An Automated Workflow to Discover the Structure-Stability Relations for Radiation Hard Molecular Semiconductors - Bornschlegl, Andreas; Duchstein, Patrick; Wu, Jianchang; Rocha-Ortiz, Juan S.; Caicedo-Reina, Mauricio; Ortiz, Alejandro; Insuasty, Braulio; Zahn, Dirk; Lüer, Larry; Brabec, Christoph (Journal of the American Chemical Society, 2025)
Emerging photovoltaics for outer space applications are one of the many examples where radiation hard molecular semiconductors are essential. However, due to a lack of general design principles, their resilience against extra-terrestrial high-energy radiation can currently not be predicted. In this work, the discovery of radiation hard materials is accelerated by combining the strengths of high-throughput, lab automation and machine learning. This way, a large material library of more than 130 organic hole transport materials is automatically processed, degraded, and measured. The materials are degraded under ultraviolet-C (UVC) light in a nitrogen atmosphere, serving as the conditions for electromagnetic radiation hardness tests. A value closely related to the differential quantum yield for photodegradation is extracted from the evolution of the UV-visible (UV-vis) spectra over time and used as a stability target. Following this procedure, a stability ranking spanning over 3 orders of magnitude was obtained. Combining Gaussian Process Regression based on predictors from structural fingerprints and manual filtering of the materials by features, structure-stability relations for UVC stable materials could be found: Fused aromatic ring clusters are beneficial, whereas thiophene, methoxy and vinylene groups are detrimental. Comparing the UV-vis spectra of the degraded material in film and solution, bond cleavage could be made out as the leading degradation mechanism. Even though UVC light can in principle break most organic bonds, the stable materials are able to distribute and dissipate the energy well enough so that the chemical structures remain stable. The established predictive model quantifies the effect of specific molecular features on UVC stability, allowing chemists to consider UVC stability in their molecular design strategy. In the future, a larger data set will allow to inversely design molecular semiconductors which show high performance and radiation hardness at the same time.
CRIS-Team Scopus Importer:2025-01-31