Distribution of charge carrier transport properties in organic semiconductors with Gaussian disorder
Distribution of charge carrier transport properties in organic semiconductors with Gaussian disorder
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DOI：
10.1063/1.4875683
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发表时间：
2014-05-14
影响因子：
3.2
通讯作者：
Deibel, Carsten
中科院分区：
文献类型：
--
作者：
Lorrmann, Jens;Ruf, Manuel;Deibel, Carsten
无序半导体中的电荷载流子漂移迁移率通常从飞行时间（TOF）光电流瞬态中以图形方式提取，从而产生单个渡越时间。然而，术语通行时间的定义模糊不清，无法提供统计平均值方面的流动性。在这里，我们引入了一种先进的计算程序来评估TOF瞬变，它允许从光电流瞬变中提取渡越时间和迁移率的整个分布，而不是单个值。该方法扩展了Scott等人的工作（Phys. Rev. B 46，8603（1992）），适用于具有高斯态密度的无序系统，并且其精度使用一维Monte Carlo模拟来验证。我们证明了这种新方法的优越性，通过比较它的常见的几何分析孔TOF瞬态测量聚（3-己基噻吩-2，5-二基）。所提取的分布提供了对电荷载流子传输的非常详细和准确的分析。例如，不仅可以计算由平均渡越时间给出的迁移率，还可以计算平均迁移率。而后者确定的宏观光电流，前者是相关的高斯无序模型内的能量无序参数σ的准确测定。我们发现，用普通几何方法得到的σ反而被低估了。(C)2014 AIP Publishing LLC.
The charge carrier drift mobility in disordered semiconductors is commonly graphically extracted from time-of-flight (TOF) photocurrent transients yielding a single transit time. However, the term transit time is ambiguously defined and fails to deliver a mobility in terms of a statistical average. Here, we introduce an advanced computational procedure to evaluate TOF transients, which allows to extract the whole distribution of transit times and mobilities from the photocurrent transient, instead of a single value. This method, extending the work of Scott et al. (Phys. Rev. B 46, 8603 (1992)), is applicable to disordered systems with a Gaussian density of states and its accuracy is validated using one-dimensional Monte Carlo simulations. We demonstrate the superiority of this new approach by comparing it to the common geometrical analysis of hole TOF transients measured on poly(3-hexyl thiophene-2,5-diyl). The extracted distributions provide access to a very detailed and accurate analysis of the charge carrier transport. For instance, not only the mobility given by the mean transit time but also the mean mobility can be calculated. Whereas the latter determines the macroscopic photocurrent, the former is relevant for an accurate determination of the energetic disorder parameter sigma within the Gaussian disorder model. sigma derived by using the common geometrical method is, as we show, underestimated instead. (C) 2014 AIP Publishing LLC.