We designed highly efficient porphyrin sensitizers with two phenyl groups at meso-positions of the macrocycle bearing two ortho-substituted long alkoxyl chains for dye-sensitized solar cells; the ortho-substituted devices exhibit significantly enhanced photovoltaic performances with the best porphyrin, LD14, showing J(SC) = 19.167 mA cm(-2), V(OC) = 0.736 V, FF = 0.711, and overall power conversion efficiency η = 10.17%.

Zinc porphyrins in a series bearing a phenylethynyl, naphthalenylethynyl, anthracenylethynyl, phenanthrenylethynyl or pyrenylethynyl substituent, denoted LD1, LD2, LD3a, LD3p or LD4, respectively, were prepared as photosensitizers for dye-sensitized solar cells. The overall efficiencies of the corresponding devices show a trend LD4 > LD3p > LD2 > LD3a > LD1. Significantly, LD4 features J SC /mA cm À2 ¼ 19.627, V OC /V ¼ 0.711, and FF ¼ 0.721, giving an efficiency h ¼ 10.06% of power conversion. This value is superior to that of a N719-based solar cell fabricated under similar experimental conditions. The remarkable performance of the LD4 cell is rationalized to be due to the broader and more red-shifted spectral feature that makes the IPCE spectrum to cover broadly across the entire visible region, 400-800 nm.

This paper proposes an evolutionary-group-based particle-swarm-optimization (EGPSO) algorithm for fuzzy-controller (FC) design. The EGPSO uses a group-based framework to incorporate crossover and mutation operations into particle-swarm optimization. The EGPSO dynamically forms different groups to select parents in crossover operations, particle updates, and replacements. An adaptive velocity-mutated operation (AVMO) is incorporated to improve search ability. The EGPSO is applied to design all of the free parameters in a zero-order Takagi-Sugeno-Kang (TSK)-type FC. The objective of EGPSO is to improve fuzzy-control accuracy and design efficiency. Comparisons with different population-based optimizations of fuzzy-control problems demonstrate the superiority of EGPSO performance. In particular, the EGPSO-designed FC is applied to mobile-robot navigation in unknown environments. In this application, the robot learns to follow object boundaries through an EGPSO-designed FC. A simple learning environment is created to build this behavior without an exhaustive collection of input-output training pairs in advance. A behavior supervisor is proposed to combine the boundary-following behavior and the target-seeking behavior for navigation, and the problem of dead cycles is considered. Successful mobile-robot navigation in simulation and real environments verifies the EGPSO-designed FC-navigation approach

Silicon “nanowires” can be formed by chemical vapor deposition of Si onto Si substrates on which nanometer-scale, Ti-containing islands have been grown. At the growth temperatures used, the Ti-containing islands remain solid and anchored to the substrate, while the Si nanowires grow out from the islands, which remain at their bases. The nanowire growth mechanism, therefore, differs from the usual vapor-liquid-solid process and provides a potential route for the formation of oriented Si nanostructures or semiconductor-metal-semiconductor structures compatible with Si integrated circuits.

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A simple hydrothermal method with titanium tetraisopropoxide (TTIP) as a precursor and triethanolamine (TEOA) as a chelating agent enabled growth in the presence of a base (diethylamine, DEA) of anatase titania nanocrystals (HD1-HD5) of controlled size. DEA played a key role to expedite this growth, for which a biphasic crystal growth mechanism is proposed. The produced single crystals of titania show octahedron-like morphology with sizes in a broad range of 30-400 nm; a typical, extra large, octahedral single crystal (HD5) of length 410 nm and width 260 nm was obtained after repeating a sequential hydrothermal treatment using HD3 and then HD4 as a seed crystal. The nanocrystals of size ~30 nm (HD1) and ~300 nm (HD5) served as active layer and scattering layer, respectively, to fabricate N719-sensitized solar cells. These HD devices showed greater V(OC) than devices of conventional nanoparticle (NP) type; the overall device performance of HD attained an efficiency of 10.2% power conversion at a total film thickness of 28 μm, which is superior to that of a NP-based reference device (η = 9.6%) optimized at a total film thickness of 18-20 μm. According to results obtained from transient photoelectric and charge extraction measurements, this superior performance of HD devices relative to their NP counterparts is due to the more rapid electron transport and greater TiO(2) potential.

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