Automated Virtual Design of Organic Semiconductors Based on Metal-Organic Frameworks

• Published in: Frontiers in materials 2022-03, Vol.9
• Main Authors: Mostaghimi, Mersad, Rêgo, Celso R. C., Haldar, Ritesh, Wöll, Christof, Wenzel, Wolfgang, Kozlowska, Mariana
• Format: Article
• Language: English
• Subjects: metal–organic framework; organic semiconductors; pentacene; structure builder; virtual design; workflow
• ISSN: 2296-8016; 2296-8016
• DOI: 10.3389/fmats.2022.840644

The arrangement of organic semiconductor molecules in a material can be modulated using different supramolecular approaches, including the metal–organic framework (MOF) approach. These arrangements result in different frameworks topologies and structures. Fabrication of materials comprising optimized assemblies and functional molecules enables efficient tailoring of material properties, including electronic responses. Since semiconducting properties are sensitive to subtle changes in the nanostructure of the material, the exploitation of MOFs has promising potential in the development of new materials with designed structure and function. Based on decade-long method development, virtual design strategies have become ever more important, and such design methods profit from the availability of automated tools. Such tools enable screening of huge libraries of organic molecules in in silico models of the structure of three-dimensional nanoscale assemblies as the prerequisite to predict their functionality. In this report, we present and demonstrate the application of an automated workflow tool developed for MOFs of the primitive cubic (PCU) topology. We use pentacene-based ditopic linkers of a varied chemical composition and pillar linkers of different molecular sizes to automatically generate PCU MOFs, sample their structural dynamics at finite temperature, and predict electronic coupling matrix elements in vibrationally averaged assemblies. We demonstrate the change of the intermolecular ordering in the resulting MOFs and its impact on the semiconducting properties. This development lays the basis of an extendable framework to automatically model a wide variety of MOFs and characterize their function with respect to properties, such as conduction properties, absorption, and interaction with light. The developed workflow protocol and tools are available at https://github.com/KIT-Workflows/PCU-MOF .