KAIST

About: KAIST is a education organization based out in Daejeon, South Korea. It is known for research contribution in the topics: Thin film & Catalysis. The organization has 35562 authors who have published 77661 publications receiving 1852854 citations. The organization is also known as: Korea Advanced Institute of Science and Technology & KAIST university.

The structural basis of lipopolysaccharide recognition by the TLR4–MD-2 complex

Abstract: The lipopolysaccharide (LPS) of Gram negative bacteria is a well-known inducer of the innate immune response. Toll-like receptor (TLR) 4 and myeloid differentiation factor 2 (MD-2) form a heterodimer that recognizes a common 'pattern' in structurally diverse LPS molecules. To understand the ligand specificity and receptor activation mechanism of the TLR4-MD-2-LPS complex we determined its crystal structure. LPS binding induced the formation of an m-shaped receptor multimer composed of two copies of the TLR4-MD-2-LPS complex arranged symmetrically. LPS interacts with a large hydrophobic pocket in MD-2 and directly bridges the two components of the multimer. Five of the six lipid chains of LPS are buried deep inside the pocket and the remaining chain is exposed to the surface of MD-2, forming a hydrophobic interaction with the conserved phenylalanines of TLR4. The F126 loop of MD-2 undergoes localized structural change and supports this core hydrophobic interface by making hydrophilic interactions with TLR4. Comparison with the structures of tetra-acylated antagonists bound to MD-2 indicates that two other lipid chains in LPS displace the phosphorylated glucosamine backbone by approximately 5 A towards the solvent area. This structural shift allows phosphate groups of LPS to contribute to receptor multimerization by forming ionic interactions with a cluster of positively charged residues in TLR4 and MD-2. The TLR4-MD-2-LPS structure illustrates the remarkable versatility of the ligand recognition mechanisms employed by the TLR family, which is essential for defence against diverse microbial infection.

Efficient algorithms for mining outliers from large data sets

Abstract: In this paper, we propose a novel formulation for distance-based outliers that is based on the distance of a point from its kth nearest neighbor. We rank each point on the basis of its distance to its kth nearest neighbor and declare the top n points in this ranking to be outliers. In addition to developing relatively straightforward solutions to finding such outliers based on the classical nested-loop join and index join algorithms, we develop a highly efficient partition-based algorithm for mining outliers. This algorithm first partitions the input data set into disjoint subsets, and then prunes entire partitions as soon as it is determined that they cannot contain outliers. This results in substantial savings in computation. We present the results of an extensive experimental study on real-life and synthetic data sets. The results from a real-life NBA database highlight and reveal several expected and unexpected aspects of the database. The results from a study on synthetic data sets demonstrate that the partition-based algorithm scales well with respect to both data set size and data set dimensionality.

Deconstructing the crystal structures of metal-organic frameworks and related materials into their underlying nets.

Abstract: Deconstructing the Crystal Structures of Metal Organic Frameworks and Related Materials into Their Underlying Nets Michael O’Keeffe* and Omar M. Yaghi* Department of Chemistry and Biochemistry, Arizona State University, Tempe, Arizona 85287, United States Center for Reticular Chemistry, Center for Global Mentoring, Department of Chemistry and Biochemistry, University of California Los Angeles, 607 Charles E. Young Dr. East, Los Angeles, California 90095, United States Graduate School of EEWS, Korea Advanced Institute of Science and Technology, Daejeon, Korea

Stable single-unit-cell nanosheets of zeolite MFI as active and long-lived catalysts

Abstract: Zeolites-microporous crystalline aluminosilicates-are widely used in petrochemistry and fine-chemical synthesis because strong acid sites within their uniform micropores enable size- and shape-selective catalysis. But the very presence of the micropores, with aperture diameters below 1 nm, often goes hand-in-hand with diffusion limitations that adversely affect catalytic activity. The problem can be overcome by reducing the thickness of the zeolite crystals, which reduces diffusion path lengths and thus improves molecular diffusion. This has been realized by synthesizing zeolite nanocrystals, by exfoliating layered zeolites, and by introducing mesopores in the microporous material through templating strategies or demetallation processes. But except for the exfoliation, none of these strategies has produced 'ultrathin' zeolites with thicknesses below 5 nm. Here we show that appropriately designed bifunctional surfactants can direct the formation of zeolite structures on the mesoporous and microporous length scales simultaneously and thus yield MFI (ZSM-5, one of the most important catalysts in the petrochemical industry) zeolite nanosheets that are only 2 nm thick, which corresponds to the b-axis dimension of a single MFI unit cell. The large number of acid sites on the external surface of these zeolites renders them highly active for the catalytic conversion of large organic molecules, and the reduced crystal thickness facilitates diffusion and thereby dramatically suppresses catalyst deactivation through coke deposition during methanol-to-gasoline conversion. We expect that our synthesis approach could be applied to other zeolites to improve their performance in a range of important catalytic applications.

Highly Stretchable and Sensitive Strain Sensor Based on Silver Nanowire–Elastomer Nanocomposite

Abstract: The demand for flexible and wearable electronic devices is increasing due to their facile interaction with human body. Flexible, stretchable and wearable sensors can be easily mounted on clothing or directly attached onto the body. Especially, highly stretchable and sensitive strain sensors are needed for the human motion detection. Here, we report highly flexible, stretchable and sensitive strain sensors based on the nanocomposite of silver nanowire (AgNW) network and PDMS elastomer in the form of the sandwich structure (i.e., AgNW thin film embedded between two layers of PDMS). The AgNW network-elastomer nanocomposite based strain sensors show strong piezoresistivity with tunable gauge factors in the ranges of 2 to 14 and a high stretchability up to 70%. We demonstrate the applicability of our high performance strain sensors by fabricating a glove integrated with five strain sensors for the motion detection of fingers and control of an avatar in the virtual environment.