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    Solar spectral conversion for improving the photosynthetic activity in algae reactors
    (London : Nature Publishing Group, 2013) Wondraczek, L.; Batentschuk, M.; Schmidt, M.A.; Borchardt, R.; Scheiner, S.; Seemann, B.; Schweizer, P.; Brabec, C.J.
    Sustainable biomass production is expected to be one of the major supporting pillars for future energy supply, as well as for renewable material provision. Algal beds represent an exciting resource for biomass/biofuel, fine chemicals and CO2 storage. Similar to other solar energy harvesting techniques, the efficiency of algal photosynthesis depends on the spectral overlap between solar irradiation and chloroplast absorption. Here we demonstrate that spectral conversion can be employed to significantly improve biomass growth and oxygen production rate in closed-cycle algae reactors. For this purpose, we adapt a photoluminescent phosphor of the type Ca 0.59Sr0.40Eu0.01S, which enables efficient conversion of the green part of the incoming spectrum into red light to better match the Qy peak of chlorophyll b. Integration of a Ca 0.59Sr0.40Eu0.01S backlight converter into a flat panel algae reactor filled with Haematococcus pluvialis as a model species results in significantly increased photosynthetic activity and algae reproduction rate.
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    Impact of the precursor chemistry and process conditions on the cell-to-cell variability in 1T-1R based HfO2 RRAM devices
    (London : Nature Publishing Group, 2018) Grossi, A.; Perez, E.; Zambelli, C.; Olivo, P.; Miranda, E.; Roelofs, R.; Woodruff, J.; Raisanen, P.; Li, W.; Givens, M.; Costina, I.; Schubert, M.A.; Wenger, C.
    The Resistive RAM (RRAM) technology is currently in a level of maturity that calls for its integration into CMOS compatible memory arrays. This CMOS integration requires a perfect understanding of the cells performance and reliability in relation to the deposition processes used for their manufacturing. In this paper, the impact of the precursor chemistries and process conditions on the performance of HfO2 based memristive cells is studied. An extensive characterization of HfO2 based 1T1R cells, a comparison of the cell-to-cell variability, and reliability study is performed. The cells’ behaviors during forming, set, and reset operations are monitored in order to relate their features to conductive filament properties and process-induced variability of the switching parameters. The modeling of the high resistance state (HRS) is performed by applying the Quantum-Point Contact model to assess the link between the deposition condition and the precursor chemistry with the resulting physical cells characteristics.