Autonomous Battery Optimization by Deploying Distributed Experiments and Simulations
Abstract Non‐trivial relationships link individual materials properties to device‐level performance. Device optimization therefore calls for new automation approaches beyond the laboratory bench with tight integration of different research methods. This study demonstrates a Materials Acceleration Platform (MAP) in the field of battery research based on the problem‐agnostic Fast INtention‐Agnostic LEarning Server (FINALES) framework, which integrates simulations and physical experiments while leaving the active control of the hardware and software resources executing experiments or simulations with the partners running the respective units. This decentralization of control is a distinctive feature of MAPs using the FINALES framework. The connected capabilities entail the formulation and characterization of electrolytes, cell assembly and testing, early lifetime prediction, and ontology‐mapped data storage provided by institutions distributed across Europe. The infrastructure is used to optimize the ionic conductivity of electrolytes and the End Of Life (EOL) of lithium‐ion coin cells by varying the electrolyte formulation. Trends in ionic conductivity are rediscovered and the effect of the electrolyte formulation on the EOL is investigated. Further, the capability of this MAP to bridge diverse research modalities, scales, and institutions enabling system‐level investigations under asynchronous conditions while handling concurrent workflows on the material‐ and system‐level is shown, demonstrating true intention‐agnosticism.
Authors
- Johan M. Carlsson (ORCID: https://orcid.org/0000-0002-1596-0923)
- Alexey O. Sanin (ORCID: https://orcid.org/0000-0003-1796-9224)
- Giovanni Pizzi (ORCID: https://orcid.org/0000-0002-3583-4377)
- Leon Merker (ORCID: https://orcid.org/0000-0001-8959-3161)
- Jonas Busk (ORCID: https://orcid.org/0000-0003-2502-1679)
- Arghya Bhowmik (ORCID: https://orcid.org/0000-0003-3198-5116)
- Laura Rieger (ORCID: https://orcid.org/0000-0002-2986-2937)
- Monika Vogler (ORCID: https://orcid.org/0000-0001-8514-5601)
- Stefan Fuchs (ORCID: https://orcid.org/0000-0001-8121-426X)
- Felix Hanke (ORCID: https://orcid.org/0000-0002-4155-5980)
- Simon Clark (ORCID: https://orcid.org/0000-0002-8758-6109)
- Ivano E. Castelli (ORCID: https://orcid.org/0000-0001-5880-5045)
- Bojing Zhang (ORCID: https://orcid.org/0000-0001-8709-3040)
- Eibar Flores (ORCID: https://orcid.org/0000-0003-2954-1233)
- Helge S. Stein (ORCID: https://orcid.org/0000-0002-3461-0232)
- Hamidreza Hajiyani (ORCID: https://orcid.org/0000-0002-1150-0567)
- Miran Gaberšček (ORCID: https://orcid.org/0000-0002-8104-1693)
- Francisco F. Ramírez (ORCID: https://orcid.org/0000-0002-5490-6014)
- Tejs Vegge (ORCID: https://orcid.org/0000-0002-1484-0284)
- Simon Krarup Steensen (ORCID: https://orcid.org/0009-0008-8649-3542)
- François Liot
Institutions
- SINTEF (NO)
- Paul Scherrer Institute (CH)
- Dassault Systèmes (Germany) (DE)
- Helmholtz-Institute Ulm (DE)
- Max Planck Computing and Data Facility (DE)
- Dassault Systèmes (United Kingdom) (GB)
- National Institute of Chemistry (SI)
- SINTEF Industry (NO)
- École Polytechnique Fédérale de Lausanne (CH)
- Technical University of Munich (DE)
- Technical University of Denmark (DK)
Publication Details
- Journal
- Advanced Energy Materials
- Published
- 2024-10-18
- DOI
- https://doi.org/10.1002/aenm.202403263
- Citations
- 14
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 2.85
Funders
- National Science Foundation
- Center of Excellence for Learning in Education, Science and Technology
- European Commission
- Deutsche Forschungsgemeinschaft
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Danmarks Grundforskningsfond
- Board of the Swiss Federal Institutes of Technology
- Horizon 2020 Framework Programme
- National Center of Competence in Research Materials’ Revolution: Computational Design and Discovery of Novel Materials