Linked by strings of diphenylhexatriene (DPH) molecules, beta- and gamma-cyclodextrins (CDs) can form nanotube aggregates that contain as many as approximately 20 betaCDs (20 nanometers long) or approximately 20 to 35 gammaCDs (20 to 35 nanometers long). Nanotube formation was indicated in solution, by fluorescence anisotropy and light scattering results, and on graphite surfaces, by scanning tunneling microscopy. Tubes were not observed for the smaller alphaCDs. Molecular modeling shows that CD cavity size and the rodlike DPH structure are key factors in nanotube formation. Spectra generated by proton nuclear magnetic resonance indicate the inclusion of DPH in the interior of the CDs and formation of nanotubes in betaCDs and gammaCDs only. The photophysical properties of DPH are affected by its arrangement into a one-dimensional array within the CD nanotube, possibly because of exciton formation.

This paper addresses the fundamental theoretical development of a linear optimal noncausal control for wave energy converters (WECs) in a closed analytic form. It is well known that wave energy converter control is a noncausal control problem, i.e. the future wave information contributes to the present control action. This paper provides a reliable, efficient and simple linear optimal controller with guaranteed stability for WEC control problem. The proposed WEC linear optimal control (LOC) consists of a causal linear state feedback part and an anticausal linear feedforward part to incorporate the influence of future incoming waves. The stability of the closed-loop WEC control system with the proposed linear optimal controller is proven. The contribution of the noncausal term using wave prediction information to the optimal control and the energy output is analyzed quantitatively. The proposed linear controller can be more preferred when constraint satisfaction becomes a less important issue for mild sea states and some well-designed WECs with an ample operation range. The proposed optimal control strategy can be extended for a generic class of energy maximization problems. Numerical simulations are presented to justify the efficacy of the proposed WEC optimal control.

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Homogeneous dispersion and functionalization of pristine multiwalled carbon nanotubes (MWNTs) in various organic solvents was achieved by a simple ultrasonic process in the presence of an azide copolymer, poly(4-azidophenyl methacrylate-co-methyl acrylate)(P(APM-co-MA)). The copolymes were noncovalently attached to the surface of the MWNTs via pi-pi interactions to form MWNT-P(APM-co-MA) composites. The composites were characterized by transmission electron microscopy, thermogravimetric analysis, Raman spectra and UV-vis spectra. The solution dispersion of the MWNT-P(APM-co-MA) composites were used to prepare superhydrophobic cotton fabric by a facile dip-coating approach. MWNTs were covalently attached to the surface of the cotton fabric through the chemical reactions between the azide groups of P(APM-co-MA) with both MWNTs and cotton fibers. The reactions are based on UV-activated nitrene chemistry. Owing to the nanoscale roughness introduced by the attachment of MWNTs, the cotton fabric surface was transformed from hydrophilic to superhydrophobic with an apparent water contact angle of 154 degrees . Since MWNTs were covalently attached on the surface of the cotton fabric, the superhydrophobicity possesses high stability and chemical durability.

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SUMMARYExperimental techniques for testing dynamically substructured systems are currently receiving attention in a wide range of structural, aerospace and automotive engineering environments. Dynamic substructuring enables full-size, critical components to be physically tested within a laboratory (as physical substructures), while the remaining parts are simulated in real-time (as numerical substructures). High quality control is required to achieve synchronization of variables at the substructuring interfaces and to compensate for additional actuator system(s) dynamics, nonlinearities, uncertainties and time-varying parameters within the physical substructures. This paper presents the substructuring approach and associated controller designs for performance testing of an aseismic, base-isolation system, which is comprised of roller-pendulum isolators and controllable, nonlinear magnetorheological dampers. Roller-pendulum isolators are typically mounted between the protected structure and its foundation and have a fundamental period of oscillation far-removed from the predominant periods of any earthquake. Such semi-active damper systems can ensure safety and performance requirements, whereas the implementation of purely active systems can be problematic in this respect. A linear inverse dynamics compensation and an adaptive controller are tailored for the resulting nonlinear synchronization problem. Implementation results favourably compare the effectiveness of the adaptive substructuring method against a conventional shaking-table technique. A 1.32% error resulted compared with the shaking-table response. Ultimately, the accuracy of the substructuring method compared with the response of the shaking-table is dependent upon the fidelity of the numerical substructure.

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Snow distribution modeling is important to hydrological research of alpine catchments, for the temporal and spatial evolution of snow cover has significant influence on snowmelt runoff. However, few snow distribution models have considered the slope effect on drifting snow transport. In this work, a drifting snow parameterization scheme considering the slope effect is proposed, and a snow distribution model based on snowfall and snow drifting simulations is established for alpine terrain. The validation wind‐tunnel experiments and field observations show high accuracy of our model in snow depth evaluation. Then we have analyzed the snow deposition patterns of complex terrain in detail. The results show different deposition patterns for snowfall and drifting snow, for deposition patterns for snowfall are controlled by both terrain and wind, while deposition patterns for drifting snow are mainly dominantly controlled by terrain, and the erosion or deposition rate is sensitive to the local wind speed. This work has considerable value in improving the accuracy of snow distribution prediction in alpine area, which we believe is essential for hydrological research of alpine catchments.