research
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Non-Adiabatic Reaction Mechanism Identified at Conical Intersection
(Professor Kim(center) and Ph.D. candidates Kyung Chul Woo (left) and Kang Do Hyung)
Research team led by Professor Sang Kyu Kim at KAIST Department of Chemistry observed two distinct reaction pathways that occur at conical intersection where two different adiabatic potential energy surfaces cross at the same nuclear configuration.
Professor Kim previously identified the existence and molecular structure of conical intersection in 2010. In this following study, the team accurately measured reaction rates of two totally different reaction pathways activated only at conical intersection where the seminal Born-Oppenheimer approximation breaks down.
This study led by Kyung Chul Woo (1st author) and Do Hyung Kang, both Ph.D. candidates at KAIST, was published in Journal of the American Chemical Society in November 7th, 2017.
Chemical reaction induced by light occurs in excited electronic states where the reaction outcome is often destined by coupling among different electronic states mediated by nuclear motions during chemical reaction. Such a coupling is most critical and important at the conical intersection as nonadiabtic surface-hopping is most probable at situation where the Born-Oppenheimer approximation fails.
Professor Kim used spectroscopic methods in 2010 to experimentally observe conical intersection of polyatomic molecule. And yet, it was not possible to disentangle complex dynamic processes with frequency-domain study only.
The research team used pico-second time-resolution kinetic energy resolved mass spectrometry to identify two possible distinct reaction pathways in both energy and time domains.,.
The research team demonstrated that the reactive flux prepared at the conical intersection is bifurcated into adiabatic or non-adiabatic reaction pathways. These two pathways are quite distinct in terms of reaction rates, energy releases, and product branching ratios.
This is the first study to capture the moment of bifurcation dynamics at the conical intersection for complex polyatomic molecular system. The study could contribute to conceptual improvement in understanding complicated nonadiabatic dynamics in general.
Professor Kim said, “Basic science research is essential in understanding and wisely using the nature. New technological advances cannot be made without the advancement in basic science.” He continued, “I hope this study could lead to growth in many young academic talents in basic sciences.”
(Figure 1. Reaction graph starting from reaction intersection that divides into adiabatic reaction pathway (red) and non-adiabatic pathway (blue))
2017.12.19 View 6389 -
Technology to Find Optimum Drug Target for Cancer Developed
(Professor Kwang-Hyun Cho (right) and lead author Dr. Minsoo Choi)
A KAIST research team led by Professor Kwang-Hyun Cho of the Department of Bio and Brain Engineering developed technology to find the optimum drug target according to the type of cancer cell. The team used systems biology to analyze molecular network dynamics that reflect genetic mutations in cancer cells and to predict drug response. The technology could contribute greatly to future anti-cancer drug development.
There are many types of genetic variations found in cancer cells, including gene mutations and copy number variations. These variations differ in cancer cells even within the same type of cancer, and thus the drug response varies cell by cell. Cancer researchers worked towards identifying frequently occurring genetic variations in cancer patients and, in particular, the mutations that can be used as an index for specific drugs. Previous studies focused on identifying a single genetic mutation or creating an analysis of the structural characteristics of a gene network. However, this approach was limited in its inability to explain the biological properties of cancer which are induced by various gene and protein interactions in cancer cells, which result in differences in drug response.
Gene mutations in cancer cells not only affect the function of the affected gene, but also other genes that interact with the mutated gene and proteins. As a consequence, one mutation could lead to changes in the dynamical properties of the molecular network. Therefore, the responses to anti-cancer drugs by cancer cells differ. The current treatment approach that ignores molecular network dynamics and targets a few cancer-related genes is only effective on a fraction of patients, while many other patients exhibit resistance to the drug.
Professor Cho’s team integrated a large-scale computer simulation using super-computing and cellular experiments to analyze changes in molecular network dynamics in cancer cells.
This led to development of technology to find the optimum drug target according to the type of cancer cells by predicting drug response. This technology was applied to the molecular network of known tumor suppressor p53. The team used large-scale cancer cell genomic data available from The Cancer Cell Line Encyclopedia (CCLE) to construct different molecular networks specific to the characteristics of genetic variations.
Perturbation analysis on drug response in each molecular network was used to quantify changes in cancer cells from drug response and similar networks were clustered. Then, computer simulations were used to analyze the synergetic effects in terms of efficacy and combination to predict the level of drug response. Based on the simulation results from various cancer cell lines including lung, breast, bone, skin, kidney, and ovary cancers were used in drug response experiments for compare analysis.
This technique can be applied in any molecular network to identify the optimum drug target for personalized medicine.
The research team suggests that the technology can analyze varying drug response due to the heterogeneity of cancer cells by considering the overall modulatory interactions rather than focusing only on a specific gene or protein. Further, the technology aids the prediction of causes of drug resistance and thus the identification of the optimum drug target to inhibit the resistance. This could be core source technology that can be used in drug repositioning, a process of applying existing drugs to new disease targets.
Professor Cho said, “Genetic variations in cancer cells are the cause of diverse drug response, but a complete analysis had not yet been made.” He continued, “Systems biology allowed the simulation of drug responses by cancer cell molecular networks to identify fundamental principles of drug response and optimum drug targets using a new conceptual approach.”
This research was published in Nature Communications on December 5 and was funded by Ministry of Science and ICT and National Research Foundation of Korea.
(Figure 1. Drug response prediction for each cancer cell type from computer simulation and cellular experiment verification for comparison)
(Figure 2. Drug response prediction based on cancer cell molecular network dynamics and clustering of cancer cells by their molecular networks)
(Figure 3. Identification of drug target for each cancer cell type by cellular molecular network analysis and establishment for personalized medicine strategy for each cancer patient)
2017.12.15 View 7178 -
New Quantum Mechanical States Observed
(Professor Han (far right) and his research team)
A KAIST research team observed a new quantum mechanical magnetic state ‘Jeff = 3/2.’ This first observation of ‘Jeff=3/2’ could be the foundation for future research on superconductivity and quantum magnetism.
In quantum mechanics, total angular momentum is defined as the sum of spin and orbital angular momenta and is denoted with the ‘J.’ The newly identified magnetic moment can be described as a kind of angular momentum that occurs when specific conditions are met and has been denoted ‘Jeff’ with the meaning ‘effective angular momentum’ in the field. Jeff=3/2 has been a topic of discussion but was yet to be observed.
The research was co-led by Professor Myung Joon Han of the Department of Physics at Chung-Ang University in Korea, RIKEN in Japan, and the Argonne National Laboratory in the US. This research was published in Nature Communications on October 14, 2017.
In academia, spin-orbital coupling was known to lead to a unique quantum state and has been an active area of recent research. In contrast to magnetic moment by electron spin and orbital, the effective magnetic moment Jeff, formed from the coupling of the two, shows a unique ground state and interaction patterns, which could lead to new phenomena and properties.
Most studies in the last decade focused on ‘Jeff=1/2’, but there has not been any observation of ‘Jeff=3/2’, which led to slow progress. In 2014, the research team led by Prof. Han theoretically predicted the possibility of the ‘Jeff=3/2’ state in a certain type of materials based on molecular orbital, instead of atomic orbital. In the current study, the team applied the Selection Rule of quantum mechanics for the ‘Jeff=3/2’ state, which differs to the general spin moment, in order to experimentally detect this moment.
When electrons near the atomic nucleus are excited by X-rays, the excited electrons can be absorbed or re-emitted through interactions with other electrons. Here, the Selection Rule is applied to electrons. According to quantum mechanics, this rule is very unique in the ‘Jeff=3/2’ state and ‘Jeff=3/2’ is predicted to be distinguishable from general spin states. The prediction that was made using this idea was verified through the experiment using electrons extracted from tantalum at two different energy levels. In this material, the unique quantum mechanical interference by the ‘Jeff=3/2’ moment can be taken as direct evidence for its existence.
The new quantum state is very unique from any of the previously known magnetic states and this study could be the starting point for future research on the ‘Jeff=3/2’ moment. Further, this finding could contribute to future research on various properties of the magnetic states and its interactions.
(Figure 1: Crystal structure, MO levels, and RIXS process in GaTa4Se8.)
(Figure 2: Cluster model calculations of the L3 and L2 RIXS spectra)
2017.12.14 View 5921 -
A New Spin Current Generating Material Developed
(Professor Park(left) and Ph.D. candidate Kim)
Magnetic random-access memory (MRAM) is a non-volatile device made of thin magnetic film that can maintain information without an external power supply, in contrast to conventional silicon-based semiconductor memory. It also has the potential for high-density integration and high-speed operation.
The operation of MRAM involves the control of the magnetization direction by exerting spin current-induced torque on a magnetic material. Spin current is generated using electricity in conventional MRAM, but this study developed materials technology that generates spin current using heat.
A KAIST research team led by Professor Byong-Guk Park of the Department of Materials Science and Engineering developed a material that generates spin current from heat, which can be utilized for a new operation principle for MRAM.
There have been theoretical reports on the spin Nernst effect, the phenomenon of the thermal generation of spin current, but is yet to have been experimentally proven due to technological limitations. However, the research team introduced a spin Nernst magnetoresistance measurement method using tungsten (W) and platinum (Pt) with high spin orbit coupling which allows for the experimental identification of the spin Nernst effect. They also demonstrated that the efficiency of spin current generation from heat is similar to that of spin current generated from electricity.
Professor Park said, “This research has great significance in experimentally proving spin current generation from heat, a new physical phenomenon. We aim to develop the technology as a new operational method for MRAM through further research. This can lower power consumption, and is expected to contribute to the advancement of electronics requiring low power requirement such as wearable, mobile, and IOT devices”.
This research was conducted as a joint research project with Professor Kyung-Jin Lee at Korea University and Professor Jong-Ryul Jeong at Chungnam National University. It was published in Nature Communications online on November 9 titled “Observation of transverse spin Nernst magnetoresistance induced by thermal spin current in ferromagnet/non-magnet bilayers.” Ph.D. candidate Dong-Jun Kim at KAIST is the first author. This research was funded by the Ministry of Science and ICT.
(Schematic diagram of spin Nernst magnetoresistance)
(Research result of new spin current generating materials)
2017.12.08 View 8467 -
Expanding Gas Storage Capacity of Nanoporous Materials
A KAIST research team led by Professor Jihan Kim of the Department of Chemical and Biomolecular Engineering has successfully proposed a rational defect engineering methodology that can greatly enhance the gas storage capacity of nanoporous materials. The team conducted a high-throughput computational screening of a large experimental metal-organic framework database to identify 13 candidate materials that could experience significant methane uptake enhancement with only a small proportion of linker vacancy defects.
This research was published online on November 16 in Nature Communications, with M.S. candidate Sanggyu Chong from KAIST as the first author and post-doctorate researcher Günther Thiele from the Department of Chemistry at UC Berkeley as a contributing author.
Metal-organic frameworks, hereinafter MOF, are crystalline nanoporous materials that are comprised of metal clusters and organic linkers continuously bound together by coordination bonds. Due to their ultrahigh surface areas and pore volumes, they have been widely studied for various energy and environment applications.
Similar to other crystalline materials, MOFs are never perfectly crystalline and are likely to contain several different types of defects within their crystalline structures. Among these defects, linker vacancy defects, or the random absence of linker vacancies in their designated bonding positions, are known to be controllable by practicing careful control over the synthesis conditions.
The research team combined the concepts of rational defect engineering over the linker vacancy defects and the potential presence of inaccessible pores within MOFs to propose a methodology where controlled the introduction of linker vacancy defects could lead to a dramatic enhancement in gas adsorption and storage capacities.
The study utilized a Graphic Processing Unit (GPU) code developed by Professor Kim in a high-throughput computational screening of 12,000 experimentally synthesized MOFs to identify the structures with significant amounts of pores that were inaccessible for methane. In determining the presence of inaccessible pores, a flood-fill algorithm was performed over the energy-low regions of the structure, which is the same algorithm used for filling an area with color in Microsoft Paint.
For the MOFs with significant amounts of inaccessible pores, as determined from the screening, the research team emulated linker vacancy defects in their crystalline structures so that the previously inaccessible pores would be newly merged into the main adsorption channel with the introduction of defects for additional surface area and pore volume available for adsorption. The research team successfully identified 13 structures that would experience up to a 55.56% increase in their methane uptake with less than 8.33% of the linker vacancy defects.
The research team believes that this rational defect engineering scheme can be further utilized for many other applications in areas such as selective adsorption of an adsorbate from a gas mixture and the semi-permanent capture of gas molecules.
This research was conducted with the support of the Mid-career Research Program of the National Research Foundation of Korea.
Figure1. A diagram for flood fill algorithm and example of identification of inaccessible regions within the MOFs, using the flood fill algorithm
Figure2. Methane energy contours before and after detect introduction
2017.12.04 View 8103 -
Technology Detecting RNase Activity
(Ph.D. candidate Chang Yeol Lee)
A KAIST research team of Professor Hyun Gyu Park at Department of Chemical and Biomolecular Engineering developed a new technology to detect the activity of RNase H, a RNA degrading enzyme. The team used highly efficient signal amplification reaction termed catalytic hairpin assembly (CHA) to effectively analyze the RNase H activity. Considering that RNase H is required in the proliferation of retroviruses such as HIV, this research finding could contribute to AIDS treatments in the future, researchers say.
This study led by Ph.D. candidates Chang Yeol Lee and Hyowon Jang was chosen as the cover for Nanoscale (Issue 42, 2017) published in 14 November.
The existing techniques to detect RNase H require expensive fluorophore and quencher, and involve complex implementation. Further, there is no way to amplify the signal, leading to low detection efficiency overall. The team utilized CHA technology to overcome these limitations. CHA amplifies detection signal to allow more sensitive RNase H activity assay.
The team designed the reaction system so that the product of CHA reaction has G-quadruplex structures, which is suitable to generate fluorescence. By using fluorescent molecules that bind to G-quadruplexes to generate strong fluorescence, the team could develop high performance RNase H detection method that overcomes the limitations of existing techniques. Further, this technology could screen inhibitors of RNase H activity.
The team expects that the research finding could contribute to AIDS treatment. AIDS is disease caused by HIV, a retrovirus that utilizes reverse transcription, during which RNA is converted to DNA. RNase H is essential for reverse transcription in HIV, and thus inhibition of RNase H could in turn inhibit transcription of HIV DNA.
Professor Park said, “This technology is applicable to detect various enzyme activities, as well as RNase H activity.” He continued, “I hope this technology could be widely used in research on enzyme related diseases.”
This study was funded by Global Frontier project and Mid-career Researcher Support project of the Ministry of Science and ICT.
2017.11.28 View 6933 -
New Photocatalyst Converts Carbon Dioxide to 99% Pure Fuel
(Professor Song, Ph.D. candidates Kim, and Lim (from left))
A KAIST research team led by Professor Hyunjoon Song of the Department of Chemistry developed a metal oxide nanocatalyst that converts carbon dioxide to 99% pure methane. This technology directly uses sunlight to convert carbon dioxide into methane, which is more efficient in terms of energy storage capacity, compared to the conventional way of storing the electricity produced by solar cells in batteries. The research team used cheap catalytic materials to significantly enhance the reaction efficiency and selectivity of the chemical energy storage method.
This research was conducted as a joint research project with Professor Ki Min Nam at Mokpo National University with co-first authors Dr. Kyung-Lyul Bae and Ph.D. candidates Jinmo Kim and Chan Kyu Lim. The study was published in Nature Communications on November 7.
Although there is growing interest in sunlight as an energy resource, its usage has been limited to daytime and the power output varies with the weather. If sunlight could be directly converted to chemical energy, such as fuel, the limitations of energy storage and its usage could be overcome. In particular, the usage of sunlight to convert carbon dioxide, a main cause of the greenhouse effect in our atmosphere, is of great interest since both energy and environmental issues can be addressed. However, the stability of carbon dioxide made it difficult to convert it to other molecules. Thus, there was a need for a catalyst with enhanced efficiency and selectivity.
Professor Song’s team synthesized zinc oxide nanoparticles, often used in sun cream. The nanoparticles were then bound to copper oxide as single particles, forming a colloidal form of zinc oxide-copper oxide nanoparticles. Zinc oxides produce high energy electrons using light, and this energy is used to convert carbon dioxide into methane. Further, zinc oxide can also produce electrons with light and transfer the electrons to copper oxide. Similar to the principles of photosynthesis in leaves, the electron transfer reaction could be maintained for a long time. As a consequence, although the reaction was conducted in aqueous solution, methane of 99% purity could be obtained from carbon dioxide.
Conventional heterogeneous photocatalysts were in solid powder form with irregular structures and were not dispersed in water. Professor Song’s team used a nanochemical synthesis method to control the structure of the catalyst particles to be regular and maintained over a large surface area. This led to increasing carbon dioxide conversion activity by hundreds of fold in solution compared to existing catalysts.
Professor Song said, “A long time will be needed for the commercialization of the direct conversion reaction of carbon dioxide using sunlight. However, the precise control of catalyst structures at nanoscale would enhance the efficiency of photocatalyst reactions.” He continued, “Applying this method to various phtocatalysts will maximize the catalysts performance.”
(Figure 1. Scheme for carbon dioxide conversion reaction using nano photocatalyst in aqueous solution)
(Figure 2. Structure, photocatalytic CO2 conversion, and stability of ZnO-Cu2O nanocatalyst )
2017.11.13 View 8702 -
Mutant Gene Network in Colon Cancer Identified
The principles of the gene network for colon tumorigenesis have been identified by a KAIST research team. The principles will be used to find the molecular target for effective anti-cancer drugs in the future. Further, this research gained attention for using a systems biology approach, which is an integrated research area of IT and BT.
The KAIST research team led by Professor Kwang-Hyun Cho for the Department of Bio and Brain Engineering succeeded in the identification. Conducted by Dr. Dongkwan Shin and student researchers Jonghoon Lee and Jeong-Ryeol Gong, the research was published in Nature Communications online on November 2.
Human cancer is caused by genetic mutations. The frequency of the mutations differs by the type of cancer; for example, only around 10 mutations are found in leukemia and childhood cancer, but an average of 50 mutations are found in adult solid cancers and even hundreds of mutations are found in cancers due to external factors, such as with lung cancer.
Cancer researchers around the world are working to identify frequently found genetic mutations in patients, and in turn identify important cancer-inducing genes (called ‘driver genes’) to develop targets for anti-cancer drugs. However, gene mutations not only affect their own functions but also affect other genes through interactions. Therefore, there are limitations in current treatments targeting a few cancer-inducing genes without further knowledge on gene networks, hence current drugs are only effective in a few patients and often induce drug resistance.
Professor Cho’s team used large-scale genomic data from cancer patients to construct a mathematical model on the cooperative effects of multiple genetic mutations found in gene interaction networks. The basis of the model construction was The Cancer Genome Atlas (TCGA) presented at the International Cancer Genome Consortium. The team successfully quantified the effects of mutations in gene networks to group colon cancer patients by clinical characteristics.
Further, the critical transition phenomenon that occurs in tumorigenesis was identified using large-scale computer simulation analysis, which was the first hidden gene network principle to be identified. Critical transition is the phenomenon in which the state of matter is suddenly changed through phase transition. It was not possible to identify the presence of transition phenomenon in the past, as it was difficult to track the sequence of gene mutations during tumorigenesis.
The research team used a systems biology-based research method to find that colon cancer tumorigenesis shows a critical transition phenomenon if the known driver gene mutations follow sequentially. Using the developed mathematical model, it can be possible to develop a new anti-cancer targeting drug that most effectively inhibits the effects of many gene mutations found in cancer patients. In particular, not only driver genes, but also other passenger genes affected by the gene mutations, could be evaluated to find the most effective drug targets.
Professor Cho said, “Little was known about the contribution of many gene mutations during tumorigenesis.” He continued, “In this research, a systems biology approach identified the principle of gene networks for the first time to suggest the possibility of anti-cancer drug target identification from a new perspective.”
This research was funded by the Ministry of Science and ICT and the National Research Foundation of Korea.
Figure1. Formation of giant clusters via mutation propagation
Figure2. Critical transition phenomenon by cooperative effect of mutations in tumorigenesis
2017.11.10 View 8182 -
Highly Flexible Organic Flash Memory for Foldable and Disposable Electronics
A KAIST team reported ultra-flexible organic flash memory that is bendable down to a radius of 300μm. The memory exhibits a significantly-long projected retention rate with a programming voltage on par with the present industrial standards.
A joint research team led by Professor Seunghyup Yoo of the School of Electrical Engineering and Professor Sung Gap Im of the Department of Chemical and Biomolecular Engineering said that their memory technology can be applied to non-conventional substrates, such as plastics and papers, to demonstrate its feasibility over a wide range of applications.
With Dr. Seungwon Lee and Dr. Hanul Moon playing the role of leading authors, the research was published in Nature Communications on September 28.
Flash memory is a non-volatile, transistor-based data-storage device that has become essential in most electronic systems in daily life. With straightforward operation mechanisms and easy integration into NAND or NOR array architecture, flash memory has been established as the most successful and dominant non-volatile memory technology by far.
Despite promising demonstrations in the early stages of organic electronics, the overall progress in this field has been far slower than that of thin-film transistors (TFTs) or other devices based on flexible materials. It has been challenging, in particular, to develop flash memory that simultaneously exhibits a significant level of flexibility and performance. This is mainly due to the scarcity of flexible dielectric layers, which are responsible for the tunneling and blocking of charges.
The solution processing used for the preparation of most of the polymeric dielectric layers also makes it difficult to use them in flash memory due to the complexity involved in the formation of the bilayer dielectric structure, which is the key to flash memory operations.
The research team tried to overcome these hurdles and realize highly flexible flash memory by employing thin polymeric insulators grown with initiated chemical vapor deposition (iCVD), a vapor-phase growth technique for polymers that was previously shown to be promising for the fabrication of flexible TFTs. It was further shown that these iCVD-based polymeric insulators, when coupled with rational device design and material choice, can make a significant contribution to flash memory as well.
Memory using conventional polymer insulating films has often required a voltage as high as 100 V (volt) in order to attain long memory retention. If the device is made to operate at a low voltage, the short retention period of less than a month was problematic.
The KAIST team produced flash memory with programming voltages around 10 V and a projected data retention time of over 10 years, while maintaining its memory performance even at a mechanical strain of 2.8%. This is a significant improvement over the existing inorganic insulation layer-based flash memory that allowed only a 1% strain.
The team demonstrated the virtually foldable memory devices by fabricating the proposed flash memory on a 6-micrometer-thick ultrathin plastic film. In addition, it succeeded in producing them on printing paper, opening a way for disposable smart electronic products such as electronic paper and electronic business card.
Professor Yoo said, " This study well illustrates that even highly flexible flash memory can be made to have a practically viable level of performance, so that it contributes to full-fledged wearable electronic devices and smart electronic paper."
(Figure 1. Structure of flexible flash memory )
(Figure 2. Foldable flash memory)
2017.11.06 View 9245 -
Highly Sensitive and Fast Indoor GNSS Signal Acquisition Technology
(Professor Seung-Hyun Kong (right) and Research Fellow Tae-Sun Kim)
A research team led by Professor Seung-Hyun Kong at the Cho Chun Shik Graduate School of Green Transportation, KAIST, developed high-speed, high-sensitivity Global Navigation Satellite System (GNSS) signal acquisition (search and detection) technology that can produce GNSS positioning fixes indoors.
Using the team’s new technology, GNSS signals will be sufficient to identify locations anywhere in the world, both indoors and outdoors. This new research finding was published in the international journal IEEE Signal Processing Magazine (IEEE SPM) this September.
Global Positioning System (GPS) developed by the U.S. Department of Defense in the 1990s is the most widely-used satellite-based navigation system, and GNSS is a terminology to indicate conventional satellite based navigation systems, such as GPS and Russian GLONASS, as well as new satellite-based navigation systems under development, such as European GALILEO, Chinese COMPASS, and other regional satellite-based navigation systems.
In general, GNSS signals are transmitted all over the globe from 20,000 km above the Earth and thus a GNSS signal received by a small antennae in an outdoor environment has weak signal power. In addition, GNSS signals penetrating building walls become extremely weak so the signal can be less than 1/1000th of the signal power received outside.
Using conventional acquisition techniques including the frequency-domain correlation technique to acquire an extremely weak GNSS signal causes the computational cost to increase by over a million times and the processing time for acquisition also increases tremendously. Because of this, indoor measurement techniques using GNSS signals were considered practically impossible for the last 20 years.
To resolve such limitations, the research team developed a Synthesized Doppler-frequency Hypothesis Testing (SDHT) technique to dramatically reduce the acquisition time and computational load for extremely weak GNSS signals indoors.
In general, GNSS signal acquisition is a search process in which the instantaneous accurate code phase and Doppler frequency of the incoming GNSS signal are identified. However, the number of Doppler frequency hypotheses grows proportionally to the coherent correlation time that should be necessarily increased to detect weak signals. In practice, the coherent correlation time should be more than 1000 times longer for extremely weak GNSS signals so the number of Doppler frequency hypotheses is greater than 20,000. On the other hand, the SDHT algorithm indirectly tests the Doppler frequency hypothesis utilizing the coherent correlation results of neighboring hypotheses.
Therefore, using SDHT, only around 20 hypotheses are tested using conventional correlation techniques and the remaining 19,980 hypotheses are calculated with simple mathematical operations. As a result, SDHT achieves a huge computational cost reduction (by about 1000 times) and is 800 times faster for signal acquisition compared to conventional techniques. This means only about 15 seconds is required to detect extremely weak GNSS signals in buildings using a personal computer.
The team predicts further studies for strengthening SDHT technology and developing positioning systems robust enough to multipath in indoor environments will allow indoor GNSS measurements within several seconds inside most buildings using GNSS alone.
Professor Kong said, “This development made us the leader in indoor GNSS positioning technology in the world.” He continued, “We hope to commercialize indoor GNSS systems to create a new market.” The research team is currently registering a patent in Korea and applying for patents overseas, as well as planning to commercialize the technology with the help of the Institute for Startup KAIST.
(Figure1. Positioning Results for the GPS Indoor Positioning System using SDHT Technology)
2017.11.02 View 7107 -
Platinum Single Atom Catalysts for 'Direct Formic Acid Fuel Cells'
(Professor Hyunjoo Lee (left) and Ph.D. candidate Jiwhan Kim)
A research team co-led by Professor Hyunjoo Lee at the Department of Chemical and Biomolecular Engineering at KAIST and Professor Jeong Woo Han from the University of Seoul synthesized highly stable high-Pt-content single atom catalysts for direct formic acid fuel cells. The amount of platinum can be reduced to 1/10 of that of conventional platinum nanoparticle catalysts.
Platinum (Pt) catalysts have been used in various catalytic reactions due to their high activity and stability. However, because Pt is rare and expensive, it is important to reduce the amount of Pt used. Pt single atom catalysts can reduce the size of the Pt particles to the size of an atom. Thus, the cost of Pt catalysts can be minimized because all of the Pt atoms can participate in the catalytic reactions. Additionally, single atom catalysts have no ensemble site in which two or more atoms are attached, and thus, the reaction selectivity is different from that of nanoparticle catalysts.
Despite these advantages, single atom catalysts are easily aggregated and less stable due to their low coordination number and high surface free energy. It is difficult to develop a single atom catalyst with high content and high stability, and thus, its application in practical devices is limited.
Direct formic acid fuel cells can be an energy source for next-generation portable devices because liquid formic acid as a fuel is safer and easier to store and transport than high-pressure hydrogen gas.
To improve the stability of Pt single atom catalysts, Professor Lee’s group developed a Pt-Sn single atom alloy structure on an antimony-doped tin oxide (ATO) support. This structure has been proven by computational calculations which show that Pt single atoms substitute antimony sites in the antimony-tin alloy structure and are thermodynamically stable. This catalyst has been shown to have a higher activity up to 50 times per weight of Pt than that of the commercial catalyst, Pt/C, in the oxidation of formic acid, and the stability of the catalyst was also remarkably high.
Professor Lee’s group also used a single atomic catalyst in a 'direct formic acid fuel cell’ consisting of membranes and electrodes. It is the first attempt to apply a single atomic catalyst to a full cell. In this case, an output similar to that of the commercial catalyst could be obtained by using 1/10 of the platinum compared to the commercial Pt/C catalyst.
Ph.D. candidate Jiwhan Kim from KAIST was the first author of the research. This research was published online on September 11 in Advanced Energy Materials.
This research was carried out with the support of the Samsung Electronics Future Technology Development Center.
(Figure 1. Concept photograph for Pt single atom catalysts.)
(Figure 2. Pt single atom catalysts by HAADF-STEM analysis (bright white circles))
2017.10.31 View 7654 -
High-Speed Motion Core Technology for Magnetic Memory
(Professor Kab-Jin Kim of the Department of Physics)
A joint research team led by Professor Kab-Jin Kim of the Department of Physics, KAIST and Professor Kyung-Jin Lee at Korea University developed technology to dramatically enhance the speed of next generation domain wall-based magnetic memory. This research was published online in Nature Materials on September 25.
Currently-used memory materials, D-RAM and S-RAM, are fast but volatile, leading to memory loss when the power is switched off. Flash memory is non-volatile but slow, while hard disk drives (HDD) have greater storage but are high in energy usage and weak in physical shock tolerance.
To overcome the limitations of existing memory materials, ‘domain wall-based, magnetic memory’ is being researched. The core mechanism of domain wall magnetic memory is the movement of a domain wall by the current. Non-volatility is secured by using magnetic nanowires and the lack of mechanical rotation reduced power usage. This is a new form of high density, low power next-generation memory.
However, previous studies showed the speed limit of domain wall memory to be hundreds m/s at maximum due to the ‘Walker breakdown phenomenon’, which refers to velocity breakdown from the angular precession of a domain wall. Therefore, there was a need to develop core technology to remove the Walker breakdown phenomenon and increase the speed for the commercialization of domain wall memory.
Most domain wall memory studies used ferromagnetic bodies, which cannot overcome the Walker breakdown phenomenon. The team discovered that the use of ‘ferrimagnetic‘ GdFeCo at certain conditions could overcome the Walker breakdown phenomenon and using this mechanism they could increase domain wall speed to over 2Km/s at room temperature.
Domain wall memory is high-density, low-power, and non-volatile memory. The memory could be the leading next-generation memory with the addition of the high speed property discovered in this research.
Professor Kim said, “This research is significant in discovering a new physical phenomenon at the point at which the angular momentum of a ferrimagnetic body is 0 and it is expected to advance the implementation of next-generation memory in the future.”
This research was funded by the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP) (No. 2017R1C1B2009686, NRF-2016R1A5A1008184) and by the DGIST R&D Program of the Ministry of Science, ICT and Future Planning (17-BT-02).
(Figure 1. Concept Map of Domain Wall Memory Material using Ferrimagnetic Body)
(Figure 2. Scheme and Experimental Results of Domain Wall Speed Measurements)
2017.10.30 View 8759