Synthesis of Mesostructured Conducting Polymer-Carbon Nanocomposites and Their Electrochemical Performance

A conducting polymer layer was introduced into the pore surface of mesoporous carbon via vapor infiltration of a monomer and subsequent chemical oxidative polymerization. The polypyrrole, conducting polymer has attracted considerable attention due to the high electrical conductivity and stability under ambient conditions. The mesoporous carbon-polypyrrole nanocomposite exhibited the retained porous structure, such as mesoporous carbon with a three-dimensionally connected pore system after intercalation of the polypyrrole layer. In addition, the controllable addition of pyrrole monomer can provide the mesoporous carbon-polypyrrole nanocomposites with a tunable amount of polypyrrole and texture property. The polypyrrole layer improved the electrode performance in the electrochemical double layer capacitor. This improved electrochemical performance was attributed to the high surface area, open pore system with three-dimensionally interconnected mesopores, and reversible redox behavior of the conducting polypyrrole. Furthermore, the correlation between the amount of polypyrrole and capacitance was investigated to check the effect of the polypyrrole layer on the electrochemical performance.the Brain Korea 21 program of the Korea Ministry of Education and Korea Science and Engineering Foundation through the Hyperstructured Organic Materials Research Center

A Simple Synthesis of Mesoporous Carbons with Tunable Mesopores Using a Colloidal Template-Mediated Vapor Deposition Polymerization

Mesoporous carbons with highly uniform and tunable mesopores were fabricated by one-step vapor deposition polymerization (VDP) using colloidal silica particles as templates and polyacrylonitrile (PAN) as a carbon precursor.This work was supported by the Brain Korea 21 program of the Korea Ministry of Education and Korea Science and Engineering Foundation through the Hyperstructured Organic Materials Research Center

Co-Evaluation of Pattern Matching Algorithms on IoT Devices with Embedded GPUs

Pattern matching is an important building block for many security applications, including Network Intrusion Detection Systems (NIDS). As NIDS grow in functionality and complexity, the time overhead and energy consumption of pattern matching become a significant consideration that limits the deployability of such systems, especially on resource-constrained devices.\ua0On the other hand, the emergence of new computing platforms, such as embedded devices with integrated, general-purpose Graphics Processing Units (GPUs), brings new, interesting challenges and opportunities for algorithm design in this setting: how to make use of new architectural features and how to evaluate their effect on algorithm performance. Up to now, work that focuses on pattern matching for such platforms has been limited to specific algorithms in isolation.In this work, we present a systematic and comprehensive benchmark that allows us to co-evaluate both existing and new pattern matching algorithms on heterogeneous devices equipped with embedded GPUs, suitable for medium- to high-level IoT deployments. We evaluate the algorithms on such a heterogeneous device, in close connection with the architectural features of the platform and provide insights on how these features affect the algorithms\u27 behavior. We find that, in our target embedded platform, GPU-based pattern matching algorithms have competitive performance compared to the CPU and consume half as much energy as the CPU-based variants.\ua0Based on these insights, we also propose HYBRID, a new pattern matching approach that efficiently combines techniques from existing approaches and outperforms them by 1.4x, across a range of realistic and synthetic data sets. Our benchmark details the effect of various optimizations, thus providing a path forward to make existing security mechanisms such as NIDS deployable on IoT devices

LightBox: Full-stack Protected Stateful Middlebox at Lightning Speed

Running off-site software middleboxes at third-party service providers has been a popular practice. However, routing large volumes of raw traffic, which may carry sensitive information, to a remote site for processing raises severe security concerns. Prior solutions often abstract away important factors pertinent to real-world deployment. In particular, they overlook the significance of metadata protection and stateful processing. Unprotected traffic metadata like low-level headers, size and count, can be exploited to learn supposedly encrypted application contents. Meanwhile, tracking the states of 100,000s of flows concurrently is often indispensable in production-level middleboxes deployed at real networks. We present LightBox, the first system that can drive off-site middleboxes at near-native speed with stateful processing and the most comprehensive protection to date. Built upon commodity trusted hardware, Intel SGX, LightBox is the product of our systematic investigation of how to overcome the inherent limitations of secure enclaves using domain knowledge and customization. First, we introduce an elegant virtual network interface that allows convenient access to fully protected packets at line rate without leaving the enclave, as if from the trusted source network. Second, we provide complete flow state management for efficient stateful processing, by tailoring a set of data structures and algorithms optimized for the highly constrained enclave space. Extensive evaluations demonstrate that LightBox, with all security benefits, can achieve 10Gbps packet I/O, and that with case studies on three stateful middleboxes, it can operate at near-native speed.Comment: Accepted at ACM CCS 201

Evaluation of the Reverse Mortgage Option in Korea: A Long Straddle Perspective

This study explored the option value embedded in a reverse mortgage in Korea through an empirical analysis, using the Black–Scholes option-pricing model. The value of a reverse mortgage is affected by the variation in house prices. However, older homeowners using reverse mortgages are able to choose this option due to the unique characteristics of reverse mortgages, such as non-recourse clauses or being able to redeem the loan. This paper found the following results. First, the call option value is 5.8% of the house price at the age of 60, under the assumption of a KRW three hundred million house value, while the put option value is only 2.0%. Contrary to what it is at sixty years of age, only the call option value will remain when the homeowner reaches the age of 80. Second, this article analyzed the sensitivity of the key variables of real-option analytical models, such as the change of the exercise price, the change of the risk-free rate, volatility, and maturity, on the option value of a reverse mortgage. The sensitivity results of the key variables supported economic rationales for the option pricing model

Morphology adjustable CoxN with 3D mesoporous structure and amorphous N-doped carbon for overall water splitting

© 2020 Elsevier B.V. In order to improve the efficiency of the water splitting system, many researchers have focused on controlling the nanostructure of the catalysts, which could reduce the overpotential value of the overall water splitting process. Herein, we report the characteristics of the overall water splitting of cobalt nitrides synthesized in the same way but differing only in the temperature of nitridation. Hierarchical phases (Co3N, Co3N/Co4N, and Co4N) and structures (mesoporous nanocubes, porous nanocubes, and aggregated particles) of CoxN with different thickness of amorphous N-doped carbon allowed CoxN to have different overpotential values (419 mV, 557 mV, and 606 mV at a current density of 10 mA∙cm−2), which is in contrast to known theoretical electrical properties. Our research about the comparison of hierarchical structure of CoxN offers the potential as advanced electrocatalysts for many materials that have not yet been morphologically controlled

High‐Efficiency Anion‐Exchange Membrane Water Electrolyzer Enabled by Ternary Layered Double Hydroxide Anode

Developing high-efficiency and low-cost oxygen-evolving electrodes in anion exchange membrane (AEM) water electrolysis technology is one of the major challenges. Herein, it is demonstrated that the surface corrosion of a conventional Ni foam electrode in the presence of Fe3+ and V3+ cations can transform it into an electrode with a high catalytic performance for oxygen evolution reaction (OER). The corroded electrode consists of a ternary NiFeV layered double hydroxide (LDH) nanosheet array supported on the Ni foam surface. This NiFeV LDH electrode achieves an OER current density of 100 mA cm(-2) at an overpotential of 272 mV in 1 m KOH, outperforming the IrO2 catalyst by 180 mV. Density functional theory calculations reveal that the unique structure and the presence of vanadium in NiFeV LDH play a key role in achieving improved OER activity. When coupled with a commercial Pt/C cathode catalyst, the resulting AEM water electrolyzer achieves a cell current density as high as 2.1 A cm(-2) at a voltage of only 1.8 V-cell in 1 m KOH, which is similar to the performance of the proton exchange membrane water electrolyzer obtained from the IrO2 and Pt/C catalysts pair.11Nsciescopu