Kaist

KAIST Identifies the Trigger of the Hyperactivatio..

(Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering) Scientists have been investigating the negative effects that the hyperactivation of fibrosis has on fibrotic diseases and cancer. A KAIST research team unveiled a positive feedback loop that bi-stably activates fibroblasts in collaboration with Samsung Medical Center. This finding will contribute to developing therapeutic targets for both fibrosis and cancer.    Human fibroblasts are dormant in normal tissue, but show radical activation during wound healing. However, the principle that induces their explosive activation has not yet been identified.    Here, Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering, in collaboration with Professor Seok-Hyung Kim from Samsung Medical Center, discovered the principle of a circuit that continuously activates fibroblasts.   They constructed a positive feedback loops (PFLs) where Twist1, Prrx1, and Tenascin-C (TNC) molecules consecutively activate fibroblasts. They confirmed that these are the main inducers of fibroblast activation by conducting various experiments, including molecular biological tests, mathematical modeling, animal testing, and computer simulations to conclude that they are the main inducers of fibroblast activation.    According to their research, Twist 1 is a key regulator of cancer-associated fibroblasts, which directly upregulates Prrx1 and then triggers TNC, which also increases Twist1 expression. This circuit consequently forms a Twist-Prrx1-TNC positive feedback loop.   Activated fibroblasts need to be deactivated after wounds are healed. However, if the PFLs continue, the fibroblasts become the major cause of worsening fibrotic diseases and cancers.   Therefore, the team expects that Twist1-Prrx1-TNC positive PFLs will be applied for novel and effective therapeutic targeting of fibrotic diseases and cancers.    This research was published in Nature Communications on August 1, 2018.    Figure 1. Twist1 increases tenascin-c expression in cancer-associated fibroblasts. Twist1 is a potent but indirect inducer of tenascin-c (TNC), which is essential for maintaining Twist1 expression in cancer-associated fibroblasts (CAFs).   Figure 2. Summary of the study. The Twist1-Prrx1-TNC positive feedback regulation provides clues for understanding the activation of fibroblasts during wound healing under normal conditions, as well as abnormally activated fibroblasts in pathological conditions such as cancerous and fibrotic diseases. Under normal conditions, the PFL acts as a reversible bistable switch by which the activation of fibroblasts is “ON" above a sufficient level of stimulation and “OFF" for the withdrawal of the stimulus. However, this switch can be permanently turned on under pathologic conditions by continued activation of the PFL, resulting in sustained proliferation of fibroblasts.

Levitating 2D semiconductor for better performance

(from top: Professor Yeon Sik Jung and PhD candidate Soomin Yim)   Atomically thin 2D semiconductors have been drawing attention for their superior physical properties over silicon semiconductors; nevertheless, they are not the most appealing materials due to their structural instability and costly manufacturing process. To shed some light on these limitations, a KAIST research team suspended a 2D semiconductor on a dome-shaped nanostructure to produce a highly efficient semiconductor at a low cost.   2D semiconducting materials have emerged as alternatives for silicon-based semiconductors because of their inherent flexibility, high transparency, and excellent carrier transport properties, which are the important characteristics for flexible electronics.   Despite their outstanding physical and chemical properties, they are oversensitive to their environment due to their extremely thin nature. Hence, any irregularities in the supporting surface can affect the properties of 2D semiconductors and make it more difficult to produce reliable and well performing devices. In particular, it can result in serious degradation of charge-carrier mobility or light-emission yield.   To solve this problem, there have been continued efforts to fundamentally block the substrate effects. One way is to suspend a 2D semiconductor; however, this method will degrade mechanical durability due to the absence of a supporter underneath the 2D semiconducting materials.   Professor Yeon Sik Jung from the Department of Materials Science and Engineering and his team came up with a new strategy based on the insertion of high-density topographic patterns as a nanogap-containing supporter between 2D materials and the substrate in order to mitigate their contact and to block the substrate-induced unwanted effects.    More than 90％ of the dome-shaped supporter is simply an empty space because of its nanometer scale size. Placing a 2D semiconductor on this structure creates a similar effect to levitating the layer. Hence, this method secures the mechanical durability of the device while minimizing the undesired effects from the substrate. By applying this method to the 2D semiconductor, the charge-carrier mobility was more than doubled, showing a significant improvement of the performance of the 2D semiconductor.   Additionally, the team reduced the price of manufacturing the semiconductor. In general, constructing an ultra-fine dome structure on a surface generally involves costly equipment to create individual patterns on the surface. However, the team employed a method of self-assembling nanopatterns in which molecules assemble themselves to form a nanostructure. This method led to reducing production costs and showed good compatibility with conventional semiconductor manufacturing processes.    Professor Jung said, “This research can be applied to improve devices using various 2D semiconducting materials as well as devices using graphene, a metallic 2D material. It will be useful in a broad range of applications, such as the material for the high speed transistor channels for next-generation flexible displays or for the active layer in light detectors.”   This research, led by PhD candidate Soomin Yim, was published in Nano Letters in April.      Figure 1. Image of a 2D semiconductor using dome structures

Improved Efficiency and Stability of CQD Solar Cel..

(from left: Professor Jung-Yong Lee and Dr. Se-Woong Baek)   Recently, the power conversion efficiency (PCE) of colloidal quantum dot (CQD)-based solar cells has been enhanced, paving the way for their commercialization in various fields; nevertheless, they are still a long way from being commercialized due to their efficiency not matching their stability. In this research, a KAIST team achieved highly stable and efficient CQD-based solar cells by using an amorphous organic layer to block oxygen and water permeation.   CQD-based solar cells are light-weight, flexible, and they boost light harvesting by absorbing near-infrared lights. Especially, they draw special attention for their optical properties controlled efficiently by changing the quantum dot sizes. However, they are still incompatible with existing solar cells in terms of efficiency, stability, and cost. Therefore, there is great demand for a novel technology that can simultaneously improve both PCE and stability while using an inexpensive electrode material.   Responding to this demand, Professor Jung-Yong Lee from the Graduate School of Energy, Environment, Water and Sustainability and his team introduced a technology to improve the efficiency and stability of CQD-based solar cells.   The team found that an amorphous organic thin film has a strong resistance to oxygen and water. Using these properties, they employed this doped organic layer as a top-hole selective layer (HSL) for the PbS CQD solar cells, and confirmed that the hydro/oxo-phobic properties of the layer efficiently protected the PbS layer. According to the molecular dynamics simulations, the layer significantly postponed the oxygen and water permeation into the PbS layer. Moreover, the efficient injection of the holes in the layer reduced interfacial resistance and improved performance.   With this technology, the team finally developed CQD-based solar cells with excellent stability. The PCE of their device stood at 11.7％ and maintained over 90％ of its initial performance when stored for one year under ambient conditions.    Professor Lee said, “This technology can be also applied to QD LEDs and Perovskite devices. I hope this technology can hasten the commercialization of CQD-based solar cells.”   This research, led by Dr. Se-Woong Baek and a Ph.D. student, Sang-Hoon Lee, was published in Energy & Environmental Science on May 10.    Figure 1. The schematic of the equilibrated structure of the amorphous organic film   Figure 2. Schematic illustration of CQD-based solar cells and graphs showing their performance

KAIST Reveals Mathematical Principle behind AI’s ‘..

(from left: Professor Jong Chul Ye, PhD candidates Yoseob Han and Eunju Cha)   A KAIST research team identified the geometrical structure of artificial intelligence (AI) and discovered the mathematical principles of highly performing artificial neural networks, which can be applicable in fields such as medical imaging.    Deep neural networks are an exemplary method of implementing deep learning, which is at the core of the AI technology, and have shown explosive growth in recent years. This technique has been used in various fields, such as image and speech recognition as well as image processing.    Despite its excellent performance and usefulness, the exact working principles of deep neural networks has not been well understood, and they often suffer from unexpected results or errors. Hence, there is an increasing social and technical demand for interpretable deep neural network models.   To address these issues, Professor Jong Chul Ye from the Department of Bio & Brain Engineering and his team attempted to find the geometric structure in a higher dimensional space where the structure of the deep neural network can be easily understood. They proposed a general deep learning framework, called deep convolutional framelets, to understand the mathematical principle of a deep neural network in terms of the mathematical tools in Harmonic analysis.    As a result, it was found that deep neural networks’ structure appears during the process of decomposition of high dimensionally lifted signal via Hankel matrix, which is a high-dimensional structure formerly studied intensively in the field of signal processing.   In the process of decomposing the lifted signal, two bases categorized as local and non-local basis emerge. The researchers found that non-local and local basis functions play a role in pooling and filtering operation in convolutional neural network, respectively.    Previously, when implementing AI, deep neural networks were usually constructed through empirical trial and errors. The significance of the research lies in the fact that it provides a mathematical understanding on the neural network structure in high dimensional space, which guides users to design an optimized neural network.   They demonstrated improved performance of the deep convolutional framelets’ neural networks in the applications of image denoising, image pixel in painting, and medical image restoration.     Professor Ye said, “Unlike conventional neural networks designed through trial-and-error, our theory shows that neural network structure can be optimized to each desired application and are easily predictable in their effects by exploiting the high dimensional geometry. This technology can be applied to a variety of fields requiring interpretation of the architecture, such as medical imaging.”   This research, led by PhD candidates Yoseob Han and Eunju Cha, was published in the April 26th issue of the SIAM Journal on Imaging Sciences.    Figure 1. The design of deep neural network using mathematical principles   Figure 2. The results of image noise cancelling   Figure 3. The artificial neural network restoration results in the case where 80％ of the pixels are lost

Professor Emeritus Jung Ki Park Won the IBA Techno..

(Professor Emeritus Jung Ki Park) Professor Emeritus Jung Ki Park from the Department of Chemical and Biomolecular Engineering received the IBA Technology Award from the International Battery Association (IBA).   IBA 2018 was held from March 11 to 16 on Jeju Island, which was the first time it was hosted in Korea. The conference was an excellent opportunity to let the world know the level of the Korean rechargeable battery industry and its technology.    Professor Park delivered his keynote speech titled Advances in Lithium Batteries in Korea at the conference and received the IBA Technology Award as the first Korean recipient.   ?Professor Park is a world-renowned scholar who was a groundbreaker in the rechargeable battery industry. He was recognized by the IBA Award Committee for his contributions carrying out research and development, fostering competent people, and enhancing the lithium rechargeable battery industry in Korea over the last 30 years.    Professor Park said, “It is my great honor to receive this award, which is the best international award in the field of rechargeable batteries. I would like to share this with my colleagues and students. As competition in the rechargeable industry intensifies, systemic cooperation among industries, academia, and government is needed for the continued development of the battery industry in Korea.

Seong-Tae Kim Wins Robert-Wagner All-Conference Be..

(Ph.D. candidate Seong-Tae Kim) Ph.D. candidate Seong-Tae Kim from the School of Electrical Engineering won the Robert Wagner All-Conference Best Student Paper Award during the 2018 International Society for Optics and Photonics (SPIE) Medical Imaging Conference, which was held in Houston last month.   Kim, supervised by Professor Yong Man Ro, received the award for his paper in the category of computer-aided diagnosis. His paper, titled “ICADx: Interpretable Computer-Aided Diagnosis of Breast Masses”, was selected as the best paper out of 900 submissions. The conference selects the best paper in nine different categories. His research provides new insights on diagnostic technology to detect breast cancer powered by deep learning.

Recognizing Seven Different Face Emotions on a Mob..

(Professor Hoi-Jun Yoo)   A KAIST research team succeeded in achieving face emotion recognition on a mobile platform by developing an AI semiconductor IC that processes two neural networks on a single chip.   Professor Hoi-Jun Yoo and his team (Primary researcher: Jinmook Lee Ph. D. student) from the School of Electrical Engineering developed a unified deep neural network processing unit (UNPU).    Deep learning is a technology for machine learning based on artificial neural networks, which allows a computer to learn by itself, just like a human.   The developed chip adjusts the weight precision (from 1 bit to 16 bit) of a neural network inside of the semiconductor in order to optimize energy efficiency and accuracy. With a single chip, it can process a convolutional neural network (CNN) and recurrent neural network (RNN) simultaneously. CNN is used for categorizing and recognizing images while RNN is for action recognition and speech recognition, such as time-series information.    Moreover, it enables an adjustment in energy efficiency and accuracy dynamically while recognizing objects. To realize mobile AI technology, it needs to process high-speed operations with low energy, otherwise the battery can run out quickly due to processing massive amounts of information at once. According to the team, this chip has better operation performance compared to world-class level mobile AI chips such as Google TPU. The energy efficiency of the new chip is 4 times higher than the TPU.   In order to demonstrate its high performance, the team installed UNPU in a smartphone to facilitate automatic face emotion recognition on the smartphone. This system displays a user’s emotions in real time. The research results for this system were presented at the 2018 International Solid-State Circuits Conference (ISSCC) in San Francisco on February 13.   Professor Yoo said, “We have developed a semiconductor that accelerates with low power requirements in order to realize AI on mobile platforms. We are hoping that this technology will be applied in various areas, such as object recognition, emotion recognition, action recognition, and automatic translation. Within one year, we will commercialize this technology.”

KAIST, First to Win the Cube Satellite Competition

?Professor Hyochoong Bang from the Department of Aerospace Engineering and his team received the Minister of Science and ICT Award at the 1st Cube Satellite Competition.   The team actually participated in the competition in 2012, but it took several years for the awarding ceremony since it took years for the satellites to be designed, produced, and launched.   The KAIST team successfully developed a cube satellite, named ‘Little Intelligent Nanosatellite of KAIST (LINK)’ and completed its launch in April 2017.   LINK (size: 20cmx10cmx10cm, weight: 2kg) mounted mass spectrometry and Langmuir probe for Earth observation. The Langmuir probe was developed by Professor Kyoung Wook Min from the Department of Physics, KAIST.   Yeerang Lim, a PhD student from the Department of Aerospace Engineering said, “I still remember the feeling that I had on the day when LINK launched into orbit and sent back signals. I hope that space exploration is not something far away but attainable for us in near future.”

Professor Jungwon Kim Wins the 8th Haerim Optics a..

(Professor Jungwon Kim)   Professor Jungwon Kim from the Department of Mechanical Engineering received the 8th Haerim Optics and Photonics Award from the Optical Society of Korea (OSK).   He was recognized for his dedication to pioneering the field of microwave photonics by developing ultra-low noise fiber photonics lasers.   The Haerim Optics and Photonics Award is given to an outstanding researcher who has made academic contributions in the field of optics and photonics for the last five years.   The name of the award (Haerim) comes from the pen-name of the renowned scholar, Professor Un-Chul Paek, because it is maintained using funds he contributed to the OSK.   The OSK will confer the award on February 8 during the 29th OSK Annual Meeting and Winter Conference of 2018.