Predicting the excited-state properties of crystalline organic semiconductors using GW+BSE and machine learning

This journal contribution is published Open Access by the publisher. Follow the DOI link to retrieve a copy of the full text. This work was supported by the National Science Foundation (NSF) Designing Materials to Revolutionize and Engineer our Future (DMREF) program under award DMR-2323749. This research used resources of the Argonne Leadership Computing Facility (ALCF), which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357.