Preparation of a CO-tolerant PtRuxSny/C electrocatalyst with an optimal Ru/Sn ratio by selective Sn-deposition on the surfaces of Pt and Ru

A CO-tolerant PtRu_xSn_y/C electrocatalyst, with an optimal x/y ratio of 0.8/0.2, was prepared by selectively depositing Sn on the metallic surface of PtRu_0.8/C for use as the anode in a polymer electrolyte membrane fuel cell. The CO tolerance of the catalyst was greater when Sn was added by chemical vapor deposition (CVD) than by a conventional precipitation method because most of the Sn added by CVD was located in the vicinity of Pt and Ru surfaces, on which CO molecules were strongly adsorbed. Accordingly, the bi-functional mechanism of CO oxidation, which involved the migration of oxygenated species from the Sn to the adsorbed CO, was expected to be promoted to greater extents in the catalysts prepared by Sn-CVD than those prepared by Sn-precipitation. On the other hand, the ligand-effect mechanism of CO oxidation, which was facilitated by the Pt-Ru alloy formation, was not much affected by the added Sn because the Pt-Ru alloy remained unchanged, particularly when y ≤ 0.2. Among PtRu_xSn_y/C catalysts prepared by Sn-CVD, one prepared by partially substituting Sn for Ru in the PtRu_1.0/C catalyst, e.g., PtRu_0.8Sn_0.2/C, showed higher CO tolerance than one prepared by simply adding Sn to the PtRu_1.0/C catalyst, e.g., PtRu_1.0Sn_0.2/C, which demonstrated the importance of an optimum x/y ratio in the design of the ternary PtRu_xSn_y/C catalysts.     

Fast and gate-count efficient arithmetic logic unit

A CMOS arithmetic logic unit is presented with a minimum number of transistors and high speed arithmetic operations. Multiple carry chain adders and a novel 1 bit adder, are used in a carry select adder. The carry chain adder has a high degree of shared gates with a low propagation delay     

Bemerkungen zum Gebrauch der Einheiten

Ohne Zusammenfassung     

Periodicity in software vulnerability discovery,patching and exploitation

Periodicity in key processes related to software vulnerabilities need to be taken into account for assessing security at a given time. Here, we examine the actual multi-year field datasets for some of the most used software systems (operating systems and Web-related software) for potential annual variations in vulnerability discovery processes. We also examine weekly periodicity in the patching and exploitation of the vulnerabilities. Accurate projections of the vulnerability discovery process are required to optimally allocate the effort needed to develop patches for handling discovered vulnerabilities. A time series analysis that combines the periodic pattern and longer-term trends allows the developers to predict future needs more accurately. We analyze eighteen datasets of software systems for annual seasonality in their vulnerability discovery processes. This analysis shows that there are indeed repetitive annual patterns. Next, some of the datasets from a large number of major organizations that record the result of daily scans are examined for potential weekly periodicity and its statistical significance. The results show a 7-day periodicity in the presence of unpatched vulnerabilities, as well as in the exploitation pattern. The seasonal index approach is used to examine the statistical significance of the observed periodicity. The autocorrelation function is used to identify the exact periodicity. The results show that periodicity needs to be considered for optimal resource allocations and for evaluation of security risks.     

Si‐core/SiGe‐shell channel nanowire FET for sub‐10‐nm logic technology in the THz regime

The p‐type nanowire field‐effect transistor (FET) with a SiGe shell channel on a Si core is optimally designed and characterized using in‐depth technology computer‐aided design (TCAD) with quantum models for sub‐10‐nm advanced logic technology. SiGe is adopted as the material for the ultrathin shell channel owing to its two primary merits of high hole mobility and strong Si compatibility. The SiGe shell can effectively confine the hole because of the large valence‐band offset (VBO) between the Si core and the SiGe channel arranged in the radial direction. The proposed device is optimized in terms of the Ge shell channel thickness, Ge fraction in the SiGe channel, and the channel length (L_g) by examining a set of primary DC and AC parameters. The cutoff frequency (f_T) and maximum oscillation frequency (f_max) of the proposed device were determined to be 440.0 and 753.9 GHz when L_g is 5 nm, respectively, with an intrinsic delay time (τ) of 3.14 ps. The proposed SiGe‐shell channel p‐type nanowire FET has demonstrated a strong potential for low‐power and high‐speed applications in 10‐nm‐and‐beyond complementary metal‐oxide‐semiconductor (CMOS) technology.     

Engineering the Charge Transport of Ag Nanocrystals for Highly Accurate,Wearable Temperature Sensors through All‐Solution Processes

All‐nanocrystal (NC)‐based and all‐solution‐processed wearable resistance temperature detectors (RTDs) are introduced. The charge transport mechanisms of Ag NC thin films are engineered through various ligand treatments to design high performance RTDs. Highly conductive Ag NC thin films exhibiting metallic transport behavior with high positive temperature coefficients of resistance (TCRs) are achieved through tetrabutylammonium bromide treatment. Ag NC thin films showing hopping transport with high negative TCRs are created through organic ligand treatment. All‐solution‐based, one‐step photolithography techniques that integrate two distinct opposite‐sign TCR Ag NC thin films into an ultrathin single device are developed to decouple the mechanical effects such as human motion. The unconventional materials design and strategy enables highly accurate, sensitive, wearable and motion‐free RTDs, demonstrated by experiments on moving or curved objects such as human skin, and simulation results based on charge transport analysis. This strategy provides a low cost and simple method to design wearable multifunctional sensors with high sensitivity which could be utilized in various fields such as biointegrated sensors or electronic skin.     

Modeling Skewness in Vulnerability Discovery

A vulnerability discovery model attempts to model the rate at which the vulnerabilities are discovered in a software product. Recent studies have shown that the S‐shaped Alhazmi–Malaiya Logistic (AML) vulnerability discovery model often fits better than other models and demonstrates superior prediction capabilities for several major software systems. However, the AML model is based on the logistic distribution, which assumes a symmetrical discovery process with a peak in the center. Hence, it can be expected that when the discovery process does not follow a symmetrical pattern, an asymmetrical distribution based discovery model might perform better. Here, the relationship between performance of S‐shaped vulnerability discovery models and the skewness in target vulnerability datasets is examined. To study the possible dependence on the skew, alternative S‐shaped models based on the Weibull, Beta, Gamma and Normal distributions are introduced and evaluated. The models are fitted to data from eight major software systems. The applicability of the models is examined using two separate approaches: goodness of fit test to see how well the models track the data, and prediction capability using average error and average bias measures. It is observed that an excellent goodness of fit does not necessarily result in a superior prediction capability. The results show that when the prediction capability is considered, all the right skewed datasets are represented better with the Gamma distribution‐based model. The symmetrical models tend to predict better for left skewed datasets; the AML model is found to be the best among them. Copyright © 2013 John Wiley & Sons, Ltd.     

Simultaneous determination of pesticide residues in fruits and vegetables by GC/MS (SCAN mode) and HPLC

A method was developed for simultaneous determination of pesticide residues in fruits and vegetables. Residues were extracted from samples with acetonitrile, followed by a salting-out step and a partitioning step with n-hexane at the same time. Co-extractives were removed with ENVI-Carb/LC-NH2 mini-column cleanup. Analysis was performed by GC/MS (SCAN mode) and HPLC. Of the 139 pesticides spiked at 0.1 or 0.5 microgram/g into 6 fruits and vegetables (spinach, tomato, apple, radish, cabbage and carrot), recoveries of 117 pesticides were between 70 and 120%. This method is appropriate for determining these pesticides and for screening several other pesticides for which the recoveries were < or = 70% or > or = 120% (imazalil, etc.). The limits of detection for most pesticides in this method were equal to or lower than those of the bulletin method in Japan.