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Recombinant E. Coli As a Biofactory for the Biosynthesis of Diverse Nanomaterials
(Distinguished Professor Lee and PhD candidate Choi) A metabolic research group at KAIST and Chung-Ang University in Korea has developed a recombinant E. coli strain that biosynthesizes 60 different nanomaterials covering 35 elements on the periodic table. Among the elements, the team could biosynthesize 33 novel nanomaterials for the first time, advancing the forward design of nanomaterials through the biosynthesis of various single and multi-elements. The study analyzed the nanomaterial biosynthesis conditions using a Pourbaix diagram to predict the producibility and crystallinity. Researchers studied a Pourbaix diagram to predict the stable chemical species of each element for nanomaterial biosynthesis at varying levels of reduction potential (Eh) and pH. Based on the Pourbaix diagram analyses, the initial pH of the reaction was changed from 6.5 to 7.5, resulting in the biosynthesis of various crystalline nanomaterials that were previously amorphous or not synthesized. This strategy was extended to biosynthesize multi-element nanomaterials. Various single and multi-element nanomaterials biosynthesized in this research can potentially serve as new and novel nanomaterials for industrial applications such as catalysts, chemical sensors, biosensors, bioimaging, drug delivery, and cancer therapy. A research group consisting of PhD candidate Yoojin Choi, Associate Professor Doh Chang Lee, and Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering at KAIST and Associate Professor Tae Jung Park of the Department of Chemistry at Chung-Ang University reported the synthesis. This study, entitled “Recombinant Escherichia coli as a biofactory for various single- and multi-element nanomaterials,” was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on May 21. A recent successful biosynthesis of nanomaterials under mild conditions without requiring physical and chemical treatments has triggered the exploration of the full biosynthesis capacity of a biological system for producing a diverse range of nanomaterials as well as for understanding biosynthesis mechanisms for crystalline versus amorphous nanomaterials. There has been increased interest in synthesizing various nanomaterials that have not yet been synthesized for various applications including semiconducting materials, enhanced solar cells, biomedical materials, and many others. This research reports the construction of a recombinant E. coli strain that co-expresses metallothionein, a metal binding protein, and phytochelatin synthase that synthesizes the metal-binding peptide phytochelatin for the biosynthesis of various nanomaterials. Subsequently, an E. coli strain was engineered to produce a diverse range of nanomaterials, including those never biosynthesized before, by using 35 individual elements from the periodic table and also by combining multi-elements. Distinguished Professor Lee said, “An environmentally-friendly and sustainable process is of much interest for producing nanomaterials by not only chemical and physical methods but biological synthesis. Moreover, there has been much attention paid to producing diverse and novel nanomaterials for new industrial applications. This is the first report to predict the biosynthesis of various nanomaterials, by far the largest number of various single- and multi-elements nanomaterials. The strategies used for nanomaterial biosynthesis in this research will be useful for further diversifying the portfolio of nanomaterials that can be manufactured.” Figure: The biosynthesis of diverse nanomaterials using recombinant E. coli. This schematic diagram shows the overall conceptualization of the biosynthesis of various single and multi-element nanomaterials using recombinant E. coli under incubation with corresponding elemental precursors. The 35 elements that were tested to biosynthesize nanomaterials are shown in black circles on the periodic table.
2018.05.23
View 9132
A High-Performance and Cost Effective Hydrogen Sensor
(Research team of Professor Park, Professor Jung, and research fellow Gao Min) A KAIST research team reported a high-performance and cost effective hydrogen sensor using novel fabrication process based on the combination of polystyrene nanosphere lithography and semiconductor microfabrication processes. The research team, led by Professor Inkyu Park in the Department of Mechanical Engineering and Professor Yeon Sik Jung in the Department of Materials Science and Engineering, fabricated a nanostructured high-performance hydrogen gas sensor based on a palladium-decorated silicon nanomesh structure made using a polystyrene nanosphere self-assembly method. Their study was featured as the front cover article of journal “Small” (Publisher: Wiley-VCH) on March 8, 2018. The nanosphere lithography method utilizes the self-assembly of a nanosphere monolayer. This could be an alternative choice for achieving uniform and well-ordered nanopatterns with minimum sub-10 nanometer dimensions. The research team said that the small dimensions of the silicon enhanced the palladium-gating effect and thus dramatically improved the sensitivity. Hydrogen gas is widely considered to be one of the most promising next-generation energy resources. Also, it is a very important material for various industrial applications such as hydrogen-cooled systems, petroleum refinement, and metallurgical processes. However, hydrogen, which is highly flammable, is colorless and odorless and thus difficult to detect with human senses. Therefore, developing hydrogen gas sensors with high sensitivity, fast response, high selectivity, and good stability is of significant importance for the rising hydrogen economy. Silicon nanowire-based devices have been employed as efficient components in high-performance sensors for detecting gases and other chemical and biological components. Since the nanowires have a high surface-to-volume ratio, they respond more sensitively to the surrounding environment. The research team’s gas sensor shows dramatically improved hydrogen gas sensitivity compared with a silicon thin film sensor without nanopatterns. Furthermore, a buffered oxide etchant (BOE) treatment of the silicon nanomesh structure results in an additional performance improvement through suspension of nanomesh strutures from the substrate and surface roughening. The sensor device shows a fast hydrogen response (response time < 5 seconds) and 10 times higher selectivity to hydrogen gas among other gases. Their sensing performance is stable and shows repeatable responses in both dry and high-humidity ambient environments. Professor Park said that his approach will be very useful for the fabrication of low-cost, high-performance sensors for chemical and biological detection with applications to mobile and wearable devices in the coming era of internet of things (IoTs). (Figure 1: The front cover image of Small dated on March 8.) (Figure 2: Gas sensor responses upon the exposure to H2 at various concentrations.)
2018.05.21
View 7866
Platinum Catalyst Has Price Lowed and Durability Doubled
(Professor Cho in the Department of Materials Science and Engineering) Professor EunAe Cho in the Department of Materials Science and Engineering reported a fuel cell catalyst that shows 12 times higher performance and twice the durability than previously used platinum catalyst. Fuel cells, eco-friendly power generators, are said to be running air purifiers. A hydrogen vehicle powered by fuel cells can allegedly purify more than 98 percent of the particulate matter and ultrafine particles from the amount of air that 70 adults breathe. Despite this peculiarity, the high price of platinum, which is used as an electrode catalyst, remains a big challenge to accelerating commercialization. In addition, recently developed ‘nano-structured platinum catalysts’ have not yet commercialized due to its meager oxygen reduction reaction and durability in fuel cell. Addressing all those challenges, Professor Cho’s team reported a platinum catalyst costing 30 percent less but boasting 12 times higher performance. The research team, to this end, combined the platinum with nickel, then applied various metallic elements for making the most efficient performance. Among others, they found that the addition of gallium can modulate the oxygen intermediate binding energy, leading to enhanced catalytic activity of the oxygen reduction reaction. They made octahedron nanoparticle platinum-nickel alloy and could efficiently achieve 12-times high performance with the platinum catalyst by adding gallium to the surface of octahedron. Existing fuel cell catalysts have issues in practical fuel cell applications. However, Professor Cho’s team experimentally proved the high performance of the catalyst even in the fuel cell, and is expected to be practically applied to the existing procedure. First author JeongHoon Lim said their work demonstrates the gallium-added octahedral nanoparticles can be utilized as a highly active and durable oxygen reduction reaction catalyst in practical fuel cell applications. It will make it feasible for the mass production of the catalysts. Professor Cho also said, “Our study realized the two main goals: an affordable price and increased performance of fuel cells. We hope this will make a contribution to the market competitiveness of fuel cell electric vehicles.” This research was described in Nano Letters in April and was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP), the National Research Foundation (NRF), and the Agency for Defense Development (ADD). (Figure: HAADF STEM images with EDX analyses and line scanning profiles of (a) Ga-PtNi/C and (b) PtNi/C during the voltage-cycling tests. The composition changes of Ni, Pt, and Ga atoms in the nanoparticles were determined by EDX (inset in the EDX mapping results)).
2018.05.15
View 6150
Capillary Forces at Work for Lithium-Sulfur Batteries
Professor Do Kyung Kim from the KAIST Department of Materials Science and Engineering and his team succeeded in developing high-areal-capacity lithium sulfur batteries (Li-S batteries) by capturing polysulfide with carbon nanofibers. This research will provide new batteries to replace existing lithium rechargeable batteries, shifting the commercialization of related technologies ahead. Electrical vehicles and large-scale energy storage systems necessitate the development of batteries with high energy density and cost effectiveness, and Li-S batteries are known to be one of the promising alternatives to the predominant lithium ion batteries. With six times as much energy density, Li-S batteries theoretically thrust electric vehicle to twice the distance of lithium ion batteries. Therefore, they have been spotlighted as next-generation lithium rechargeable batteries because they can go up to 400km once charged. However, several issues make it challenging to readily commercialize Li-S batteries. The low electrical conductivity of sulfur, volumetric expansion and contraction of the battery during charge and discharge, and permanent damage of the electrode caused by the dissolution of the lithium polysulfide into the electrolyte – known as the “shuttle effect” – are three of the biggest obstacles to commercial-grade Li-S batteries. While there have been numerous attempts to curb, avoid, or alleviate these issues — such as the physical encapsulation of sulfur using various metal oxides or carbonaceous matrices — most of them entail utilizing zero-dimensional (0D) carbon materials. This encapsulation method has been somewhat effective in enhancing the electrical conductivity of sulfur while simultaneously tolerating some volumetric alterations and suppressing the shuttle effect. The downside of 0D carbon material-based encapsulation methods is their complicated synthetic processing and the limited mass loading of sulfur. With this in mind, the team set out to employ one-dimensional (1D) carbon materials instead. Unlike the 0D case, 1D carbon materials render a large surface area and a long-range conduction path for electrons and lithium ions. Being 1D also solves the undesirable high-contact resistance problem frequently encountered by 0D carbon material-based encapsulation. The key to developing the proposed material was to exploit the capillary force to decrease the energy associated with the dissolution of polysulfides. As such, carbon nanofibers (CNFs) were found to be suitable for high-areal-capacity lithium-sulfur batteries since capillary force acting between CNFs can take advantage of the high electrical conductivity with the suppressed dissolution of sulfides. The research findings show that sulfur was successfully contained in between the CNFs by wetting due to the capillary force without the need for complicated synthetic processing, as in the 0D case. The research results indicate that the sulfur contained per unit area (mg/cm2) is five times greater for the newly implemented method, which then enabled the lithium-sulfur battery to achieve an areal capacity of 7 mAh/cm2, which amounts to as much as at most seven times that of conventional lithium ion batteries. First author Jong Hyuk Yun stated that the unprecedented methods utilized in this study will help further and widen the progress of lithium batteries in general. Meanwhile, Professor Kim said, “This study brought us closer to commercial-grade high-capacity Li-S batteries, which are applicable for a wide variety of products, including electric vehicles, unmanned aerial vehicles (UAVs), and drones.” This research, led by PhD candidate Yun, was published in the 18th issue of this year’s Nano Letters. Figure 1. Electrochemical reaction leading to the containment of the sulfur within the carbon nanofiber and the corresponding specific capacity of the battery over a number of charge-discharge cycles Figure 2. SEM images of the first discharged electrode containing lithium sulfide at the junction between the nanofibers, and the first charged electrode Figure 3. carbon nanofiber effectively absorbing liquid based lithium polysulfide
2018.05.14
View 6450
New Material for Generating Energy-Efficient Spin Currents
(Professor Byong-Guk Park (left) and Professor Kab-Jin Kim) Magnetic random access memory (MRAM) is emerging as next-generation memory. It allows information to be kept even without an external power supply and its unique blend of high density and high speed operation is driving global semiconductor manufacturers to develop new versions continuously. A KAIST team, led by Professor Byong-Guk Park in the Department of Materials Science and Engineering and Professor Kab-Jin Kim in the Department of Physics, recently has developed a new material which enables the efficient generation of a spin current, the core part of operating MRAM. This new material consisting of ferromagnet-transition metal bilayers can randomly control the direction of the generated spin current unlike the existing ones. They also described a mechanism for spin-current generation at the interface between the bottom ferromagnetic layer and the non-magnetic spacer layer, which gives torques on the top magnetic layer that are consistent with the measured magnetization dependence. When applying this to spin-orbit torque magnetic memory, it shows the increased efficiency of spin torque and generation of the spin current without an external magnetic field. High-speed operation, the distinct feature of spin-orbit torque-based MRAM that carries its non-volatility, can significantly reduce the standby power better than SRAM. This new material will expect to speed up the commercialization of MRAM. The research team said that this magnetic memory will further be applied to mobile, wearable, and IoT devices. This study, conducted in collaboration with Professor Kyung-Jin Lee from Korea University and Dr. Mark Stiles from the National Institute of Standards and Technology in the US, was featured in Nature Materials in March. The research was funded by the Creative Materials Discovery Program of the Ministry of Science and ICT. (Figure: Ferromagnet-transition metal bilayers which can randomly control the direction of the generated spin current)
2018.05.11
View 7688
Escalation of Competition Leads to Conflict in Competitive Networks of F1 Drivers
(Professor Wonjae Lee at the Graduate School of Culture Technology) A new study has revealed that people with similar social status in similar age groups are more likely to clash with each other. This rivalry could likely lead to taking more risks in fair weather conditions. Competition, while is often seen as beneficial, can escalate into destructive conflict. This occurs, for instance, when athletes sabotage each other or when rival executives get caught up in a career-derailing fight. These escalations, which lead to conflict, are especially likely among similar-status competitors, who are fraught with discordant understandings of who is superior to whom. A research team of KAIST, the US Treasury, INSEAD, and the European School of Management and Technology (ESMT) examined the link between status similarity and conflict as well as the conditions under which this link holds by using panel data on Formula 1 races from 1970 through 2014. For the study, the research team analyzed a total of 506 collision cases by 355 F1 drivers over 45 years. The team found that similar-status F1 drivers are more prone to collide, especially when they are age-similar, performing well, and feeling safe. When these boundary conditions are met, structural equivalence likely triggers antagonism among interactants. This research deepens the understanding of when violent conflict emerges and when prevention efforts are called for. Professor Lee from the Graduate School of Culture Technology at KAIST said, “People are not sure about their identity when facing competitors of a similar status. People tend to confirm their own stature by beating an opponent.” The team investigated the factors that escalate competition into dangerous conflict. Recently, sociological theorizing claims that such escalations are particularly likely in pairs of structurally equivalent actors who have the same relations with the same third parties. Using the F1 data, the research team modeled the probability that two drivers would collide on a racetrack as a function of their structural equivalence in a dynamic network of competitive relationships. Professor Lee added, “We fully understand that the drivers who ranked first and second are likely to have more conflict because they meet more frequently and know each other well. We also regulated all those conditions and confirmed that our hypothesis worked right throughout the data analysis.” Professor Lee, who wrote his doctoral thesis on tennis tournaments for identifying the ideal organizational structure, said that sports tournaments would be best optimized for comprehending the nature of organizational structures. Tournaments, even those with rankings based on objective criteria, are in fact intensely social. However, most prior empirical work in this area has relied only on official information on competitors’ performance, thus failing to capture the important elements of past competitive encounters. “It is not so easy to obtain data on rivalries and conflicts inside an organization. However, in sports, the performances of athletes are all recorded and the data can be utilized as a very objective methodology for understanding social relations and their structural affects. Official positions in tournaments, although clearly informative, can also be reductionist –excluding the emotionally salient features of competitors’ histories and forcing competitors together on a scalar metric, even when the competitors themselves do not see each other as comparable. The results from sample-split models are important for social networking research, which has paid scant attention to the contextual conditions in which structural equivalence is most consequential for social action – especially hostile social actions. The study suggests that new work will benefit from examining how demographic overlap, network stability, and perceived costs of conflict “activate” a structurally equivalent relationship to the point that it is not only salient but also conducive to conflict. Professor Lee said, “Sociology mainly investigates the positive results of social success and collaboration. This study shows that any violent activities, including homicide, also have something to do with organizational and social structural equivalence.” This study was co-led by Professor Matthew Bothner from ESMT in Germany, Professor Henning Piezunk from INSEAD in France, and Dr. Richard Haynes from the US Treasury and was featured at the PNAS (Proceedings of the National Academy of Sciences of the USA) in March. (Figure: Drivers' competitive network and collisions. Nodes are drivers. Nodes enricled in black are labeled by name. Edges denote joint competition in at least one race. Red edges connecting indicate that the two drivers collided at least once. Using Fruchtermna-Reingold, nodes are generally proximte to the extendt that their average structural equivalence (over all races, from 1970 to 2014) is high.)
2018.04.24
View 5871
Animal Cyborg: Behavioral Control by 'Toy' Craving Circuit
Children love to get toys from parents for their birthday present. This craving toward items also involves object hoarding disorders and shopping addiction. However, the biological meaning of why the brain pursues objects or items has remained unknown. Part of the answer may lie with a neural circuit in the hypothalamus associated with “object craving,” says neuroscientist Daesoo Kim from the Department of Biological Sciences at KAIST. His research team found that some neurons in the hypothalamus are activated during playing with toys in mice. Thanks to optogenetics, they proved that these neurons in the hypothalamus actually governs obsessive behavior toward non-food objects in mice. “When we stimulate a neuron in the hypothalamus of mice, they anxiously chased target objects. We found evidence that the neural circuits in the medial preoptic area (MPA) modulate “object craving,” the appetite for possessing objects” said Professor Kim. Researchers also proved that the MPA circuit facilitate hunting behavior in response to crickets, a natural prey to mice, showing the role of this circuit for catching prey. Further, the MPA nerves send excitatory signals to the periaqueductal gray (PAG), located around the cerebral aqueduct, to create such behavior. The team named this circuit the ‘MPA-PAG’ circuit. The team showed that they could control mammalian behavior for the first time with this scheme of MPA-Induced Drive Assisted Steering (MIDAS), in which a mouse chase the target objects in the front of head during stimulation of the MPA-PAG circuit. MIDAS allows mice to overcome obstacles to move in a desired path using optogenetics. (Professor Daesoo Kim) Professor Kim, who teamed up with Professor Phill Seung Lee in the Department of Mechanical Engineering, explained the significance of the research, “This study provides evidence to treat brain disorders such as compulsive hoarding and kleptomania. It also contributes to the development of technology to control the behavior of animals and humans using strong innate motivation, and thus could impact neuro-economics, defense, and disaster relief.” He said the team would like to complete the neural circuit map governing behaviors of possession and hunting in the near future by exploring correlations with other neural behaviors controlling possessing and hunting activities. This research was funded by the Samsung Science and Technology Foundation and published in Nature Neuroscience in March 2018. (Figure 1: Schematics showing possessive behavior induced by the MPA neural circuit) (Figure 2: Schematics of the MIDAS system that controls mammals behavior using the desire to possess. A MIDAS mouse is following the bait object controlled wirelessly.)
2018.04.23
View 7750
Deep Learning Predicts Drug-Drug and Drug-Food Interactions
A Korean research team from KAIST developed a computational framework, DeepDDI, that accurately predicts and generates 86 types of drug-drug and drug-food interactions as outputs of human-readable sentences, which allows in-depth understanding of the drug-drug and drug-food interactions. Drug interactions, including drug-drug interactions (DDIs) and drug-food constituent interactions (DFIs), can trigger unexpected pharmacological effects, including adverse drug events (ADEs), with causal mechanisms often unknown. However, current prediction methods do not provide sufficient details beyond the chance of DDI occurrence, or require detailed drug information often unavailable for DDI prediction. To tackle this problem, Dr. Jae Yong Ryu, Assistant Professor Hyun Uk Kim and Distinguished Professor Sang Yup Lee, all from the Department of Chemical and Biomolecular Engineering at Korea Advanced Institute of Science and Technology (KAIST), developed a computational framework, named DeepDDI, that accurately predicts 86 DDI types for a given drug pair. The research results were published online in Proceedings of the National Academy of Sciences of the United States of America (PNAS) on April 16, 2018, which is entitled “Deep learning improves prediction of drug-drug and drug-food interactions.” DeepDDI takes structural information and names of two drugs in pair as inputs, and predicts relevant DDI types for the input drug pair. DeepDDI uses deep neural network to predict 86 DDI types with a mean accuracy of 92.4% using the DrugBank gold standard DDI dataset covering 192,284 DDIs contributed by 191,878 drug pairs. Very importantly, DDI types predicted by DeepDDI are generated in the form of human-readable sentences as outputs, which describe changes in pharmacological effects and/or the risk of ADEs as a result of the interaction between two drugs in pair. For example, DeepDDI output sentences describing potential interactions between oxycodone (opioid pain medication) and atazanavir (antiretroviral medication) were generated as follows: “The metabolism of Oxycodone can be decreased when combined with Atazanavir”; and “The risk or severity of adverse effects can be increased when Oxycodone is combined with Atazanavir”. By doing this, DeepDDI can provide more specific information on drug interactions beyond the occurrence chance of DDIs or ADEs typically reported to date. DeepDDI was first used to predict DDI types of 2,329,561 drug pairs from all possible combinations of 2,159 approved drugs, from which DDI types of 487,632 drug pairs were newly predicted. Also, DeepDDI can be used to suggest which drug or food to avoid during medication in order to minimize the chance of adverse drug events or optimize the drug efficacy. To this end, DeepDDI was used to suggest potential causal mechanisms for the reported ADEs of 9,284 drug pairs, and also predict alternative drug candidates for 62,707 drug pairs having negative health effects to keep only the beneficial effects. Furthermore, DeepDDI was applied to 3,288,157 drug-food constituent pairs (2,159 approved drugs and 1,523 well-characterized food constituents) to predict DFIs. The effects of 256 food constituents on pharmacological effects of interacting drugs and bioactivities of 149 food constituents were also finally predicted. All these prediction results can be useful if an individual is taking medications for a specific (chronic) disease such as hypertension or diabetes mellitus type 2. Distinguished Professor Sang Yup Lee said, “We have developed a platform technology DeepDDI that will allow precision medicine in the era of Fourth Industrial Revolution. DeepDDI can serve to provide important information on drug prescription and dietary suggestions while taking certain drugs to maximize health benefits and ultimately help maintain a healthy life in this aging society.” Figure 1. Overall scheme of Deep DDDI and prediction of food constituents that reduce the in vivo concentration of approved drugs
2018.04.18
View 9177
KAIST Develops Sodium Ion Batteries using Copper Sulfide
A KAIST research team recently developed sodium ion batteries using copper sulfide anode. This finding will contribute to advancing the commercialization of sodium ion batteries (SIBs) and reducing the production cost of any electronic products with batteries. Professor Jong Min Yuk and Emeritus Professor Jeong Yong Lee from Department of Materials Science and Engineering succeeded in developing a new anode material suitable for use in a SIB. Compared to the existing anode materials, the copper sulfide anode was measured to exhibit 1.5 times better cyclability with projected 40% reduction in cost. Batteries used in various applications including mobile phones are lithium ion batteries, mostly referred as Li-ion batteries or LIBs. Though they are popularly used until now, large-scale energy storage systems require much inexpensive and abundant materials. Hence, a SIB has attracted enormous attention for their advantage over a lithium counterpart. However, one main obstacle to commercialization of SIB is the lack of suitable anodes that exhibit high capacity and the cycling stability of the battery. Hence, the research team recognized this need for a good anode material that could offer high electrical conductivity and theoretical capacity. The material was found to be copper sulfide, preferably in nanoplates, which “prefers to make an alloy with sodium and is thus promising for high capacity and long-term cyclability.” Further analysis presented in the study reveals that copper sulfide undergoes crystallographic tuning to make a room for sodium insertion. Results indicate that the sodium ion-insertion capacity of copper sulfide is as much as 1.5 times that of lithium ions for graphite. Furthermore, a battery with this new anode material retains 90% of its original capacity for 250 charge-discharge cycles. With the natural abundance of sodium in seawater, this development may contribute to reduction in battery costs, which can be translated into up to 30% cut in the price of various consumer electronics. Professor Lee expressed his hope for “the production of next-generation, high-performance sodium ion batteries”. Professor Yuk said, “These days, people are showing a great deal of interest in products related to renewable energy due to recent micro-dust issues ongoing in Korea. This study may help Korea get a head-start on renewable energy products”. This research, led by PhD candidate Jae Yeol Park and Dr. Sung Joo Kim, was published online in Nature Communications on March 2. Figure 1. The sodiation process of copper sulfide
2018.04.17
View 5424
Producing 50x More Stable Adsorbent
A KAIST research team developed a technology to increase the stability of amine-containing adsorbents by fifty times, moving one step further toward commercializing stable adsorbents that last longer. Professor Minkee Choi from the Department of Chemical and Biomolecular Engineering and his team succeeded in developing amine-containing adsorbents that show high oxidative stability. The capture of the greenhouse gas carbon dioxide is an active ongoing research field, and some of the latest advancements point to amine-containing adsorbents as an efficient and environment-friendly way to capture carbon dioxide. However, existing amine-containing adsorbents are known to be unstable under oxidation, which chemically breaks down the adsorbent, thereby making it difficult to rely on amine-containing adsorbents for repeated and continued use. The researchers have discovered that the miniscule amount of iron and copper present in the amine accelerate the oxidative breakdown of the amine-containing adsorbent. Upon this discovery, they proposed the use of a chelator substance, which essentially suppresses the activation of the impurities. The team demonstrates that the proposed method renders the adsorbent up to 50 times slower in its deactivation rate due to oxidation, compared to conventional polyethyleneimine (PEI) / silica adsorbents. Figure 1 illustrates the superior performance of this oxidation-stable amine-containing adsorbent (shown in black squares), whose carbon dioxide-capturing capacity deteriorates by only a small amount (~8%). Meanwhile, the carbon dioxide-capturing capacity of the PEI/silica adsorbent (shown in red diamonds) degrades dramatically after being exposed to oxidative aging for 30 days. This stability under oxidation is expected to have brought amine-containing adsorbents one step closer to commercialization. As such, first author Woosung Choi describes the significance of this study as “having brought solid carbon dioxide adsorbents to commercializable standards”. In fact, Professor Choi explains that commercialization steps for his team’s carbon dioxide adsorbents are already underway. He further set forth his aim to “develop the world’s best carbon dioxide capture adsorbent”. This research, led by the PhD candidate Woosung Choi, was published online in Nature Communications on February 20. Figure 1. Carbon dioxide working capacity against oxidative aging time. Performance of the proposed method (black) degrades much more slowly (~50x) than that of existing methods. The novel adsorbent is thus shown to be more robust to oxidation.
2018.04.16
View 4947
Formation of Burning Ice in Oceanic Clay Rich Sediment Disclosed
(from left: Professor Tae-Hyuk Kwon and PhD candidate Taehyung Park) A KAIST research team has identified the formation of natural gas hydrates, so-called flammable ice, formed in oceans. Professor Tae-Hyuk Kwon from the Department of Civil & Environmental Engineering and his team found that clay minerals in oceanic clay-rich sedimentary deposits promote formation of gas hydrates and proposed the principle of gas hydrate formation in the clayey sedimentary layers. Gas hydrates are ice-like crystalline structures composed of hydrogen-bonded water molecules encapsulating gas molecules. They are also known as burning ice. Their deposits are so huge that they gain attention for alternative energy. Conventionally, it was believed that formation of gas hydrates is limited in clay sedimentary deposits; however, unexpected abundance of natural gas hydrates in oceanic clay-rich sedimentary deposits raised the issue of how they formed. The surfaces of natural clay minerals are negatively charged and, thus, unavoidably generate physicochemical interactions between clay and water. Such clay-water interactions have a critical role in the occurrence of natural gas hydrates in clay-rich sedimentary formations. However, there has been experimental difficulty in analyzing hydrate formation because of the cations contained in clay particles, which balance the clay surface charges. Therefore, clay particles inevitably release the cations when mixed with water, which complicates the interpretation of experimental results. To overcome this limitation, the team polarized water molecules with an electric field and monitored the induction times of water molecules forming gas hydrates. They found that the 10 kV/m of electric field promoted gas hydrate nucleation under certain conditions rather than slowing it down, due to the partial breakage of the hydrogen bonded water clusters and the lowered thermal energy of water molecules. Professor Kwon said, “Through this research, we gained better insight into the origin of gas hydrates occurrence in clay-rich sedimentary deposits. In the near future, we will soon be able to commercially produce methane gas from natural gas hydrate deposits.” This research, led by PhD candidate Taehyung Park, was published online in Environmental Science and Technology on February 3. (doi: 10.1021/acs.est.7b05477) Figure 1. Formation of gas hydrates with water molecules Figure 2. Enhancement and inhibition of gas hydrates
2018.04.09
View 5518
Printed Thermo-Plasmonic Heat Patterns for Neurological Disorder Treatment
(Professor Nam and Dr. Kang, right) A KAIST team presented a highly customizable neural stimulation method. The research team developed a technology that can print the heat pattern on a micron scale to enable the control of biological activities remotely. The researchers integrated a precision inkjet printing technology with bio-functional thermo-plasmonic nanoparticles to achieve a ‘selective nano-photothermal neural stimulation method.’ The research team of Professor Yoonkey Nam at the Department of Bio and Brain Engineering expects this will serve as an enabling technology for personalized precision neuromodulation therapy for patients with neurological disorders. The nano-photothermal neural stimulation method uses the thermo-plasmonic effect of metal nanoparticles to modulate the activities of neuronal networks. With the thermo-plasmonic effect, metal nanoparticles can absorb specific wavelength of illuminated light to efficiently generate localized heat. The research team discovered the inhibitory behavior of spontaneous activities of neurons upon photothermal stimulation four years ago. Since then, they have developed this technology to control hyperactive behaviors of neurons and neural circuits, which is often found in neurological disorders such as epilepsy. In order to overcome the limitation on the spatial selectivity and resolution of the previously developed nano-photothermal method, the team adopted an inkjet printing technology to micro pattern the plasmonic nanoparticles (a few tens of microns), and successfully demonstrated that the nano-photothermal stimulation can be selectively applied according to the printed patterns. The researchers applied a polyelectrolyte layer-by-layer coating method to printing substrates in a way to improve the pattern fidelity and achieve the uniform assembly of nanoparticles. The electrostatic attraction between the printed nanoparticles and the coated printing substrate also helped the stability of the attached nanoparticles. Because the polyelectrolyte coating is biocompatible, biological experiments including cell culture are possible with the technology developed in this work. Using printed gold nanorod particles in a few tens of microns resolution over a several centimeters area, the researchers showed that highly complex heat patterns can be precisely formed upon light illumination according to the printing image. Lastly, the team confirmed that the printed heat patterns can selectively and instantaneously inhibit the activities of cultured hippocampal neurons upon near-infrared light illumination. Because the printing process is applicable to thin and flexible substrates, the technology can be easily applied to implantable neurological disorder treatment devices and wearable devices. By selectively applying the heat patterns to only the desired cellular areas, customized and personalized photothermal neuromodulation therapy can be applied to patients. “The fact that any desired heat patterns can be simply ‘printed’ anywhere broadens the applicability of this technology in many engineering fields. In bioengineering, it can be applied to neural interfaces using light and heat to modulate physiological functions. As another engineering application, for example, printed heat patterns can be used as a new concept of anti-counterfeit applications,” said the principal investigator, Yoonkey Nam at KAIST. This work, led mainly by Dr. Hongki Kang, was published in ACS Nano on February 5th 2018.
2018.04.06
View 5933
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