3D hierarchical rutile TiO2 and metal-free organic sensitizer producing dye-sensitized solar cells 8.6% conversion efficiency

Three-dimensional (3D) hierarchical nanoscale architectures comprised of building blocks, with specifically engineered morphologies, are expected to play important roles in the fabrication of 'next generation' microelectronic and optoelectronic devices due to their high surface-to-volume ratio as well as opto-electronic properties. Herein, a series of well-defined 3D hierarchical rutile TiO2 architectures (HRT) were successfully prepared using a facile hydrothermal method without any surfactant or template, simply by changing the concentration of hydrochloric acid used in the synthesis. The production of these materials provides, to the best of our knowledge, the first identified example of a ledgewise growth mechanism in a rutile TiO2 structure. Also for the first time, a Dye-sensitized Solar Cell (DSC) combining a HRT is reported in conjunction with a high-extinction-coefficient metal-free organic sensitizer (D149), achieving a conversion efficiency of 5.5%, which is superior to ones employing P25 (4.5%), comparable to state-of-the-art commercial transparent titania anatase paste (5.8%). Further to this, an overall conversion efficiency 8.6% was achieved when HRT was used as the light scattering layer, a considerable improvement over the commercial transparent/reflector titania anatase paste (7.6%), a significantly smaller gap in performance than has been seen previously.

Robust superhydrophobicity of hierarchical ZnO hollow microspheres fabricated by two-step self-assembly

Superhydrophobic and superhydrophilic surfaces have been extensively investigated due to their importance for industrial applications. It has been reported, however, that superhydrophobic surfaces are very sensitive to heat, ultraviolet (UV) light, and electric potential, which interfere with their long-term durability. In this study, we introduce a novel approach to achieve robust superhydrophobic thin films by designing architecture-defined complex nanostructures. A family of ZnO hollow microspheres with controlled constituent architectures in the morphologies of 1D nanowire networks, 2D nanosheet stacks, and 3D mesoporous nanoball blocks, respectively, was synthesized via a two-step self-assembly approach, where the oligomers or the constituent nanostructures with specially designed structures are first formed from surfactant templates, and then further assembled into complex morphologies by the addition of a second co-surfactant. The thin films composed of two-step synthesized ZnO hollow microspheres with different architectures presented superhydrophobicities with contact angles of 150°-155°, superior to the contact angle of 103° for one-step synthesized ZnO hollow microspheres with smooth and solid surfaces. Moreover, the robust superhydrophobicity was further improved by perfluorinated silane surface modification. The perfluorinated silane treated ZnO hollow microsphere thin films maintained excellent hydrophobicity even after 75 h of UV irradiation. The realization of environmentally durable superhydrophobic surfaces provides a promising solution for their long-term service under UV or strong solar light irradiations.

System-level analysis of network interfaces for hierarchical MPSoCs

Network Interfaces (NIs) are used in Multiprocessor System-on-Chips (MPSoCs) to connect CPUs to a packet switched Network-on-Chip. In this work we introduce a new NI architecture for our hierarchical CoreVA-MPSoC. The CoreVA-MPSoC targets streaming applications in embedded systems. The main contribution of this paper is a system-level analysis of different NI configurations, considering both software and hardware costs for NoC communication. Different configurations of the NI are compared using a benchmark suite of 10 streaming applications. The best performing NI configuration shows an average speedup of 20 for a CoreVA-MPSoC with 32 CPUs compared to a single CPU. Furthermore, we present physical implementation results using a 28 nm FD-SOI standard cell technology. A hierarchical MPSoC with 8 CPU clusters and 4 CPUs in each cluster running at 800MHz requires an area of 4.56mm2.

Performance estimation of streaming applications for hierarchical MPSoCs

Parallel programming and effective partitioning of applications for embedded many-core architectures requires optimization algorithms. However, these algorithms have to quickly evaluate thousands of different partitions. We present a fast performance estimator embedded in a parallelizing compiler for streaming applications. The estimator combines a single execution-based simulation and an analytic approach. Experimental results demonstrate that the estimator has a mean error of 2.6% and computes its estimation 2848 times faster compared to a cycle accurate simulator.

RACK: RApid Clustering using K-means algorithm

The k-means algorithm is an extremely popular technique for clustering data. One of the major limitations of the k-means is that the time to cluster a given dataset D is linear in the number of clusters, k. In this paper, we employ height balanced trees to address this issue. Specifically, we make two major contributions, (a) we propose an algorithm, RACK (acronym for RApid Clustering using k-means), which takes time favorably comparable with the fastest known existing techniques, and (b) we prove an expected bound on the quality of clustering achieved using RACK. Our experimental results on large datasets strongly suggest that RACK is competitive with the k-means algorithm in terms of quality of clustering, while taking significantly less time.

Intent Based Clustering of Search Engine Query Log

The keyword based search technique suffers from the problem of synonymic and polysemic queries. Current approaches address only theproblem of synonymic queries in which different queries might have the same information requirement. But the problem of polysemic queries,i.e., same query having different intentions, still remains unaddressed. In this paper, we propose the notion of intent clusters, the members of which will have the same intention. We develop a clustering algorithm that uses the user session information in query logs in addition to query URL entries to identify cluster of queries having the same intention. The proposed approach has been studied through case examples from the actual log data from AOL, and the clustering algorithm is shown to be successful in discerning the user intentions.

Clustering kinetics in aluminium-silver alloys

Resistometric studies of isochronal and isothermal annealing of an Al-0.64 at.% Ag alloy have given a value of 0.13 ± 0.02 eV for the silver-vacancy binding energy and 0.55 ± 0.03 eV for the migration energy of solute atoms.

Clustering phenomena in Al-4.4 at. % Zn alloy with 0.03 and 0.08 at. % Ag additions

The influence of 0.03 and 0.08 at. % Ag additions on the clustering of Zn atoms in an Al-4.4 at. % Zn alloy has been studied by resistometry. The effect of quenching and ageing temperatures shows that the ageing-ratio method of calculating the vacancy-solute atom binding energy is not applicable to these alloys. Zone-formation in Al-Zn is unaffected by Ag additions, but the zone-reversion process seems to be influenced. Apparent vacancy-formation energies in the binary and ternary alloys have been used to evaluate the v-Ag atom binding energy as 0.21 eV. It is proposed that, Ag and Zn being similar in size, the relative vacancy binding results from valency effects, and that in Al-Zn-Ag alloys clusters of Zn and Ag may form simultaneously, unaffected by the presence of each other. © 1970 Chapman and Hall Ltd.

Clustering and solute-vacancy binding energies in Al-4.4% Zn alloy with 0.01% ternary additions

Isochronal and isothermal ageing experiments have been carried out to determine the influence of 0.01 at. % addition of a second solute on the clustering rate in the quenched Al-4,4 a/o Zn alloy. The influence of quenching and ageing temperatures has been interpreted to obtain the apparent vacancy formation and vacancy migration energies in the various ternary alloys. Using a vacancy-aided clustering model the following values of binding free energy have been evaluated: Ce-0.18; Dy-0.24; Fe-0.18; Li-0.25; Mn-0.27; Nb-0.18; Pt-0.23; Sb-0.21; Si-0.30; Y-0.25; and Yb-0.23 (± 0.02 eV). These binding energy values refer to that between a solute atom and a single vacancy. The values of vacancy migration energy (c. 0.4 eV) and the experimental activation energy for solute diffusion (c. 1.1 eV) are unaffected by the presence of the ternary atoms in the Al-Zn alloy.

Resistometric studies of solute-vacancy interactions and clustering kinetics in an FCC matrix [AlZn Alloy with Ag, Ce, Dy, Li, Nb, Pt, Sb, Y, or Yb]

Al-4.4 a/oZn and Al-4.4 a/oZn with Ag, Ce, Dy, Li, Nb, Pt, Y, or Yb, alloys have been investigated by resistometry with a view to study the solute-vacancy interactions and clustering kinetics in these alloys. Solute-vacancy binding energies have been evaluated for all these elements by making use of appropriate methods of evaluation. Ag and Dy additions yield some interesting results and these have been discussed in the thesis. Solute-vacancy binding energy values obtained here have been compared with other available values and discussed. A study of the type of interaction between vacancies and solute atoms indicates that the valency effect is more predominant than the elastic effect.

Clustering in Concept Association Networks

We view association of concepts as a complex network and present a heuristic for clustering concepts by taking into account the underlying network structure of their associations. Clusters generated from our approach are qualitatively better than clusters generated from the conventional spectral clustering mechanism used for graph partitioning.

Test of the Clustering Hypothesis in the Helsinki Exchanges

This paper investigates the clustering pattern in the Finnish stock market. Using trading volume and time as factors capturing the clustering pattern in the market, the Keim and Madhavan (1996) and the Engle and Russell (1998) model provide the framework for the analysis. The descriptive and the parametric analysis provide evidences that an important determinant of the famous U-shape pattern in the market is the rate of information arrivals as measured by large trading volumes and durations at the market open and close. Precisely, 1) the larger the trading volume, the greater the impact on prices both in the short and the long run, thus prices will differ across quantities. 2) Large trading volume is a non-linear function of price changes in the long run. 3) Arrival times are positively autocorrelated, indicating a clustering pattern and 4) Information arrivals as approximated by durations are negatively related to trading flow.