Comparison of perchloroethylene extraction techniques in soil gas survey quantification

Subsurface pollution by volatile organic compounds has emerged as a widespread problem in industrialized countries. This study compares static headspace technique and methanol extraction/purge-and-trap analysis followed by thermal desorption/gas chromatography in attempts for quantification of gas survey results in the determination of these chemicals in soil. Several soils were contaminated with aqueous solution of perchloroethylene (PCE) (140 mg L⁻¹) using a vapor treatment method. Soil spiking took place up to 24 h in desiccator by exposing individual soil samples contained in open 40 mL glass vials to PCE evaporated from the solution. After exposure the samples were stored and analyzed within 2 days. The achieved results strongly suggest that gas extraction can provide quantitative results, regarding PCE concentration in soils, which are not significantly different from liquid based extraction analysis.      

Correlation of band electronic structure with efficiency in perovskite solar cells with vanadium (Ⅳ) oxide thin film buffers

Perovskite solar cells have been studied extensively in the area of perovskite solar cells because they have a comparatively free hysteresis. Through fabrication of a perovskite solar cell based on a vanadium oxide buffer, this study clarified the mechanism of electron and hole transport in the laminated layer upon irradiation with light. The power conversion efficiency (PCE) of the Vanadium (Ⅳ) oxide (VO₂) sputtering process device was approximately 13% and with the spin-coating process was 8.5%. To investigate the physicochemical origin of such PCE differences depending on the process type, comprehensive band alignment and band structure analyses of the actual cell stacks were performed using X-ray photoelectron spectroscopy depth measurements. Accordingly, it was found that the inconsistent valence band offset between the perovskite absorption layer and V₂O₅ layer as a function of the VO₂ process type caused a difference in the hole transport, resulting in the difference in the efficiency.     

PARTICULATE CONCENTRATION ENRICHMENT OF PRIMARY AIR IN PULVERIZED COAL BOILERS

Particulate concentration enrichment (PCE) of primary air favors flame ignition and stabilization, and the reduction of NOx emission in pulverized coal combustion. The methods used for PCE are summarized in five categories:Cyclone PCE, Elbow PCE, Blunt-body PCE, Hydrodynamic PCE and Swirling PCE. Practice of each PCE method is illustrated with typical burners and the associated pros and cons are discussed. It is found that the same principle prevails in all PCE methods, that is, due to inertial difference, solid particles preferentially decelerate and separate from the gas stream when the main flow deviates in flow orientation. From analysis of various P-C burners, PCE design is deemed to yet comprise “rule of thumb” practice. Some discussions regarding PCE application are given.     

有机光伏器件激活层的微结构有序性与电荷输运

本文在对有机光伏电池载流子产生机理分析的基础上,从有机光伏电池激活层的微观结构对光电转换效率影响的角度,系统介绍了目前该领域的一些重要研究成果,详细分析了影响光电转换效率的主要因素,并提出了一系列改善光伏电池效率的方法,对未来该领域的研究作了展望。     

快速热退火处理ZnO电子传输层对聚合物太阳能电池性能的改善

采用快速热退火对ZnO薄膜进行后处理,制作了ITO/ZnO/PTB7：PC₇₁BM/MoO₃/Ag结构的倒置聚合物太阳能电池,器件能量转换效率达到了8.1%,与传统热退火工艺相比提高了11.26%。通过原子力显微镜、扫描电子显微镜、X光衍射谱、透射光谱和荧光谱对不同退火条件下制备的ZnO薄膜进行表征和分析。结果表明,经快速热退火处理的ZnO薄膜具有良好的c轴取向结晶特性、较大的晶粒尺寸和表面粗糙度,有效地降低了器件的串联电阻R_s,增大了器件的短路电流J_sc和填充因子FF。

     

翼吊式飞机跨声速气动特性的不确定性分析

针对随机不确定性可能带来翼吊式飞机严重气动性能波动的问题,提出了一种基于主动学习加点策略的Gauss过程回归(Gaussian process regression, GPR)代理模型方法用于不确定性分析,该主动学习加点策略能够有效地降低模型不确定性,提高不确定预测的精度。关注来流不确定性输入,分别使用Smolyak稀疏网格多项式混沌展开(polynomial chaos expansion, PCE)方法和基于主动学习加点策略的GPR代理模型方法,结合Sobol灵敏度分析对翼-身-短舱-挂架几何进行了不确定性分析。结果表明,在跨声速条件下,攻角和Mach数的不确定性会引起翼吊式飞机升力系数和阻力系数的剧烈波动,其中升力系数的波动同时受攻角和Mach数的影响,阻力系数的波动主要由Mach数决定。

     

基于多项式混沌拓展模型和bootstrap的结构可靠性分析方法

多项式混沌拓展(polynomial chaos expansion,PCE)模型现已发展为全局灵敏度分析的强大工具,却很少作为替代模型用于可靠性分析。针对该模型缺乏误差项从而很难构造主动学习函数来逐步更新的事实,在结构可靠性分析的框架下提出了基于PCE模型和bootstrap重抽样的仿真方法来计算失效概率。首先,对试验设计(experimental design)使用bootstrap重抽样步骤以刻画PCE模型的预测误差;其次,基于这个局部误差构造主动学习函数,通过不断填充试验设计以自适应地更新模型,直到能够精确地逼近真实的功能函数;最后,当PCE模型具有足够精确的拟合、预测能力,再使用蒙特卡洛仿真方法来计算失效概率。提出的平行加点策略既能在模型更新过程中找到改进模型拟合能力的"最好"的点,又考虑了模型拟合的计算量;而且,当失效概率的数量级较低时,PCE-bootstrap步骤与子集仿真(subset simulation)的结合能进一步加速失效概率估计量的收敛。本文方法将PCE模型在概率可靠性领域的应用从灵敏度分析延伸到了可靠性分析,同时,算例分析结果显示了该方法的精确性和高效性。