthesized highly stable high-Pt-content single atom catalysts for direct formic acid fuel cells. The amount of platinum can be reduced to 1/10 of that of conventional platinum nanoparticle catalysts. Platinum (Pt) catalysts have been used in various catalytic reactions due to their high activity and stability. However, because Pt is rare and expensive, it is important to reduce the amount of Pt used. Pt single atom catalysts can reduce the size of the Pt particles to the size of an atom. Thus, the cost of Pt catalysts can be minimized because all of the Pt atoms can participate in the catalytic reactions. Additionally, single atom catalysts have no ensemble site in which two or more atoms are attached, and thus, the reaction selectivity is different from that of nanoparticle catalysts. Despite these advantages, single atom catalysts are easily aggregated and less stable due to their low coordination number and high surface free energy. It is difficult to develop a single atom catalyst with high content and high stability, and thus, its application in practical devices is limited. Direct formic acid fuel cells can be an energy source for next-generation portable devices because liquid formic acid as a fuel is safer and easier to store and transport than high-pressure hydrogen gas. To improve the stability of Pt single atom catalysts, Professor Lee’s group developed a Pt-Sn single atom alloy structure on an antimony-doped tin oxide (ATO) support. This structure has been proven by computational calculations which show that Pt single atoms substitute antimony sites in the antimony-tin alloy structure and are thermodynamically stable. This catalyst has been shown to have a higher activity up to 50 times per weight of Pt than that of the commercial catalyst, Pt/C, in the oxidation of formic acid, and the stability of the catalyst was also remarkably high. Professor Lee’s group also used a single atomic catalyst in a 'direct formic acid fuel cell’ consisting of membranes and electrodes. It is the first attempt to apply a single atomic catalyst to a full cell. In this case, an output similar to that of the commercial catalyst could be obtained by using 1/10 of the platinum compared to the commercial Pt/C catalyst. Ph.D. candidate Jiwhan Kim from KAIST was the first author of the research. This research was published online on September 11 in Advanced Energy Materials. This research was carried out with the support of the Samsung Electronics Future Technology Development Center. < Figure 1. Concept photograph for Pt single atom catalysts. > < Figure 2. Pt single atom catalysts by HAADF-STEM analysis (bright white circles) >

Highly Sensitive and Fast Indoor GNSS Signal Acqui..

< Professor Seung-Hyun Kong (right) and Research Fellow Tae-Sun Kim> A research team led by Professor Seung-Hyun Kong at the Cho Chun Shik Graduate School of Green Transportation, KAIST, developed high-speed, high-sensitivity Global Navigation Satellite System (GNSS) signal acquisition (search and detection) technology that can produce GNSS positioning fixes indoors. Using the team’s new technology, GNSS signals will be sufficient to identify locations anywhere in the world, both indoors and outdoors. This new research finding was published in the international journal IEEE Signal Processing Magazine (IEEE SPM) this September. Global Positioning System (GPS) developed by the U.S. Department of Defense in the 1990s is the most widely-used satellite-based navigation system, and GNSS is a terminology to indicate conventional satellite based navigation systems, such as GPS and Russian GLONASS, as well as new satellite-based navigation systems under development, such as European GALILEO, Chinese COMPASS, and other regional satellite-based navigation systems. In general, GNSS signals are transmitted all over the globe from 20,000 km above the Earth and thus a GNSS signal received by a small antennae in an outdoor environment has weak signal power. In addition, GNSS signals penetrating building walls become extremely weak so the signal can be less than 1/1000th of the signal power received outside. Using conventional acquisition techniques including the frequency-domain correlation technique to acquire an extremely weak GNSS signal causes the computational cost to increase by over a million times and the processing time for acquisition also increases tremendously. Because of this, indoor measurement techniques using GNSS signals were considered practically impossible for the last 20 years. To resolve such limitations, the research team developed a Synthesized Doppler-frequency Hypothesis Testing (SDHT) technique to dramatically reduce the acquisition time and computational load for extremely weak GNSS signals indoors. In general, GNSS signal acquisition is a search process in which the instantaneous accurate code phase and Doppler frequency of the incoming GNSS signal are identified. However, the number of Doppler frequency hypotheses grows proportionally to the coherent correlation time that should be necessarily increased to detect weak signals. In practice, the coherent correlation time should be more than 1000 times longer for extremely weak GNSS signals so the number of Doppler frequency hypotheses is greater than 20,000. On the other hand, the SDHT algorithm indirectly tests the Doppler frequency hypothesis utilizing the coherent correlation results of neighboring hypotheses. Therefore, using SDHT, only around 20 hypotheses are tested using conventional correlation techniques and the remaining 19,980 hypotheses are calculated with simple mathematical operations. As a result, SDHT achieves a huge computational cost reduction (by about 1000 times) and is 800 times faster for signal acquisition compared to conventional techniques. This means only about 15 seconds is required to detect extremely weak GNSS signals in buildings using a personal computer. The team predicts further studies for strengthening SDHT technology and developing positioning systems robust enough to multipath in indoor environments will allow indoor GNSS measurements within several seconds inside most buildings using GNSS alone. Professor Kong said, “This development made us the leader in indoor GNSS positioning technology in the world.” He continued, “We hope to commercialize indoor GNSS systems to create a new market.” The research team is currently registering a patent in Korea and applying for patents overseas, as well as planning to commercialize the technology with the help of the Institute for Startup KAIST. < Figure1. Positioning Results for the GPS Indoor Positioning System using SDHT Technology >

Ultra-Fast and Ultra-Sensitive Hydrogen Sensor

A KAIST team made an ultra-fast hydrogen sensor that can detect hydrogen gas levels under 1％ in less than seven seconds. The sensor also can detect hundreds of parts per million levels of hydrogen gas within 60 seconds at room temperature. A research group under Professor Il-Doo Kim in the Department of Materials Science and Engineering at KAIST, in collaboration with Professor Reginald M. Penner of the University of California-Irvine, has developed an ultra-fast hydrogen gas detection system based on a palladium (Pd) nanowire array coated with a metal-organic framework (MOF). Hydrogen has been regarded as an eco-friendly next-generation energy source. However, it is a flammable gas that can explode even with a small spark. For safety, the lower explosion limit for hydrogen gas is 4 vol％ so sensors should be able to detect the colorless and odorless hydrogen molecule quickly. The importance of sensors capable of rapidly detecting colorless and odorless hydrogen gas has been emphasized in recent guidelines issued by the U.S. Department of Energy. According to the guidelines, hydrogen sensors should detect 1 vol％ of hydrogen in air in less than 60 seconds for adequate response and recovery times. To overcome the limitations of Pd-based hydrogen sensors, the research team introduced a MOF layer on top of a Pd nanowire array. Lithographically patterned Pd nanowires were simply overcoated with a Zn-based zeolite imidazole framework (ZIF-8) layer composed of Zn ions and organic ligands. ZIF-8 film is easily coated on Pd nanowires by simple dipping (for 2?6 hours) in a methanol solution including Zn (NO3)2·6H2O and 2-methylimidazole. < This cover image depicts lithographically-patterned Pd nanowires overcoated with a Zn-based zeolite imidazole framework (ZIF-8) layer. > As synthesized ZIF-8 is a highly porous material composed of a number of micro-pores of 0.34 nm and 1.16 nm, hydrogen gas with a kinetic diameter of 0.289 nm can easily penetrate inside the ZIF-8 membrane, while large molecules (> 0.34 nm) are effectively screened by the MOF filter. Thus, the ZIF-8 filter on the Pd nanowires allows the predominant penetration of hydrogen molecules, leading to the acceleration of Pd-based H2 sensors with a 20-fold faster recovery and response speed compared to pristine Pd nanowires at room temperature. Professor Kim expects that the ultra-fast hydrogen sensor can be useful for the prevention of explosion accidents caused by the leakage of hydrogen gas. In addition, he expects that other harmful gases in the air can be accurately detected through effective nano-filtration by using of a variety of MOF layers. This study was carried out by Ph.D. candidate Won-Tae Koo (first author), Professor Kim (co-corresponding author), and Professor Penner (co-corresponding author). The study has been published in the online edition of ACS Nano, as the cover-featured image for the September issue. < Figure 1. Representative image for this paper published in ACS Nano, August, 18. > < Figure 2. Images of Pd nanowire array-based hydrogen sensors, scanning electron microscopy image of a Pd nanowire covered by a metal-organic framework layer, and the hydrogen sensing properties of the sensors. > < Figure 3. Schematic illustration of a metal-organic framework (MOF). The MOF, consisting of metal ions and organic ligands, is a highly porous material with an ultrahigh surface area. The various structures of MOFs can be synthesized depending on the kinds of metal ions and organic ligands. > < (From left) Professor Kim, Ph.D. candidate Koo, and Professor Penner >

Semiconductor Patterning of Seven Nanometers Techn..

A research team led by Professor Sang Ouk Kim in the Department of Materials Science and Engineering at KAIST has developed semiconductor manufacturing technology using a camera flash. This technology can manufacture ultra-fine patterns over a large area by irradiating a single flash with a seven-nanometer patterning technique for semiconductors. It can facilitate the manufacturing of highly efficient, integrated semiconductor devices in the future. Technology for the Artificial Intelligence (AI), the Internet of Things (IoTs), and big data, which are the major keys for the fourth Industrial Revolution, require high-capacity, high-performance semiconductor devices. It is necessary to develop lithography technology to produce such next-generation, highly integrated semiconductor devices. Although related industries have been using conventional photolithography for small patterns, this technique has limitations for forming a pattern of sub-10 nm patterns.? Molecular assembly patterning technology using polymers has been in the spotlight as the next generation technology to replace photolithography because it is inexpensive to produce and can easily form sub-10 nm patterns. However, since it generally takes a long time for heat treatment at high-temperature or toxic solvent vapor treatment, mass production is difficult and thus its commercialization has been limited. The research team introduced a camera flash that instantly emits strong light to solve the issues of polymer molecular assembly patterning. Using a flash can possibly achieve a semiconductor patterning of seven nanometers within 15 milliseconds (1 millisecond = 1/1,000 second), which can generate a temperature of several hundred degrees Celsius in several tens of milliseconds. The team has demonstrated that applying this technology to polymer molecular assembly allows a single flash of light to form molecular assembly patterns. The team also identified its compatibility with polymer flexible substrates, which are impossible to process at high temperatures. Through these findings, the technology can be applied to the fabrication of next-generation, flexible semiconductors. The researchers said the camera flash photo-thermal process will be introduced into molecular assembly technology and this highly-efficiency technology can accelerate the realization of molecular assembly semiconductor technology. Professor Kim, who led the research, said, “Despite its potential, molecular assembly semiconductor technology has remained a big challenge in improving process efficiency.” “This technology will be a breakthrough for the practical use of molecular assembly-based semiconductors.” The paper was published in the international journal, Advanced Materials on August 21 with first authors, researcher Hyeong Min Jin and PhD candidate Dae Yong Park. The research, sponsored by the Ministry of Science and ICT, was co-led Professor by Keon Jae Lee in the Department of Materials Science and Engineering at KAIST, and Professor Kwang Ho Kim in the School of Materials Science and Engineering at Pusan National University. < 1. Formation of semiconductor patterns using a camera flash> < Schematic diagram of molecular assembly pattern using a camera flash > < Self-assembled patterns>

A Novel and Practical Fab-route for Superomniphobi..

(clockwise from left: Jaeho Choi, Hee Tak Kim, Shin-Hyun Kim) A joint research team led by Professor Hee Tak Kim and Shin-Hyun Kim in the Department of Chemical and Biomolecular Engineering at KAIST developed a fabrication technology that can inexpensively produce surfaces capable of repelling liquids, including water and oil. The team used the photofluidization of azobenzene molecule-containing polymers to generate a superomniphobic surface which can be applied for developing stain-free fabrics, non-biofouling medical tubing, and corrosion-free surfaces. Mushroom-shaped surface textures, also called doubly re-entrant structures, are known to be the most effective surface structure that enhances resistance against liquid invasion, thereby exhibiting superior superomniphobic property. However, the existing procedures for their fabrication are highly delicate, time-consuming, and costly. Moreover, the materials required for the fabrication are restricted to an inflexible and expensive silicon wafer, which limits the practical use of the surface. To overcome such limitations, the research team used a different approach to fabricate the re-entrant structures called localized photofludization by using the peculiar optical phenomenon of azobenzene molecule-containing polymers (referred to as azopolymers). It is a phenomenon where an azopolymer becomes fluidized under irradiation, and the fluidization takes place locally within the thin surface layer of the azopolymer. With this novel approach, the team facilitated the localized photofluidization in the top surface layer of azopolymer cylindrical posts, successfully reconfiguring the cylindrical posts to doubly re-entrant geometry while the fluidized thin top surface of an azopolymer is flowing down. The structure developed by the team exhibits a superior superomniphobic property even for liquids infiltrating the surface immediately. Moreover, the superomniphobic property can be maintained on a curved target surface because its surficial materials are based on high molecules. Furthermore, the fabrication procedure of the structure is highly reproducible and scalable, providing a practical route to creating robust omniphobic surfaces. Professor Hee Tak Kim said, “Not only does the novel photo-fluidization technology in this study produce superior superomniphobic surfaces, but it also possesses many practical advantages in terms of fab-procedures and material flexibility; therefore, it could greatly contribute to real uses in diverse applications.” Professor Shin-Hyun Kim added, “The designed doubly re-entrant geometry in this study was inspired by the skin structure of springtails, insects dwelling in soil that breathe through their skin. As I carried out this research, I once again realized that humans can learn from nature to create new engineering designs.” The paper (Jaeho Choi as a first author) was published in ACS Nano, an international journal for Nano-technology, in August. < Schematic diagram of mushroom-shaped structure fabrication > < SEM image of mushroom-shaped structure > < Image of superomniphobic property of different types of liquid >

The Medici Effect： Highly Flexible, Wearable Displ..

< Ph.D. candidate Seungyeop Choi > How do you feel when technology you saw in a movie is made into reality? Collaboration between the electrical engineering and textile industries has made TVs or smartphone screens displaying on clothing a reality. A research team led by Professor Kyung Cheol Choi at the School of Electrical Engineering presented wearable displays for various applications including fashion, IT, and healthcare. Integrating OLED (organic light-emitting diode) into fabrics, the team developed the most highly flexible and reliable technology for wearable displays in the world. Recently, information displays have become increasingly important as they construct the external part of smart devices for the next generation. As world trends are focusing on the Internet of Things (IoTs) and wearable technology, the team drew a lot of attention by making great progress towards commercializing clothing-shaped ‘wearable displays’. The research for realizing displays on clothing gained considerable attention from academia as well as industry when research on luminescence formed in fabrics was introduced in 2011; however, there was no technology for commercializing it due to its surface roughness and flexibility. Because of this technical limitation, clothing-shaped wearable displays were thought to be unreachable technology. However, the KAIST team recently succeeded in developing the world’s most highly efficient, light-emitting clothes that can be commercialized. The research team used two different approaches, fabric-type and fiber-type, in order to realize clothing-shaped wearable displays. In 2015, the team successfully laminated a thin planarization sheet thermally onto fabric to form a surface that is compatible with the OLEDs approximately 200 hundred nanometers thick. Also, the team reported their research outcomes on enhancing the reliability of operating fiber-based OLEDs. In 2016, the team introduced a dip-coating method, capable of uniformly depositing layers, to develop polymer light-emitting diodes, which show high luminance even on thin fabric. Based on the research performance in 2015 and 2016, Ph.D. candidate Seungyeop Choi took the lead in the research team and succeeded in realizing fabric-based OLEDs, showing high luminance and efficiency while maintaining the flexibility of the fabric. The long-term reliability of this wearable device that has the world’s best electrical and optical characteristics was verified through their self-developed, organic and inorganic encapsulation technology. According to the team, their wearable device facilitates the operation of OLEDs even at a bending radius of 2mm. According to Choi, “Having wavy structures and empty spaces, fiber plays a significant role in lowering the mechanical stress on the OLEDs.” “Screen displayed on our daily clothing is no longer a future technology,” said Professor Choi. “Light-emitting clothes will have considerable influence on not only the e-textile industry but also the automobile and healthcare industries.” Moreover, the research team remarked, “It means a lot to realize clothing-shaped OLEDs that have the world’s best luminance and efficiency. It is the most flexible fabric-based light-emitting device among those reported. Moreover, noting that this research carried out an in-depth analysis of the mechanical characteristics of the clothing-spared, light-emitting device, the research performance will become a guideline for developing the fabric-based electronics industry.” This research was funded by the Ministry of Trade, Industry and Energy and collaborated with KOLON Glotech, INC. The research performance was published in Scientific Reports in July. < OLEDs operating in fabrics > < Current-voltage-luminance and efficiency of the highly flexible, fabric-based OLEDs;Image of OLEDs after repetitive bending tests;Verification of flexibility through mechanical simulation >

Discovery of an Optimal Drug Combination： Overcomi..

A KAIST research team presented a novel method for improving medication treatment for liver cancer using Systems Biology, combining research from information technology and the life sciences. Professor Kwang-Hyun Cho in the Department of Bio and Brain Engineering at KAIST conducted the research in collaboration with Professor Jung-Hwan Yoon in the Department of Internal Medicine at Seoul National University Hospital. This research was published in Hepatology in September 2017 (available online from August 24, 2017). Liver cancer is the fifth and seventh most common cancer found in men and women throughout the world, which places it second in the cause of cancer deaths. In particular, Korea has 28.4 deaths from liver cancer per 100,000 persons, the highest death rate among OECD countries and twice that of Japan. Each year in Korea, 16,000 people get liver cancer on average, yet the five-year survival rate stands below 12％. According to the National Cancer Information Center, lung cancer (17,399) took the highest portion of cancer-related deaths, followed by liver cancer (11,311) based on last year data. Liver cancer is known to carry the highest social cost in comparison to other cancers and it causes the highest fatality in earlier age groups (40s-50s). In that sense, it is necessary to develop a new treatment that mitigates side effects yet elevates the survival rate. There are ways in which liver cancer can be cured, such as surgery, embolization, and medication treatments; however, the options become limited for curing progressive cancer, a stage in which surgical methods cannot be executed. Among anticancer medications, Sorafenib, a drug known for enhancing the survival rate of cancer patients, is a unique drug allowed for use as a targeted anticancer medication for progressive liver cancer patients. Its sales reached more than ten billion KRW annually in Korea, but its efficacy works on only about 20％ of the treated patients. Also, acquired resistance to Sorafenib is emerging. Additionally, the action mechanism and resistance mechanism of Sorafenib is only vaguely identified. Although Sorafenib only extends the survival rate of terminal cancer patients less than three months on average, it is widely being used because drugs developed by global pharmaceutical companies failed to outperform its effectiveness. Professor Cho’s research team analyzed the expression changes of genes in cell lines in response to Sorafenib in order to identify the effect and the resistance mechanism of Sorafenib. As a result, the team discovered the resistance mechanism of Sorafenib using Systems Biology analysis. By combining computer simulations and biological experiments, it was revealed that protein disulfide isomerase (PDI) plays a crucial role in the resistance mechanism of Sorafenib and that its efficacy can be improved significantly by blocking PDI. The research team used mice in the experiment and discovered the synergic effect of PDI inhibition with Sorafenib for reducing liver cancer cells, known as hepatocellular carcinoma. Also, more PDIs are shown in tissue from patients who possess a resistance to Sorafenib. From these findings, the team could identify the possibility of its clinical applications. The team also confirmed these findings from clinical data through a retrospective cohort study. “Molecules that play an important role in cell lines are mostly put under complex regulation. For this reason, the existing biological research has a fundamental limitations for discovering its underlying principles,” Professor Cho said. “This research is a representative case of overcoming this limitation of traditional life science research by using a Systems Biology approach, combining IT and life science. It suggests the possibility of developing a new method that overcomes drug resistance with a network analysis of the targeted drug action mechanism of cancer.” The research was supported by the National Research Foundation of Korea (NRF) and funded by the Ministry of Science and ICT. < Figure 1. Simulation results from cellular experiments using hepatocellular carcinoma > < Figure 2. Network analysis and computer simulation by using the endoplasmic reticulum (ER) stress network > < Figure 3. ER stress network model >

Solutal Marangoni Flows of Miscible Liquid Drive T..

< Professor Hyoungsoo Kim, Department of Mechanical Engineering, KAIST > A research team led by Hyoungsoo Kim, a professor of Mechanical Engineering at KAIST, succeeded in quantifying the phenomenon called, the Marangoni effect, which occurs at the interface between alcohol and water. It is expected that this finding will be a valuable resource used for effectively removing impurities from a surface fluid without any contamination, and developing materials that can replace surfactants. This research, co-conducted with a research team led by Professor Howard A. Stone at Princeton University, was published online in Nature Physics on July 31. The Marangoni effect, also known as tears of wine, is generated when two fluids having a different surface tension meet, causing finite mixing, spreading time and length scale. Typically, people believe that infinitely miscible liquids immediately mix together; however, it is not always true according to this paper. The typical surface tension of alcohol is three times lower than that of water, and this different surface tension generates the Marangoni-driven convection flow at the interface of the two liquids. In addition, there is a certain amount of time required for them to mix. This phenomenon has been discussed many times since it was discovered in early the 20th century, yet there was a limit to quantifying and explaining it. Professor Kim, considering the mixing and spreading mechanism, used various flow visualization techniques and equipment for capturing high speed images in his experiment. Through the flow visualization methods, the team succeeded in quantifying and explaining the complex, physicochemical phenomenon generated between water and alcohol. Moreover, they developed a theoretical model to predict the physicochemical hydrodynamic phenomena. The theoretical model can predict the speed of Marangoni-driven convection flow, the area of a drop of alcohol and the time required to develop the flow field. Hence, this model can map out types of materials (e.g., alcohol) and the volume of a drop of liquid as applicable to target a specific situation. Moreover, the research team believes that the interfacial flow enables the driving of bulk flows and that it can be a source of technology for effectively delivering drugs and removing impurities from a surface of substance without causing secondary contamination. Above all, the results show a possibility for replacing surfactant with alcohol as a material used for delivering drugs. In the case of the drug delivery, some drugs are encapsulated with a surfactant in order to be effectively transported in vivo; however, the surfactant accumulates in the body, which can cause various side effects, such as heart disease. Therefore, using new materials like alcohol for drug delivery will contribute to preventing the side effects caused by the surfactant. “The surfactant is used for delivering drugs, but it is difficult to be expelled from the body. This will cause various side effects, such as heart diseases in asthmatic patients,” said Professor Kim. “I hope that using new materials, like alcohol, will free people from these side effects.” (Marangoni-driven convection flow generated at the interface between water and alcohol, and the flow visualization results) < A drop of alcohol on a water surface > < Comparison of mixing structures on the surface > < Marangoni mixing flow under the free surface >

Multi-Device Mobile Platform for App Functionality..

Case 1. Mr. Kim, an employee, logged on to his SNS account using a tablet PC at the airport while traveling overseas. However, a malicious virus was installed on the tablet PC and some photos posted on his SNS were deleted by someone else. Case 2. Mr. and Mrs. Brown are busy contacting credit card and game companies, because his son, who likes games, purchased a million dollars worth of game items using his smartphone. Case 3. Mr. Park, who enjoys games, bought a sensor-based racing game through his tablet PC. However, he could not enjoy the racing game on his tablet because it was not comfortable to tilt the device for game control. The above cases are some of the various problems that can arise in modern society where diverse smart devices, including smartphones, exist. Recently, new technology has been developed to easily solve these problems. Professor Insik Shin from the School of Computing has developed ‘Mobile Plus,’ which is a mobile platform that can share the functionalities of applications between smart devices. This is a novel technology that allows applications to easily share their functionalities without needing any modifications. Smartphone users often use Facebook to log in to another SNS account like Instagram, or use a gallery app to post some photos on their SNS. These examples are possible, because the applications share their login and photo management functionalities. The functionality sharing enables users to utilize smartphones in various and convenient ways and allows app developers to easily create applications. However, current mobile platforms such as Android or iOS only support functionality sharing within a single mobile device. It is burdensome for both developers and users to share functionalities across devices because developers would need to create more complex applications and users would need to install the applications on each device. To address this problem, Professor Shin’s research team developed platform technology to support functionality sharing between devices. The main concept is using virtualization to give the illusion that the applications running on separate devices are on a single device. They succeeded in this virtualization by extending a RPC (Remote Procedure Call) scheme to multi-device environments. This virtualization technology enables the existing applications to share their functionalities without needing any modifications, regardless of the type of applications. So users can now use them without additional purchases or updates. Mobile Plus can support hardware functionalities like cameras, microphones, and GPS as well as application functionalities such as logins, payments, and photo sharing. Its greatest advantage is its wide range of possible applications. Professor Shin said, "Mobile Plus is expected to have great synergy with smart home and smart car technologies. It can provide novel user experiences (UXs) so that users can easily utilize various applications of smart home/vehicle infotainment systems by using a smartphone as their hub." This research was published at ACM MobiSys, an international conference on mobile computing that was hosted in the United States on June 21. < Figure1. Users can securely log on to SNS accounts by using their personal devices > < Figure 2. Parents can control impulse shopping of their children. > < Figure 3. Users can enjoy games more and more by using the smartphone as a controller >

Analysis of Gas Adsorption Properties for Amorphou..

Professor Jihan Kim from the Department of Chemical and Biomolecular Engineering at KAIST has developed a method to predict gas adsorption properties of amorphous porous materials. Metal-organic frameworks (MOFs) have large surface area and high density of pores, making them appropriate for various energy and environmental-related applications. And although most MOFs are crystalline, these structures can deform during synthesis and/or industrial processes, leading to loss in long-range order. Unfortunately, without the structural information, existing computer simulation techniques cannot be used to model these materials. In this research, Professor Kim’s research team demonstrated that one can replace the material properties of structurally deformed MOFs with those of crystalline MOFs to indirectly analyze/model the material properties of amorphous materials. First, the team conducted simulations on methane gas adsorption properties for over 12,000 crystalline MOFs to obtain a large training set data, and created a resulting structure-property map. Upon mapping the experimental data of amorphous MOFs onto the structure-property map, results showed that regardless of crystallinity, the gas adsorption properties of MOFs showed congruence and consistency amongst one another. Based on these findings, selected crystalline MOFs with the most similar gas adsorption properties as the collapsed structure from the 12,000 candidates. Then, the team verified that the adsorption properties of these similar MOFs can be successfully transferred to the deformed MOFs across different temperatures and even to different gas molecules (e.g. hydrogen), demonstrating transferability of properties. These findings allow material property prediction in porous materials such as MOFs without structural information, and the techniques here can be used to better predict and understand optimal materials for various applications including, carbon dioxide capture, gas storage and separations. This research was conducted in collaboration with Professor Dae-Woon Lim at Kyoto University, Professor Myunghyun Paik at Seoul National University, Professor Minyoung Yoon at Gachon University, and Aadesh Harale at Saudi Arabian Oil Company. The research was published in the Proceedings of the National Academy of Sciences (PNAS) online on 10 July and the co-first authors were Ph. D. candidate WooSeok Jeong and Professor Dae-Woon Lim. This research was funded by the Saudi Aramco-KAIST CO2 Management Center. < Figure 1. Trends in structure - material property map and in collapsed structures > < Figure 2. Transferability between the experimental results of collapsed MOFs and the simulation results of crystalline MOFs >