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No full textDepartment of Biological Sciencesclos
Cooperative H-bonding on the Topology Controlled Polyether toward Advanced Adhesive Materials
No full textDepartment of ChemistryAs a crucial molecular interaction in nature, hydrogen bonding (H-bonding) is important to express their own characteristic and unique phenomena such as RNA, DNA, and protein. Inspired by this remarkable feature in H-bonding, a lot of researches have been done to design and synthesize novel functional materials and polymers including self-assembly supra-molecules, polymer blends and nanocomposites displaying interesting thermal and mechanical properties. Herein, we successfully introduced the carbonyl benzoic acid group that can induce the cooperative H-bonding in the topology controlled PGs (i.e. linear, hyper-branched, and branched cyclic types) to synthesis poly(glycidoxy carbonyl benzoic acid)s (PGCBAs)) via the simple post-polymerization process while showing high conversion in a short time. In the synthesis process, we here present a new strategy for enhancing the conversion from post-polymerization using DBU via nucleophilic catalysis mechanism. The obtained topology controlled PGCBAs contain H-bonding donor and acceptor in a single repeating unit that can induce the intramolecular and intermolecular H-bonding and they were characterized by NMR, GPC and show the interesting phenomena in the bulk and the solution state depending on the polymer topologies. The high synergistic interaction from the intermolecular and intramolecular H-bonding in the topology-controlled PGCBAs show interesting pH sensitive properties in the solution phase and stronger adhesion strength in the bulk phase compared to the conventional adhesives by the secondary interaction. We prove that it is possible to improve the adhesive performance by adjusting and controlling the interaction of H-bonding between polymer chains by simply mixing each of functional groups and topologies. Therefore, why it is important to control the topologies of a polymer, and different properties can be exhibited with the same chemical structure. Finally, as a result of the cell viability assay, we expect that PGCBAs can be used in biological fields owing to its excellent biocompatibility.clos
Crown Ether-based Hyperbranced Polymers Composed of N-Heterocyclic Linkages for Proton Conductivity
No full textSchool of Energy and Chemical Engineering (Energy Engineering)clos
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Get PDFDepartment of DesignAlthough archiving daily moods in a diary is a common behavior, reflection is difficult because of the pressure brought about by continuous self-tracking of personal moods. In this paper, I developed Lumino, a standalone device that enables users to log their daily moods with colored lights and switch mode to show the log by physically sliding a circular lighting plate. The results of three-week in-field study with six participants revealed that Lumino helped users encounter emotional archives as it separated reflective experiences from daily life activities. Moreover, Lumino helped prevent deep reflection on negative emotions and maintained privacy through abstract color expression. I also found user???s various trials to control emotion reflections in their own usage patterns. I propose considerations for augmenting daily mood recording experiences combined with existing diary practices and further implications for designing how to support positively the negative reflections in everyday spaces.ope
FunRank : Finding 1-day Vulnerabilities with Data-flow Analysis
No full textDepartment of Computer Science and Engineeringclos
?????? ???????????? ???????????? ????????? AumoML??? ?????? ?????? ????????????
No full textDepartment of Industrial EngineeringIn recent years, AutoML has emerged as a promising technique for reducing computational and time cost by automating the development of machine learning models. Existing AutoML tools cannot be applied directly to process predictive monitoring (PPM), because they do not support several configuration param- eters that are PPM-specific, such as trace bucketing or encoding. In other words, they are only specialized in finding the best configuration of machine learning model hyperparameters. In this thesis, we present a simple yet extensible framework for AutoML in PPM. The framework uses genetic algorithms to explore a configuration space containing both PPM-specific parameters and the traditional machine learning model hyperparameters. We design four different types of experiments to verify the effectiveness of the proposed approach, comparing its performance in respect of random search of the configuration space, using two pub- licly available event logs. The results demonstrate that the proposed approach outperforms consistently the random search.ope
Improving the Performance of Big Data Analytics Platforms by Task and I/O Granularity Adjustment
Get PDFDepartment of Computer Science and EngineeringWith the massive increase in the amount of semi-structured and unstructured web data, big data analytics platforms have emerged and started to evolve rapidly. Apache Hadoop has been developed for batch processing on a large dataset, and systems for interactive and general purpose applications have been developed alongside NoSQL databases. Numerous efforts have been made to improve the performance of Hadoop and NoSQL databases, including utilizing a new device called NVMM for NoSQL databases. Nonetheless, their performance is still far from satisfactory due to inadequate granularity for tasks and I/O. In this dissertation, we present novel techniques to improve the performance of Apache Hadoop and NVMM-based LSM-tree by adjusting task and I/O granularity.
First, we analyze YARN container overhead and present dynamic input split size adjustment scheme, which can logically combine multiple HDFS blocks and increase the input size of each container, thereby enabling a single map wave and reducing the number of containers and their initialization overhead. Experimental results shows that we can avoid recurring container overhead by selecting the right size for input splits and reducing the number of containers. Second, we present a novel HDFS block coalescing scheme that mitigates the YARN con tainer overhead. Our assorted block coalescing scheme combines multiple HDFS blocks and creates large input splits of various sizes, reducing the number of containers and their initializa tion overhead. Our experimental study shows the block coalescing scheme significantly reduces the container overhead while it achieves good load balancing and job scheduling fairness without impairing the degree of overlap between map phase and reduce phase.
Third, we discuss design choice of using NVMM for indexing structure in NoSQL databases and present ZipperDB, a key-value store that redesigns LSM-tree for byte-addressable persistent memory. To benefit from the byte-addressability of persistent memory, ZipperDB employs byte addressable persistent SkipLists and performs Zipper Compaction, a novel in-place compaction algorithm that merges two adjacent persistent SkipLists without compromising the failure atomicity. The byte-addressable compaction helps mitigate the write amplification problem, which is known to be the root cause of the write stall problem in LSM-tree.
Finally, we present ListDB, a write-optimized key-value store for NVMM to overcome the gap between DRAM and NVMM write latencies and thereby, resolve the write stall problem. ListDB consists of three novel techniques: (i) byte-addressable Index-Unified Logging, which incrementally converts write-ahead logs into SkipLists, (ii) Braided SkipList, a simple NUMA aware SkipList that effectively reduces the NUMA effects of NVMM, and (iii) NUMA-aware Zipper Compaction. Using the three techniques, ListDB makes background flush and com paction fast enough to resolve the infamous write stall problem and shows 1.6x and 25x higher write throughputs than PACTree and Intel Pmem-RocksDB, respectively.ope
Magnitude- and order-controlling of frequency modulation with nonlinear acoustic metamaterials.
Get PDFDepartment of Mechanical EngineeringThis thesis aims to control the magnitude and order of frequency modulation with nonlinear acoustic metamaterials. Frequency modulation is a nonlinear phenomenon that changes the frequency of a wave. Since frequency modulation can easily and actively provide waves with the desired frequency, it has been widely used. However, the frequency modulation has a technical issue that the magnitude is small and the order cannot be changed because the nonlinearity of conventional medium is generally small and constant. To overcome this problem, we investigate the underlying physics of frequency modulation and propose metamaterials that can control the magnitude and order of frequency modulation. Based on the underlying physics, the magnitude and order of the frequency modulation can be controlled by effective material properties and nonlinear parameters, respectively. Therefore, the metamaterial for magnitude-controlling of frequency modulation is designed based on the concept of coiling-up space, which can control effective material properties by the degree of coiling. On the other hand, the metamaterial for order-controlling of frequency modulation is designed based on the chevron beam, which can control nonlinear parameters by the initial angle. The performance of metamaterials for magnitude- and order-controlling of the frequency modulation are numerically validated.ope
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No full textDepartment of Materials Science and EngineeringExfoliated flakes of two-dimensional (2D) materials have achieved considerable step forward for industrial uses, including electronic devices, catalysts, and energy transformation and reservoir, due to their distinct qualities at atomic-level thicknesses. 2D layered solids possess a high surface-to-volume ratio and physical and chemical versatilities for operation as high-performance conducting materials in electrochemical energy systems, which make them distinctive from their bulk counterparts. Graphene and its analogueshave shown promise as the conducting materialshowever, their low structural stability and restricted inter-layer space severely limit their capacitance and rate performance. In addition, to achieve excellent cycling life and energy density, affordable nanomaterial-based electrode providing reversible redox reactions and mechanical stiffness should be developed. As materials for electrochemically operational conductors, MXenes, a category of 2D transition metal carbides, carbonitrides, and nitrides, have received substantial research interest. The 2D layered claylike structure of MXenes possessing an uncommon blend of ceramic and metallic qualities allows fast redox activity by fertile surface terminations while maintaining high conductivity. Furthermore, MXenes have significantly greater inter-layer spacing than carbon-based conductors, which facilitates rapid ion diffusion and volume expansion. Emphasis is given to processing routes for building conducting connects and mechanical scaffolds that provide easy access to electrolyte ions (associated with charge transfer) and increased capacities at high power rates for numerous cycles. For the realistic operation of MXenes for durable electrochemical catalysts and energy storage, preparation and stabilizing strategies on a large scale are also essential.
In this thesis, the conditions for synthesis and exfoliation processes were optimized to address the intricate quality control of 2D MXene products from the parent MAX phases, which is the most critical issue for the final attainments of devices or membranes. High-quality interfaces and well-crystalline nature of the as-exfoliated MXene flakes were confirmed by development of realistic and scalable multifunctional coating processes. At first, we demonstrate that a pelletization approach could produce a chemically ideal Ti3AlC2 MAX phase with excellent yields and manufacturability. (Chapter 2). The Ti3AlC2 was capable of being exfoliated into 1~2-layers-thick 2D Ti3C2Tx MXenes, and their adaptability was validated by the creation of a workable MXene ink that demonstrated coating-thickness uniformity and outstanding electrical performances as those of a film generated by vacuum filtering.
To suggest a scalable assembly technique for functional multiscale architecture, we report the fabrication of strong and conductingfilms using 2D MXenes as building blocks with guest species (Chapter 3). Ultrathin and robust B4C composite films for neutron shielding were fabricated without heating or casting, by mixing Ti3C2Tx MXene flakes. The evaluation of the layered structure of MXene flakes with different surface properties, contents, and sizes of the B4C filler enabled the optimization of the matrix capacity, resulting in the tunable neutron-shielding ability. The hybrid coatings exhibited excellent protection efficiency with mechanical flexibility that was promising for wearability.
In Chapter 4, a solution-processable production of patterned Ti3C2Tx MXene mesh via scalable blade coating was conducted to fabricate transparent devices with well-aligned assembly and excellent optoelectronic properties. On the other hand, a patterned 2D MXene electrode having a thickness less than 20 nm has been obtained by controlling the reactive ion etching conditions. Both macroscale MXene mesh and microscale 2D MXene conductors exhibited high electrical conductivity due to the percolation connect based on Ti3C2Tx MXene flakes and could be transferred, forming integration with other electronic materials (e.g., metals and channel materials) and soft polymers.
The final section reported the development of MXene adsorbent for precious metals with enhanced dispersibility to tackle the restacking problem of the delaminated flakes and severe oxidation issues in aqueous solvents (Chapter 5). In-plane crystallite dimensions and thickness of the dispersed 2D flakes of Ti3C2Tx MXene were controlled by a ball-milling process of the powder to increase the operational sites for adsorption and access to aqueous electrolytes. Based on the dispersibility, high surface area, and well preserved electrochemically operational sites, the developed MXene adsorbent exhibited excellent adsorption efficiency for Au and Ag througha chemisorption mechanism, which was described by empirical isotherms and dynamics.ope
Low-temperature crystallization of LaFeO3 perovskite with inherent catalytically surface for the enhanced oxygen evolution reaction
No full textThis study reports a facile and economic method for LaFeO3 perovskite crystallization process at low temperature range from 300 ??C to 500 ??C and an outstanding oxygen evolution reaction (OER) catalyst based on inherent catalytically surface. As a key material for low temperature synthesis, cyanogel-peroxo-complex as a metastable molecular precursor was synthesized via ligand exchange using potassium cyanide solution to provide superoxo (O2???) ligand to Fe-CN-La gel structure, leading to a high degree of crystallinity with ideal ABO3 stoichiometry at low temperatures (400 ??? 500 ??C). Electrocatalysts based on LaFeO3 nanoparticles were fabricated, showing an outstanding OER performance with low overpotential of ??? 438 mV at 100 mA/cm2 and small Tafel slope of 61 mV??dec???1 under alkaline conditions, better than commercialized available IrOx/C catalysts. Its OER performance is attributed to the inherent oxygen-deficient layer at the surface created at low temperature (300 ??C). Long-term stability test shows no significant change (< 1%) in the potential during 50 h, indicating a high stability of such catalysts