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A New Strategy for the Optimal Electroreduction of CO2 to High-Value Products
-Researchers suggest that modulation of local CO2 concentration improves the selectivity, conversion rate, and electrode stability, and shed a new light on the electrochemical CO2 reduction technology for controlling emissions at a low cost.- A KAIST research team presented three novel approaches for modulating local carbon dioxide (CO2) concentration in gas-diffusion electrode (GDE)-based flow electrolyzers. Their study also empirically demonstrated that providing a moderate local CO2 concentration is effective in promoting Carbon–Carbon (C–C) coupling reactions toward the production of multi-carbon molecules. This work, featured in the May 20th issue of Joule, serves as a rational guide to tune CO2 mass transport for the optimal production of valuable multi-carbon products. Amid global efforts to reduce and recycle anthropogenic CO2 emissions, CO2 electrolysis holds great promise for converting CO2 into useful chemicals that were traditionally derived from fossil fuels. Many researches have been attempting to improve the selectivity of CO2 for commercially and industrially high-value multi-carbon products such as ethylene, ethanol, and 1-propanol, due to their high energy density and large market size. In order to achieve the highly-selective conversion of CO2 into valuable multi-carbon products, past studies have focused on the design of catalysts and the tuning of local environment related to pH, cations, and molecular additives. Conventional CO2 electrolytic systems relied heavily on an alkaline electrolyte that is often consumed in large quantities when reacting with CO2, and thus led to an increase in the operational costs. Moreover, the life span of a catalyst electrode was short, due to its inherent chemical reactivity. In their recent study, a group of KAIST researchers led by Professor Jihun Oh from the Department of Materials Science and Engineering reported that the local CO2 concentration has been an overlooked factor that largely affects the selectivity toward multi-carbon products. Professor Oh and his researchers Dr. Ying Chuan Tan, Hakhyeon Song, and Kelvin Berm Lee proposed that there is an intimate relation between local CO2 and multi-carbon product selectivity during electrochemical CO2 reduction reactions. The team employed the mass-transport modeling of a GDE-based flow electrolyzer that utilizes copper oxide (Cu2O) nanoparticles as model catalysts. They then identified and applied three approaches to modulate the local CO2 concentration within a GDE-based electrolytic system, including 1) controlling the catalyst layer structure, 2) CO2 feed concentration, and 3) feed flow rate. Contrary to common intuition, the study showed that providing a maximum CO2 transport leads to suboptimal multi-carbon product faradaic efficiency. Instead, by restricting and providing a moderate local CO2 concentration, C–C coupling can be significantly enhanced. The researchers demonstrated experimentally that the selectivity rate increased from 25.4% to 61.9%, and from 5.9% to 22.6% for the CO2 conversion rate. When a cheap milder near-neutral electrolyte was used, the stability of the CO2 electrolytic system improved to a great extent, allowing over 10 hours of steady selective production of multi-carbon products. Dr. Tan, the lead author of the paper, said, “Our research clearly revealed that the optimization of the local CO2 concentration is the key to maximizing the efficiency of converting CO2 into high-value multi-carbon products.” Professor Oh added, “This finding is expected to deliver new insights to the research community that variables affecting local CO2 concentration are also influential factors in the electrochemical CO2 reduction reaction performance. My colleagues and I hope that our study becomes a cornerstone for related technologies and their industrial applications.” This work was supported by the Korean Ministry of Science and ICT (MSIT) Creative Materials Discovery Program. Publication: Tan, Y. C et al. (2020) ‘Modulating Local CO2 Concentration as a General Strategy for Enhancing C−C Coupling in CO2 Electroreduction’, Joule, Vol. 4, Issue 5, pp. 1104-1120. Available online at https://doi.org/10.1016/j.joule.2020.03.013 Profile: Jihun Oh, PhD Associate Professor firstname.lastname@example.org http://les.kaist.ac.kr/ Laboratory for Energy and Sustainability (LE&S) Department of Materials Science and Engineering (MSE) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Republic of Korea Profile: Ying Chuan Tan, PhD email@example.com LE&S, MSE, KAIST Profile: Hakhyeon Song, PhD Candidate firstname.lastname@example.org LE&S, MSE, KAIST Profile: Kelvin Berm Lee, M.S. Candidate email@example.com LE&S, MSE, KAIST (END)
From Dark to Light in a Flash: Smart Film Lets Windows Switch Autonomously
Researchers have developed a new easy-to-use smart optical film technology that allows smart window devices to autonomously switch between transparent and opaque states in response to the surrounding light conditions. The proposed 3D hybrid nanocomposite film with a highly periodic network structure has empirically demonstrated its high speed and performance, enabling the smart window to quantify and self-regulate its high-contrast optical transmittance. As a proof of concept, a mobile-app-enabled smart window device for Internet of Things (IoT) applications has been realized using the proposed smart optical film with successful expansion to the 3-by-3-inch scale. This energy-efficient and cost-effective technology holds great promise for future use in various applications that require active optical transmission modulation. Flexible optical transmission modulation technologies for smart applications including privacy-protection windows, zero-energy buildings, and beam projection screens have been in the spotlight in recent years. Conventional technologies that used external stimuli such as electricity, heat, or light to modulate optical transmission had only limited applications due to their slow response speeds, unnecessary color switching, and low durability, stability, and safety. The optical transmission modulation contrast achieved by controlling the light scattering interfaces on non-periodic 2D surface structures that often have low optical density such as cracks, wrinkles, and pillars is also generally low. In addition, since the light scattering interfaces are exposed and not subject to any passivation, they can be vulnerable to external damage and may lose optical transmission modulation functions. Furthermore, in-plane scattering interfaces that randomly exist on the surface make large-area modulation with uniformity difficult. Inspired by these limitations, a KAIST research team led by Professor Seokwoo Jeon from the Department of Materials Science and Engineering and Professor Jung-Wuk Hong of the Civil and Environmental Engineering Department used proximity-field nanopatterning (PnP) technology that effectively produces highly periodic 3D hybrid nanostructures, and an atomic layer deposition (ALD) technique that allows the precise control of oxide deposition and the high-quality fabrication of semiconductor devices. The team then successfully produced a large-scale smart optical film with a size of 3 by 3 inches in which ultrathin alumina nanoshells are inserted between the elastomers in a periodic 3D nanonetwork. This “mechano-responsive” 3D hybrid nanocomposite film with a highly periodic network structure is the largest smart optical transmission modulation film that exists. The film has been shown to have state-of-the-art optical transmission modulation of up to 74% at visible wavelengths from 90% initial transmission to 16% in the scattering state under strain. Its durability and stability were proved by more than 10,000 tests of harsh mechanical deformation including stretching, releasing, bending, and being placed under high temperatures of up to 70°C. When this film was used, the transmittance of the smart window device was adjusted promptly and automatically within one second in response to the surrounding light conditions. Through these experiments, the underlying physics of optical scattering phenomena occurring in the heterogeneous interfaces were identified. Their findings were reported in the online edition of Advanced Science on April 26. KAIST Professor Jong-Hwa Shin’s group and Professor Young-Seok Shim at Silla University also collaborated on this project. Donghwi Cho, a PhD candidate in materials science and engineering at KAIST and co-lead author of the study, said, “Our smart optical film technology can better control high-contrast optical transmittance by relatively simple operating principles and with low energy consumption and costs.” “When this technology is applied by simply attaching the film to a conventional smart window glass surface without replacing the existing window system, fast switching and uniform tinting are possible while also securing durability, stability, and safety. In addition, its wide range of applications for stretchable or rollable devices such as wall-type displays for a beam projection screen will also fulfill aesthetic needs,” he added. This work was supported by the National Research Foundation of Korea (NRF), and the Korean Ministries of Science, ICT and Future Planning (MSIP), and Science and ICT (MSIT). Publication: Cho, D, et al. (2020) ‘High-Contrast Optical Modulation from Strain-Indicated Nanogaps at 3D Heterogeneous Interfaces’ Advanced Science, 1903708. Available online at https://doi.org/10.1002/advs.201903708 Profile: Seokwoo Jeon, PhD Professor firstname.lastname@example.org https://fdml.kaist.ac.kr/ Flexible Device and Metamaterials Lab (FDML) Department of Materials Science and Engineering (MSE) Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.krDaejeon 34141, Korea Profile: Jung-Wuk Hong, PhD Associate Professor email@example.com http://aaml.kaist.ac.kr Advanced Applied Mechanics Laboratory (AAML) Department of Civil and Environmental Engineering KAIST Profile: Donghwi Cho PhD Candidate firstname.lastname@example.orgFDML, MSE, KAIST Profile: Young-Seok Shim, PhD Assistant Professor email@example.com Division of Materials Science and Engineering Silla University https://www.silla.ac.kr Busan 46958, Korea (END)
Universal Virus Detection Platform to Expedite Viral Diagnosis
Reactive polymer-based tester pre-screens dsRNAs of a wide range of viruses without their genome sequences The prompt, precise, and massive detection of a virus is the key to combat infectious diseases such as Covid-19. A new viral diagnostic strategy using reactive polymer-grafted, double-stranded RNAs will serve as a pre-screening tester for a wide range of viruses with enhanced sensitivity. Currently, the most widely using viral detection methodology is polymerase chain reaction (PCR) diagnosis, which amplifies and detects a piece of the viral genome. Prior knowledge of the relevant primer nucleic acids of the virus is quintessential for this test. The detection platform developed by KAIST researchers identifies viral activities without amplifying specific nucleic acid targets. The research team, co-led by Professor Sheng Li and Professor Yoosik Kim from the Department of Chemical and Biomolecular Engineering, constructed a universal virus detection platform by utilizing the distinct features of the PPFPA-grafted surface and double-stranded RNAs. The key principle of this platform is utilizing the distinct feature of reactive polymer-grafted surfaces, which serve as a versatile platform for the immobilization of functional molecules. These activated surfaces can be used in a wide range of applications including separation, delivery, and detection. As long double-stranded RNAs are common byproducts of viral transcription and replication, these PPFPA-grafted surfaces can detect the presence of different kinds of viruses without prior knowledge of their genomic sequences. “We employed the PPFPA-grafted silicon surface to develop a universal virus detection platform by immobilizing antibodies that recognize double-stranded RNAs,” said Professor Kim. To increase detection sensitivity, the research team devised two-step detection process analogues to sandwich enzyme-linked immunosorbent assay where the bound double-stranded RNAs are then visualized using fluorophore-tagged antibodies that also recognize the RNAs’ double-stranded secondary structure. By utilizing the developed platform, long double-stranded RNAs can be detected and visualized from an RNA mixture as well as from total cell lysates, which contain a mixture of various abundant contaminants such as DNAs and proteins. The research team successfully detected elevated levels of hepatitis C and A viruses with this tool. “This new technology allows us to take on virus detection from a new perspective. By targeting a common biomarker, viral double-stranded RNAs, we can develop a pre-screening platform that can quickly differentiate infected populations from non-infected ones,” said Professor Li. “This detection platform provides new perspectives for diagnosing infectious diseases. This will provide fast and accurate diagnoses for an infected population and prevent the influx of massive outbreaks,” said Professor Kim. This work is featured in Biomacromolecules. This work was supported by the Agency for Defense Development (Grant UD170039ID), the Ministry of Science and ICT (NRF-2017R1D1A1B03034660, NRF-2019R1C1C1006672), and the KAIST Future Systems Healthcare Project from the Ministry of Science and ICT (KAISTHEALTHCARE42). Profile:-Professor Yoosik KimDepartment of Chemical and Biomolecular Engineeringhttps://qcbio.kaist.ac.kr KAIST-Professor Sheng LiDepartment of Chemical and Biomolecular Engineeringhttps://bcpolymer.kaist.ac.kr KAIST Publication:Ku et al., 2020. Reactive Polymer Targeting dsRNA as Universal Virus Detection Platform with Enhanced Sensitivity. Biomacromolecules (https://doi.org/10.1021/acs.biomac.0c00379).
Visualization of Functional Components to Characterize Optimal Composite Electrodes
Researchers have developed a visualization method that will determine the distribution of components in battery electrodes using atomic force microscopy. The method provides insights into the optimal conditions of composite electrodes and takes us one step closer to being able to manufacture next-generation all-solid-state batteries. Lithium-ion batteries are widely used in smart devices and vehicles. However, their flammability makes them a safety concern, arising from potential leakage of liquid electrolytes. All-solid-state lithium ion batteries have emerged as an alternative because of their better safety and wider electrochemical stability. Despite their advantages, all-solid-state lithium ion batteries still have drawbacks such as limited ion conductivity, insufficient contact areas, and high interfacial resistance between the electrode and solid electrolyte. To solve these issues, studies have been conducted on composite electrodes in which lithium ion conducting additives are dispersed as a medium to provide ion conductive paths at the interface and increase the overall ionic conductivity. It is very important to identify the shape and distribution of the components used in active materials, ion conductors, binders, and conductive additives on a microscopic scale for significantly improving the battery operation performance. The developed method is able to distinguish regions of each component based on detected signal sensitivity, by using various modes of atomic force microscopy on a multiscale basis, including electrochemical strain microscopy and lateral force microscopy. For this research project, both conventional electrodes and composite electrodes were tested, and the results were compared. Individual regions were distinguished and nanoscale correlation between ion reactivity distribution and friction force distribution within a single region was determined to examine the effect of the distribution of binder on the electrochemical strain. The research team explored the electrochemical strain microscopy amplitude/phase and lateral force microscopy friction force dependence on the AC drive voltage and the tip loading force, and used their sensitivities as markers for each component in the composite anode. This method allows for direct multiscale observation of the composite electrode in ambient condition, distinguishing various components and measuring their properties simultaneously. Lead author Dr. Hongjun Kim said, “It is easy to prepare the test sample for observation while providing much higher spatial resolution and intensity resolution for detected signals.” He added, “The method also has the advantage of providing 3D surface morphology information for the observed specimens.” Professor Seungbum Hong from the Department of Material Sciences and Engineering said, “This analytical technique using atomic force microscopy will be useful for quantitatively understanding what role each component of a composite material plays in the final properties.” “Our method not only will suggest the new direction for next-generation all-solid-state battery design on a multiscale basis but also lay the groundwork for innovation in the manufacturing process of other electrochemical materials.” This study is published in ACS Applied Energy Materials and supported by the Big Science Research and Development Project under the Ministry of Science and ICT and the National Research Foundation of Korea, the Basic Research Project under the Wearable Platform Materials Technology Center, and KAIST Global Singularity Research Program for 2019 and 2020. Publication:Kim, H, et al. (2020) ‘Visualization of Functional Components in a Lithium Silicon Titanium Phosphate-Natural Graphite Composite Anode’. ACS Applied Energy Materials, Volume 3, Issue 4, pp. 3253-3261. Available online at https://doi.org/10.1021/acsaem.9b02045 Profile: Seungbum Hong Professor firstname.lastname@example.org http://mii.kaist.ac.kr/ Materials Imaging and Integration Laboratory Department of Material Sciences and Engineering KAIST
Highly Efficient Charge-to-Spin Interconversion in Graphene Heterostructures
Researchers present a new route for designing a graphene-based active spintronic component KAIST physicists described a route to design the energy-efficient generation, manipulation and detection of spin currents using nonmagnetic two-dimensional materials. The research team, led by Professor Sungjae Cho, observed highly efficient charge-to-spin interconversion via the gate-tunable Rashba-Edelstien effect (REE) in graphene heterostructures. This research paves the way for the application of graphene as an active spintronic component for generating, controlling, and detecting spin current without ferromagnetic electrodes or magnetic fields. Graphene is a promising spintronic component owing to its long spin diffusion length. However, its small spin-orbit coupling limits the potential of graphene in spintronic applications since graphene cannot be used to generate, control, or detect spin current. “We successfully increased the spin-orbit coupling of graphene by stacking graphene on top of 2H-TaS2, which is one of the transition metal dichalcogenide materials with the largest spin-orbit coupling. Graphene now can be used to generate, control, and detect spin current,” Professor Cho said. The Rashba-Edelstein effect is a physical mechanism that enables charge current-to-spin current interconversion by spin-dependent band structure induced by the Rashba effect, a momentum-dependent splitting of spin bands in low-dimensional condensed matter systems. Professor Cho’s group demonstrated the gate-tunable Rashba-Edelstein effect in a multilayer graphene for the first time. The Rahsba-Edelstein effect allows the two-dimensional conduction electrons of graphene to be magnetized by an applied charge current and form a spin current. Furthermore, as the Fermi level of graphene, tuned by gate voltage, moves from the valence to conduction band, the spin current generated by graphene reversed its spin direction. This spin reversal is useful in the design of low-power-consumption transistors utilizing spins in that it provides the carrier “On” state with spin up holes (or spin down electrons) and the "Off" state with zero net spin polarization at so called “charge neutrality point” where numbers of electrons and holes are equal. “Our work is the first demonstration of charge-to-spin interconversion in a metallic TMD (transition-metal dichalcogenides) and graphene heterostructure with a spin polarization state controlled by a gate. We expect that the all-electrical spin-switching effect and the reversal of non-equilibrium spin polarization by the application of gate voltage is applicable for the energy-efficient generation and manipulation of spin currents using nonmagnetic van der Waals materials,” explained Professor Cho. This study (https://pubs.acs.org/doi/10.1021/acsnano.0c01037) was supported by the National Research Foundation of Korea. Publication: Lijun Li, Jin Zhang, Gyuho Myeong, Wongil Shin, Hongsik Lim, Boram Kim, Seungho Kim, Taehyeok Jin, Stuart Cavill, Beom Seo Kim, Changyoung Kim, Johannes Lischner, Aires Ferreira, and Sungjae Cho, Gate-Tunable Reversible Rashba−Edelstein Effect in a Few-Layer Graphene/2H-TaS2 Heterostructure at Room Temperature. ACS Nano 2020. Link to download the paper: https://pubs.acs.org/doi/10.1021/acsnano.0c01037 Profile: Professor Sungjae Cho, PhD email@example.com http://qtak.kaist.ac.kr Department of Physics Korea Advanced Institute of Science and Technology (KAIST) https://www.kaist.ac.kr Daejeon 34141, Korea
A Theoretical Boost to Nano-Scale Devices
- Researchers calculate the quasi-Fermi levels in molecular junctions applying an initio approach. - Semiconductor companies are struggling to develop devices that are mere nanometers in size, and much of the challenge lies in being able to more accurately describe the underlying physics at that nano-scale. But a new computational approach that has been in the works for a decade could break down these barriers. Devices using semiconductors, from computers to solar cells, have enjoyed tremendous efficiency improvements in the last few decades. Famously, one of the co-founders of Intel, Gordon Moore, observed that the number of transistors in an integrated circuit doubles about every two years—and this ‘Moore’s law’ held true for some time. In recent years, however, such gains have slowed as firms that attempt to engineer nano-scale transistors hit the limits of miniaturization at the atomic level. Researchers with the School of Electrical Engineering at KAIST have developed a new approach to the underlying physics of semiconductors. “With open quantum systems as the main research target of our lab, we were revisiting concepts that had been taken for granted and even appear in standard semiconductor physics textbooks such as the voltage drop in operating semiconductor devices,” said the lead researcher Professor Yong-Hoon Kim. “Questioning how all these concepts could be understood and possibly revised at the nano-scale, it was clear that there was something incomplete about our current understanding.” “And as the semiconductor chips are being scaled down to the atomic level, coming up with a better theory to describe semiconductor devices has become an urgent task.” The current understanding states that semiconductors are materials that act like half-way houses between conductors, like copper or steel, and insulators, like rubber or Styrofoam. They sometimes conduct electricity, but not always. This makes them a great material for intentionally controlling the flow of current, which in turn is useful for constructing the simple on/off switches—transistors—that are the foundation of memory and logic devices in computers. In order to ‘switch on’ a semiconductor, a current or light source is applied, exciting an electron in an atom to jump from what is called a ‘valence band,’ which is filled with electrons, up to the ‘conduction band,’ which is originally unfilled or only partially filled with electrons. Electrons that have jumped up to the conduction band thanks to external stimuli and the remaining ‘holes’ are now able to move about and act as charge carriers to flow electric current. The physical concept that describes the populations of the electrons in the conduction band and the holes in the valence band and the energy required to make this jump is formulated in terms of the so-called ‘Fermi level.’ For example, you need to know the Fermi levels of the electrons and holes in order to know what amount of energy you are going to get out of a solar cell, including losses. But the Fermi level concept is only straightforwardly defined so long as a semiconductor device is at equilibrium—sitting on a shelf doing nothing—and the whole point of semiconductor devices is not to leave them on the shelf. Some 70 years ago, William Shockley, the Nobel Prize-winning co-inventor of the transistor at the Bell Labs, came up with a bit of a theoretical fudge, the ‘quasi-Fermi level,’ or QFL, enabling rough prediction and measurement of the interaction between valence band holes and conduction band electrons, and this has worked pretty well until now. “But when you are working at the scale of just a few nanometers, the methods to theoretically calculate or experimentally measure the splitting of QFLs were just not available,” said Professor Kim. This means that at this scale, issues such as errors relating to voltage drop take on much greater significance. Kim’s team worked for nearly ten years on developing a novel theoretical description of nano-scale quantum electron transport that can replace the standard method—and the software that allows them to put it to use. This involved the further development of a bit of math known as the Density Functional Theory that simplifies the equations describing the interactions of electrons, and which has been very useful in other fields such as high-throughput computational materials discovery. For the first time, they were able to calculate the QFL splitting, offering a new understanding of the relationship between voltage drop and quantum electron transport in atomic scale devices. In addition to looking into various interesting non-equilibrium quantum phenomena with their novel methodology, the team is now further developing their software into a computer-aided design tool to be used by semiconductor companies for developing and fabricating advanced semiconductor devices. The study, featured at the Proceedings of the National Academy of Sciences of the USA on May 12, was supported by the National Research Foundation and the Korea Institute of Science and Technology Information Supercomputing Center. Image caption: The newly developed formalism and QFL splitting analysis led to new ways of characterizing extremely scaled-down semiconductor devices and the technology computer-aided design (TCAD) of next- generation nano-electronic/energy/bio devices. Image credit: Yong-Hoon Kim, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Publication: Juho Lee, Hyeonwoo Yeo, and Yong-Hoon Kim. (2020) ‘Quasi-Fermi level splitting in nanoscale junctions from ab initio.’ Proceedings of the National Academy of Sciences of the United States of America (PNAS), Volume 117, Issue 19, pp.10142-101488. Available online at https://doi.org/10.1073/pnas.1921273117 Profile: Yong-Hoon Kim Professor firstname.lastname@example.org http://nanocore.kaist.ac.kr/ 1st-Principles Nano-Device Computing Lab School of Electrical Engineering KAIST (END)
Simple Molecular Reagents to Treat Alzheimer’s Disease
- Researchers report minimalistic principles for designing small molecules with multiple reactivities against dementia. - Sometimes the most complex problems actually have very simple solutions. A group of South Korean researchers reported an efficient and effective redox-based strategy for incorporating multiple functions into simple molecular reagents against neurodegenerative disorders. The team developed redox-active aromatic molecular reagents with a simple structural composition that can simultaneously target and modulate various pathogenic factors in complex neurodegenerative disorders such as Alzheimer’s disease. Alzheimer’s disease is one of the most prevalent neurodegenerative disorders, affecting one in ten people over the age of 65. Early-onset dementia also increasingly affects younger people. A number of pathogenic elements such as reactive oxygen species, amyloid-beta, and metal ions have been suggested as potential causes of Alzheimer’s disease. Each element itself can lead to Alzheimer’s disease, but interactions between them may also aggravate the patient’s condition or interfere with the appropriate clinical care. For example, when interacting with amyloid-beta, metal ions foster the aggregation and accumulation of amyloid-beta peptides that can induce oxidative stress and toxicity in the brain and lead to neurodegeneration. Because these pathogenic factors of Alzheimer’s disease are intertwined, developing therapeutic agents that are capable of simultaneously regulating metal ion dyshomeostasis, amyloid-beta agglutination, and oxidative stress responses remains a key to halting the progression of the disease. A research team led by Professor Mi Hee Lim from the Department of Chemistry at KAIST demonstrated the feasibility of structure-mechanism-based molecular design for controlling a molecule’s chemical reactivity toward the various pathological factors of Alzheimer’s disease by tuning the redox properties of the molecule. This study, featured as the ‘ACS Editors’ Choice’ in the May 6th issue of the Journal of the American Chemical Society (JACS), was conducted in conjunction with KAIST Professor Mu-Hyun Baik’s group and Professor Joo-Young Lee’s group at the Asan Medical Center. Professor Lim and her collaborators rationally designed and generated 10 compact aromatic molecules presenting a range of redox potentials by adjusting the electronic distribution of the phenyl, phenylene, or pyridyl moiety to impart redox-dependent reactivities against the multiple pathogenic factors in Alzheimer’s disease. During the team’s biochemical and biophysical studies, these designed molecular reagents displayed redox-dependent reactivities against numerous desirable targets that are associated with Alzheimer’s disease such as free radicals, metal-free amyloid-beta, and metal-bound amyloid-beta. Further mechanistic results revealed that the redox properties of these designed molecular reagents were essential for their function. The team demonstrated that these reagents engaged in oxidative reactions with metal-free and metal-bound amyloid-beta and led to chemical modifications. The products of such oxidative transformations were observed to form covalent adducts with amyloid-beta and alter its aggregation. Moreover, the administration of the most promising candidate molecule significantly attenuated the amyloid pathology in the brains of Alzheimer’s disease transgenic mice and improved their cognitive defects. Professor Lim said, “This strategy is straightforward, time-saving, and cost-effective, and its effect is significant. We are excited to help enable the advancement of new therapeutic agents for neurodegenerative disorders, which can improve the lives of so many patients.” This work was supported by the National Research Foundation (NRF) of Korea, the Institute for Basic Science (IBS), and the Asan Institute for Life Sciences. Image credit: Professor Mi Hee Lim, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of the news coverage of this paper only. Publication: Kim, M. et al. (2020) ‘Minimalistic Principles for Designing Small Molecules with Multiple Reactivities against Pathological Factors in Dementia.’ Journal of the American Chemical Society (JACS), Volume 142, Issue 18, pp.8183-8193. Available online at https://doi.org/10.1021/jacs.9b13100 Profile: Mi Hee Lim Professor email@example.com http://sites.google.com/site/miheelimlab Lim Laboratory Department of Chemistry KAIST Profile: Mu-Hyun Baik Professor firstname.lastname@example.org https://baik-laboratory.com/ Baik Laboratory Department of Chemistry KAIST Profile: Joo-Yong Lee Professor email@example.com Asan Institute for Life Sciences Asan Medical Center (END)
Researchers Present a Microbial Strain Capable of Massive Succinic Acid Production
A research team led by Distinguished Professor Sang Yup Lee reported the production of a microbial strain capable of the massive production of succinic acid with the highest production efficiency to date. This strategy of integrating systems metabolic engineering with enzyme engineering will be useful for the production of industrially competitive bio-based chemicals. Their strategy was described in Nature Communications on April 23. The bio-based production of industrial chemicals from renewable non-food biomass has become increasingly important as a sustainable substitute for conventional petroleum-based production processes relying on fossil resources. Here, systems metabolic engineering, which is the key component for biorefinery technology, is utilized to effectively engineer the complex metabolic pathways of microorganisms to enable the efficient production of industrial chemicals. Succinic acid, a four-carbon dicarboxylic acid, is one of the most promising platform chemicals serving as a precursor for industrially important chemicals. Among microorganisms producing succinic acid, Mannheimia succiniciproducens has been proven to be one of the best strains for succinic acid production. The research team has developed a bio-based succinic acid production technology using the M. succiniciproducens strain isolated from the rumen of Korean cow for over 20 years and succeeded in developing a strain capable of producing succinic acid with the highest production efficiency. They carried out systems metabolic engineering to optimize the succinic acid production pathway of the M. succiniciproducens strain by determining the crystal structure of key enzymes important for succinic acid production and performing protein engineering to develop enzymes with better catalytic performance. As a result, 134 g per liter of succinic acid was produced from the fermentation of an engineered strain using glucose, glycerol, and carbon dioxide. They were able to achieve 21 g per liter per hour of succinic acid production, which is one of the key factors determining the economic feasibility of the overall production process. This is the world’s best succinic acid production efficiency reported to date. Previous production methods averaged 1~3 g per liter per hour. Distinguished professor Sang Yup Lee explained that his team’s work will significantly contribute to transforming the current petrochemical-based industry into an eco-friendly bio-based one. “Our research on the highly efficient bio-based production of succinic acid from renewable non-food resources and carbon dioxide has provided a basis for reducing our strong dependence on fossil resources, which is the main cause of the environmental crisis,” Professor Lee said. This work was supported by the Technology Development Program to Solve Climate Changes via Systems Metabolic Engineering for Biorefineries and the C1 Gas Refinery Program from the Ministry of Science and ICT through the National Research Foundation of Korea.
Breastfeeding Helps Prevent Mothers from Developing Diabetes after Childbirth
A team of South Korean researchers found that lactation can lower the incidence and reduce the risk of maternal postpartum diabetes. The researchers identified that lactation increases the mass and function of pancreatic beta cells through serotonin production. The team suggested that sustained improvements in pancreatic beta cells, which can last for years even after the cessation of lactation, improve mothers’ metabolic health in addition to providing health benefits for infants. Pregnancy imposes a substantial metabolic burden on women through weight gain and increased insulin resistance. Various other factors, including a history of gestational diabetes, maternal age, and obesity, further affect women’s risk of progressing to diabetes after delivery, and the risk of postpartum diabetes increases more in women who have had gestational diabetes and/or repeated deliveries. Diabetes-related complications include damage to blood vessels, which can lead to cardiovascular and cerebrovascular diseases such as heart attack and stroke, and problems with the nerves, eyes, kidneys, and many more. Since diabetes can pose a serious threat to mothers’ metabolic health, the management of maternal metabolic risk factors is important, especially in the peripartum period. Previous epidemiological studies have reported that lactation reduces the risk of postpartum diabetes, but the mechanisms underlying this benefit have remained elusive. The study, published in Science Translational Medicine on April 29, explains the biology underpinning this observation on the beneficial effects of lactation. Professor Hail Kim from the Graduate School of Medical Science and Engineering at KAIST led and jointly conducted the study in conjunction with researchers from the Seoul National University Bundang Hospital (SNUBH) and Chungnam National University (CNU) in Korea, and the University of California, San Francisco (UCSF) in the US. In their study, the team observed that the milk-secreting hormone ‘prolactin’ in lactating mothers not only promotes milk production, but also plays a major role in stimulating insulin-secreting pancreatic beta cells that regulate blood glucose in the body. The researchers also found that ‘serotonin’, known as a chemical that contributes to wellbeing and happiness, is produced in pancreatic beta cells during lactation. Serotonin in pancreatic beta cells act as an antioxidant and reduce oxidative stress, making mothers’ beta cells healthier. Serotonin also induces the proliferation of beta cells, thereby increasing the beta cell mass and helping maintain proper glucose levels. The research team conducted follow-up examinations on a total of 174 postpartum women, 85 lactated and 99 non-lactated, at two months postpartum and annually thereafter for at least three years. The results demonstrated that mothers who had undergone lactation improved pancreatic beta cell mass and function, and showed improved glucose homeostasis with approximately 20mg/dL lower glucose levels, thereby reducing the risk of postpartum diabetes in women. Surprisingly, this beneficial effect was maintained after the cessation of lactation, for more than three years after delivery. Professor Kim said, “We are happy to prove that lactation benefits female metabolic health by improving beta cell mass and function as well as glycemic control.” “Our future studies on the modulation of the molecular serotonergic pathway in accordance with the management of maternal metabolic risk factors may lead to new therapeutics to help prevent mothers from developing metabolic disorders,” he added. This work was supported by grants from the National Research Foundation (NRF) and the National Research Council of Science and Technology (NST) of Korea, the National Institutes of Health (NIH), the Larry L. Hillblom Foundation, and the Health Fellowship Foundation. Image credit: Professor Hail Kim, KAIST Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only. Publication: Moon, J. H et al. (2020) ‘Lactation improves pancreatic β cell mass and function through serotonin production.’ Science Translational Medicine, 12, eaay0455. Available online at https://doi.org/10.1126/scitranslmed.aay0455 Profile: Hail Kim, MD, PhD firstname.lastname@example.org Associate Professor Graduate School of Medical Science and Engineering (GSMSE) Korea Advanced Institute of Science and Technology (KAIST) Profile: Hak Chul Jang, MD, PhD email@example.com Professor Division of Endocrinology and Metabolism Seoul National University Bundang Hospital (SNUBH) President Korean Diabetes Association Profile: Joon Ho Moon, MD, PhD firstname.lastname@example.org Clinical Fellow Division of Endocrinology and Metabolism SNUBH Profile: Hyeongseok Kim, MD, PhD email@example.com Assistant Professor Chungnam National University (CNU) Profile: Professor Michael S. German, MD Michael.German@ucsf.edu Professor Diabetes Center University of California, San Francisco (UCSF) (END)
A Study Finds Neuropeptide Somatostatin Enhances Visual Processing
Researchers have confirmed that neuropeptide somatostatin can improve cognitive function in the brain. A research group of Professor Seung-Hee Lee from the Department of Biological Sciences at KAIST found that the application of neuropeptide somatostatin improves visual processing and cognitive behaviors by reducing excitatory inputs to parvalbumin-positive interneurons in the cortex. This study, reported at Science Advances on April 22nd (EST), sheds a new light on the therapeutics of neurodegenerative diseases. According to a recent study in Korea, one in ten seniors over 65 is experiencing dementia-related symptoms in their daily lives such like memory loss, cognitive decline, and motion function disorders. Professor Lee believes that somatostatin treatment can be directly applied to the recovery of cognitive functions in Alzheimer’s disease patients. Professor Lee started this study noting the fact that the level of somatostatin expression was dramatically decreased in the cerebral cortex and cerebrospinal fluid of Alzheimer’s disease patients Somatostatin-expressing neurons in the cortex are known to exert the dendritic inhibition of pyramidal neurons via GABAergic transmission. Previous studies focused on their inhibitory effects on cortical circuits, but somatostatin-expressing neurons can co-release somatostatin upon activation. Despite the abundant expression of somatostatin and its receptors in the cerebral cortex, it was not known if somatostatin could modulate cognitive processing in the cortex. The research team demonstrated that the somatostatin treatment into the cerebral cortex could enhance visual processing and cognitive behaviors in mice. The research team combined behaviors, in vivo and in vitro electrophysiology, and electron microscopy techniques to reveal how the activation of somatostatin receptors in vivo enhanced the ability of visual recognition in animals. Interestingly, somatostatin release can reduce excitatory synaptic transmission to another subtype of GABAergic interneurons, parvalbumin (PV)-expressing neurons. As somatostatin is a stable and safe neuropeptide expressed naturally in the mammalian brain, it was safe to be injected into the cortex and cerebrospinal fluid, showing a potential application to drug development for curing cognitive disorders in humans. Professor Lee said, “Our research confirmed the key role of the neuropeptide SST in modulating cortical function and enhancing cognitive ability in the mammalian brain. I hope new drugs can be developed based on the function of somatostatin to treat cognitive disabilities in many patients suffering from neurological disorders.” This study was supported by the National Research Foundation of Korea. Publication: Song, Y. H et al. (2020) ‘Somatostatin enhances visual processing and perception by suppressing excitatory inputs to parvalbumin-positive interneurons in V1’, Science Advances, 6(17). Available online at https://doi.org/10.1126/sciadv.aaz0517 Profile: Seung-Hee Lee Associate Professor firstname.lastname@example.org https://sites.google.com/site/leelab2013/ Sensory Processing Lab (SPL) Department of Biological Sciences (BIO) Korea Advanced Institute of Science and Technology (KAIST) Profile: You-Hyang Song Researcher (Ph.D.) email@example.com SPL, KAIST BIO Profile: Yang-Sun Hwang Researcher (M.S.) firstname.lastname@example.org SPL, KAIST BIO (END)
A Global Campaign of ‘Facts before Rumors’ on COVID-19 Launched
- A KAIST data scientist group responds to facts and rumors on COVID-19 for global awareness of the pandemic. - Like the novel coronavirus, rumors have no borders. The world is fighting to contain the pandemic, but we also have to deal with the appalling spread of an infodemic that is as contagious as the virus. This infodemic, a pandemic of false information, is bringing chaos and extreme fear to the general public. Professor Meeyoung Cha’s group at the School of Computing started a global campaign called ‘Facts before Rumors,’ to prevent the spread of false information from crossing borders. She explained, “We saw many rumors that had already been fact-checked long before in China and South Korea now begin to circulate in other countries, sometimes leading to detrimental results. We launched an official campaign, Facts before Rumors, to deliver COVID-19-related facts to countries where the number of cases is now increasing.” She released the first set of facts on March 26 via her Twitter account @nekozzang. Professor Cha, a data scientist who has focused on detecting global fake news, is now part of the COVID-19 AI Task Force at the Global Strategy Institute at KAIST. She is also leading the Data Science Group at the Institute for Basic Science (IBS) as Chief Investigator. Her research group worked in collaboration with the College of Nursing at Ewha Woman’s University to identify 15 claims about COVID-19 that circulated on social networks (SNS) and among the general public. The team fact-checked these claims based on information from the WHO and CDCs of Korea and the US. The research group is now working on translating the list of claims into Portuguese, Spanish, Persian, Chinese, Amharic, Hindi, and Vietnamese. Delivering facts before rumors, the team says, will help contain the disease and prevent any harm caused by misinformation. The pandemic, which spread in China and South Korea before arriving in Europe and the US, is now moving into South America, Africa, and Southeast Asia. “We would like to play a part in preventing the further spread of the disease with the provision of only scientifically vetted, truthful facts,” said the team. For this campaign, Professor Cha’s team investigated more than 200 rumored claims on COVID-19 in China during the early days of the pandemic. These claims spread in different levels: while some were only relevant locally or in larger regions of China, others propagated in Asia and are now spreading to countries that are currently most affected by the disease. For example, the false claim which publicized that ‘Fireworks can help tame the virus in the air’ only spread in China. Other claims such as ‘Eating garlic helps people overcome the disease’ or ‘Gargling with salt water prevents the contraction of the disease,’ spread around the world even after being proved groundless. The team noted, however, that the times at which these claims propagate are different from one country to another. “This opens up an opportunity to debunk rumors in some countries, even before they start to emerge,” said Professor Cha. Kun-Woo Kim, a master’s candidate in the Department of Industrial Design who joined this campaign and designed the Facts before Rumors chart also expressed his hope that this campaign will help reduce the number of victims. He added, “I am very grateful to our scientists who quickly responded to the Fact Check in these challenging times.”
COVID-19 Map Shows How the Global Pandemic Moves
- A School of Computing team facilitated the data from COVID-19 to show the global spread of the virus. - The COVID-19 map made by KAIST data scientists shows where and how the virus is spreading from China, reportedly the epicenter of the disease. Professor Meeyoung Cha from the School of Computing and her group facilitated data based on the number of confirmed cases from January 22 to March 22 to analyze the trends of this global epidemic. The statistics include the number of confirmed cases, recoveries, and deaths across major continents based on the number of confirmed case data during that period. The moving dot on the map strikingly shows how the confirmed cases are moving across the globe. According to their statistics, the centroid of the disease starts from near Wuhan in China and moved to Korea, then through the European region via Italy and Iran. The data is collected by a graduate student from the School of Computing, Geng Sun, who started the process during the time he was quarantined since coming back from his home in China. An undergraduate colleague of Geng's, Gabriel Camilo Lima who made the map, is now working remotely from his home in Brazil since all undergraduate students were required to move out of the dormitory last week. The university closed all undergraduate housing and advised the undergraduate students to go back home in a preventive measure to stop the virus from spreading across the campus. Gabriel said he calculated the centroid of all confirmed cases up to a given day. He explained, “I weighed each coordinate by the number of cases in that region and country and calculated an approximate center of gravity.” “The Earth is round, so the shortest path from Asia to Europe is often through Russia. In early March, the center of gravity of new cases was moving from Asia to Europe. Therefore, the centroid is moving to the west and goes through Russia, even though Russia has not reported many cases,” he added. Professor Cha, who is also responsible for the Data Science Group at the Institute for Basic Science (IBS) as the Chief Investigator, said their group will continue to update the map using public data at https://ds.ibs.re.kr/index.php/covid-19/. (END)
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