technology
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KAIST Develops Thread-like, Flexible Thermoelectric Materials Applicable in Extreme Environments
A team of Korean researchers developed a thermoelectric material that can be used in wearable devices, such as smart clothing, and while maintaining stable thermal energy performance even in extreme environments. It has dramatically resolved the dilemma of striking the balance between achieving good performance and the mechanical flexibility of thermoelectric materials, which has been a long-standing challenge in the field of thermoelectric materials, and has also proven the possibility of commercialization.
KAIST (President Kwang-Hyung Lee) announced on the 21st that a joint research team of Professor Yeon Sik Jung of the Department of Materials Science and Engineering and Professor Inkyu Park of the Department of Mechanical Engineering, in collaboration with the research teams of Professor Min-Wook Oh of Hanbat National University (President Yong Jun Oh) and Dr. Jun-Ho Jeong of the Korea Institute of Machinery and Materials (President Seoghyun Ryu), have successfully developed ‘bismuth telluride (Bi2Te3) thermoelectric fibers,’ an innovative energy harvesting solution for next-generation flexible electronic devices.
Thermoelectric materials are materials that generate voltage when there is a temperature difference and convert thermal energy into electrical energy. Currently, about 70% of energy being lost as wasted heat, so due attention is being given to research on these as sustainable energy materials that can recover and harvesting energy from this waste heat.
Most of the heat sources around us are curved, such as the human body, vehicle exhaust pipes, and cooling fins. Inorganic thermoelectric materials based on ceramic materials boast high thermoelectric performance, but they are fragile and difficult to produce in curved shapes. On the other hand, flexible thermoelectric materials using existing polymer binders can be applied to surfaces of various shapes, but their performance was limited due to the low electrical conductivity and high thermal resistance of the polymer.
Existing flexible thermoelectric materials contain polymer additives, but the inorganic thermoelectric material developed by the research team is not flexible, so they overcame these limitations by twisting nano ribbons instead of additives to produce a thread-shaped thermoelectric material. Inspired by the flexibility of inorganic nano ribbons, the research team used a nanomold-based electron beam deposition technique to continuously deposit nano ribbons and then twisted them into a thread shape to create bismuth telluride (Bi2Te3) inorganic thermoelectric fibers.
These inorganic thermoelectric fibers have higher bending strength than existing thermoelectric materials, and showed almost no change in electrical properties even after repeated bending and tensile tests of more than 1,000 times. The thermoelectric device created by the research team generates electricity using temperature differences, and if clothes are made with fiber-type thermoelectric devices, electricity can be generated from body temperature to operate other electronic devices.
< Figure 1. Schematic diagram and actual image of the all-inorganic flexible thermoelectric yarn made without polymer additives >
In fact, the possibility of commercialization was proven through a demonstration of collecting energy by embedding thermoelectric fibers in life jackets or clothing. In addition, it opened up the possibility of building a high-efficiency energy harvesting system that recycles waste heat by utilizing the temperature difference between the hot fluid inside a pipe and the cold air outside in industrial settings.
Professor Yeon Sik Jung said, "The inorganic flexible thermoelectric material developed in this study can be used in wearable devices such as smart clothing, and it can maintain stable performance even in extreme environments, so it has a high possibility of being commercialized through additional research in the future." Professor Inkyu Park also emphasized, "This technology will become the core of next-generation energy harvesting technology, and it is expected to play an important role in various fields from waste heat utilization in industrial sites to personal wearable self-power generation devices."
This study, in which Hanhwi Jang, a Ph.D. student at KAIST's Department of Materials Science and Engineering, Professor Junseong Ahn of Korea University, Sejong Campus, and Dr. Yongrok Jeong of Korea Atomic Energy Research Institute contributed equally as joint first authors, was published in the online edition of the international academic journal Advanced Materials on September 17, and was selected as the back-cover paper in recognition of its excellence. (Paper title: Flexible All-Inorganic Thermoelectric Yarns)
Meanwhile, this study was conducted through the Mid-career Researcher Support Program and the Future Materials Discovery Program of the National Research Foundation of Korea, and the support from the Global Bio-Integrated Materials Center, the Ministry of Trade, Industry and Energy, and the Korea Institute of Industrial Technology Evaluation and Planning (KEIT) upon the support by the Ministry of Science and ICT.
2024.10.21 View 1218 -
KAIST researchers developed a novel ultra-low power memory for neuromorphic computing
A team of Korean researchers is making headlines by developing a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and its ultra-low power consumption.
KAIST (President Kwang-Hyung Lee) announced on April 4th that Professor Shinhyun Choi's research team in the School of Electrical Engineering has developed a next-generation phase change memory* device featuring ultra-low-power consumption that can replace DRAM and NAND flash memory.
☞ Phase change memory: A memory device that stores and/or processes information by changing the crystalline states of materials to be amorphous or crystalline using heat, thereby changing its resistance state.
Existing phase change memory has the problems such as expensive fabrication process for making highly scaled device and requiring substantial amount of power for operation. To solve these problems, Professor Choi’s research team developed an ultra-low power phase change memory device by electrically forming a very small nanometer (nm) scale phase changeable filament without expensive fabrication processes. This new development has the groundbreaking advantage of not only having a very low processing cost but also of enabling operating with ultra-low power consumption.
DRAM, one of the most popularly used memory, is very fast, but has volatile characteristics in which data disappears when the power is turned off. NAND flash memory, a storage device, has relatively slow read/write speeds, but it has non-volatile characteristic that enables it to preserve the data even when the power is cut off.
Phase change memory, on the other hand, combines the advantages of both DRAM and NAND flash memory, offering high speed and non-volatile characteristics. For this reason, phase change memory is being highlighted as the next-generation memory that can replace existing memory, and is being actively researched as a memory technology or neuromorphic computing technology that mimics the human brain.
However, conventional phase change memory devices require a substantial amount of power to operate, making it difficult to make practical large-capacity memory products or realize a neuromorphic computing system. In order to maximize the thermal efficiency for memory device operation, previous research efforts focused on reducing the power consumption by shrinking the physical size of the device through the use of the state-of-the-art lithography technologies, but they were met with limitations in terms of practicality as the degree of improvement in power consumption was minimal whereas the cost and the difficulty of fabrication increased with each improvement.
In order to solve the power consumption problem of phase change memory, Professor Shinhyun Choi’s research team created a method to electrically form phase change materials in extremely small area, successfully implementing an ultra-low-power phase change memory device that consumes 15 times less power than a conventional phase change memory device fabricated with the expensive lithography tool.
< Figure 1. Illustrations of the ultra-low power phase change memory device developed through this study and the comparison of power consumption by the newly developed phase change memory device compared to conventional phase change memory devices. >
Professor Shinhyun Choi expressed strong confidence in how this research will span out in the future in the new field of research saying, "The phase change memory device we have developed is significant as it offers a novel approach to solve the lingering problems in producing a memory device at a greatly improved manufacturing cost and energy efficiency. We expect the results of our study to become the foundation of future electronic engineering, enabling various applications including high-density three-dimensional vertical memory and neuromorphic computing systems as it opened up the possibilities to choose from a variety of materials.” He went on to add, “I would like to thank the National Research Foundation of Korea and the National NanoFab Center for supporting this research.”
This study, in which See-On Park, a student of MS-PhD Integrated Program, and Seokman Hong, a doctoral student of the School of Electrical Engineering at KAIST, participated as first authors, was published on April 4 in the April issue of the renowned international academic journal Nature. (Paper title: Phase-Change Memory via a Phase-Changeable Self-Confined Nano-Filament)
This research was conducted with support from the Next-Generation Intelligent Semiconductor Technology Development Project, PIM AI Semiconductor Core Technology Development (Device) Project, Excellent Emerging Research Program of the National Research Foundation of Korea, and the Semiconductor Process-based Nanomedical Devices Development Project of the National NanoFab Center.
2024.04.04 View 4705 -
KAIST Team Develops an Insect-Mimicking Semiconductor to Detect Motion
The recent development of an “intelligent sensor” semiconductor that mimics the optic nerve of insects while operating at ultra-high speeds and low power offers extensive expandability into various innovative technologies. This technology is expected to be applied to various fields including transportation, safety, and security systems, contributing to both industry and society.
On February 19, a KAIST research team led by Professor Kyung Min Kim from the Department of Materials Science and Engineering (DMSE) announced the successful developed an intelligent motion detector by merging various memristor* devices to mimic the visual intelligence** of the optic nerve of insects.
*Memristor: a “memory resistor” whose state of resistance changes depending on the input signal
**Visual intelligence: the ability to interpret visual information and perform calculations within the optic nerve
With the recent advances in AI technology, vision systems are being improved by utilizing AI in various tasks such as image recognition, object detection, and motion analysis. However, existing vision systems typically recognize objects and their behaviour from the received image signals using complex algorithms. This method requires a significant amount of data traffic and higher power consumption, making it difficult to apply in mobile or IoT devices.
Meanwhile, insects are known to be able to effectively process visual information through an optic nerve circuit called the elementary motion detector, allowing them to detect objects and recognize their motion at an advanced level. However, mimicking this pathway using conventional silicon integrated circuit (CMOS) technology requires complex circuits, and its implementation into actual devices has thus been limited.
< Figure 1. Working principle of a biological elementary motion detection system. >
Professor Kyung Min Kim’s research team developed an intelligent motion detecting sensor that operates at a high level of efficiency and ultra-high speeds. The device has a simple structure consisting of only two types of memristors and a resistor developed by the team. The two different memristors each carry out a signal delay function and a signal integration and ignition function, respectively. Through them, the team could directly mimic the optic nerve of insects to analyze object movement.
< Figure 2. (Left) Optical image of the M-EMD device in the left panel (scale bar 200 μm) and SEM image of the device in the right panel (scale bar: 20 μm). (Middle) Responses of the M-EMD in positive direction. (Right) Responses of the M-EMD in negative direction. >
To demonstrate its potential for practical applications, the research team used the newly developed motion detector to design a neuromorphic computing system that can predict the path of a vehicle. The results showed that the device used 92.9% less energy compared to existing technology and predicted motion with more accuracy.
< Figure 3. Neuromorphic computing system configuration based on motion recognition devices >
Professor Kim said, “Insects make use of their very simple visual intelligence systems to detect the motion of objects at a surprising high speed. This research is significant in that we could mimic the functions of a nerve using a memristor device.” He added, “Edge AI devices, such as AI-topped mobile phones, are becoming increasingly important. This research can contribute to the integration of efficient vision systems for motion recognition, so we expect it to be applied to various fields such as autonomous vehicles, vehicle transportation systems, robotics, and machine vision.”
This research, conducted by co-first authors Hanchan Song and Min Gu Lee, both Ph.D. candidates at KAIST DMSE, was published in the online issue of Advanced Materials on January 29.
This research was supported by the Mid-Sized Research Project by the National Research Foundation of Korea, the Next-Generation Intelligent Semiconductor Technology Development Project, the PIM Artificial Intelligence Semiconductor Core Technology Development Project, the National Nano Fab Center, and the Leap Research Project by KAIST.
2024.02.29 View 4172 -
Professor Shinhyun Choi’s team, selected for Nature Communications Editors’ highlight
[ From left, Ph.D. candidates See-On Park and Hakcheon Jeong, along with Master's student Jong-Yong Park and Professor Shinhyun Choi ]
See-On Park, Hakcheon Jeong, Jong-Yong Park - a team of researchers under the leadership of Professor Shinhyun Choi of the School of Electrical Engineering, developed a highly reliable variable resistor (memristor) array that simulates the behavior of neurons using a metal oxide layer with an oxygen concentration gradient, and published their work in Nature Communications. The study was selected as the Nature Communications' Editor's highlight, and as the featured article posted on the main page of the journal's website.
Link : https://www.nature.com/ncomms/
[ Figure 1. The featured image on the main page of the Nature Communications' website introducing the research by Professor Choi's team on the memristor for artificial neurons ]
Thesis title: Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing.
( https://doi.org/10.1038/s41467-022-30539-6 )
At KAIST, their research was introduced on the 2022 Fall issue of Breakthroughs, the biannual newsletter published by KAIST College of Engineering.
This research was conducted with the support from the Samsung Research Funding & Incubation Center of Samsung Electronics.
2022.11.01 View 5903 -
Professor Kang’s Team Receives the IEEE Jack Newbauer Memorial Award
Professor Joonhyuk Kang of the School of Electrical Engineering received the IEEE Vehicular Technology Society’s 2021 Jack Neubauer Memorial Award for his team’s paper published in IEEE Transactions on Vehicular Technology. The Jack Neubauer Memorial Award recognizes the best paper published in the IEEE Transactions on Vehicular Technology journal in the last five years.
The team of authors, Professor Kang, Professor Sung-Ah Chung at Kyungpook National University, and Professor Osvaldo Simeone of King's College London reported their research titled Mobile Edge Computing via a UAV-Mounted Cloudlet: Optimization of Bit Allocation and Path Planning in IEEE Transactions on Vehicular Technology, Vol. 67, No. 3, pp. 2049-2063, in March 2018.
Their paper shows how the trajectory of aircraft is optimized and resources are allocated when unmanned aerial vehicles perform edge computing to help mobile device calculations. This paper has currently recorded nearly 400 citations (based on Google Scholar). "We are very happy to see the results of proposing edge computing using unmanned aerial vehicles by applying optimization theory, and conducting research on trajectory and resource utilization of unmanned aerial vehicles that minimize power consumption," said Professor Kang.
2021.07.12 View 6355 -
Electrosprayed Micro Droplets Help Kill Bacteria and Viruses
With COVID-19 raging around the globe, researchers are doubling down on methods for developing diverse antimicrobial technologies that could be effective in killing a virus, but harmless to humans and the environment.
A recent study by a KAIST research team will be one of the responses to such efforts. Professor Seung Seob Lee and Dr. Ji-hun Jeong from the Department of Mechanical Engineering developed a harmless air sterilization prototype featuring electrosprayed water from a polymer micro-nozzle array. This study is one of the projects being supported by the KAIST New Deal R&D Initiative in response to COVID-19. Their study was reported in Polymer.
The electrosprayed microdroplets encapsulate reactive oxygen species such as hydroxyl radicals, superoxides that are known to have an antimicrobial function. The encapsulation prolongs the life of reactive oxygen species, which enable the droplets to perform their antimicrobial function effectively. Prior research has already proven the antimicrobial and encapsulation effects of electrosprayed droplets.
Despite its potential for antimicrobial applications, electrosprayed water generally operates under an electrical discharge condition, which can generate ozone. The inhalation of ozone is known to cause damage to the respiratory system of humans. Another technical barrier for electrospraying is the low flow rate problem. Since electrospraying exhibits the dependence of droplet size on the flow rate, there is a limit for the amount of water microdroplets a single nozzle can produce.
With this in mind, the research team developed a dielectric polymer micro-nozzle array to perform the multiplexed electrospraying of water without electrical discharge. The polymer micro-nozzle array was fabricated using the MEMS (Micro Electro-Mechanical System) process. According to the research team, the nozzle can carry five to 19 micro-nozzles depending on the required application.
The high aspect ratio of the micro-nozzle and an in-plane extractor were proposed to concentrate the electric field at the tip of the micro-nozzle, which prevents the electrical discharge caused by the high surface tension of water. A micro-pillar array with a hydrophobic coating around the micro-nozzle was also proposed to prevent the wetting of the micro-nozzle array.
The polymer micro-nozzle array performed in steady cone jet mode without electrical discharge as confirmed by high-speed imaging and nanosecond pulsed imaging. The water microdroplets were measured to be in the range of six to 10 μm and displayed an antimicrobial effect on Escherichia coli and Staphylococcus aureus.
Professor Lee said, “We believe that this research can be applied to air conditioning products in areas that require antimicrobial and humidifying functions.”
Publication:
Jeong, J. H., et al. (2020) Polymer micro-atomizer for water electrospray in the cone jet mode. Polymer. Vol. No. 194, 122405. Available online at https://doi.org/10.1016/j.polymer.2020.122405
Profile: Seung Seob Lee, Ph.D.
sslee97@kaist.ac.kr
http://mmst.kaist.ac.kr/
Professor
Department of Mechanical Engineering (ME)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr
Daejeon 34141, Korea
Profile: Ji-hun Jeong, Ph.D.
jiuni6022@kaist.ac.kr
Postdoctoral researcher
Department of Mechanical Engineering (ME)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr
Daejeon 34141, Korea
(END)
2020.12.21 View 11079 -
KAIST Joins IBM Q Network to Accelerate Quantum Computing Research and Foster Quantum Industry
KAIST has joined the IBM Q Network, a community of Fortune 500 companies, academic institutions, startups, and research labs working with IBM to advance quantum computing for business and science.
As the IBM Q Network’s first academic partner in Korea, KAIST will use IBM's advanced quantum computing systems to carry out research projects that advance quantum information science and explore early applications. KAIST will also utilize IBM Quantum resources for talent training and education in preparation for building a quantum workforce for the quantum computing era that will bring huge changes to science and business. By joining the network, KAIST will take a leading role in fostering the ecosystem of quantum computing in Korea, which is expected to be a necessary enabler to realize the Fourth Industrial Revolution.
Professor June-Koo Rhee who also serves as Director of the KAIST Information Technology Research Center (ITRC) of Quantum Computing for AI has led the agreement on KAIST’s joining the IBM Q Network. Director Rhee described quantum computing as "a new technology that can calculate mathematical challenges at very high speed and low power” and also as “one that will change the future.”
Director Rhee said, “Korea started investment in quantum computing relatively late, and thus requires to take bold steps with innovative R&D strategies to pave the roadmap for the next technological leap in the field”. With KAIST joining the IBM Q Network, “Korea will be better equipped to establish a quantum industry, an important foundation for securing national competitiveness,” he added.
The KAIST ITRC of Quantum Computing for AI has been using the publicly available IBM Quantum Experience delivered over the IBM Cloud for research, development and training of quantum algorithms such as quantum artificial intelligence, quantum chemical calculation, and quantum computing education.
KAIST will have access to the most advanced IBM Quantum systems to explore practical research and experiments such as diagnosis of diseases based on quantum artificial intelligence, quantum computational chemistry, and quantum machine learning technology. In addition, knowledge exchanges and sharing with overseas universities and companies under the IBM Q Network will help KAIST strengthen the global presence of Korean technology in quantum computing.
About IBM Quantum
IBM Quantum is an industry-first initiative to build quantum systems for business and science applications. For more information about IBM's quantum computing efforts, please visit www.ibm.com/ibmq.
For more information about the IBM Q Network, as well as a full list of all partners, members, and hubs, visit https://www.research.ibm.com/ibm-q/network/
©Thumbnail Image: IBM.
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2020.09.29 View 7826 -
Brain-inspired Artificial Intelligence in Robots
(from left: PhD candidate Su Jin An, Dr. Jee Hang Lee and Professor Sang Wan Lee)
Research groups in KAIST, the University of Cambridge, Japan’s National Institute for Information and Communications Technology, and Google DeepMind argue that our understanding of how humans make intelligent decisions has now reached a critical point in which robot intelligence can be significantly enhanced by mimicking strategies that the human brain uses when we make decisions in our everyday lives.
In our rapidly changing world, both humans and autonomous robots constantly need to learn and adapt to new environments. But the difference is that humans are capable of making decisions according to the unique situations, whereas robots still rely on predetermined data to make decisions.
Despite the rapid progress being made in strengthening the physical capability of robots, their central control systems, which govern how robots decide what to do at any one time, are still inferior to those of humans. In particular, they often rely on pre-programmed instructions to direct their behavior, and lack the hallmark of human behavior, that is, the flexibility and capacity to quickly learn and adapt.
Applying neuroscience in robotics, Professor Sang Wan Lee from the Department of Bio and Brain Engineering, KAIST and Professor Ben Seymour from the University of Cambridge and Japan’s National Institute for Information and Communications Technology proposed a case in which robots should be designed based on the principles of the human brain. They argue that robot intelligence can be significantly enhanced by mimicking strategies that the human brain uses during decision-making processes in everyday life.
The problem with importing human-like intelligence into robots has always been a difficult task without knowing the computational principles for how the human brain makes decisions –in other words, how to translate brain activity into computer code for the robots’ ‘brains’.
However, researchers now argue that, following a series of recent discoveries in the field of computational neuroscience, there is enough of this code to effectively write it into robots. One of the examples discovered is the human brain’s ‘meta-controller’, a mechanism by which the brain decides how to switch between different subsystems to carry out complex tasks. Another example is the human pain system, which allows them to protect themselves in potentially hazardous environments. “Copying the brain’s code for these could greatly enhance the flexibility, efficiency, and safety of robots,” Professor Lee said.
The team argued that this inter-disciplinary approach will provide just as many benefits to neuroscience as to robotics. The recent explosion of interest in what lies behind psychiatric disorders such as anxiety, depression, and addiction has given rise to a set of sophisticated theories that are complex and difficult to test without some sort of advanced situation platform.
Professor Seymour explained, “We need a way of modelling the human brain to find how it interacts with the world in real-life to test whether and how different abnormalities in these models give rise to certain disorders. For instance, if we could reproduce anxiety behavior or obsessive-compulsive disorder in a robot, we could then predict what we need to do to treat it in humans.”
The team expects that producing robot models of different psychiatric disorders, in a similar way to how researchers use animal models now, will become a key future technology in clinical research.
The team also stated that there may also be other benefits to humans and intelligent robots learning, acting, and behaving in the same way. In future societies in which humans and robots live and work amongst each other, the ability to cooperate and empathize with robots might be much greater if we feel they think like us.
Professor Seymour said, “We might think that having robots with the human traits of being a bit impulsive or overcautious would be a detriment, but these traits are an unavoidable by-product of human-like intelligence. And it turns out that this is helping us to understand human behavior as human.”
The framework for achieving this brain-inspired artificial intelligence was published in two journals, Science Robotics (10.1126/scirobotics.aav2975) on January 16 and Current Opinion in Behavioral Sciences (10.1016/j.cobeha.2018.12.012) on February 6, 2019.
Figure 1. Overview of neuroscience - robotics approach for decision-making. The figure details key areas for interdisciplinary study (Current Opinion in Behavioral Sciences)
Figure 2. Brain-inspired solutions to robot learning. Neuroscientific views on various aspects of learning and cognition converge and create a new idea called prefrontal metacontrol, which can inspire researchers to design learning agents that can address various key challenges in robotics such as performance-efficiency-speed, cooperation-competition, and exploration-exploitation trade-offs (Science Robotics)
2019.02.20 View 5577 -
The First Award for Concept Cars, Future Mobility of the Year
KAIST will host an award to recognize the most visionary and inspiring concept cars of the year.
The ‘Future Mobility of the Year (FMOTY)’ Awards recognize concept cars that have made outstanding contributions to future mobility. The first awards ceremony will take place in Korea in March 2019.
The awards will be given to concept cars that exhibit innovative services and practical transportation technology in three categories: private mobility, public and commercial mobility, and personal mobility.
To ensure a fair judging process, the contest invited influential and eminent journalists in the automotive field. They will evaluate the social values and innovative contributions of the concept cars that will pave the way for next-generation transportation.
Concept cars have been neglected in existing automobile awards, such as the ‘Car of the Year’ because they have been considered experimental prototypes only built for showcasing a new vision for the quite far future.
The FMOTY Awards will brings concept cars back into the spotlight and showcase the best ideas and social values of mind-blowing concept cars.
Among 45 concept cars, fifteen candidates were selected as finalists after the initial screening that took place over the last three months: including models from Audi, BMW, Mercedes-Benz, Peugeot, Porsche, Renault, Toyota, Volkswagen, and Volvo. The winners will be announced and awarded in Seoul on March 28th.
Kyung-soo Kim, Dean of the Cho Chun Shik Graduate School of Green Transportation which organizes the award said, “As the automobile industry undergoes an era of transformation, it is crucial to recognize the efforts of automobile companies who are making attempts to create novel forms of mobility. That is why we launched the FMOTY Awards, hoping to add a future-oriented spirit to the existing awards that consider finished vehicles only. By selecting the best concept car, the FMOTY Awards will expand public attention from the present to the future.”
Details can be found on the official website of FMOTY ( www.fmoty.org), where photos of the finalists are also available for download ( http://bitly.kr/JTUUp).
Figure 1. Finalists for the 'Future Mobility of the Year'
2019.02.13 View 6351 -
Sound-based Touch Input Technology for Smart Tables and Mirrors
(from left: MS candidate Anish Byanjankar, Research Assistant Professor Hyosu Kim and Professor Insik Shin)
Time passes so quickly, especially in the morning. Your hands are so busy brushing your teeth and checking the weather on your smartphone. You might wish that your mirror could turn into a touch screen and free up your hands. That wish can be achieved very soon. A KAIST team has developed a smartphone-based touch sound localization technology to facilitate ubiquitous interactions, turning objects like furniture and mirrors into touch input tools.
This technology analyzes touch sounds generated from a user’s touch on a surface and identifies the location of the touch input. For instance, users can turn surrounding tables or walls into virtual keyboards and write lengthy e-mails much more conveniently by using only the built-in microphone on their smartphones or tablets. Moreover, family members can enjoy a virtual chessboard or enjoy board games on their dining tables.
Additionally, traditional smart devices such as smart TVs or mirrors, which only provide simple screen display functions, can play a smarter role by adding touch input function support (see the image below).
Figure 1.Examples of using touch input technology: By using only smartphone, you can use surrounding objects as a touch screen anytime and anywhere.
The most important aspect of enabling the sound-based touch input method is to identify the location of touch inputs in a precise manner (within about 1cm error). However, it is challenging to meet these requirements, mainly because this technology can be used in diverse and dynamically changing environments. Users may use objects like desks, walls, or mirrors as touch input tools and the surrounding environments (e.g. location of nearby objects or ambient noise level) can be varied. These environmental changes can affect the characteristics of touch sounds.
To address this challenge, Professor Insik Shin from the School of Computing and his team focused on analyzing the fundamental properties of touch sounds, especially how they are transmitted through solid surfaces.
On solid surfaces, sound experiences a dispersion phenomenon that makes different frequency components travel at different speeds. Based on this phenomenon, the team observed that the arrival time difference (TDoA) between frequency components increases in proportion to the sound transmission distance, and this linear relationship is not affected by the variations of surround environments.
Based on these observations, Research Assistant Professor Hyosu Kim proposed a novel sound-based touch input technology that records touch sounds transmitted through solid surfaces, then conducts a simple calibration process to identify the relationship between TDoA and the sound transmission distance, finally achieving accurate touch input localization.
The accuracy of the proposed system was then measured. The average localization error was lower than about 0.4 cm on a 17-inch touch screen. Particularly, it provided a measurement error of less than 1cm, even with a variety of objects such as wooden desks, glass mirrors, and acrylic boards and when the position of nearby objects and noise levels changed dynamically. Experiments with practical users have also shown positive responses to all measurement factors, including user experience and accuracy.
Professor Shin said, “This is novel touch interface technology that allows a touch input system just by installing three to four microphones, so it can easily turn nearby objects into touch screens.”
The proposed system was presented at ACM SenSys, a top-tier conference in the field of mobile computing and sensing, and was selected as a best paper runner-up in November 2018.
(The demonstration video of the sound-based touch input technology)
2018.12.26 View 7734 -
Dr. Sejeong Kim Recognized as Excellent Young Scientist
(Dr. Sejeong Kim)
Dr. Sejeong Kim, a postdoctoral research associate in the School of Mathematical and Physical Sciences at the University of Technology Sydney was honored to receive the Excellence Award for a Young Scientist by the Korea Federation of Women’s Science & Technology Association (KOFWST). The award ceremony will be held on October 31 in Seoul.
KOFWST recognizes ten promising young female scientists and engineers every year who show significant potential, passion, and remarkable achievement in their work. The awardees are selected among those who finished their degree within the previous five years. Dr. Kim earned her Ph.D. in physics at KAIST in 2014 and was selected as the winner in the field of physics in recognition of her outstanding research activities in photonics.
Dr. Kim conducted various research activities in the field of photonics and was published in high impact journals including Nano Letters and Advanced materials. In July, she developed the first photonic cavity from van der Waals materials and published the study in Nature Communications titled “Photonic Crystal Cavities from Hexagonal Boron Nitride.” At UTS, she carries out research activities supervised by Professor Igor Aharonovich and has engaged in many science outreach activities.
2018.10.18 View 5008 -
Formation of Burning Ice in Oceanic Clay Rich Sediment Disclosed
(from left: Professor Tae-Hyuk Kwon and PhD candidate Taehyung Park) A KAIST research team has identified the formation of natural gas hydrates, so-called flammable ice, formed in oceans.
Professor Tae-Hyuk Kwon from the Department of Civil & Environmental Engineering and his team found that clay minerals in oceanic clay-rich sedimentary deposits promote formation of gas hydrates and proposed the principle of gas hydrate formation in the clayey sedimentary layers.
Gas hydrates are ice-like crystalline structures composed of hydrogen-bonded water molecules encapsulating gas molecules. They are also known as burning ice. Their deposits are so huge that they gain attention for alternative energy.
Conventionally, it was believed that formation of gas hydrates is limited in clay sedimentary deposits; however, unexpected abundance of natural gas hydrates in oceanic clay-rich sedimentary deposits raised the issue of how they formed.
The surfaces of natural clay minerals are negatively charged and, thus, unavoidably generate physicochemical interactions between clay and water. Such clay-water interactions have a critical role in the occurrence of natural gas hydrates in clay-rich sedimentary formations.
However, there has been experimental difficulty in analyzing hydrate formation because of the cations contained in clay particles, which balance the clay surface charges. Therefore, clay particles inevitably release the cations when mixed with water, which complicates the interpretation of experimental results.
To overcome this limitation, the team polarized water molecules with an electric field and monitored the induction times of water molecules forming gas hydrates.
They found that the 10 kV/m of electric field promoted gas hydrate nucleation under certain conditions rather than slowing it down, due to the partial breakage of the hydrogen bonded water clusters and the lowered thermal energy of water molecules.
Professor Kwon said, “Through this research, we gained better insight into the origin of gas hydrates occurrence in clay-rich sedimentary deposits. In the near future, we will soon be able to commercially produce methane gas from natural gas hydrate deposits.”
This research, led by PhD candidate Taehyung Park, was published online in Environmental Science and Technology on February 3. (doi: 10.1021/acs.est.7b05477)
Figure 1. Formation of gas hydrates with water molecules
Figure 2. Enhancement and inhibition of gas hydrates
2018.04.09 View 6017