Perea J Darío, Langner Stefan, Salvador Michael, Kontos Janos, Jarvas Gabor, Winkler Florian, Machui Florian, Görling Andreas, Dallos Andras, Ameri Tayebeh, Brabec Christoph J
Institute of Materials for Electronics and Energy Technology (i-MEET), Friedrich-Alexander-Universität Erlangen-Nürnberg , Martensstrasse 7, 91058 Erlangen, Germany.
Instituto de Telecomunicações, Instituto Superior Tecnico , Av. Rovisco Pais, P-1049-001 Lisboa, Portugal.
J Phys Chem B. 2016 May 19;120(19):4431-8. doi: 10.1021/acs.jpcb.6b00787. Epub 2016 May 4.
The solubility of organic semiconductors in environmentally benign solvents is an important prerequisite for the widespread adoption of organic electronic appliances. Solubility can be determined by considering the cohesive forces in a liquid via Hansen solubility parameters (HSP). We report a numerical approach to determine the HSP of fullerenes using a mathematical tool based on artificial neural networks (ANN). ANN transforms the molecular surface charge density distribution (σ-profile) as determined by density functional theory (DFT) calculations within the framework of a continuum solvation model into solubility parameters. We validate our model with experimentally determined HSP of the fullerenes C60, PC61BM, bisPC61BM, ICMA, ICBA, and PC71BM and through comparison with previously reported molecular dynamics calculations. Most excitingly, the ANN is able to correctly predict the dispersive contributions to the solubility parameters of the fullerenes although no explicit information on the van der Waals forces is present in the σ-profile. The presented theoretical DFT calculation in combination with the ANN mathematical tool can be easily extended to other π-conjugated, electronic material classes and offers a fast and reliable toolbox for future pathways that may include the design of green ink formulations for solution-processed optoelectronic devices.
有机半导体在环境友好型溶剂中的溶解度是有机电子器件广泛应用的重要前提。溶解度可以通过基于汉森溶解度参数（HSP）考虑液体中的内聚能来确定。我们报告了一种使用基于人工神经网络（ANN）的数学工具来确定富勒烯HSP的数值方法。ANN将在连续溶剂化模型框架内通过密度泛函理论（DFT）计算确定的分子表面电荷密度分布（σ-分布）转换为溶解度参数。我们通过实验测定的富勒烯C60、PC61BM、双PC61BM、ICMA、ICBA和PC71BM的HSP以及与先前报道的分子动力学计算结果进行比较，验证了我们的模型。最令人兴奋的是，尽管在σ-分布中没有关于范德华力的明确信息，但ANN能够正确预测富勒烯溶解度参数的色散贡献。所提出的理论DFT计算与ANN数学工具相结合，可以很容易地扩展到其他π共轭电子材料类别，并为未来的研究途径提供了一个快速且可靠的工具箱，这些途径可能包括用于溶液处理光电器件的绿色油墨配方设计。
