Kaist

Lifespan of Fuel Cells Maximized Using Small Amoun..

(Professor Jung (far right) and his team) Fuel cells are key future energy technology that is emerging as eco-friendly and renewable energy sources. In particular, solid oxide fuel cells composed of ceramic materials gain increasing attention for their ability to directly convert various forms of fuel such as biomass, LNG, and LPG to electric energy. KAIST researchers described a new technique to improve chemical stability of electrode materials which can extend the lifespan by employing a very little amount of metals. The core factor that determines the performance of solid oxide fuel cells is the cathode at which the reduction reaction of oxygen occurs. Conventionally, oxides with perovskite structure (ABO3) are used in cathodes. However, despite the high performance of perovskite oxides at initial operation, the performance decreases with time, limiting their long-term use. In particular, the condition of high temperature oxidation state required for cathode operation leads to surface segregation phenomenon, in which second phases such as strontium oxide (SrOx) accumulate on the surface of oxides, resulting in decrease in electrode performance. The detailed mechanism of this phenomenon and a way to effectively inhibit it has not been suggested. Using computational chemistry and experimental data, Professor WooChul Jung’s team at the Department of Materials Science and Engineering observed that local compressive states around the Sr atoms in a perovskite electrode lattice weakened the Sr-O bond strength, which in turn promote strontium segregation. The team identified local changes in strain distribution in perovskite oxide as the main cause of segregation on strontium surface. Based on these findings, the team doped different sizes of metals in oxides to control the extent of lattice strain in cathode material and effectively inhibited strontium segregation. Professor Jung said, “This technology can be implemented by adding a small amount of metal atoms during material synthesis, without any additional process.” He continued, “I hope this technology will be useful in developing high-durable perovskite oxide electrode in the future.” The study co-led by Professor Jung and Professor Jeong Woo Han at Department of Chemical Engineering, University of Seoul was featured as the cover of Energy and Environmental Science in the first issue of 2018. ?(Figure1.Correlation between the extent of lattice strain in electrode, strontium segregation, and electrode reaction.)??(Figure 2. Cathode surface of solid oxide fuel cell stabilized using the developed technology)

A Parallel MRI Method Accelerating Imaging Time Pr..

KAIST researchers proposed new technology that reduces MRI (magnetic resonance imaging) acquisition time to less than a sixth of the conventional method. They made a reconstruction method using machine learning of multilayer perception (MLP) algorithm to accelerate imaging time. High-quality image can be reconstructed from subsampled data using the proposed method. This method can be further applied to various k-space subsampling patterns in a phase encoding direction, and its processing can be performed in real time. The research, led by Professor Hyun Wook Park from the Department of Electrical Engineering, was described in Medical Physics as the cover paper last December. Ph.D. candidate Kinam Kwon is the first author. MRI is an imaging technique that allows various contrasts of soft tissues without using radioactivity. Since MRI could image not only anatomical structures, but also functional and physiological features, it is widely used in medical diagnoses. However, one of the major shortcomings of MRI is its long imaging time. It induces patients’ discomfort, which is closely related to voluntary and involuntary motions, thereby deteriorating the quality of the MR images. In addition, lengthy imaging times limit the system’s throughput, which results in the long waiting times of patients as well as the increased medical expenses. To reconstruct MR images from subsampled data, the team applied the MLP to reduce aliasing artifacts generated by subsampling in k-space. The MLP is learned from training data to map aliased input images into desired alias-free images. The input of the MLP is all voxels in the aliased lines of multichannel real and imaginary images from the subsampled k-space data, and the desired output is all voxels in the corresponding alias-free line of the root-sum-of-squares of multichannel images from fully sampled k-space data. Aliasing artifacts in an image reconstructed from subsampled data were reduced by line-by-line processing of the learned MLP architecture. Reconstructed images from the proposed method are better than those from compared methods in terms of normalized root-mean-square error. The proposed method can be applied to image reconstruction for any k-space subsampling patterns in a phase encoding direction. Moreover, to further reduce the reconstruction time, it is easily implemented by parallel processing. To address the aliasing artifact phenomenon, the team employed a parallel imaging technique using several receiver coils of various sensitivities and a compressed sensing technique using sparsity of signals. Existing methods are heavily affected by sub-sampling patterns, but the team’s technique is applicable for various sub-sampling patterns, resulting in superior reconstructed images compared to existing methods, as well as allowing real-time reconstruction. Professor Park said, "MRIs have become essential equipment in clinical diagnosis. However, the time consumption and the cost led to many inconveniences." He continued, "This method using machine learning could greatly improve the patients’ satisfaction with medical service." This research was funded by the Ministry of Science and ICT.(Firgure 1. Cover of Medical Physics for December 2017) (Figure 2. Concept map for the suggested network) (Figure 3. Concept map for conventional MRI image acquisition and accelerated image acquisiton)

Aerial Vehicle Flying Freely with Independently Co..

Professor Dongsoo Har and his team in Cho Chun Shik Graduate School of Green Transportation in Korea Advanced Institute of Science and Technology (KAIST) lately developed an aerial vehicle that is able to control the main wings separately and independently. Aerial vehicles in a typical category have main wings fixed to the body (fuselage) in an integrated form. Shape of main wings, namely airfoil, produces lift force, thanks to aerodynamic interaction with air, and achieves commensurate energy efficiency. Yet, it is difficult for them to make agile movements due to the large turn radius. Banking the aerial vehicle that accounts for eventual turn comes from the adjustment of small ailerons mounted on the trailing edge of the wings. Aerial vehicles in another typical category gain thrust power by rotating multiple propellers. They can make agile movements by changing speed of motors rotating the propellers. For instance, pitch(movement up and down along vertical axis) down for moving forward with quadcopters is executed by increased speed of two rear rotors and unchanged or decreased speed of two front rotors. Rotor represents revolving part of motor. However, they are even less energy-efficient, owing to the absence of lift force created by wings. Taking these technical issues of existing types of aerial vehicles into account, his team designed the main wings of the aerial vehicle to be controlled separately and independently. Their aerial vehicle (named Nsphere drone) executing all the thinkable flight modes, pitch/yaw(twisting or rotating around a vertical axis)/roll(turning over on a horizontal axis), is sketched in Figure 1 and actual flight of the aerial vehicle carrying out all possible types of flight modes is shown in Figure 2. Nsphere drone facilitates controlling the tilting angles of main wings and thus the direction of thrust power created by motors on the leading edge of main wings. Additional motor at the tail of Nsphere drone provides extra lifting force when trying vertical take-off and offers extra thrust power, by tilting the motor upward, while flying forward. Nsphere drone can change flight mode in the air from vertical to horizontal and vice versa. Due to the ability in rotating wings as well as changing the direction of thrust power come by the tail motor, the Nsphere drone with independently controlled wings can take off and land vertically without runway and auxiliary equipment. Someone might say that it is similar to aerial vehicles that have tilt rotors attached to fixed wings for vertical take-off and landing. However, advantage of Nsphere drone is the ability in tilting each main wing entirely, thereby changing angle of attack of each wing. Angle of attack indicates the angle between the oncoming air or relative wind and a reference line on the aerial vehicle or wing. In general, lift force is affected by the angle of attack. Therefore, Nsphere drone can freely control the amount of lift force gained by each wing. This allows agile movements of Nsphere drone in the horizontal flight mode. Nsphere drone can fly like a copter type aerial vehicle in the vertical flight mode, and like a fixed-wing type aerial vehicle in the horizontal flight mode. The trial to separate main wings entirely from the fuselage is very challenging. The separation of the main wings is realized by using supports that hold the main wings. One support penetrates both wings and two separate supports grab wings individually. It is also possible to apply this technology to large size aerial vehicle by including the fuselage as a part of the support for tilting wings. Part of the fuselage can be redesigned and integrated with main wings, taking plug-in structure to be coupled to the main fuselage and to stand thrust and air pressure. Figure 1. Flight modes with independently controlled wings Figure 2. Aerial vehicle with independently controlled wings demonstrates the capability in executing vertical and horizontal flight modes, as well as vertical take-off and landing. Nsphere drone controls each wing independently according to target flight mode. The output of the control is sensed by sensors installed in Nsphere drone and undergoes an adjustment process until desired flight operation is achieved. Through this operational process, the Nsphere drone can make agile movements in ways that might not be attained by other aerial vehicles. The team expects that the Nsphere drone, which is able to acquire energy efficiency, swiftness and speed, can be adopted for short and mid-distance air traffic delivery. Particularly, it can be distributed like the flying taxi announced by Uber and NASA in November 2017 and it can be effectively used for logistics delivery services such http:// as Amazon’s Prime Air. Professor Har said, “Nsphere drone can be used for various fields, including airway transportation, military aerial vehicles, surveillance, general safety management, and logistics delivery services. Separate and independent control of the main wings gives us the chance to employ diverse and effective flying methods. Imagine a jet fighter that is able to evade a missile by the separate control of main wings http://. Just a bit of control could be enough for evading. Our flight mechanism is valid across the range of flight speed”. At the beginning of the design process in 2016, his team filed patents to countries including Korea, U.S., and China, on various implementation methods, including plug-in structure coupled to the main fuselage, for separate and independent control of main wings. Click the image to watch the clip of Nsphere Drone

Fiber OLEDs, Thinner Than a Hair

(Seonil Kwon, PhD Candidate)Professor Kyung Cheol Choi from the School of Electrical Engineering and his team succeeded in fabricating highly efficient Organic Light-Emitting Diodes (OLEDs) on an ultra-thin fiber. The team expects the technology, which produces high-efficiency, long-lasting OLEDs, can be widely utilized in wearable displays.Existing fiber-based wearable displays’ OLEDs show much lower performance compared to those fabricated on planar substrates. This low performance caused a limitation for applying it to actual wearable displays.In order to solve this problem, the team designed a structure of OLEDs compatible to fiber and used a dip-coating method in a three-dimensional structure of fibers. Through this method, the team successfully developed efficient OLEDs that are designed to last a lifetime and are still equivalent to those on planar substrates.The team identified that solution process planar OLEDs can be applied to fibers without any reduction in performance through the technology. This fiber OLEDs exhibited luminance and current efficiency values of over 10,000 cd/m^2(candela/square meter) and 11 cd/A (candela/ampere).The team also verified that the fiber OLEDs withstood tensile strains of up to 4.3% while retaining more than 90% of their current efficiency. In addition, they could be woven into textiles and knitted clothes without causing any problems.Moreover, the technology allows for fabricating OLEDs on fibers with diameters ranging from 300㎛ down to 90㎛, thinner than a human hair, which attests to the scalability of the proposed fabrication scheme.Noting that every process is carried out at a low temperature (~105℃), fibers vulnerable to high temperatures can also employ this fabrication scheme.Professor Choi said, “Existing fiber-based wearable displays had limitations for applicability due to their low performance. However, this technology can fabricate OLEDs with high performance on fibers. This simple, low-cost process opens a way to commercialize fiber-based wearable displays.” This research led by a PhD candidate Seonil Kwon was published online in the international journal for nanoscience, Nano Letters, on December 6. (Fiber-based OLEDs woven into knitted clothes)?This work was funded by the Engineering Research Center of Excellence Program (Grant No. NRF-2017R1A5A1014708) and Nano-Material Technology Development Program (Grant No. NRF-2016M3A7B4910635) by the National Research Foundation of Korea, the Ministry of Science and ICT of Korea.

One-Step Production of Aromatic Polyesters by E. c..

KAIST systems metabolic engineers defined a novel strategy for microbial aromatic polyesters production fused with synthetic biology from renewable biomass. The team of Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering produced aromatic polyesters from Escherichia coli (E. coli) strains by applying microbial fermentation, employing direct microbial fermentation from renewable feedstock carbohydrates. This is the first report to determine a platform strain of engineered E. coli capable of producing environmentally friendly aromatic polyesters. This engineered E. coli strain, if desired, has the potential to be used as a platform strain capable of producing various high-valued aromatic polyesters from renewable biomass. This research was published in Nature Communications on January 8. Conventionally, aromatic polyesters boast solid strength and heat stability so that there has been a great deal of interest in fermentative production of aromatic polyesters from renewable non-food biomass, but without success. However, aromatic polyesters are only made by feeding the cells with corresponding aromatic monomers as substrates, and have not been produced by direct fermentation from renewable feedstock carbohydrates such as glucose. To address this issue, the team prescribed the detailed procedure for aromatic polyester production through identifying CoA-transferase that activates phenylalkanoates into their corresponding CoA derivatives. In this process, researchers employed metabolic engineering of E. coli to produce phenylalkanoates from glucose based on genome-scale metabolic flux analysis. In particular, the KAIST team made a modulation of gene expression to produce various aromatic polyesters having different monomer fractions. The research team successfully produced aromatic polyesters, a non-natural polymer using the strategy that combines systems metabolic engineering and synthetic biology. They succeeded in biosynthesis of various kinds of aromatic polyesters through the system, thus proving the technical excellence of the environmentally friendly biosynthetic system of this research. Furthermore, his team also proved the potential of expanding the range of aromatic polyesters from renewable resources, which is expected to play an important role in the bio-plastic industry. Professor Lee said, “An eco-friendly and sustainable chemical industry is the key global agenda every nation faces. We are making a research focus to a biochemical industry free from petroleum dependence, and conducting diverse research activities to address the issue. This novel technology we are presenting will serve as an opportunity to advance the biochemical industry moving forward.” This work was supported by the Intelligent Synthetic Biology Center through the Global Frontier Project (2011-0031963) and also by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries (NRF-2012M1A2A2026556 and NRF-2012M1A2A2026557) from the Ministry of Science and ICT through the National Research Foundation of Korea. Figure: Biosynthesis of aromatic polyesters by metabolically engineered E. coli.This schematic diagram shows the overall conceptualization of how metabolically engineered E. coli produced aromatic polyesters from glucose.

Ultra-Low Power Flexible Memory Using 2D Materials

(Professor Choi and Ph.D. candidate Jang) KAIST research team led by Professor Sung-Yool Choi at School of Electrical Engineering and Professor Sung Gap Im at the Department of Chemical and Biomolecular Engineering developed high-density, ultra-low power, non-volatile, flexible memory technology using 2D materials. The team used ultrathin molybdenum disulfide (MoS2) with atomic-scale thickness as the channel material and high-performance polymeric insulator film as the tunneling dielectric material. This research was published on the cover of Advanced Functional Materials on November 17. KAIST graduate Myung Hun Woo, a researcher at Samsung Electronics and Ph.D. candidate Byung Chul Jang are first authors. The surge of new technologies such as Internet of Things (IoT), Artificial Intelligence (AI), and cloud server led to the paradigm shift from processor-centric computing to memory-centric computing in the industry, as well as the increase in demand of wearable devices. This led to an increased need for high-density, ultra-low power, non-volatile flexible memory. In particular, ultrathin MoS2 as semiconductor material has been recently regarded as post-silicon material. This is due to its ultrathin thickness of atomic-scale which suppresses short channel effect observed in conventional silicon material, leading to advantages in high- density and low-power consumption. Further, this thickness allows the material to be flexible, and thus the material is applicable to wearable devices. However, due to the dangling-bond free surface of MoS2 semiconductor material, it is difficult to deposit the thin insulator film to be uniform and stable over a large area via the conventional atomic layer deposition process. Further, the currently used solution process makes it difficult to deposit uniformly low dielectric constant (k) polymeric insulator film with sub-10 nm thickness on a large area, thus indicating that the memory device utilizing the conventional solution-processed polymer insulator film cannot be operated at low-operating voltage and is not compatible with photolithography. The research team tried to overcome the hurdles and develop high-density, ultra-low power, non-volatile flexible memory by employing a low-temperature, solvent-free, and all-dry vapor phase technique named initiated chemical vapor deposition (iCVD) process. Using iCVD process, tunneling polymeric insulator film with 10 nm thickness was deposited uniformly on MoS2 semiconductor material without being restricted by the dangling bond-free surface of MoS2. The team observed that the newly developed MoS2-based non-volatile memory can be operated at low-voltage (around 10V), in contrast to the conventional MoS2-based non-volatile memory that requires over 20V. Professor Choi said, “As the basis for the Fourth Industrial revolution technologies including AI and IoT, semiconductor device technology needs to have characteristics of low-power and flexibility, in clear contrast to conventional memory devices.” He continued, “This new technology is significant in developing source technology in terms of materials, processes, and devices to contribute to achieve these characteristics.” This research was supported by the Global Frontier Center for Advanced Soft Electronics and the Creative Materials Discovery Program by funded the National Research Foundation of Korea of Ministry of Science and ICT. ( Figure 1. Cover of Advanced Functional Materials) (Figure 2. Concept map for the developed non-volatile memory material and high-resolution transmission electron microscopy image for material cross-section )

Technology to Find Optimum Drug Target for Cancer ..

(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)

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)