A theoretical understanding of the microstructure of organic semiconducting polymers and blends is vital to further advance the optoelectronic device performance of organic electronics. We outline the theoretical framework of a combined numerical approach based on polymeric solution theory to study the microstructure of polymer:small molecule blends. We feed the results of ab initio density functional theory quantum chemistry calculations into an artificial neural network for the determination of solubility parameters. These solubility parameters are used to calculate Flory−Huggings intermolecular parameters. We further show that the theoretical values are in line with experimentally determined data. On the basis of the Flory−Huggings parameters, we establish a figure of merit as a relative metric for assessing the phase diagrams of organic semiconducting blends in thin films. This is demonstrated for polymer:fullerene blend films on the basis of the prototypical polymers poly(3-hexylthiophene-2,5-diyl) (P3HT) and poly [(5,6-difluoro-2,1,3-benzothiadiazol-4,7-diyl)-alt-(3,3-di(2-octyldodecyl)-2,2,5,2;5,2-quaterthiophen-5,5-diyl)] (PffBT4T-2OD). After confirming the applicability of our model with a broader range of materials and differences in molecular weight, we suggest that this combined model should be able to inform design criteria and processing guidelines for existing and new high performance semiconducting blends for organic electronics applications with ideal and stable solid state morphology.

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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.

Despite the ever growing use of capillary electrophoresis in biomedical research and the biopharmaceutical industry, the development of data interpretation methods is lagging behind. In this paper we report the design and implementation of a coinjected triple-internal standard method to alleviate the need of an accompanying run of the maltooligosaccharide ladder for glucose unit (GU) calculation. Based on the migration times of the coinjected standards of maltose, maltotriose, and maltopentadecaose (bracketing the peaks of interest), a data processing approach was designed and developed to set up a virtual ladder that was used for GU calculation. The data processing was tested in terms of the calculated GU values of human IgG glycans, and the resulting relative standard deviation was ≤1.07%. This approach readily supports high-throughput capillary electrophoresis systems by significantly speeding up the processing time for glycan structural assignment.