Revealing processing stability landscape of organic solar cells with automated research platforms and machine learning

Du X, Lüer L, Heumueller T, Classen A, Liu C, Berger C, Wagner J, Le Corre VM, Cao J, Xiao Z, Ding L, Forberich K, Li N, Hauch J, Brabec CJ (2024)

Publication Type: Journal article

Publication year: 2024

Journal

InfoMat Wiley

DOI: 10.1002/inf2.12554

Abstract

We use an automated research platform combined with machine learning to assess and understand the resilience against air and light during production of organic photovoltaic (OPV) devices from over 40 donor and acceptor combinations. The standardized protocol and high reproducibility of the platform results in a dataset of high variety and veracity to deploy machine learning models to encounter links between stability and chemical, energetic, and morphological structure. We find that the strongest predictor for air/light resilience during production is the effective gap Eg,eff which points to singlet oxygen rather than the superoxide anion being the dominant agent in degradation under processing conditions. A similarly good prediction of air/light resilience can also be achieved by considering only features from chemical structure, that is, information which is available prior to any experimentation.

Authors with CRIS profile

Jens Hauch
Christoph Brabec

Involved external institutions

Forschungszentrum Jülich / Research Centre Jülich (FZJ)

Germany (DE) Hunan University of Science and Technology

China (CN) National Center for Nanoscience and Technology (NCNST) / 国家纳米科学中心

China (CN)

How to cite

APA:

Du, X., Lüer, L., Heumueller, T., Classen, A., Liu, C., Berger, C.,... Brabec, C.J. (2024). Revealing processing stability landscape of organic solar cells with automated research platforms and machine learning. InfoMat. https://doi.org/10.1002/inf2.12554

MLA:

Du, Xiaoyan, et al. "Revealing processing stability landscape of organic solar cells with automated research platforms and machine learning." InfoMat (2024).

BibTeX: Download