Multiscale Modeling of Organic-Inorganic Semiconductor Materials: Opportunities and Challenges

摘要

We discuss our recent advances in the multiscale modeling of organic-inorganic semiconductor materials, highlighting the impact that has been achieved using a combination of methods at different length- and time-scales. We also discuss the challenges and limitations that remain for the community to address. Test cases related to all-organic solar cells composed of a COF framework of pores filled with fullerene molecules, heterepitactical crystal growth of C60 on pentacene, and an accelereated Bayesian search to find energetically stable polymorphs of a small molecule organic semiconductor. We propose the advantage of embracing a new field that we call "physical analytics" that combines information from simulations, modeling and experiments with machine learning-informed Bayesian search techniques to help us tackle high dimensional, often combinatorially complex problems in materials science.