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Designing novel hybrid materials provides a means of controlling electrical, magnetic, or optical properties. [1][2][3][4][5][6][7][8] There have been numerous studies on preparing nanocomposite materials. One approach is synthesizing inorganic nanoparticles within the microdomain of a well-ordered block-copolymer template. [9][10][11][12] In a second approach the self-assembled microdomain morphology of block copolymers is used to control the spatial arrangement of nanoscopic elements within the materials. [4,[13][14][15][16] The manipulation of the location of the nanoparticles in the materials can be achieved by controlling the sizes and the surface properties of the nanoparticles. Recent theoretical arguments suggest that synergistic interactions between self-organizing particles and a self-assembling matrix material may lead to hierarchically ordered structures. [17][18][19] These predictions were recently confirmed in a study of a diblock copolymer having cylindrical microdomains with added nanoparticles. In this study a co-operative coupled interaction was found that led to hierarchically ordered structures upon thermal-or solvent-annealing where self-orienting, self-assembling arrays of microdomains were found without the use of external fields.[20] However, the details of the structural evolution, and the means of manipulating the synergistic interactions, were not described, and this is key for generalizing these concepts to different systems. In a recent study, to capture the detailed structural evolution of the self-assembly process in thin films of nanoparticles/copolymer-mixtures, in situ grazing-incident small-angle X-ray scattering (GISAXS) was used. In situ GISAXS has unique advantages: the sample is intact; the structure can be probed quickly at exactly the same place at different annealing times; and, in addition, the X-ray beam passes through quite a large area of the sample, which provides average information about the structure inside the sample. Here, we report on the structural evolution in thin films of a polystyrene-block-poly(2-vinylpyridine) copolymer, denoted as PS-b-P2VP, mixed with tri-n-octylphosphine oxide (TOPO)-covered CdSe nanoparticles. Even with the strong interfacial interactions of P2VP with the substrate, the addition of the nanoparticles to the strongly microphase-separated copolymer is seen to modify interfacial interactions and cause the microdomains to orient normal to the surface. In conjunction with our previous studies, a generality of these synergistic interactions is suggested.CdSe nanoparticles functionalized with TOPO ligands were prepared using established high-temperature procedures.[23] A series of experiments with different concentrations of the nanoparticles in the polymer has been tested. The condition of the effective low concentration of nanoparticles has been chosen in order to reveal the scattering from the block-polymer matrix. Solutions containing ca. 3 wt % PS-b-P2VP (54.9 K-18.6 K, cylindrical morphology, polydispersity index (PDI) = 1.06, Polymer ...

We used the x-ray-extended range technique to measure the x-ray mass attenuation coefficients of silver in the 15-50 keV energy range with a level of uncertainty between 0.27% and 0.4% away from the K-edge. The imaginary part of the atomic form factor of silver was derived by subtracting the scattering component from the measured total mass attenuation coefficients. Discrepancies between the measured mass attenuation coefficients and alternative theoretical predictions are discussed.

The problem of probabilistic forecasting and online simulation of real-time electricity market with stochastic generation and demand is considered. By exploiting the parametric structure of the direct current optimal power flow, a new technique based on online dictionary learning (ODL) is proposed. The ODL approach incorporates real-time measurements and historical traces to produce forecasts of joint and marginal probability distributions of future locational marginal prices, power flows, and dispatch levels, conditional on the system state at the time of forecasting. Compared with standard Monte Carlo simulation techniques, the ODL approach offers several orders of magnitude improvement in computation time, making it feasible for online forecasting of market operations. Numerical simulations on large and moderate size power systems illustrate its performance and complexity features and its potential as a tool for system operators. Index Terms-Dictionary learning, electricity market, machine learning in power systems, power flow distributions, probabilistic price forecasting.

A study of the specular and off-specular (diffuse) x-ray scattering of a diblock copolymer is presented. In the ordered state the surface of the diblock copolymer is covered with islands. It is shown that the periodicity in the ordered state in the direction normal to the surface in a specular scan differs from the periodicity in the same direction observed in an off-specular scan. This result is explained by an analytical calculation of the differential cross section. The introduction of the statistical properties of the island distribution allows a complete analytical calculation of the transverse scans yielding the determination of the mean distance between the islands and the average size of an island.

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