Band gap engineering and modifying surface of TiO2 nanostructures by Fe2O3 for enhanced-performance of dye sensitized solar cell

Well-crystallized Fe₂O₃-modified TiO₂ nanoparticles are prepared by a hydrothermal method and were successfully used as the photoanode of dye-sensitized solar cell (DSSC). Structural, optical and thermal characterizations were carried out by SEM, XRD, AFM, EDAX, DTG, TG and UV–vis spectroscopy. We show that the solar conversion efficiency, incident photocurrent efficiency (IPCE) and fill factor (FF) of Fe₂O₃-modified TiO₂ are significantly increased, about 40%, compared those of to bare TiO₂. DSSC shows power conversion efficiency of 7.27% based on Fe₂O₃-modified TiO₂ while TiO₂ anatase shows 5.10% solar conversion efficiency. The high improvement in cell performance is attributed to the enhanced light harvesting and high specific surface area for adsorbing more dye molecules in Fe₂O₃-modified TiO₂ nanostructures.     

基于 Q 学习的生物启发式目标导向导航路径规划模型

为解决未知环境中移动机器人面向目标运行时最优路径获取问题，本文提出一种基于Q学习的生物启发式目标导向导航路径规划模型。该模型包括基于Q学习的空间探索、基于认知图运行控制和最优路径选择3部分。首先，在空间探索中，通过位置细胞的放电情况表征位置状态，采用ε动态取值方式进行状态-动作学习，生成认知图，并给出空间探索阶段最优路径。其次，在基于认知图的运行控制中，分别依据最大动作细胞放电率原则和群体动作细胞原则进行运行方向选择，采用多尺度位置更新间距进行位置更新，得到不同认知图下最优路径。最后，对比分析空间探索阶段和运行控制阶段路径规划结果，选取最优路径。仿真结果表明，所提模型可行，采用ε动态取值方式进行空间探索可得到较好的路径规划结果；运行体在充分的空间探索后，可提供可行、有效的面向目标运行的路径。