Langner S, Häse F, Perea JD, Stubhan T, Hauch J, Roch LM, Heumüller T, Aspuru-Guzik A, Brabec C (2020)
Publication Type: Journal article
Publication year: 2020
Article Number: 1907801
Fundamental advances to increase the efficiency as well as stability of organic photovoltaics (OPVs) are achieved by designing ternary blends, which represents a clear trend toward multicomponent active layer blends. The development of high-throughput and autonomous experimentation methods is reported for the effective optimization of multicomponent polymer blends for OPVs. A method for automated film formation enabling the fabrication of up to 6048 films per day is introduced. Equipping this automated experimentation platform with a Bayesian optimization, a self-driving laboratory is constructed that autonomously evaluates measurements to design and execute the next experiments. To demonstrate the potential of these methods, a 4D parameter space of quaternary OPV blends is mapped and optimized for photostability. While with conventional approaches, roughly 100 mg of material would be necessary, the robot-based platform can screen 2000 combinations with less than 10 mg, and machine-learning-enabled autonomous experimentation identifies stable compositions with less than 1 mg.
APA:
Langner, S., Häse, F., Perea, J.D., Stubhan, T., Hauch, J., Roch, L.M.,... Brabec, C. (2020). Beyond Ternary OPV: High-Throughput Experimentation and Self-Driving Laboratories Optimize Multicomponent Systems. Advanced Materials. https://doi.org/10.1002/adma.201907801
MLA:
Langner, Stefan, et al. "Beyond Ternary OPV: High-Throughput Experimentation and Self-Driving Laboratories Optimize Multicomponent Systems." Advanced Materials (2020).
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