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AI to Determine When to Intervene with Your Driving
(Professor Uichin Lee (left) and PhD candidate Auk Kim) Can your AI agent judge when to talk to you while you are driving? According to a KAIST research team, their in-vehicle conservation service technology will judge when it is appropriate to contact you to ensure your safety. Professor Uichin Lee from the Department of Industrial and Systems Engineering at KAIST and his research team have developed AI technology that automatically detects safe moments for AI agents to provide conversation services to drivers. Their research focuses on solving the potential problems of distraction created by in-vehicle conversation services. If an AI agent talks to a driver at an inopportune moment, such as while making a turn, a car accident will be more likely to occur. In-vehicle conversation services need to be convenient as well as safe. However, the cognitive burden of multitasking negatively influences the quality of the service. Users tend to be more distracted during certain traffic conditions. To address this long-standing challenge of the in-vehicle conversation services, the team introduced a composite cognitive model that considers both safe driving and auditory-verbal service performance and used a machine-learning model for all collected data. The combination of these individual measures is able to determine the appropriate moments for conversation and most appropriate types of conversational services. For instance, in the case of delivering simple-context information, such as a weather forecast, driver safety alone would be the most appropriate consideration. Meanwhile, when delivering information that requires a driver response, such as a “Yes” or “No,” the combination of driver safety and auditory-verbal performance should be considered. The research team developed a prototype of an in-vehicle conversation service based on a navigation app that can be used in real driving environments. The app was also connected to the vehicle to collect in-vehicle OBD-II/CAN data, such as the steering wheel angle and brake pedal position, and mobility and environmental data such as the distance between successive cars and traffic flow. Using pseudo-conversation services, the research team collected a real-world driving dataset consisting of 1,388 interactions and sensor data from 29 drivers who interacted with AI conversational agents. Machine learning analysis based on the dataset demonstrated that the opportune moments for driver interruption could be correctly inferred with 87% accuracy. The safety enhancement technology developed by the team is expected to minimize driver distractions caused by in-vehicle conversation services. This technology can be directly applied to current in-vehicle systems that provide conversation services. It can also be extended and applied to the real-time detection of driver distraction problems caused by the use of a smartphone while driving. Professor Lee said, “In the near future, cars will proactively deliver various in-vehicle conversation services. This technology will certainly help vehicles interact with their drivers safely as it can fairly accurately determine when to provide conversation services using only basic sensor data generated by cars.” The researchers presented their findings at the ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp’19) in London, UK. This research was supported in part by Hyundai NGV and by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT. (Figure: Visual description of safe enhancement technology for in-vehicle conversation services)
2019.11.13
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Ultrafast Quantum Motion in a Nanoscale Trap Detected
< Professor Heung-Sun Sim (left) and Co-author Dr. Sungguen Ryu (right) > KAIST researchers have reported the detection of a picosecond electron motion in a silicon transistor. This study has presented a new protocol for measuring ultrafast electronic dynamics in an effective time-resolved fashion of picosecond resolution. The detection was made in collaboration with Nippon Telegraph and Telephone Corp. (NTT) in Japan and National Physical Laboratory (NPL) in the UK and is the first report to the best of our knowledge. When an electron is captured in a nanoscale trap in solids, its quantum mechanical wave function can exhibit spatial oscillation at sub-terahertz frequencies. Time-resolved detection of such picosecond dynamics of quantum waves is important, as the detection provides a way of understanding the quantum behavior of electrons in nano-electronics. It also applies to quantum information technologies such as the ultrafast quantum-bit operation of quantum computing and high-sensitivity electromagnetic-field sensing. However, detecting picosecond dynamics has been a challenge since the sub-terahertz scale is far beyond the latest bandwidth measurement tools. A KAIST team led by Professor Heung-Sun Sim developed a theory of ultrafast electron dynamics in a nanoscale trap, and proposed a scheme for detecting the dynamics, which utilizes a quantum-mechanical resonant state formed beside the trap. The coupling between the electron dynamics and the resonant state is switched on and off at a picosecond so that information on the dynamics is read out on the electric current being generated when the coupling is switched on. NTT realized, together with NPL, the detection scheme and applied it to electron motions in a nanoscale trap formed in a silicon transistor. A single electron was captured in the trap by controlling electrostatic gates, and a resonant state was formed in the potential barrier of the trap. The switching on and off of the coupling between the electron and the resonant state was achieved by aligning the resonance energy with the energy of the electron within a picosecond. An electric current from the trap through the resonant state to an electrode was measured at only a few Kelvin degrees, unveiling the spatial quantum-coherent oscillation of the electron with 250 GHz frequency inside the trap. Professor Sim said, “This work suggests a scheme of detecting picosecond electron motions in submicron scales by utilizing quantum resonance. It will be useful in dynamical control of quantum mechanical electron waves for various purposes in nano-electronics, quantum sensing, and quantum information”. This work was published online at Nature Nanotechnology on November 4. It was partly supported by the Korea National Research Foundation through the SRC Center for Quantum Coherence in Condensed Matter. For more on the NTT news release this article, please visit https://www.ntt.co.jp/news2019/1911e/191105a.html -ProfileProfessor Heung-Sun Sim Department of PhysicsDirector, SRC Center for Quantum Coherence in Condensed Matterhttps://qet.kaist.ac.kr KAIST -Publication:Gento Yamahata, Sungguen Ryu, Nathan Johnson, H.-S. Sim, Akira Fujiwara, and Masaya Kataoka. 2019. Picosecond coherent electron motion in a silicon single-electron source. Nature Nanotechnology (Online Publication). 6 pages. https://doi.org/10.1038/s41565-019-0563-2
2019.11.05
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Tungsten Suboxide Improves the Efficiency of Platinum in Hydrogen Production
< PhD Candidate Jinkyu Park and Professor Jinwoo Lee > Researchers presented a new strategy for enhancing catalytic activity using tungsten suboxide as a single-atom catalyst (SAC). This strategy, which significantly improves hydrogen evolution reaction (HER) in metal platinum (pt) by 16.3 times, sheds light on the development of new electrochemical catalyst technologies. Hydrogen has been touted as a promising alternative to fossil fuels. However, most of the conventional industrial hydrogen production methods come with environmental issues, releasing significant amounts of carbon dioxide and greenhouse gases. Electrochemical water splitting is considered a potential approach for clean hydrogen production. Pt is one of the most commonly used catalysts to improve HER performance in electrochemical water splitting, but the high cost and scarcity of Pt remain key obstacles to mass commercial applications. SACs, where all metal species are individually dispersed on a desired support material, have been identified as one way to reduce the amount of Pt usage, as they offer the maximum number of surface exposed Pt atoms. Inspired by earlier studies, which mainly focused on SACs supported by carbon-based materials, a KAIST research team led by Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering investigated the influence of support materials on the performance of SACs. Professor Lee and his researchers suggested mesoporous tungsten suboxide as a new support material for atomically dispersed Pt, as this was expected to provide high electronic conductivity and have a synergetic effect with Pt. They compared the performance of single-atom Pt supported by carbon and tungsten suboxide respectively. The results revealed that the support effect occurred with tungsten suboxide, in which the mass activity of a single-atom Pt supported by tungsten suboxide was 2.1 times greater than that of single-atom Pt supported by carbon, and 16.3 times higher than that of Pt nanoparticles supported by carbon. The team indicated a change in the electronic structure of Pt via charge transfer from tungsten suboxide to Pt. This phenomenon was reported as a result of strong metal-support interaction between Pt and tungsten suboxide. HER performance can be improved not only by changing the electronic structure of the supported metal, but also by inducing another support effect, the spillover effect, the research group reported. Hydrogen spillover is a phenomenon where adsorbed hydrogen migrates from one surface to another, and it occurs more easily as the Pt size becomes smaller. The researchers compared the performance of single-atom Pt and Pt nanoparticles supported by tungsten suboxide. The single-atom Pt supported by tungsten suboxide exhibited a higher degree of hydrogen spillover phenomenon, which enhanced the Pt mass activity for hydrogen evolution up to 10.7 times compared to Pt nanoparticles supported by tungsten suboxide. Professor Lee said, “Choosing the right support material is important for improving electrocatalysis in hydrogen production. The tungsten suboxide catalyst we used to support Pt in our study implies that interactions between the well-matched metal and support can drastically enhance the efficiency of the process.” This research was supported by the Ministry of Science and ICT and introduced in the International Edition of the German journal Angewandte Chemie. Figure. Schematic representation of hydrogen evolution reaction (HER) of pseudo single-atom Pt supported by tungsten suboxide -Publication Jinkyu Park, Dr. Seonggyu Lee, Hee-Eun Kim, Ara Cho, Seongbeen Kim, Dr. Youngjin Ye, Prof. Jeong Woo Han, Prof. Hyunjoo Lee, Dr. Jong Hyun Jang, and Prof. Jinwoo Lee. 2019. Investigation of the Support Effect in Atomically Dispersed Pt on WO3−x for Utilization of Pt in the Hydrogen Evolution Reaction. International Edition of Angewandte Chemie. Volume No. 58. Issue No. 45. 6 pages. https://doi.org/10.1002/anie.201908122 -ProfileProfessor Jinwoo LeeConvergence of Energy and Nano Science Laboratoryhttp://cens.kaist.ac.kr Department of Chemical and Biomolecular EngineeringKAIST
2019.10.28
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Image Analysis to Automatically Quantify Gender Bias in Movies
Many commercial films worldwide continue to express womanhood in a stereotypical manner, a recent study using image analysis showed. A KAIST research team developed a novel image analysis method for automatically quantifying the degree of gender bias in films. The ‘Bechdel Test’ has been the most representative and general method of evaluating gender bias in films. This test indicates the degree of gender bias in a film by measuring how active the presence of women is in a film. A film passes the Bechdel Test if the film (1) has at least two female characters, (2) who talk to each other, and (3) their conversation is not related to the male characters. However, the Bechdel Test has fundamental limitations regarding the accuracy and practicality of the evaluation. Firstly, the Bechdel Test requires considerable human resources, as it is performed subjectively by a person. More importantly, the Bechdel Test analyzes only a single aspect of the film, the dialogues between characters in the script, and provides only a dichotomous result of passing the test, neglecting the fact that a film is a visual art form reflecting multi-layered and complicated gender bias phenomena. It is also difficult to fully represent today’s various discourse on gender bias, which is much more diverse than in 1985 when the Bechdel Test was first presented. Inspired by these limitations, a KAIST research team led by Professor Byungjoo Lee from the Graduate School of Culture Technology proposed an advanced system that uses computer vision technology to automatically analyzes the visual information of each frame of the film. This allows the system to more accurately and practically evaluate the degree to which female and male characters are discriminatingly depicted in a film in quantitative terms, and further enables the revealing of gender bias that conventional analysis methods could not yet detect. Professor Lee and his researchers Ji Yoon Jang and Sangyoon Lee analyzed 40 films from Hollywood and South Korea released between 2017 and 2018. They downsampled the films from 24 to 3 frames per second, and used Microsoft’s Face API facial recognition technology and object detection technology YOLO9000 to verify the details of the characters and their surrounding objects in the scenes. Using the new system, the team computed eight quantitative indices that describe the representation of a particular gender in the films. They are: emotional diversity, spatial staticity, spatial occupancy, temporal occupancy, mean age, intellectual image, emphasis on appearance, and type and frequency of surrounding objects. Figure 1. System Diagram Figure 2. 40 Hollywood and Korean Films Analyzed in the Study According to the emotional diversity index, the depicted women were found to be more prone to expressing passive emotions, such as sadness, fear, and surprise. In contrast, male characters in the same films were more likely to demonstrate active emotions, such as anger and hatred. Figure 3. Difference in Emotional Diversity between Female and Male Characters The type and frequency of surrounding objects index revealed that female characters and automobiles were tracked together only 55.7 % as much as that of male characters, while they were more likely to appear with furniture and in a household, with 123.9% probability. In cases of temporal occupancy and mean age, female characters appeared less frequently in films than males at the rate of 56%, and were on average younger in 79.1% of the cases. These two indices were especially conspicuous in Korean films. Professor Lee said, “Our research confirmed that many commercial films depict women from a stereotypical perspective. I hope this result promotes public awareness of the importance of taking prudence when filmmakers create characters in films.” This study was supported by KAIST College of Liberal Arts and Convergence Science as part of the Venture Research Program for Master’s and PhD Students, and will be presented at the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW) on November 11 to be held in Austin, Texas. Publication: Ji Yoon Jang, Sangyoon Lee, and Byungjoo Lee. 2019. Quantification of Gender Representation Bias in Commercial Films based on Image Analysis. In Proceedings of the 22nd ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). ACM, New York, NY, USA, Article 198, 29 pages. https://doi.org/10.1145/3359300 Link to download the full-text paper: https://files.cargocollective.com/611692/cscw198-jangA--1-.pdf Profile: Prof. Byungjoo Lee, MD, PhD byungjoo.lee@kaist.ac.kr http://kiml.org/ Assistant Professor Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Ji Yoon Jang, M.S. yoone3422@kaist.ac.kr Interactive Media Lab Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea Profile: Sangyoon Lee, M.S. Candidate sl2820@kaist.ac.kr Interactive Media Lab Graduate School of Culture Technology (CT) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea (END)
2019.10.17
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Two Professors Recognized for the National R&D Excellence 100
< Professor Haeng-Ki Lee (left) and Professor Jeong-Ho Lee (right) > Two KAIST professors were listed among the 2019 National R&D Excellence 100 announced by the Ministry of Science and ICT and the Korea Institute of S&T Evaluation and Planning. Professor Haeng-Ki Lee from the Department of Civil and Environmental Engineering was recognized in the field of mechanics and materials for his research on developing new construction materials through the convergence of nano- and biotechnologies. In the field of life and marine science, Professor Jeong-Ho Lee from the Graduate School of Medical Science and Engineering was lauded for his research of diagnostic tools and therapies for glioblastoma and pediatric brain tumors. A certificate from the Minister of Ministry of Science and ICT will be conferred to these two professors, and their names will be inscribed on a special 2019 National R&D Excellence 100 plaque to celebrate their achievements. The professors will also be given privileges during the process of new R&D project selection. (END)
2019.10.15
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Professor Byong-Guk Park Named Scientist of October
< Professor Byong-Guk Park > Professor Byong-Guk Park from the Department of Materials Science and Engineering was selected as the ‘Scientist of the Month’ for October 2019 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Park was recognized for his contributions to the advancement of spin-orbit torque (SOT)-based magnetic random access memory (MRAM) technology. He received 10 million KRW in prize money. A next-generation, non-volatile memory device MRAM consists of thin magnetic films. It can be applied in “logic-in-memory” devices, in which logic and memory functionalities coexist, thus drastically improving the performance of complementary metal-oxide semiconductor (CMOS) processors. Conventional MRAM technology is limited in its ability to increase the operation speed of a memory device while maintaining a high density. Professor Park tackled this challenge by introducing a new material, antiferromagnet (IrMn), that generates a sizable amount of SOT as well as an exchange-bias field, which makes successful data writing possible without an external magnetic field. This research outcome paved the way for the development of MRAM, which has a simple device structure but features high speeds and density. Professor Park said, “I feel rewarded to have forwarded the feasibility and applicability of MRAM. I will continue devoting myself to studying further on the development of new materials that can help enhance the performance of memory devices." (END)
2019.10.10
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Object Identification and Interaction with a Smartphone Knock
(Professor Lee (far right) demonstrate 'Knocker' with his students.) A KAIST team has featured a new technology, “Knocker”, which identifies objects and executes actions just by knocking on it with the smartphone. Software powered by machine learning of sounds, vibrations, and other reactions will perform the users’ directions. What separates Knocker from existing technology is the sensor fusion of sound and motion. Previously, object identification used either computer vision technology with cameras or hardware such as RFID (Radio Frequency Identification) tags. These solutions all have their limitations. For computer vision technology, users need to take pictures of every item. Even worse, the technology will not work well in poor lighting situations. Using hardware leads to additional costs and labor burdens. Knocker, on the other hand, can identify objects even in dark environments only with a smartphone, without requiring any specialized hardware or using a camera. Knocker utilizes the smartphone’s built-in sensors such as a microphone, an accelerometer, and a gyroscope to capture a unique set of responses generated when a smartphone is knocked against an object. Machine learning is used to analyze these responses and classify and identify objects. The research team under Professor Sung-Ju Lee from the School of Computing confirmed the applicability of Knocker technology using 23 everyday objects such as books, laptop computers, water bottles, and bicycles. In noisy environments such as a busy café or on the side of a road, it achieved 83% identification accuracy. In a quiet indoor environment, the accuracy rose to 98%. The team believes Knocker will open a new paradigm of object interaction. For instance, by knocking on an empty water bottle, a smartphone can automatically order new water bottles from a merchant app. When integrated with IoT devices, knocking on a bed’s headboard before going to sleep could turn off the lights and set an alarm. The team suggested and implemented 15 application cases in the paper, presented during the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019) held in London last month. Professor Sung-Ju Lee said, “This new technology does not require any specialized sensor or hardware. It simply uses the built-in sensors on smartphones and takes advantage of the power of machine learning. It’s a software solution that everyday smartphone users could immediately benefit from.” He continued, “This technology enables users to conveniently interact with their favorite objects.” The research was supported in part by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea funded by the Ministry of Science and ICT and an Institute for Information & Communications Technology Promotion (IITP) grant funded by the Ministry of Science and ICT. Figure: An example knock on a bottle. Knocker identifies the object by analyzing a unique set of responses from the knock, and automatically launches a proper application or service.
2019.10.02
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Professor Hyun Gyu Park Appointed as Associate Editor for Biosensors and Bioelectronics
Professor Hyun Gyu Park from the Department of Chemical and Biomolecular Engineering was appointed as an associate editor for Biosensors and Bioelectronics, an international journal published by Elsevier. Biosensors and Bioelectronics is one of the top SCI journals in the fields of chemistry and analytical science (IF 9.518 as of 2018). Professor Park was recognized and appointed as the associate editor for this journal due to his outstanding research achievements in the fields of nucleic acid engineering, biosensors, and nanobiotechnology. Professor Park will serve as the associate editor from this October until December 2021. (END)
2019.10.01
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Two More Cross-generation Collaborative Labs Open
< President Sung-Chul Shin (sixth from the left) and Professor Sun Chang Kim (seventh from the left) at the signboard ceremony of KAIST BioDesigneering Laboratory > KAIST opened two more cross-generation collaborative labs last month. KAIST BioDesigneering Laboratory headed by Professor Sun Chang Kim from the Department of Biological Sciences and Nanophotonics Laboratory led by Professor Yong-Hee Lee from the Department of Physics have been selected to receive 500 million KRW funding for five years. A four-member selection committee including the former President of ETH Zürich Professor Emeritus Ralph Eichler and Professor Kwang-Soo Kim of Harvard Medical School conducted a three-month review and evaluation for this selection to be made. With these two new labs onboard, a total of six cross-generation collaborative labs will be operated on campus. The operation of cross-generation collaborative labs has been in trial since March last year, as one of the KAIST’s Vision 2031 research innovation initiatives. This novel approach is to pair up senior and junior faculty members for sustaining research and academic achievements even after the senior researcher retires, so that the spectrum of knowledge and research competitiveness can be extended to future generations. The selected labs will be funded for five years, and the funding will be extended if necessary. KAIST will continue to select new labs every year. One of this year’s selectees Professor Sun Chang Kim will be teamed up with Professor Byung-Kwan Cho from the same department and Professor Jung Kyoon Choi from the Department of Bio and Brain Engineering to collaborate in the fields of synthetic biology, systems biology, and genetic engineering. This group mainly aims at designing and synthesizing optimal genomes that can efficiently manufacture protein drug and biomedical active materials. They will also strive to secure large amounts of high-functioning natural active substances, new adhesive antibacterial peptides, and eco-friendly ecological restoration materials. It is expected that collaboration between these three multigenerational professors will help innovate their bio-convergence technology and further strengthen their international competitiveness in the global bio-market. Another world-renowned scholar Professor Yong-Hee Lee of photonic crystal laser study will be joined by Professor Minkyo Seo from the same department and Professor Hansuek Lee from the Graduate School of Nanoscience and Technology. They will explore the extreme limits of light-material interaction based on optical micro/nano resonators, with the goal of developing future nonlinear optoelectronic and quantum optical devices. The knowledge and technology newly gained from the research are expected to provide an important platform for a diverse range of fields from quantum communications to biophysics. (END)
2019.09.06
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Algorithm Identifies Optimal Pairs for Composing Metal-Organic Frameworks
The integration of metal-organic frameworks (MOFs) and other metal nanoparticles has increasingly led to the creation of new multifunctional materials. Many researchers have integrated MOFs with other classes of materials to produce new structures with synergetic properties. Despite there being over 70,000 collections of synthesized MOFs that can be used as building blocks, the precise nature of the interaction and the bonding at the interface between the two materials still remains unknown. The question is how to sort out the right matching pairs out of 70,000 MOFs. An algorithmic study published in Nature Communications by a KAIST research team presents a clue for finding the perfect pairs. The team, led by Professor Ji-Han Kim from the Department of Chemical and Biomolecular Engineering, developed a joint computational and experimental approach to rationally design MOF@MOFs, a composite of MOFs where an MOF is grown on a different MOF. Professor Kim’s team, in collaboration with UNIST, noted that the metal node of one MOF can coordinately bond with the linker of a different MOF and the precisely matched interface configurations at atomic and molecular levels can enhance the likelihood of synthesizing MOF@MOFs. They screened thousands of MOFs and identified optimal MOF pairs that can seamlessly connect to one another by taking advantage of the fact that the metal node of one MOF can form coordination bonds with the linkers of the second MOF. Six pairs predicted from the computational algorithm successfully grew into single crystals. This computational workflow can readily extend into other classes of materials and can lead to the rapid exploration of the composite MOFs arena for accelerated materials development. Even more, the workflow can enhance the likelihood of synthesizing MOF@MOFs in the form of large single crystals, and thereby demonstrated the utility of rationally designing the MOF@MOFs. This study is the first algorithm for predicting the synthesis of composite MOFs, to the best of their knowledge. Professor Kim said, “The number of predicted pairs can increase even more with the more general 2D lattice matching, and it is worth investigating in the future.” This study was supported by Samsung Research Funding & Incubation Center of Samsung Electronics. (Figure: An example of a rationally synthesized MOF@MOFs (cubic HKUST-1@MOF-5 ))
2019.08.30
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Distinguished Professor Sukbok Chang Donates His Prize Money
The honoree of the 2019 Korea Best Scientist and Technologist Award, Distinguished Professor Sukbok Chang donated his prize money of one hundred million KRW to the Chemistry Department Scholarship Fund and the Lyu Keun-Chul Sports Complex Management Fund during a donation ceremony last week. Professor Chang won the award last month in recognition of his pioneering achievements and lifetime contributions to the development of carbon-hydrogen activation strategies, especially for carbon-carbon, carbon-nitrogen, and carbon-oxygen formations. Professor Chang, a world renowned chemist, has been recognized for his highly selective catalytic systems, allowing the controlled defunctionalization of bio-derived platform substrates under mild conditions and opening a new avenue for the utilization of biomass-derived platform chemicals. “All my achievements are the results of my students’ hard work and dedication. I feel very fortunate to have such talented team members. I want to express my sincere gratitude for such a great research environment that we have worked together in so far,” said Professor Chang at the ceremony. KAIST President Sung-Chul Shin said, “Not only will Professor Chang’s donation make a significant contribution to the Department of Chemistry, but also to the improvement of the Lyu Keun-Chul Sports Complex’s management, which directly links to the health and welfare of the KAIST community.” Professor Chang currently holds the position of distinguished professor at KAIST and director of the Center for Catalytic Hydrocarbon Functionalizations in the Institute for Basic Science (IBS). He previously received the Kyung-Ahm Academic Award in 2013 and the Korea Toray Science Award in 2018. All these prize money also went to the school. (END)
2019.08.26
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Highly Uniform and Low Hysteresis Pressure Sensor to Increase Practical Applicability
< 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.krDaejeon 34129, Korea (END)
2019.08.19
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