Electrocatalytically active platinum (Pt) nanoparticles on a carbon nanotube (CNT) with enhanced nucleation and stability have been demonstrated through introduction of electron-conducting polyaniline (PANI) to bridge the Pt nanoparticles and CNT walls with the presence of platinum-nitride (Pt-N) bonding and π-π bonding. The Pt colloids were prepared through ethanol reduction under the protection of aniline, the CNT was dispersed well with the existence of aniline in the solution, and aniline was polymerized in the presence of a protonic acid (HCl) and an oxidant (NH(4)S(2)O(8)). The synthesized PANI is found to wrap around the CNT as a result of π-π bonding, and highly dispersed Pt nanoparticles are loaded onto the CNT with narrowly distributed particle sizes ranging from 2.0 to 4.0 nm due to the polymer stabilization and existence of Pt-N bonding. The Pt-PANI/CNT catalysts are electroactive and exhibit excellent electrochemical stability and therefore promise potential applications in proton exchange membrane fuel cells.

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Population is a key indicator of socioeconomic development, urban planning and environmental protection, particularly for developing countries like China. But, census data for any given area are neither always available nor adequately reflect the internal differences of population. The authors tried to overcome this problem by spatializing the population across China through utilizing integer night-time imagery (Defense Meteorological Satellite Program/Operational Linescan System, DMSP/OLS) and land-use data. In creating the population linear regression model, night-time light intensity and lit areas, under different types of land use, were employed as predictor variables, and census data as dependent variables. To improve model performance, eight zones were created using night-time imagery clustering and shortest path algorithm. The population model is observed to have a coefficient of determination (R 2 ) ranging from 0.80 to 0.95 in the research area, which remained the same in different years. A comparison of the results of this study with those of other researchers shows that the spatialized population density map, prepared on the basis of night-time imagery, reflects the population distribution character more explicitly and in greater detail.