Korean
KAIST Unveils the Hidden Control Architecture of B..
(Professor Kwang-Hyun Cho and his team) A KAIST research team identified the intrinsic control architecture of brain networks. The control properties will contribute to providing a fundamental basis for the exogenous control of brain networks and, therefore, has broad implications in cognitive and clinical neuroscience. Although efficiency and robustness are often regarded as having a trade-off relationship, the human brain usually exhibits both attributes when it performs complex cognitive functions. Such optimality must be rooted in a specific coordinated control of interconnected brain regions, but the understanding of the intrinsic control architecture of brain networks is lacking. Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering and his team investigated the intrinsic control architecture of brain networks. They employed an interdisciplinary approach that spans connectomics, neuroscience, control engineering, network science, and systems biology to examine the structural brain networks of various species and compared them with the control architecture of other biological networks, as well as man-made ones, such as social, infrastructural and technological networks. In particular, the team reconstructed the structural brain networks of 100 healthy human adults by performing brain parcellation and tractography with structural and diffusion imaging data obtained from the Human Connectome Project database of the US National Institutes of Health. The team developed a framework for analyzing the control architecture of brain networks based on the minimum dominating set (MDSet), which refers to a minimal subset of nodes (MD-nodes) that control the remaining nodes with a one-step direct interaction. MD-nodes play a crucial role in various complex networks including biomolecular networks, but they have not been investigated in brain networks. By exploring and comparing the structural principles underlying the composition of MDSets of various complex networks, the team delineated their distinct control architectures. Interestingly, the team found that the proportion of MDSets in brain networks is remarkably small compared to those of other complex networks. This finding implies that brain networks may have been optimized for minimizing the cost required for controlling networks. Furthermore, the team found that the MDSets of brain networks are not solely determined by the degree of nodes, but rather strategically placed to form a particular control architecture. Consequently, the team revealed the hidden control architecture of brain networks, namely, the distributed and overlapping control architecture that is distinct from other complex networks. The team found that such a particular control architecture brings about robustness against targeted attacks (i.e., preferential attacks on high-degree nodes) which might be a fundamental basis of robust brain functions against preferential damage of high-degree nodes (i.e., brain regions). Moreover, the team found that the particular control architecture of brain networks also enables high efficiency in switching from one network state, defined by a set of node activities, to another – a capability that is crucial for traversing diverse cognitive states. Professor Cho said, “This study is the first attempt to make a quantitative comparison between brain networks and other real-world complex networks. Understanding of intrinsic control architecture underlying brain networks may enable the development of optimal interventions for therapeutic purposes or cognitive enhancement.” This research, led by Byeongwook Lee, Uiryong Kang and Hongjun Chang, was published in iScience (10.1016/j.isci.2019.02.017) on March 29, 2019. Figure 1. Schematic of identification of control architecture of brain networks. Figure 2. Identified control architectures of brain networks and other real-world complex networks.
On-chip Drug Screening for Identifying Antibiotic ..
(from left: Seunggyu Kimand Professor Jessie Sungyun Jeon) A KAIST research team developed a microfluidic-based drug screening chip that identifies synergistic interactions between two antibiotics in eight hours. This chip can be a cell-based drug screening platform for exploring critical pharmacological patterns of antibiotic interactions, along with potential applications in screening other cell-type agents and guidance for clinical therapies. Antibiotic susceptibility testing, which determines types and doses of antibiotics that can effectively inhibit bacterial growth, has become more critical in recent years with the emergence of antibiotic-resistant pathogenic bacteria strains. To overcome the antibiotic-resistant bacteria, combinatory therapy using two or more kinds of antibiotics has been gaining considerable attention. However, the major problem is that this therapy is not always effective; occasionally, unfavorable antibiotic pairs may worsen results, leading to suppressed antimicrobial effects. Therefore, combinatory testing is a crucial preliminary process to find suitable antibiotic pairs and their concentration range against unknown pathogens, but the conventional testing methods are inconvenient for concentration dilution and sample preparation, and they take more than 24 hours to produce the results. To reduce time and enhance the efficiency of combinatory testing, Professor Jessie Sungyun Jeon from the Department of Mechanical Engineering, in collaboration with Professor Hyun Jung Chung from the Department of Biological Sciences, developed a high-throughput drug screening chip that generates 121 pairwise concentrations between two antibiotics. The team utilized a microfluidic chip with a sample volume of a few tens of microliters. This chip enabled 121 pairwise concentrations of two antibiotics to be automatically formed in only 35 minutes. They loaded a mixture of bacterial samples and agarose into the microchannel and injected reagents with or without antibiotics into the surrounding microchannel. The diffusion of antibiotic molecules from the channel with antibiotics to the one without antibiotics resulted in the formation of two orthogonal concentration gradients of the two antibiotics on the bacteria-trapping agarose gel. The team observed the inhibition of bacterial growth by the antibiotic orthogonal gradients over six hours with a microscope, and confirmed different patterns of antibiotic pairs, classifying the interaction types into either synergy or antagonism. Professor Jeon said, “The feasibility of microfluidic-based drug screening chips is promising, and we expect our microfluidic chip to be commercialized and utilized in near future.” This study, led by Seunggyu Kim, was published in Lab on a Chip (10.1039/c8lc01406j) on March 21, 2019. Figure 1. Back cover image for the “Lab on a Chip”. Figure 2. Examples of testing results using the microfluidic chips developed in this research.
True-meaning Wearable Displays: Self-powered, Wash..
(Video: The washing process of wearing display module) When we think about clothes, they are usually formed with textiles and have to be both wearable and washable for daily use; however, smart clothing has had a problem with its power sources and moisture permeability, which causes the devices to malfunction. This problem has now been overcome by a KAIST research team, who developed a textile-based wearable display module technology that is washable and does not require an external power source. To ease out the problem of external power sources and enhance the practicability of wearable displays, Professor Kyung Cheol Choi from the School of Electrical Engineering and his team fabricated their wearing display modules on real textiles that integrated polymer solar cells (PSCs) with organic light emitting diodes (OLEDs). PSCs have been one of the most promising candidates for a next-generation power source, especially for wearable and optoelectronic applications because they can provide stable power without an external power source, while OLEDs can be driven with milliwatts. However, the problem was that they are both very vulnerable to external moisture and oxygen. The encapsulation barrier is essential for their reliability. The conventional encapsulation barrier is sufficient for normal environments; however, it loses its characteristics in aqueous environments, such as water. It limits the commercialization of wearing displays that must operate even on rainy days or after washing. To tackle this issue, the team employed a washable encapsulation barrier that can protect the device without losing its characteristics after washing through atomic layer deposition (ALD) and spin coating. With this encapsulation technology, the team confirmed that textile-based wearing display modules including PSCs, OLEDs, and the proposed encapsulation barrier exhibited little change in characteristics even after 20 washings with 10-minute cycles. Moreover, the encapsulated device operated stably with a low curvature radius of 3mm and boasted high reliability. Finally, it exhibited no deterioration in properties over 30 days even after being subjected to both bending stress and washing. Since it uses a less stressful textile, compared to conventional wearable electronic devices that use traditional plastic substrates, this technology can accelerate the commercialization of wearing electronic devices. Importantly, this wearable electronic device in daily life can save energy through a self-powered system. Professor Choi said, “I could say that this research realized a truly washable wearable electronic module in the sense that it uses daily wearable textiles instead of the plastic used in conventional wearable electronic devices. Saving energy with PSCs, it can be self-powered, using nature-friendly solar energy, and washed. I believe that it has paved the way for a ‘true-meaning wearable display’ that can be formed on textile, beyond the attachable form of wearable technology.” This research, in collaboration with Professor Seok Ho Cho from Chonnam National University and led by Eun Gyo Jeong, was published in Energy and Environmental Science (10.1039/c8ee03271h) on January 18, 2019. Figure 1. Schematic and photo of a washable wearing display module Figure 2. Cover page of Energy and Environmental Science
Wafer-scale multilayer fabrication of silk fibroin..
A KAIST research team developed a novel fabrication method for the multilayer processing of silk-based microelectronics. This technology for creating a biodegradable silk fibroin film allows microfabrication with polymer or metal structures manufactured from photolithography. It can be a key technology in the implementation of silk fibroin-based biodegradable electronic devices or localized drug delivery through silk fibroin patterns. Silk fibroins are biocompatible, biodegradable, transparent, and flexible, which makes them excellent candidates for implantable biomedical devices, and they have also been used as biodegradable films and functional microstructures in biomedical applications. However, conventional microfabrication processes require strong etching solutions and solvents to modify the structure of silk fibroins. To prevent the silk fibroin from being damaged during the process, Professor Hyunjoo J. Lee from the School of Electrical Engineering and her team came up with a novel process, named aluminum hard mask on silk fibroin (AMoS), which is capable of micropatterning multiple layers composed of both fibroin and inorganic materials, such as metal and dielectrics with high-precision microscale alignment. The AMoS process can make silk fibroin patterns on devices, or make patterns on silk fibroin thin films with other materials by using photolithography, which is a core technology in the current microfabrication process. The team successfully cultured primary neurons on the processed silk fibroin micro-patterns, and confirmed that silk fibroin has excellent biocompatibility before and after the fabrication process and that it also can be applied to implanted biological devices. Through this technology, the team realized the multilayer micropatterning of fibroin films on a silk fibroin substrate and fabricated a biodegradable microelectric circuit consisting of resistors and silk fibroin dielectric capacitors in a silicon wafer with large areas. They also used this technology to position the micro-pattern of the silk fibroin thin film closer to the flexible polymer-based brain electrode, and confirmed the dye molecules mounted on the silk fibroin were transferred successfully from the micropatterns. Professor Lee said, “This technology facilitates wafer-scale, large-area processing of sensitive materials. We expect it to be applied to a wide range of biomedical devices in the future. Using the silk fibroin with micro-patterned brain electrodes can open up many new possibilities in research on brain circuits by mounting drugs that restrict or promote brain cell activities.” This research, in collaboration with Dr. Nakwon Choi from KIST and led by PhD candidate Geon Kook, was published in ACS AMI (10.1021/acsami.8b13170) on January 16, 2019. Figure 1. The cover page of ACS AMI Figure 2. Fibroin microstructures and metal patterns on a fibroin produced by using the AMoS mask. Figure 3. Biocompatibility assessment of the AMoS Process. Top: Schematics image of a) fibroin-coated silicon b) fibroin-pattered silicon and c) gold-patterned fibroin. Bottom: Representative confocal microscopy images of live (green) and dead (red) primary cortical neurons cultured on the substrates.
Novel Material Properties of Hybrid Perovskite Nan..
(from left: Juho Lee, Dr. Muhammad Ejaz Khan and Professor Yong-Hoon Kim) A KAIST research team reported a novel non-linear device with the founding property coming from perovskite nanowires. They showed that hybrid perovskite-derived, inorganic-framework nanowires can acquire semi-metallicity, and proposed negative differential resistance (NDR) devices with excellent NDR characteristics that resulted from a novel quantum-hybridization NDR mechanism, implying the potential of perovskite nanowires to be realized in next-generation electronic devices. Organic-inorganic hybrid halide perovskites have recently emerged as prominent candidates for photonic applications due to their excellent optoelectronic properties as well as their low cost and facile synthesis processes. Prominent progresses have been already made for devices including solar cells, light-emitting diodes, lasers and photodetectors. However, research on electronic devices based on hybrid halide perovskites has not been actively pursued compared with their photonic device counterparts. Professor Yong-Hoon Kim from the School of Electrical Engineering and his team took a closer look at low-dimensional organic-inorganic halide perovskite materials, which have enhanced quantum confinement effects, and particularly focused on the recently synthesized trimethylsulfonium (TMS) lead triiodide (CH3)3SPbI3. Using supercomputer simulations, the team first showed that stripping the (CH3)3S or TMS organic ligands from the TMS PbI3 perovskite nanowires results in semi-metallic PbI3 columns, which contradicts the conventional assumption of the semiconducting or insulating characteristics of the inorganic perovskite framework. Utilizing the semi-metallic PbI3 inorganic framework as the electrode, the team designed a tunneling junction device from perovskite nanowires and found that they exhibit excellent nonlinear negative differential resistance (NDR) behavior. The NDR property is a key to realizing next-generation, ultra-low-power, and multivalued non-linear devices. Furthermore, the team found that this NDR originates from a novel mechanism that involves the quantum-mechanical hybridization between channel and electrode states. Professor Kim said, “This research demonstrates the potential of quantum mechanics-based computer simulations to lead developments in advanced nanomaterials and nanodevices. In particular, this research proposes a new direction in the development of a quantum mechanical tunneling device, which was the topic for which the Nobel Laureate in Physics in 1973 was awarded to Dr. Leo Esaki. This research, led by Dr. Muhammad Ejaz Khan and PhD candidate Juho Lee, was published online in Advanced Functional Materials (10.1002/adfm.201807620) on January 7, 2019. Figure. The draft version of the cover page of 'Advanced Functional Materials'
Kimchi Toolkit by Costa Rican Summa Cum Laude Help..
(Maria Jose Reyes Castro with her kimchi toolkit application) Every graduate feels a special attachment to their school, but for Maria Jose Reyes Castro who graduated summa cum laude in the Department of Industrial Design this year, KAIST will be remembered for more than just academics. She appreciates KAIST for not only giving her great professional opportunities, but also helping her find the love of her life. During her master’s course, she completed an electronic kimchi toolkit, which optimizes kimchi’s flavor. Her kit uses a mobile application and smart sensor to find the fermentation level of kimchi by measuring its pH level, which is closely related to its fermentation. A user can set a desired fermentation level or salinity on the mobile application, and it provides the best date to serve it. Under the guidance of Professor Daniel Saakes, she conducted research on developing a kimchi toolkit for beginners (Qualified Kimchi: Improving the experience of inexperienced kimchi makers by developing a monitoring toolkit for kimchi). “I’ve seen many foreigners saying it’s quite difficult to make kimchi. So I chose to study kimchi to help people, especially those who are first-experienced making kimchi more easily,” she said. She got recipes from YouTube and studied fermentation through academic journals. She also asked kimchi experts to have a more profound understanding of it. Extending her studies, she now works for a startup specializing in smart farms after starting last month. She conducts research on biology and applies it to designs that can be used practically in daily life. Her tie with KAIST goes back to 2011 when she attended an international science camp in Germany. She met Sunghan Ro (’19 PhD in Nanoscience and Technology), a student from KAIST and now her husband. He recommended for her to enroll at KAIST because the school offers an outstanding education and research infrastructure along with support for foreign students. At that time, Castro had just begun her first semester in electrical engineering at the University of Costa Rica, but she decided to apply to KAIST and seek a better opportunity in a new environment. One year later, she began her fresh start at KAIST in the fall semester of 2012. Instead of choosing her original major, electrical engineering, she decided to pursue her studies in the Department of Industrial Design, because it is an interdisciplinary field where students get to study design while learning business models and making prototypes. She said, “I felt encouraged by my professors and colleagues in my department to be creative and follow my passion. I never regret entering this major.” When Castro was pursuing her master’s program in the same department, she became interested in interaction designs with food and biological designs by Professor Saakes, who is her advisor specializing in these areas. After years of following her passion in design, she now graduates with academic honors in her department. It is a bittersweet moment to close her journey at KAIST, but “I want to thank KAIST for the opportunity to change my life for the better. I also thank my parents for being supportive and encouraging me. I really appreciate the professors from the Department of Industrial Design who guided and shaped who I am,” she said. Figure 1. The concept of the kimchi toolkit Figure 2. The scenario of the kimchi toolkit
KAIST Develops Analog Memristive Synapses for Neur..
(Professor Sung-Yool Choi from the School of Electrical Engineering) A KAIST research team developed a technology that makes a transition of the operation mode of flexible memristors to synaptic analog switching by reducing the size of the formed filament. Through this technology, memristors can extend their role to memristive synapses for neuromorphic chips, which will lead to developing soft neuromorphic intelligent systems. Brain-inspired neuromorphic chips have been gaining a great deal of attention for reducing the power consumption and integrating data processing, compared to conventional semiconductor chips. Similarly, memristors are known to be the most suitable candidate for making a crossbar array which is the most efficient architecture for realizing hardware-based artificial neural network (ANN) inside a neuromorphic chip. A hardware-based ANN consists of a neuron circuit and synapse elements, the connecting pieces. In the neuromorphic system, the synaptic weight, which represents the connection strength between neurons, should be stored and updated as the type of analog data at each synapse. However, most memristors have digital characteristics suitable for nonvolatile memory. These characteristics put a limitation on the analog operation of the memristors, which makes it difficult to apply them to synaptic devices. Professor Sung-Yool Choi from the School of Electrical Engineering and his team fabricated a flexible polymer memristor on a plastic substrate, and found that changing the size of the conductive metal filaments formed inside the device on the scale of metal atoms can make a transition of the memristor behavior from digital to analog. Using this phenomenon, the team developed flexible memristor-based electronic synapses, which can continuously and linearly update synaptic weight, and operate under mechanical deformations such as bending. The team confirmed that the ANN based on these memristor synapses can effectively classify person’s facial images even when they were damaged. This research demonstrated the possibility of a neuromorphic chip that can efficiently recognize faces, numbers, and objects. Professor Choi said, “We found the principles underlying the transition from digital to analog operation of the memristors. I believe that this research paves the way for applying various memristors to either digital memory or electronic synapses, and will accelerate the development of a high-performing neuromorphic chip.” In a joint research project with Professor Sung Gap Im (KAIST) and Professor V. P. Dravid (Northwestern University), this study was led by Dr. Byung Chul Jang (Samsung Electronics), Dr. Sungkyu Kim (Northwestern University) and Dr. Sang Yoon Yang (KAIST), and was published online in Nano Letters on January 4, 2019. Figure 1. a) Schematic illustration of a flexible pV3D3 memristor-based electronic synapse array. b) Cross-sectional TEM image of the flexible pV3D3 memristor
New LSB with Theoretical Capacity over 90%
(Professor Hee-Tak Kim and Hyunwon Chu) A KAIST research team has developed a lithium sulfur battery (LSB) that realizes 92% of the theoretical capacity and an areal capacity of 4mAh/cm2. LSBs are gaining a great deal of attention as an alternative for lithium ion batteries (LIBs) because they have a theoretical energy density up to six to seven times higher than that of LIBs, and can be manufactured in a more cost-effective way. However, LSBs face the obstacle of having a capacity reaching its theoretical maximum because they are prone to uncontrolled growth of lithium sulfide on the electrodes, which leads to blocking electron transfer. To address the problem of electrode passivation, researchers introduced additional conductive agent into the electrode; however, it drastically lowered the energy density of LSBs, making it difficult to exceed 70% of the theoretical capacity. Professor Hee-Tak Kim from the Department of Chemical and Biomolecular Engineering and his team replaced the lithium salt anions used in conventional LSB electrolytes with anions with a high donor number. The team successfully induced the three-dimensional growth of lithium sulfide on electrode surfaces and efficiently delayed the electrode passivation. Based on this electrolyte design, the research team achieved 92% of the theoretical capacity with their high-capacity sulfur electrode (4mAh/cm2), which is equivalent to that of conventional LIB cathode. Furthermore, they were able to form a stable passivation film on the surface of the lithium anode and exhibited stable operation over 100 cycles. This technology, which can be flexibly used with various types of sulfur electrodes, can mark a new milestone in the battery industry. Professor Kim said, “We proposed a new physiochemical principle to overcome the limitations of conventional LSBs. I believe our achievement of obtaining 90% of the LBSs’ theoretical capacity without any capacity loss after 100 cycles will become a new milestone.” This research, first-authored by Hyunwon Chu and Hyungjun Noh, was published in Nature Communications on January 14, 2019. It was also selected in the editor’s highlight for its outstanding achievements. Figure 1. Lithium sulfur growth and its deposition mechanism for different sulfide growth behaviors Figure 2. Capacity and cycle life characteristics of the LSBs
Hierarchical Porous Titanium Nitride Synthesized b..
(from left: Professor Jinwoo Lee and PhD candidate Won-Gwang Lim) A KAIST research team developed ultra-stable, high-rate lithium-sulfur batteries (LSBs) by using hierarchical porous titanium nitride as a sulfur host, and achieved superior cycle stability and high rate performance for LSBs. The control of large amounts of energy is required for use in an electric vehicle or smart grid system. In this sense, the development of next-generation secondary batteries is in high demand. Theoretically, LSBs have an energy density seven times higher than commercial lithium ion batteries (LIBs). Also, their production cost can be reduced dramatically since sulfur can be obtained at a low price. Despite these positive aspects, there have been several issues impeding the commercialization of LSBs, such as the low electric conductivity of sulfur, the dissolution of active materials during operation, and sluggish conversion reactions. These issues decrease the cycle stability and rate capability of batteries. To tackle those issues, Professor Jinwoo Lee from the Department of Chemical and Biomolecular Engineering and his team synthesized a well-developed hierarchical macro/mesoporous titanium nitride as a host material for sulfur. The titanium nitride has a high chemical affinity for sulfur and high electrical conductivity. As a result, it prevents the dissolution of active materials and facilitates the charge transfer. Moreover, the synergistic effect of macropore and mesopore structures allows the stable accommodation of large amounts of sulfur and facilitates the electrolyte penetration. Previously reported polar inorganic materials have a high affinity for sulfur, but it was challenging to control the porous architecture suitable to the sulfur host. This work breaks such limitations by developing a synthetic route to easily control the porous architecture of inorganic materials, which led to obtaining superior cycle stability and high rate capabilities. Professor Lee said, “Some problems still remain in commercializing LSBs as next-generation batteries. Hence, there should be a continued research on this matter to solve the issues. Through this research, we secured a key technology for ultrastable, high-rate LSBs.” This research was led by PhD candidate Won-Gwang Lim and collaborated on by Jeong Woo Han from POSTECH. It was chosen as the cover article of Advanced Materials on January 15, 2019. Figure 1. Schematic illustration for the synthetic route of co-continuous h-TiN Figure 2. The hierarchical multiscale porous structure is still retained without any collapse after the conversion to h-TiN. The good retention of the porous structure is attributed to the thick pore wall of the h-TiO₂derived from the block copolymer self-assembly Figure 3. The cover page of Advanced Materials
Brain-inspired Artificial Intelligence in Robots
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. 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. 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’. 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. 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.” 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.” <span style="font-family:;" times="" new="" roman";="" 9pt;"="" 12pt;"="">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)
KAIST Develops Core Technology for Ultra-small 3D ..
(from left: Dr. Jong-Bum Yo, PhD candidate Seong-Hwan Kimand Professor Hyo-Hoon Park) A KAIST research team developed a silicon optical phased array (OPA) chip, which can be a core component for three-dimensional image sensors. This research was co-led by PhD candidate Seong-Hwan Kim and Dr. Jong-Bum You from the National Nanofab Center (NNFC). A 3D image sensor adds distance information to a two-dimensional image, such as a photo, to recognize it as a 3D image. It plays a vital role in various electronics including autonomous vehicles, drones, robots, and facial recognition systems, which require accurate measurement of the distance from objects. Many automobile and drone companies are focusing on developing 3D image sensor systems, based on mechanical light detection and ranging (LiDAR) systems. However, it can only get as small as the size of a fist and has a high possibility of malfunctioning because it employs a mechanical method for laser beam-steering. OPAs have gained a great attention as a key component to implement solid-state LiDAR because it can control the light direction electronically without moving parts. Silicon-based OPAs are small, durable, and can be mass-produced through conventional Si-CMOS processes. However, in the development of OPAs, a big issue has been raised about how to achieve wide beam-steering in transversal and longitudinal directions. In the transversal direction, a wide beam-steering has been implemented, relatively easily, through a thermo-optic or electro-optic control of the phase shifters integrated with a 1D array. But the longitudinal beam-steering has been remaining as a technical challenge since only a narrow steering was possible with the same 1D array by changing the wavelengths of light, which is hard to implement in semiconductor processes. If a light wavelength is changed, characteristics of element devices consisting the OPA can vary, which makes it difficult to control the light direction with reliability as well as to integrate a wavelength-tunable laser on a silicon-based chip. Therefore, it is essential to devise a new structure that can easily adjust the radiated light in both transversal and longitudinal directions. By integrating tunable radiator, instead of tunable laser in a conventional OPA, Professor Hyo-Hoon Park from the School of Electrical Engineering and his team developed an ultra-small, low-power OPA chip that facilitates a wide 2D beam-steering with a monochromatic light source. This OPA structure allows the minimizing of the 3D image sensors, as small as a dragonfly’s eye. According to the team, the OPA can function as a 3D image sensor and also as a wireless transmitter sending the image data to a desired direction, enabling high-quality image data to be freely communicated between electronic devices. Kim said, “It’s not an easy task to integrate a tunable light source in the OPA structures of previous works. We hope our research proposing a tunable radiator makes a big step towards commercializing OPAs.” Dr. You added, “We will be able to support application researches of 3D image sensors, especially for facial recognition with smartphones and augmented reality services. We will try to prepare a processing platform in NNFC that provides core technologies of the 3D image sensor fabrication.” This research was published in Optics Letters on January 15. Figure 1.The manufactured OPA chip Figure 2. Schematic feature showing an application of the OPA to a 3D image sensor
A Comprehensive Metabolic Map for Production of Bi..
A KAIST research team completed a metabolic map that charts all available strategies and pathways of chemical reactions that lead to the production of various industrial bio-based chemicals. The team was led by Distinguished Professor Sang Yup Lee, who has produced high-quality metabolic engineering and systems engineering research for decades, and made the hallmark chemicals map after seven years of studies. The team presented a very detailed analysis on metabolic engineering for the production of a wide range of industrial chemicals, fuels, and materials. Surveying the current trends in the bio-based production of chemicals in industrial biotechnology, the team thoroughly examined the current status of industrial chemicals produced using biological and/or chemical reactions. This comprehensive map is expected to serve as a blueprint for the visual and intuitive inspection of biological and/or chemical reactions for the production of interest from renewable resources. The team also compiled an accompanying poster to visually present the synthetic pathways of chemicals in the context of their microbial metabolism. As metabolic engineering has become increasing powerful in addressing limited fossil resources, climate change, and other environmental issues, the number of microbially produced chemicals using biomass as a carbon source has increased substantially. The sustainable production of industrial chemicals and materials has been explored with micro-organisms as cell factories and renewable nonfood biomass as raw materials for alternative petroleum. The engineering of these micro-organism has increasingly become more efficient and effective with the help of metabolic engineering – a practice of engineering using the metabolism of living organisms to produce a desired metabolite. With the establishment of systems metabolic engineering – the integration of metabolic engineering with tools and strategies from systems biology, synthetic biology and evolutionary engineering – the speed at which micro-organisms are being engineered has reached an unparalleled pace. In order to evaluate the current state at which metabolically engineered micro-organisms can produce a large portfolio of industrial chemicals, the team conducted an extensive review of the literature and mapped them out on a poster. This resulting poster, termed the bio-based chemicals map, presents synthetic pathways for industrial chemicals, which consist of biological and/or chemical reactions. Industrial chemicals and their production routes are presented in the context of central carbon metabolic pathways as these key metabolites serve as precursors for the chemicals to be produced. The resulting biochemical map allows the detection and analysis of optimal synthetic pathways for a given industrial chemical. In addition to the poster, the authors have compiled a list of chemicals that have successfully been produced using micro-organisms and a list of the corresponding companies producing them commercially. This thorough review of the literature and the accompanying analytical summary will be an important resource for researchers interested in the production of chemicals from renewable biomass sources. Metabolically engineered micro-organisms have already made a huge contribution toward the sustainable production of chemicals using renewable resources. Professor Lee said he wanted a detailed survey of the current state and capacity of bio-based chemicals production. “We are so excited that this review and poster will expand further discussion on the production of important chemicals through engineered micro-organisms and also combined biological and chemical means in a more sustainable manner,” he explained. This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biofineries from the Ministry of Science and ICT through the National Research Foundation of Korea. For further information, Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST ( leesy@kaist.ac.kr , Tel: +82-42-350-3930) Figure: Bio-based chemicals production through biological and chemical routes. This metabolic map describes representative chemicals that can be produced either by biological and/or chemical means. Red arrows represent chemical routes and blue arrows represent biological routes. Intermediate metabolites in the metabolism of a living organism can serve as a platform toward the production of industrially relevant chemicals. A more comprehensive map presented by the team can be found as a poster in the review.