Metal Ions versus Protons: Tracking of Charge-Carrier Insertion into a Cathode Oxide in Aqueous Rechargeable Batteries

Protons in aqueous electrolytes can perform as an additional type of charge carrier for insertion/extraction in addition to the primary carrier cations in aqueous rechargeable batteries. Despite many diverse claims regarding the effect of protons, mutually conflicting experimental results and their interpretations without direct evidence have been reported over the last decade. Systematic examinations and analyses are thus imperative to clarify the conditions of proton insertion in aqueous rechargeable batteries. Utilizing V₂O₅ as a model cathode and beaker-type cells with a sufficient amount of ZnSO₄ aqueous electrolytes in this work, it is demonstrated that protons are inserted into the cathode prior to Zn-ions in low-pH conditions (pH ≤ 3.0). In stark contrast, the influence of protons on the discharge voltage and capacity is insignificant, when either the pH becomes higher (pH ≥ 4.0) or the electrolyte volume is considerably low in coin-type cells. Similar behavior of pH-dependent proton insertion is also verified in Na–, Mg–, and Al-ion electrolytes. Providing a resolution to the controversy regarding proton insertion, the present study emphasizes that the influence of protons substantially varies depending on the pH and relative volume of electrolytes in aqueous batteries.     

On measuring network robustness for weighted networks

Knowledge and Information Systems - Network robustness measures how well network structure is strong and healthy when it is under attack, such as vertices joining and leaving. It has been widely...     

Metal microparticle – Polymer composites as printable,bio/ecoresorbable conductive inks

Biologically and environmentally resorbable electronic devices support application possibilities that cannot be addressed with conventional technologies. This paper presents highly conductive, water-soluble composites that can be printed to form contacts, interconnects, antennas, and other important features that are essential to nearly all systems of this type. An optimized material formulation involves in situ polymerization to yield a polyanhydride containing a dispersion of molybdenum microparticles at appropriate concentrations. Comparisons of essential physical and electrical properties of these materials to those of composites formed with other polymers and other metal microparticles reveal the relevant considerations. Various functional demonstrations of screen-printed test structures and devices illustrate the suitability of these conductive inks for use in water-soluble electronic devices. A key advantage of the material introduced here compared to alternatives is its ability to maintain conductance over significant periods of time while immersed in relevant aqueous solutions. Studies involving live animal models establish the biocompatibility.     

Absorption effect in the calculation of a second-order nonlinear coefficient from the data of a maker fringe experiment

The effect of light absorption by sample in the analysis of Makerfringe data for estimating a second-order nonlinear coefficient hasbeen studied experimentally. Two theories, one by Jerphagnon andKurtz that neglects the absorption effect and one by Herman and Haydenthat takes into account the absorption effect, were compared with theexperimental results. It was found that Jerphagnon and Kurtz'sformula was unable to predict correctly not only the magnitude but alsothe incident angle dependence or the sample thickness dependence of thesecond harmonic signal generated by the sample with strong absorption, whereas the theory by Herman and Hayden was able to make thosepredictions fairly well. It was also found that the error in theestimated nonlinear coefficient when one uses Jerphagnon and Kurtz'sformula could be as large as 2-4 times the true value, depending onsample thickness.     

A study of a new data association and track initiation method with normalized distance squared ordering

In an underwater environment, measurements regarding true targets and false targets (clutter) can be made. Therefore, a suitable data association method to exactly detect and track a target and an efficient track initiation method for judging tracks formed by the target should be selected in this environment. This paper attempts to propose a new data association method and track initiation method to detect and track targets more effectively. Also, the performance of the new method is tested in a series of Monte Carlo simulation runs and is compared with the existing data association and track initiation methods in a cluttered environment.     

A comparative study of two techniques for improving power‐handling capability of CMOS T/R switches

This article proposes an asymmetric topology for transmit/receive (T/R) switches and more importantly presents a comparative study of both LC‐tuned and resistive body‐floating techniques for improving the power‐handling capability of the T/R switches in the same 0.18‐μm triple‐well CMOS. It is shown from simulations and measurements that the switches adopting either technique achieve comparable performances. For instance, the switch employing the LC‐tuned body‐floating technique exhibits insertion loss of 1.5 dB, isolation of 23.5 dB, and power‐handling capability of 22.5 dBm at 5.2 GHz, whereas the switch using the resistive body‐floating technique exhibits insertion loss of 1.3 dB, isolation of 24 dB, and power‐handling capability of 22.2 dBm, respectively. Therefore, one can conclude that the asymmetric topology with the resistive body‐floating technique is more suitable for designing T/R switches for wireless local area network applications as it consumes smaller silicon area. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Batch Nearest Neighbor Search for Video Retrieval

To retrieve similar videos to a query clip from a large database, each video is often represented by a sequence of high- dimensional feature vectors. Typically, given a query video containing m feature vectors, an independent nearest neighbor (NN) search for each feature vector is often first performed. After completing all the NN searches, an overall similarity is then computed, i.e., a single content-based video retrieval usually involves m individual NN searches. Since normally nearby feature vectors in a video are similar, a large number of expensive random disk accesses are expected to repeatedly occur, which crucially affects the overall query performance. Batch nearest neighbor (BNN) search is stated as a batch operation that performs a number of individual NN searches. This paper presents a novel approach towards efficient high-dimensional BNN search called dynamic query ordering (DQO) for advanced optimizations of both I/O and CPU costs. Observing the overlapped candidates (or search space) of a pervious query may help to further reduce the candidate sets of subsequent queries, DQO aims at progressively finding a query order such that the common candidates among queries are fully utilized to maximally reduce the total number of candidates. Modelling the candidate set relationship of queries by a candidate overlapping graph (COG), DQO iteratively selects the next query to be executed based on its estimated pruning power to the rest of queries with the dynamically updated COG. Extensive experiments are conducted on real video datasets and show the significance of our BNN query processing strategy.     

Automation of palm oil mills

Automation is the function of monitoring and regulating process operations non-manually or remotely to check or maintain the required processing conditions and product quality, the use of instrumental techniques of analysis in the laboratory and the use of computers for data processing and other miscellaneous applications. Applications where automation is justifiable and the impact of changing trends in automation technology, especially the recent influx of microprocessor-based systems, are discussed briefly. Applications in the palm oil mill where automation is fairly well-developed and is being developed, as well as ideas for future applications are reviewed. An example of a practical approach to automation in palm oil mills is given using automatic control of crude oil dilution.     

Using online collaboration applications for group assignments: The interplay between design and human characteristics

In recent years, educators and students are increasingly employing online collaboration applications such as Google Docs™ and PBWorks™ for group projects and assignments. Yet, the effectiveness of these emerging technologies has not been rigorously examined. Anchoring upon and informed by the existing literature, two design characteristics – sociability and visibility, and two human characteristics – gender and age, are focused on, which are salient in online collaboration applications. A field experiment was conducted to examine the direct and moderating effects of design and human characteristics on learning outcomes. The research found that sociability improved process satisfaction and positive social environment while visibility enhanced academic performance and solution satisfaction of learners. Males had higher solution satisfaction while older learners had higher academic performance. Moderating effects were also found. Both theoretical and practical implications are drawn. In particular, a rubric for online collaboration application selection for academic performance is conceived. This study provides empirical support for online collaboration application effectiveness in education which will augur well for future adoption, use and evolution.