Predicting Molecular Ordering in Deposited Molecular Films
Source abstract
Abstract
Abstract Thin films of molecular materials are commonly employed in organic light‐emitting diodes, field‐effect transistors, and solar cells. The morphology of these organic films is shown to depend heavily on the processing used during manufacturing, such as vapor co‐deposition. However, the prediction of processing‐dependent morphologies has until now posed a significant challenge, particularly in cases where self‐assembly and ordering are involved. In this work, a method is developed based on coarse‐graining that is capable of predicting molecular ordering in vapor‐deposited films of organic materials. The method is tested on an extensive database of novel and known organic semiconductors. A good agreement between the anisotropy of the refractive indices of the simulated and experimental vapor‐deposited films suggests that the method is quantitative and can predict the molecular orientations in organic films at an atomistic resolution. The methodology can be readily utilized for screening materials for organic light‐emitting diodes.
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Research context
OpenAlex topics: Machine Learning in Materials Science · Molecular Junctions and Nanostructures · Advanced Chemical Physics Studies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Max Planck Institute for Polymer Research Ackermannweg 10 55128 Mainz Germany
Merck Electronics KGaA 64293 Darmstadt Germany
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