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Estimating the impact of dye concentration on the photoelectrochemical performance of anthocyanin - sensitized solar cells: a power law model

机译:估算染料浓度对花青素敏化太阳能电池光电化学性能的影响:电力法模型

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This study investigated the relationship between the anthocyanin concentration in a series of organic fruit species and the photoelectrochemical performance of the TiO_2 dye- sensitized solar cells (DSSCs) sensitized by these dyes. It was hypothesized that organic dyes with a greater anthocyanin concentration have higher fill factors (FFs) and maximum output power (P_MAX), which would lead to higher energy conversion efficiency. Anthocyanin dye solution was extracted from eight test fruits using water as the extracting solvent. Using these test organic dyes, multiple DSSCs were assembled such that light entered through the TiO_2 side of the cell. The full current-voltage (I-V) covariations were measured at various incremental resistance values. Defining P_(MAX) as the dependent variable, a series of linear, semi-logarithmic, quadratic, and finally power law regression models were used to investigate the relationship between anthocyanin concentration and photoelectrochemical performance. Regression analysis demonstrated that the power law model (R2 = 0.86) was the best fit and experimentally sound model to predict the relationship between P_(MAX) and anthocyanin concentration. Based on this model, anthocyanin content and P_(MAX) relation approaches zero for zero concentration and follows a sublinear increase for higher concentration. Dyes extracted from blueberry and black raspberry with the highest anthocyanin content generated higher P_(MAX) with better FF and conversion efficiency. Estimating these linear and power law models is the first step in finding organic anthocyanin sources in nature that have the highest dye content to efficiently generate energy.
机译:本研究探讨花青素浓度之间的关系的一系列有机水果物质和染料的TiO_2的光电化学性能敏化由这些染料敏化太阳能电池(DSSC)。据推测,具有更大的花青素浓度有机染料具有更高的填充因子(FF)等和最大输出功率(P_MAX),这将导致更高的能量转换效率。花青素染料溶液从使用水作为提取溶剂8个测试果实萃取。使用这些试验的有机染料,多DSSC中被组装,使得通过电池的的TiO_2侧入射的光。全电流 - 电压(I-V)的共变以不同的增量电阻值进行测量。限定P_(MAX)为因变量,一系列线性的,半对数,二次,最后幂律回归模型用于研究花青素浓度和光电化学性能之间的关系。回归分析表明,幂律模型(R 2 = 0.86)为预测P_(MAX)和花青素浓度之间的关系的最佳拟合和实验声音模型。基于该模型,花青素含量和P_(MAX)关系对于零浓度接近零,并且遵循更高浓度的次线性增加。从蓝莓,黑树莓具有较高P_(MAX)产生具有更好的FF和转换效率最高的花色素苷含量提取染料。估计这些线性和幂律模型是在寻找在自然界的有机花青素源具有最高染料含量以有效地产生能量的第一步。

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