Korean
Highly Uniform and Low Hysteresis Pressure Sensor ..
< Professor Steve Park (left) and the First Author Mr. Jinwon Oh (right) > Researchers have designed a flexible pressure sensor that is expected to have a much wider applicability. A KAIST research team fabricated a piezoresistive pressure sensor of high uniformity with low hysteresis by chemically grafting a conductive polymer onto a porous elastomer template. The team discovered that the uniformity of pore size and shape is directly related to the uniformity of the sensor. The team noted that by increasing pore size and shape variability, the variability of the sensor characteristics also increases. Researchers led by Professor Steve Park from the Department of Materials Science and Engineering confirmed that compared to other sensors composed of randomly sized and shaped pores, which had a coefficient of variation in relative resistance change of 69.65%, their newly developed sensor exhibited much higher uniformity with a coefficient of variation of 2.43%. This study was reported in Small as the cover article on August 16. Flexible pressure sensors have been actively researched and widely applied in electronic equipment such as touch screens, robots, wearable healthcare devices, electronic skin, and human-machine interfaces. In particular, piezoresistive pressure sensors based on elastomer‐conductive material composites hold significant potential due to their many advantages including a simple and low-cost fabrication process. Various research results have been reported for ways to improve the performance of piezoresistive pressure sensors, most of which have been focused on increasing the sensitivity. Despite its significance, maximizing the sensitivity of composite-based piezoresistive pressure sensors is not necessary for many applications. On the other hand, sensor-to-sensor uniformity and hysteresis are two properties that are of critical importance to realize any application. The importance of sensor-to-sensor uniformity is obvious. If the sensors manufactured under the same conditions have different properties, measurement reliability is compromised, and therefore the sensor cannot be used in a practical setting. In addition, low hysteresis is also essential for improved measurement reliability. Hysteresis is a phenomenon in which the electrical readings differ depending on how fast or slow the sensor is being pressed, whether pressure is being released or applied, and how long and to what degree the sensor has been pressed. When a sensor has high hysteresis, the electrical readings will differ even under the same pressure, making the measurements unreliable. Researchers said they observed a negligible hysteresis degree which was only 2%. This was attributed to the strong chemical bonding between the conductive polymer and the elastomer template, which prevents their relative sliding and displacement, and the porosity of the elastomer that enhances elastic behavior. “This technology brings forth insight into how to address the two critical issues in pressure sensors: uniformity and hysteresis. We expect our technology to play an important role in increasing practical applications and the commercialization of pressure sensors in the near future,” said Professor Park. This work was conducted as part of the KAIST‐funded Global Singularity Research Program for 2019, and also supported by the KUSTAR‐KAIST Institute. Figure 1. Image of a porous elastomer template with uniform pore size and shape (left), Graph showing high uniformity in the sensors’ performance (right). Figure 2. Hysteresis loops of the sensor at different pressure levels (left), and after a different number of cycles (right). Figure 3. The cover page of Small Journal, Volume 15, Issue 33 Publication: Jinwon Oh, Jin‐Oh Kim, Yunjoo Kim, Han Byul Choi, Jun Chang Yang, Serin Lee, Mikhail Pyatykh, Jung Kim, Joo Yong Sim, and Steve Park. 2019. Highly Uniform and Low Hysteresis Piezoresistive Pressure Sensors Based on Chemical Grafting of Polypyrrole on Elastomer Template with Uniform Pore Size. Small. Wiley-VCH Verlag GmbH & Co. KgaA, Weinheim, Germany, Volume No. 15, Issue No. 33, Full Paper No. 201901744, 8 pages. https://doi.org/10.1002/smll.201901744 Profile: Prof. Steve Park, MS, PhD stevepark@kaist.ac.kr http://steveparklab.kaist.ac.kr/ Assistant Professor Organic and Nano Electronics Laboratory Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Mr. Jinwon Oh, MS jwoh1701@gmail.com http://steveparklab.kaist.ac.kr/ Researcher Organic and Nano Electronics Laboratory Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Prof. Jung Kim, MS, PhD jungkim@kaist.ac.kr http://medev.kaist.ac.kr/ Professor Biorobotics Laboratory Department of Mechanical Engineering Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Joo Yong Sim, PhD jsim@etri.re.kr Researcher Bio-Medical IT Convergence Research Department Electronics and Telecommunications Research Institute (ETRI) https://www.etri.re.kr Daejeon 34129, Korea (END)
Manipulating Brain Cells by Smartphone
Researchers have developed a soft neural implant that can be wirelessly controlled using a smartphone. It is the first wireless neural device capable of indefinitely delivering multiple drugs and multiple colour lights, which neuroscientists believe can speed up efforts to uncover brain diseases such as Parkinson’s, Alzheimer’s, addiction, depression, and pain. A team under Professor Jae-Woong Jeong from the School of Electrical Engineering at KAIST and his collaborators have invented a device that can control neural circuits using a tiny brain implant controlled by a smartphone. The device, using Lego-like replaceable drug cartridges and powerful, low-energy Bluetooth, can target specific neurons of interest using drugs and light for prolonged periods. This study was published in Nature Biomedical Engineering. “This novel device is the fruit of advanced electronics design and powerful micro and nanoscale engineering,” explained Professor Jeong. “We are interested in further developing this technology to make a brain implant for clinical applications.” This technology significantly overshadows the conventional methods used by neuroscientists, which usually involve rigid metal tubes and optical fibers to deliver drugs and light. Apart from limiting the subject’s movement due to bulky equipment, their relatively rigid structure causes lesions in soft brain tissue over time, therefore making them not suitable for long-term implantation. Although some efforts have been made to partly mitigate adverse tissue response by incorporating soft probes and wireless platforms, the previous solutions were limited by their inability to deliver drugs for long periods of time as well as their bulky and complex control setups. To achieve chronic wireless drug delivery, scientists had to solve the critical challenge of the exhaustion and evaporation of drugs. To combat this, the researchers invented a neural device with a replaceable drug cartridge, which could allow neuroscientists to study the same brain circuits for several months without worrying about running out of drugs. These ‘plug-n-play’ drug cartridges were assembled into a brain implant for mice with a soft and ultrathin probe (with the thickness of a human hair), which consisted of microfluidic channels and tiny LEDs (smaller than a grain of salt), for unlimited drug doses and light delivery. Controlled with an elegant and simple user interface on a smartphone, neuroscientists can easily trigger any specific combination or precise sequencing of light and drug delivery in any implanted target animal without the need to be physically inside the laboratory. Using these wireless neural devices, researchers can also easily setup fully automated animal studies where the behaviour of one animal could affect other animals by triggering light and/or drug delivery. “The wireless neural device enables chronic chemical and optical neuromodulation that has never been achieved before,” said lead author Raza Qazi, a researcher with KAIST and the University of Colorado Boulder. This work was supported by grants from the National Research Foundation of Korea, US National Institute of Health, National Institute on Drug Abuse, and Mallinckrodt Professorship. (A neural implant with replaceable drug cartridges and Bluetooth low-energy can target specific neurons.) (Micro LED controlling using smartphone application)
[AZoNano] New Strategy for Synthesizing Single-Cry..
A group of researchers from KAIST has developed a new approach for producing single-crystalline graphene quantum dots, which release stable blue light.
[Electronics Online] A powerful tool to analyze MO..
An international team, including staff from the Korea Advanced Institute of Science and Technology (Kaist; Daejeon, South Korea; www.kaist.ac.kr), led by Kaist’s professor Jeung Ku Kang, has developed a technology to analyze the gas adsorption behavior of molecules of each individual pore of a metal organic framework (MOF). Existing technology is only able to measure the amount of gas molecules adsorbed by the material, without directly observing the adsorption behavior. The team developed a realtime gas-adsorption crystallography system by integrating an existing X-ray diffraction measurement device that can provide structural information and a gas adsorption measurement device. The system allows the observation of a mesoporous MOF with multiple pores. The team categorized the adsorption behavior of MOF molecules by pore type, achieving the identification of a stepwise adsorption process that was not previously possible to analyze. The team analyzed how the pore structure and the type of adsorption molecule affect the adsorption behavior to suggest what type of MOF structure is suitable as a storage material for each type of adsorption behavior. Specifically, the team used two MOFs, PCN-224 and ZIF-412 which contain two and three different types of pore, respectively, to generate isotherms of individual pores by combining gas adsorption measurements with in situ X-ray diffraction. This isotherm decomposition approach provides access to information about the gas uptake capacity, surface area and accessible pore volume of each individual pore, as well as the impact of pore geometry on the uptake and distribution of different adsorbates within the pores. “By understanding the realtime adsorption behavior of molecules at the level of the pores that form the material, rather than the whole material, we will be able to apply this technology to develop a new high-capacity storage material,” says professor Kang. https://www.chemengonline.com/powerful-tool-analyze-mofs/?printmode=1
FIRIC-EU JRC Joint Workshop on Smart Specializatio..
The Fourth Industrial Revolution Intelligence Center (FIRIC) at KAIST discussed ‘Smart Specialization’ for regional innovation and economic growth in the wake of the Fourth Industrial Revolution during the workshop with the EU Joint Research Center (EU-JRC) in Seville, Spain last week. The two sides also agreed to sign an MOU to expand mutual collaboration. KAIST’s FIRIC was founded in cooperation with the World Economic Forum in July 2017 to carry out policy research for the promotion of science and technology-based inclusive growth and innovation and to lead related global efforts. The EU-JRC has committed to developing cohesive policies that aim to narrow regional gaps within the European Union. Founded in 1958 in Brussels, the EU-JRC has long been in charge of EU strategies for regional innovation based on emerging technologies. The workshop also covered issues related to public-private partnerships and innovation clusters from the perspective of the EU and Asia, such as the global value chain and the implementation of industrial clusters policy amid the changes in the industrial ecosystem due to digitalization, automation, and the utilization of robotics during the Fourth Industrial Revolution. In addition, the session included discussions on inclusive growth and job market changes in the era of the Fourth Industrial Revolution, addressing how Smart Specialization and the outcomes of the 4IR will shift the paradigm of current job and technology capabilities, as well as employment issues in many relevant industries. In particular, the actual case studies and their related policies and regulatory trends regarding the potential risks and ethical issues of artificial intelligence were introduced. Regarding the financial services that utilize blockchain technologies and the establishment of public sector governance for such technologies, the participating experts noted difficulties in the diffusion of blockchain-based local currencies or public services, which call for a sophisticated analytical and practical framework for innovative and transparent governance. Dr. Mark Boden, the Team Leader of the EU-JRC, introduced the EU’s initiatives to promote Smart Specialization, such as its policy process, governance design, vision sharing, and priority setting, with particular emphasis on targeted support for Smart Specialization in lagging regions. Professor So Young Kim, who is the dean of the Graduate School of Science and Technology Policy and FIRIC’s Deputy Director said, “KAIST’s global role regarding the Fourth Industrial Revolution will be expanded in the process of exploring and developing innovative models of technology-policy governance while working jointly with the EU-JRC.”
Researchers Describe a Mechanism Inducing Self-Kil..
(Professor Kim (left) and lead author Lee) Researchers have described a new mechanism which induces the self-killing of cancer cells by perturbing ion homeostasis. A research team from the Department of Biochemical Engineering has developed helical polypeptide potassium ionophores that lead to the onset of programmed cell death. The ionophores increase the active oxygen concentration to stress endoplasmic reticulum to the point of cellular death. The electrochemical gradient between extracellular and intracellular conditions plays an important role in cell growth and metabolism. When a cell’s ion homeostasis is disturbed, critical functions accelerating the activation of apoptosis are inhibited in the cell. Although ionophores have been intensively used as an ion homeostasis disturber, the mechanisms of cell death have been unclear and the bio-applicability has been limited. In the study featured at Advanced Science, the team presented an alpha helical peptide-based anticancer agent that is capable of transporting potassium ions with water solubility. The cationic, hydrophilic, and potassium ionic groups were combined at the end of the peptide side chain to provide both ion transport and hydrophilic properties. These peptide-based ionophores reduce the intracellular potassium concentration and at the same time increase the intracellular calcium concentration. Increased intracellular calcium concentrations produce intracellular reactive oxygen species, causing endoplasmic reticulum stress, and ultimately leading to apoptosis. Anticancer effects were evaluated using tumor-bearing mice to confirm the therapeutic effect, even in animal models. It was found that tumor growth was strongly inhibited by endoplasmic stress-mediated apoptosis. Lead author Dr. Dae-Yong Lee said, “A peptide-based ionophore is more effective than conventional chemotherapeutic agents because it induces apoptosis via elevated reactive oxygen species levels. Professor Yeu-Chun Kim said he expects this new mechanism to be widely used as a new chemotherapeutic strategy. This research was funded by the National Research Foundation.
Synthesizing Single-Crystalline Hexagonal Graphene..
(Figure: Uniformly ordered single-crystalline graphene quantum dots of various sizes synthesized through solution chemistry.) A KAIST team has designed a novel strategy for synthesizing single-crystalline graphene quantum dots, which emit stable blue light. The research team confirmed that a display made of their synthesized graphene quantum dots successfully emitted blue light with stable electric pressure, reportedly resolving the long-standing challenges of blue light emission in manufactured displays. The study, led by Professor O Ok Park in the Department of Chemical and Biological Engineering, was featured online in Nano Letters on July 5. Graphene has gained increased attention as a next-generation material for its heat and electrical conductivity as well as its transparency. However, single and multi-layered graphene have characteristics of a conductor so that it is difficult to apply into semiconductor. Only when downsized to the nanoscale, semiconductor’s distinct feature of bandgap will be exhibited to emit the light in the graphene. This illuminating featuring of dot is referred to as a graphene quantum dot. Conventionally, single-crystalline graphene has been fabricated by chemical vapor deposition (CVD) on copper or nickel thin films, or by peeling graphite physically and chemically. However, graphene made via chemical vapor deposition is mainly used for large-surface transparent electrodes. Meanwhile, graphene made by chemical and physical peeling carries uneven size defects. The research team explained that their graphene quantum dots exhibited a very stable single-phase reaction when they mixed amine and acetic acid with an aqueous solution of glucose. Then, they synthesized single-crystalline graphene quantum dots from the self-assembly of the reaction intermediate. In the course of fabrication, the team developed a new separation method at a low-temperature precipitation, which led to successfully creating a homogeneous nucleation of graphene quantum dots via a single-phase reaction. Professor Park and his colleagues have developed solution phase synthesis technology that allows for the creation of the desired crystal size for single nanocrystals down to 100 nano meters. It is reportedly the first synthesis of the homogeneous nucleation of graphene through a single-phase reaction. Professor Park said, "This solution method will significantly contribute to the grafting of graphene in various fields. The application of this new graphene will expand the scope of its applications such as for flexible displays and varistors.” This research was a joint project with a team from Korea University under Professor Sang Hyuk Im from the Department of Chemical and Biological Engineering, and was supported by the National Research Foundation of Korea, the Nano-Material Technology Development Program from the Electronics and Telecommunications Research Institute (ETRI), KAIST EEWS, and the BK21+ project from the Korean government.
‘Flying Drones for Rescue’
< Team USRG and Professor Shim (second from the right) > Having recently won the AI R&D Grand Challenge Competition in Korea with their drone, Team USRG (Unmanned System Research Group) led by Professor Hyunchul Shim from the School of Electrical Engineering is all geared up to take on their next challenges: the ‘Defense Advanced Research Projects Agency Subterranean Challenge (DARPA SubT Challenge)’ and ‘Lockheed Martin’s AlphaPilot Challenge’ next month. Team USRG won the obstacle course race in the ‘2019 AI R&D Grand Challenge Competition’ on July 12. They managed to successfully dominate the challenging category of ‘control intelligence.’ Having to complete the obstacle course race solely using AI systems without any connection to the internet made it difficult for most of the eight participating teams to pass the third section of the race, and only Team USRG passed the long pipeline course during their attempt in the main event. They also demonstrated, after the main event, that their drone can navigate all of the checkpoints including landing on the “H” mark using deep learning. Their drone flew through polls and pipes, and escaped from windows and mazes against strong winds, amid cheers and groans from the crowd gathered at the Korea Exhibition Center (KINTEX) in Goyang, Korea. The team was awarded three million KRW in prize money, and received a research grant worth six hundred million KRW from the Ministry of Science and ICT (MSIT). “Being ranked first in the race for which we were never given a chance for a test flight means a lot to our team. Considering that we had no information on the exact size of the course in advance, this is a startling result,” said Professor Shim. “We will carry out further research with this funding, and compete once again with the improved AI and drone technology in the 2020 competition,” he added. The AI R&D Grand Challenge Competition, which was first started in 2017, has been designed to promote AI research and development and expand its application to addressing high-risk technical challenges with significant socio-economic impact. This year’s competition presented participants with a task where they had to develop AI software technology for drones to navigate themselves autonomously during complex disaster relief operations such as aid delivery. Each team participated in one of the four tracks of the competition, and their drones were evaluated based on the criteria for each track. The divisions were broken up into intelligent context-awareness, intelligent character recognition, auditory intelligence, and control intelligence. Team USRG’s technological prowess has been already well acclaimed among international peer groups. Teamed up with NASA JPL, Caltech, and MIT, they will compete in the subterranean mission during the ‘DARPA SubT Challenge’. Team CoSTAR, as its name stands for, is working together to build ‘Collaborative SubTerranean Autonomous Resilient Robots.’ Professor Shim emphasized the role KAIST plays in Team CoSTAR as a leader in drone technology. “I think when our drone technology will be added to our peers’ AI and robotics, Team CoSTAR will bring out unsurpassable synergy in completing the subterrestrial and planetary applications. I would like to follow the footprint of Hubo, the winning champion of the 2015 DARPA Robotics Challenge and even extend it to subterranean exploration,” he said. These next generation autonomous subsurface explorers are now all optimizing the physical AI robot systems developed by Team CoSTAR. They will test their systems in more realistic field environments August 15 through 22 in Pittsburgh, USA. They have already received funding from DARPA for participating. Team CoSTAR will compete in three consecutive yearly events starting this year, and the last event, planned for 2021, will put the team to the final test with courses that incorporate diverse challenges from all three events. Two million USD will be awarded to the winner after the final event, with additional prizes of up to 200,000 USD for self-funded teams. Team USRG also ranked third in the recent Hyundai Motor Company’s ‘Autonomous Vehicle Competition’ and another challenge is on the horizon: Lockheed Martin’s ‘AlphaPilot Challenge’. In this event, the teams will be flying their drones through a series of racing gates, trying to beat the best human pilot. The challenge is hosted by Lockheed Martin, the world’s largest military contractor and the maker of the famed F-22 and F-35 stealth fighters, with the goal of stimulating the development of autonomous drones. Team USRG was selected from out of more than 400 teams from around the world and is preparing for a series of races this fall, beginning from the end of August. Professor Shim said, “It is not easy to perform in a series of competitions in just a few months, but my students are smart, hardworking, and highly motivated. These events indeed demand a lot, but they really challenge the researchers to come up with technologies that work in the real world. This is the way robotics really should be.”
Flexible User Interface Distribution for Ubiquitou..
< Research Group of Professor Insik Shin (center) > KAIST researchers have developed mobile software platform technology that allows a mobile application (app) to be executed simultaneously and more dynamically on multiple smart devices. Its high flexibility and broad applicability can help accelerate a shift from the current single-device paradigm to a multiple one, which enables users to utilize mobile apps in ways previously unthinkable. Recent trends in mobile and IoT technologies in this era of 5G high-speed wireless communication have been hallmarked by the emergence of new display hardware and smart devices such as dual screens, foldable screens, smart watches, smart TVs, and smart cars. However, the current mobile app ecosystem is still confined to the conventional single-device paradigm in which users can employ only one screen on one device at a time. Due to this limitation, the real potential of multi-device environments has not been fully explored. A KAIST research team led by Professor Insik Shin from the School of Computing, in collaboration with Professor Steve Ko’s group from the State University of New York at Buffalo, has developed mobile software platform technology named FLUID that can flexibly distribute the user interfaces (UIs) of an app to a number of other devices in real time without needing any modifications. The proposed technology provides single-device virtualization, and ensures that the interactions between the distributed UI elements across multiple devices remain intact. This flexible multimodal interaction can be realized in diverse ubiquitous user experiences (UX), such as using live video steaming and chatting apps including YouTube, LiveMe, and AfreecaTV. FLUID can ensure that the video is not obscured by the chat window by distributing and displaying them separately on different devices respectively, which lets users enjoy the chat function while watching the video at the same time. In addition, the UI for the destination input on a navigation app can be migrated into the passenger’s device with the help of FLUID, so that the destination can be easily and safely entered by the passenger while the driver is at the wheel. FLUID can also support 5G multi-view apps – the latest service that allows sports or games to be viewed from various angles on a single device. With FLUID, the user can watch the event simultaneously from different viewpoints on multiple devices without switching between viewpoints on a single screen. PhD candidate Sangeun Oh, who is the first author, and his team implemented the prototype of FLUID on the leading open-source mobile operating system, Android, and confirmed that it can successfully deliver the new UX to 20 existing legacy apps. “This new technology can be applied to next-generation products from South Korean companies such as LG’s dual screen phone and Samsung’s foldable phone and is expected to embolden their competitiveness by giving them a head-start in the global market.” said Professor Shin. This study will be presented at the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019) October 21 through 25 in Los Cabos, Mexico. The research was supported by the National Science Foundation (NSF) (CNS-1350883 (CAREER) and CNS-1618531). Figure 1. Live video streaming and chatting app scenario Figure 2. Navigation app scenario Figure 3. 5G multi-view app scenario Publication: Sangeun Oh, Ahyeon Kim, Sunjae Lee, Kilho Lee, Dae R. Jeong, Steven Y. Ko, and Insik Shin. 2019. FLUID: Flexible User Interface Distribution for Ubiquitous Multi-device Interaction. To be published in Proceedings of the 25th Annual International Conference on Mobile Computing and Networking (ACM MobiCom 2019). ACM, New York, NY, USA. Article Number and DOI Name TBD. Video Material: https://youtu.be/lGO4GwH4enA Profile: Prof. Insik Shin, MS, PhD ishin@kaist.ac.kr https://cps.kaist.ac.kr/~ishin Professor Cyber-Physical Systems (CPS) Lab School of Computing Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Sangeun Oh, PhD Candidate ohsang1213@kaist.ac.kr https://cps.kaist.ac.kr/ PhD Candidate Cyber-Physical Systems (CPS) Lab School of Computing Korea Advanced Institute of Science and Technology (KAIST) http://kaist.ac.kr Daejeon 34141, Korea Profile: Prof. Steve Ko, PhD stevko@buffalo.edu https://nsr.cse.buffalo.edu/?page_id=272 Associate Professor Networked Systems Research Group Department of Computer Science and Engineering State University of New York at Buffalo http://www.buffalo.edu/ Buffalo 14260, USA (END)
KAIST-KU Joint Research Center Opens
(President Shin (fifth from right) and Khalifa University Executive Vice President Arif Sultan Al Hammadi cut the tape during the opening ceremony of the joint research center at KAIST on July 5.) The Joint Research Center partnering KAIST and Khalifa University has been completed and the opening of the KAIST center was held on July 5, 2019, following the opening at Khalifa in April. The joint research center will explore the most impactful technologies that will change people’s lives in the face of the new industrial environment brought about by the Fourth Industrial Revolution. The breakthroughs include smart transportation and smart healthcare such as wireless electric vehicles, unmanned vehicles, and wearable healthcare devices. The two institutions signed an MOU on the Joint Research Agreement on the Technology Development for the Fourth Industrial Revolution in 2018. This is the second phase of collaboration following the partnership agreement that was signed in 2010 between the two institutions, which aimed to provide the best science and technology education as well as develop nuclear energy in the UAE. The Khalifa University delegation, headed by Executive Vice President Arif Sultan Al Hammadi and Senior Vice President of Research and Development Steven Griffiths, flew in to attend the ceremony at KAIST. President Sung-Chul Shin, Vice President for Research Hyun Wook Park, Vice President for Planning and Budget Su-chan Chae, Associate Vice President of the International Office Man-Sung Yim joined and Co-Directors of the Joint Research Center Daniel Choi from Khalifa and Jong-Hyun Kim from KAIST also participated in the opening ceremony.
Deep Learning-Powered ‘DeepEC’ Helps Accurately Un..
(Figure: Overall scheme of DeepEC) A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions. A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner. DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism. EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction. DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers. In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component. Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method. This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.” “DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim. Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.” This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT. Profile: -Professor Hyun Uk Kim (ehukim@kaist.ac.kr) https://sites.google.com/view/ehukim Department of Chemical and Biomolecular Engineering -Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr) Department of Chemical and Biomolecular Engineering http://mbel.kaist.ac.kr
High-Performance Sodium Ion Batteries Using Copper..
(Prof.Yuk and his two PhD candidates Parks) Researchers presented a new strategy for extending sodium ion batteries’ cyclability using copper sulfide as the electrode material. This strategy has led to high-performance conversion reactions and is expected to advance the commercialization of sodium ion batteries as they emerge as an alternative to lithium ion batteries. Professor Jong Min Yuk’s team confirmed the stable sodium storage mechanism using copper sulfide, a superior electrode material that is pulverization-tolerant and induces capacity recovery. Their findings suggest that when employing copper sulfide, sodium ion batteries will have a lifetime of more than five years with one charge per a day. Even better, copper sulfide, composed of abundant natural materials such as copper and sulfur, has better cost competitiveness than lithium ion batteries, which use lithium and cobalt. Intercalation-type materials such as graphite, which serve as commercialized anode materials in lithium ion batteries, have not been viable for high-capacity sodium storage due to their insufficient interlayer spacing. Thus, conversion and alloying reactions type materials have been explored to meet higher capacity in the anode part. However, those materials generally bring up large volume expansions and abrupt crystallographic changes, which lead to severe capacity degradation. The team confirmed that semi-coherent phase interfaces and grain boundaries in conversion reactions played key roles in enabling pulverization-tolerant conversion reactions and capacity recovery, respectively. Most of conversion and alloying reactions type battery materials usually experience severe capacity degradations due to having completely different crystal structures and large volume expansion before and after the reactions. However, copper sulfides underwent a gradual crystallographic change to make the semi-coherent interfaces, which eventually prevented the pulverization of particles. Based on this unique mechanism, the team confirmed that copper sulfide exhibits a high capacity and high cycling stability regardless of its size and morphology. Professor Yuk said, “Sodium ion batteries employing copper sulfide can advance sodium ion batteries, which could contribute to the development of low-cost energy storage systems and address the micro-dust issue” This study was posted in Advanced Science on April 26 online and selected as the inside back cover for June issue. (Figure: Schematic model demonstrating grain boundaries and phase interfaces formations.)