DataVXAdvanced MaterialsPaper
journal article·2020-04Open access

Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems

Stefan Langner, Florian Häse, José Darío Perea, Tobias Stubhan, Jens Hauch, Loïc M. Roch, Thomas Heumueller, Alán Aspuru‐Guzik, Christoph J. Brabec

Advanced Materials· Volume 32· Issue 14
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Source abstract

Abstract

Abstract 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.
Source: crossref · Quality: baseline

Research context

PolymersElectronic materials

OpenAlex topics: Machine Learning in Materials Science · Modular Robots and Swarm Intelligence · Electrowetting and Microfluidic Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Materials for Electronics and Energy Technology (i‐MEET) Department of Materials Science and Engineering Friedrich‐Alexander University Erlangen‐Nürnberg Martensstrasse 7 Erlangen 91058 Germany

Department of Chemistry and Chemical Biology Harvard University Cambridge MA 02138 USA

Department of Chemistry University of Toronto Toronto ON M5S 3H6 Canada

Department of Computer Science University of Toronto Toronto ON M5S 3H6 Canada

Vector Institute for Artificial Intelligence Toronto ON M5S 1M1 Canada

Forschungszentrum Jülich GmbH Helmholtz‐Institut Erlangen‐Nürnberg for Renewable Energy (IEK‐11) Immerwahrstraße 2 Erlangen 91058 Germany

Canadian Institute for Advanced Research (CIFAR) Lebovic Fellow Toronto ON M5S 1M1 Canada

Funding

Bayerisches Staatsministerium für Umwelt und Verbraucherschutz · Deutsche Forschungsgemeinschaft · Tata Sons · Bayerisches Staatsministerium für Wirtschaft und Medien, Energie und Technologie

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