Quantum-Confined ZnO Nanoshell Photoanodes for Mesoscopic Solar Cells

We present a photoanode for dye-sensitized solar cell (DSC) based on ZnO nanoshell deposited by atomic layer deposition at 150 degrees C on a mesoporous insulating template. An ultrathin layer of ZnO between. 3 and 6 nm, which exhibits quantum confinement effect, is found to be sufficient to transport the photogenerated electrons to the external contacts and exhibits near-unity collection efficiency. A 6 nm ZnO nanoshell on a 2.5 mu m mesoporous nanoparticle Al2O3 template yields photovoltaic power conversion efficiency (PCE) of 4.2% in liquid DSC. Perovskite absorber (CH3NH3PbI3) based solid state solar cells made with similar ZnO nanostructures lead to a high PCE of 7%.

Role of spectator ions in influencing the properties of dopant-free ZnO nanocrystals

Towards fundamental studies and potential applications, achieving precise control over the generation of defects in pure ZnO nanocrystals has been always intriguing. Herein, we explored the rote of spectator ions (Co2+ and Ni2+) in influencing the functional properties of ZnO nanocrystals. The crystalline quality, phase purity, and composition of as-prepared samples were thoroughly established by powder X-ray diffraction, electron microscopy (TEM and STEM), and by Raman and X-ray photoelectron spectroscopies (XPS). Despite the presence of Co2+ and Ni2+ ions in the reaction mixture, STEM-energy dispersive spectroscopy (EDS), XPS analysis, and inductively-coupled plasma mass spectrometry (ICP-MS) revealed that the ZnO nanocrystals formed are dopant-free. Even so, their luminescence and magnetic properties were substantially different from those of pure ZnO nanocrystals synthesized using a similar methodology. We attribute the origin of these properties to the defects associated with ZnO nanocrystals generated under different but optimized conditions.

Exploiting oriented attachment in stabilizing La3+-doped gallium oxide nano-spindles

Retaining the morphology of gallium oxide nanostructures during structural transformations or after doping with lanthanide ions is not facile. Here we report on the sonochemical synthesis of nearly monodisperse similar to 550 nm long nano-spindles of undoped and La-doped alpha-GaOOH. The transformation of as-prepared undoped and La-doped alpha-GaOOH powders into the corresponding undoped and La-doped Ga2O3 phases (alpha and beta) was achieved by carrying out controlled annealing at elevated temperatures under optimized conditions. The formation of gallium oxide nano-spindles is explained by invoking the phenomenon of oriented attachment, as amply supported by electron microscopy. Interestingly, the morphology of the gallium oxide nano-spindles remained conserved even after doping them with more than 1.4 at% of La3+ ions. Such robust structural stability could be attributed to the oriented attachment-type growth observed in the nano-spindles. The as-prepared samples and the corresponding annealed ones were thoroughly characterized by powder X-ray diffraction (PXRD), electron microscopy (SEM, TEM, and STEM-EDS) and X-ray photoelectron spectroscopy (XPS). Finally, photoluminescence from the single-crystalline undoped and La-doped beta-Ga2O3 was explored.

Discovering compressing serial episodes from event sequences

Most pattern mining methods yield a large number of frequent patterns, and isolating a small relevant subset of patterns is a challenging problem of current interest. In this paper, we address this problem in the context of discovering frequent episodes from symbolic time-series data. Motivated by the Minimum Description Length principle, we formulate the problem of selecting relevant subset of patterns as one of searching for a subset of patterns that achieves best data compression. We present algorithms for discovering small sets of relevant non-redundant episodes that achieve good data compression. The algorithms employ a novel encoding scheme and use serial episodes with inter-event constraints as the patterns. We present extensive simulation studies with both synthetic and real data, comparing our method with the existing schemes such as GoKrimp and SQS. We also demonstrate the effectiveness of these algorithms on event sequences from a composable conveyor system; this system represents a new application area where use of frequent patterns for compressing the event sequence is likely to be important for decision support and control.