Search Results (2)

Rare earth bisphthalocyanines (MPc₂) are of particular interest because of their behavior as single-molecular magnets, which makes them suitable for applications in molecular spintronics, high-density data storage and quantum computation. Nevertheless, MPc₂ are not commercially available, and the synthesis routes are mainly focused on obtaining substituted phthalocyanines. Two preparation routes depend on the precursor: synthesis from phthalonitrile (PN) and the metalation of free or dilithium phthalocyanine (H₂Pc and Li₂Pc). In both options, byproducts such as free-base phthalocyanine and in the first route additional PN oligomers are generated, which influence the MPc₂ yield. There are three preparation methods for these routes: heating, microwave radiation and reflux. In this research, solvothermal synthesis was applied as a new approach to prepare yttrium, lanthanum, gadolinium and terbium unsubstituted bisphthalocyanines using Li₂Pc and the rare earth(III) acetylacetonates. Purification by sublimation gave high product yields compared to those reported, namely 68% for YPc₂, 43% for LaPc₂, 63% for GdPc₂ and 62% for TbPc₂, without any detectable presence of H₂Pc. Characterization by infrared, Raman, ultraviolet–visible and X-ray photoelectron spectroscopy as well as elemental analysis revealed the main featuresof the four bisphthalocyanines, indicating the success of the synthesis of the complexes. Full article

Optimal control of reservoirs is a challenging task due to conflicting objectives, complex system structure, and uncertainties in the system. Real time control decisions suffer from streamflow forecast uncertainty. This study aims to use Probabilistic Streamflow Forecasts (PSFs) having a lead-time up to 48 h as input for the recurrent reservoir operation problem. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC). Deterministic Streamflow Forecasts (DSFs) are provided by applying random perturbations on perfect data. PSFs are synthetically generated from DSFs by a new approach which explicitly presents dynamic uncertainty evolution. We assessed different variables in the generation of stochasticity and compared the results using different scenarios. The developed real-time hourly flood control was applied to a test case which had limited reservoir storage and restricted downstream condition. According to hindcasting closed-loop experiment results, TB-MPC outperforms the deterministic counterpart in terms of decreased downstream flood risk according to different independent forecast scenarios. TB-MPC was also tested considering different number of tree branches, forecast horizons, and different inflow conditions. We conclude that using synthetic PSFs in TB-MPC can provide more robust solutions against forecast uncertainty by resolution of uncertainty in trees. Full article